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How Rust went from a side project to the world’s most-loved programming language

For decades, coders wrote critical systems in C and C++. Now they turn to Rust.

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Many software projects emerge because—somewhere out there—a programmer had a personal problem to solve.

That’s more or less what happened to Graydon Hoare. In 2006, Hoare was a 29-year-old computer programmer working for Mozilla, the open-source browser company. Returning home to his apartment in Vancouver, he found that the elevator was out of order; its software had crashed. This wasn’t the first time it had happened, either. 

Hoare lived on the 21st floor, and as he climbed the stairs, he got annoyed. “It’s ridiculous,” he thought, “that we computer people couldn’t even make an elevator that works without crashing! ” Many such crashes, Hoare knew, are due to problems with how a program uses memory. The software inside devices like elevators is often written in languages like C++ or C, which are famous for allowing programmers to write code that runs very quickly and is quite compact. The problem is those languages also make it easy to accidentally introduce memory bugs—errors that will cause a crash. Microsoft estimates that 70% of the vulnerabilities in its code are due to memory errors from code written in these languages.

Most of us, if we found ourselves trudging up 21 flights of stairs, would just get pissed off and leave it there. But Hoare decided to do something about it. He opened his laptop and began designing a new computer language, one that he hoped would make it possible to write small, fast code without memory bugs. He named it Rust, after a group of remarkably hardy fungi that are, he says, “over-engineered for survival.”

Seventeen years later, Rust has become one of the hottest new languages on the planet—maybe the hottest. There are 2.8 million coders writing in Rust, and companies from Microsoft to Amazon regard it as key to their future. The chat platform Discord used Rust to speed up its system, Dropbox uses it to sync files to your computer, and Cloudflare uses it to process more than 20% of all internet traffic. 

When the coder discussion board Stack Overflow conducts its annual poll of developers around the world, Rust has been rated the most “loved” programming language for seven years running. Even the US government is avidly promoting software in Rust as a way to make its processes more secure. The language has become, like many successful open-source projects, a barn-raising: there are now hundreds of die-hard contributors, many of them volunteers. Hoare himself stepped aside from the project in 2013, happy to turn it over to those other engineers, including a core team at Mozilla.

It isn’t unusual for someone to make a new computer language. Plenty of coders create little ones as side projects all the time. But it’s meteor-strike rare for one to take hold and become part of the pantheon of well-known languages alongside, say, JavaScript or Python or Java. How did Rust do it?

To grasp what makes Rust so useful, it’s worth taking a peek beneath the hood at how programming languages deal with computer memory.

You could, very crudely, think of the dynamic memory in a computer as a chalkboard. As a piece of software runs, it’s constantly writing little bits of data to the chalkboard, keeping track of which one is where, and erasing them when they’re no longer needed. Different computer languages manage this in different ways, though. An older language like C or C++ is designed to give the programmer a lot of power over how and when the software uses the chalkboard. That power is useful: with so much control over dynamic memory, a coder can make the software run very quickly. That’s why C and C++ are often used to write “bare metal” code, the sort that interacts directly with hardware. Machines that don’t have an operating system like Windows or Linux, including everything from dialysis machines to cash registers, run on such code. (It’s also used for more advanced computing: at some point an operating system needs to communicate with hardware. The kernels of Windows, Linux, and MacOS are all significantly written in C.)

“It’s enjoyable to write Rust, which is maybe kind of weird to say, but it’s just the language is fantastic. It’s fun. You feel like a magician, and that never happens in other languages.” Parker Timmerman, software engineer

But as speedy as they are, languages like C and C++ come with a trade-off. They require the coder to keep careful track of what memory is being written to, and when to erase it. And if you accidentally forget to erase something? You can cause a crash: the software later on might try to use a space in memory it thinks is empty when there’s really something there. Or you could give a digital intruder a way to sneak in. A hacker might discover that a program isn’t cleaning up its memory correctly—information that should have been wiped (passwords, financial info) is still hanging around—and sneakily grab that data. As a piece of C or C++ code gets bigger and bigger, it’s possible for even the most careful coder to make lots of memory mistakes, filling the software with bugs.

“In C or C++ you always have this fear that your code will just randomly explode,” says Mara Bos, cofounder of the drone firm Fusion Engineering and head of Rust’s library team.

In the ’90s, a new set of languages like Java, JavaScript, and Python became popular. These took a very different approach. To relieve stress on coders, they automatically managed the memory by using “garbage collectors,” components that would periodically clean up the memory as a piece of software was running. Presto: you could write code that didn’t have memory mistakes. But the downside was a loss of that fine-grained control. Your programs also performed more sluggishly (because garbage collection takes up crucial processing time). And software written in these languages used much more memory. So the world of programming became divided, roughly, into two tribes. If software needed to run fast or on a tiny chip in an embedded device, it was more likely to be written in C or C++. If it was a web app or mobile-phone app—an increasingly big chunk of the world of code—then you used a newer, garbage-collected language.

With Rust, Hoare aimed to create a language that split the difference between these approaches. It wouldn’t require programmers to manually figure out where in memory they were putting data; Rust would do that. But it would impose many strict rules on how data could be used or copied inside a program. You’d have to learn those coding rules, which would be more onerous than the ones in Python or JavaScript. Your code would be harder to write, but it’d be “memory safe”—no fears that you’d accidentally inserted lethal memory bugs. Crucially, Rust would also offer “concurrency safety.” Modern programs do multiple things at once—concurrently, in other words—and sometimes those different threads of code try to modify the same piece of memory at nearly the same time. Rust’s memory system would prevent this.

When he first opened his laptop to begin designing Rust, Hoare was already a 10-year veteran of software, working full time at Mozilla. Rust was just a side project at first. Hoare beavered away at it for a few years, and when he showed it to other coders, reaction was mixed. “Some enthusiasm,” he told me in an email. “A lot of eye-rolls and ‘This will never work’ or ‘This will never be usable.’”

Executives at Mozilla, though, were intrigued. Rust, they realized, could help them build a better browser engine. Browsers are notoriously complex pieces of software with many opportunities for dangerous memory bugs.

One employee who got involved was Patrick Walton, who’d joined Mozilla after deciding to leave his PhD studies in programming languages. He remembers Brendan Eich, the inventor of JavaScript, pulling him into a meeting at Mozilla: “He said, ‘Why don’t you come into this room where we’re going to discuss design decisions for Rust?’” Walton thought Rust sounded fantastic; he joined Hoare and a growing group of engineers in developing the language. Many, like Mozilla engineers Niko Matsakis and Felix Klock, had academic experience researching memory and coding languages.

In 2009, Mozilla decided to officially sponsor Rust. The language would be open source, and accountable only to the people making it, but Mozilla was willing to bootstrap it by paying engineers. A Rust group took over a conference room at the company; Dave Herman, cofounder of Mozilla Research, dubbed it “the nerd cave” and posted a sign outside the door. Over the next 10 years, Mozilla employed over a dozen engineers to work on Rust full time, Hoare estimates.

“Everyone really felt like they were working on something that could be really big,” Walton recalls. That excitement extended outside Mozilla’s building, too. By the early 2010s, Rust was attracting volunteers from around the world, from every nook of tech. Some worked for big tech firms. One major contributor was a high school student in Germany. At a Mozilla conference in British Columbia in 2010, Eich stood up to say there’d be a talk on an experimental language, and “don’t attend unless you’re a real programming language nerd,” Walton remembers. “And of course, it filled the room.”

Through the early 2010s, Mozilla engineers and Rust volunteers worldwide gradually honed Rust’s core—the way it is designed to manage memory. They created an “ownership” system so that a piece of data can be referred to by only one variable; this greatly reduces the chances of memory problems. Rust’s compiler—which takes the lines of code you write and turns them into the software that runs on a computer—would rigorously enforce the ownership rules. If a coder violated the rules, the compiler would refuse to compile the code and turn it into a runnable program.

Many of the tricks Rust employed weren’t new ideas: “They’re mostly decades-old research,” says Manish Goregaokar, who runs Rust’s developer-­tools team and worked for Mozilla in those early years. But the Rust engineers were adept at finding these well-honed concepts and turning them into practical, usable features.

As the team improved the memory-management system, Rust had increasingly little need for its own garbage collector—and by 2013, the team had removed it. Programs written in Rust would now run even faster: no periodic halts while the computer performed cleanup. There are, Hoare points out, some software engineers who would argue that Rust still possesses elements that are a bit like garbage collection—its “reference counting” system, part of how its memory-­ownership mechanics work. But either way, Rust’s performance had become remarkably efficient. It dove closer to the metal, down to where C and C++ were—yet it was memory safe.

Removing garbage collection “led to a leaner and meaner language,” says Steve Klabnik, a coder who got involved with Rust in 2012 and wrote documentation for it for the next 10 years.

Along the way, the Rust community was also building a culture that was known for being unusually friendly and open to newcomers. “No one ever calls you a noob ,” says Nell Shamrell-Harrington, a principal engineer at Microsoft who at the time worked on Rust at Mozilla. “No question is considered a stupid question.” 

Part of this, she says, is that Hoare had very early on posted a “code of conduct,” prohibiting harassment, that anyone contributing to Rust was expected to adhere to. The community embraced it, and that, longtime Rust community members say, drew queer and trans coders to get involved in Rust in higher proportions than you’d find with other languages. Even the error messages that the compiler creates when the coder makes a mistake are unusually solicitous; they describe the error, and also politely suggest how to fix it. 

“The C and C++ compiler[s], when I make mistakes, make me feel like a terrible person,” Shamrell-Harrington says with a laugh. “The Rust compiler is more like it’s guiding you to write super-safe code.”

By 2015, the team was obsessed with finally releasing a “stable” version of Rust, one reliable enough for companies to use to make software for real customers. It had been six years since Mozilla took Rust under its wing, and during that long development time, coders had been eager to try demo versions, even though they could be janky: “The compiler broke all the time,” Goregaokar says. Now it was time to get a “1.0” out into the world.

Walton remembers spending hours hunched over his laptop. Klabnik “wrote like 45 pages of documentation in the last two weeks,” he recalls. On May 15, 2015, the group finally released the first version, and groups of Rust nerds gathered for parties worldwide to celebrate.

Mozilla’s investment soon began to pay off. In 2016, a Mozilla group released Servo, a new browser engine built using Rust. The next year, another group used Rust to rewrite the part of Firefox that rendered CSS, a language used to specify the appearance of websites. The change gave the browser a noticeable performance boost. The company also used Rust to rewrite code that handled MP4 multimedia files and had been at risk of admitting unsafe, malicious code.

Rust developers—“Rustaceans,” as they’d begun to call themselves—soon heard from other companies that were trying out their new language. 

Samsung coders told Klock, who was working from Mozilla’s office in France, that they’d begun using it. Facebook (later known as Meta) used Rust to redesign software that its programmers use to manage their internal source code. “It’s hard to overstate how important it is,” says Walton, who works for Meta today.

Soon Rust was appearing at the core of some remarkably important software. In 2020, Dropbox unveiled a new version of its “sync engine”—the software that’s responsible for synchronizing files between users’ computers and Dropbox’s cloud storage—that engineers had rewritten in Rust. The system was originally coded in Python, but it was now handling billions of files (and trillions of files synchronized online). Rust made it easier—even pleasant—to handle that complexity, says Parker Timmerman, a software engineer who recently left Dropbox.

“It’s enjoyable to write Rust, which is maybe kind of weird to say, but it’s just the language is fantastic. It’s fun. You feel like a magician, and that never happens in other languages,” he says. “We definitely took a big bet—it’s a new technology.”

Some firms were discovering that Rust eased their terror about memory bugs; Mara Bos used Rust to completely rewrite her company’s software for controlling drones, which was originally written in C++. 

Others were discovering the joys of abandoning garbage collection. At Discord, engineers had long been annoyed that the garbage collector in Go—the language they’d used to build critical chunks of their software—would slow things down. Their Go software would carry out the procedure roughly every two minutes, even though the Discord engineers had written things so carefully there was no garbage to be collected. In 2020, they rewrote that system in Rust, and discovered it now ran 10 times faster. 

Even executives and engineers at Amazon Web Services, the tech giant’s cloud computing platform, have become increasingly convinced that Rust can help them write safer, faster code. “Rust is uniquely positioned to give advantages there that I can’t get from other languages. It gives you multiple superpowers in one language,” says Shane Miller, who created a Rust team at AWS before leaving the firm last year. 

Perhaps most crucially for the cloud computing giant, a study of Rust-based code found it runs so efficiently that it uses half as much electricity as a similar program written in Java, a language commonly used at AWS. “So I could create a data center that runs 2X the workloads that I have today,” Miller says. Or do the same work in a data center that’s half the size, letting you tuck one into a city instead of planting it in an exurban field.

Some longtime contributors have been made a bit nervous by Rust’s success. As tech giants adopt the language, they’re also gaining more influence over it. They have enough money to pay engineers to work full time developing Rust; several of the leaders of Rust teams, for example, are employees at Amazon and Microsoft. Other valuable contributors have to do their Rust work in their spare time; Bos, for example, does contract work on Rust for Huawei, in addition to running her drone startup, but her role as the head of Rust’s library team is unpaid. 

It’s a common dynamic with open-source projects, Bos says: big companies can afford to participate more, and they can nudge a project toward solving problems that they care about but smaller firms may not. “It does give them some influence,” she says. But thus far, she says, none of the firms have done anything to ring alarm bells. Klabnik, who’s raised concerns about Amazon’s involvement in Rust (and who left Rust last year), agrees. “Do I worry about it? Yeah. Do I think it’s particularly bad or in a worse spot than many other places? No.”

In 2021, the major tech firms paid to set up a nonprofit Rust Foundation to support volunteer coders. Led for its first two years by Miller, it offers $20,000 grants for programmers who want to work on some major feature of Rust, and “hardship” grants for contributors in short-term financial need. It’s also funding the servers that host Rust’s code, and paying for a tech firm to be available to ensure that they run 24/7. In classic open-source style, that work was previously done by “two volunteers who were basically on call 50% of their lives,” Miller says. “One of them was a student in Italy.”

The language has, improbably and rapidly, grown up. If Rust was born in 2006, it is now heading out of its adolescence and into maturity. Auto firms are adopting Rust to build crucial code that runs cars; aerospace companies are taking it up too. “It’s going to be used everywhere,” predicts Dropbox’s Timmerman. Microsoft executives have even publicly suggested what many other tech firms are likely pondering behind closed doors: that it will use Rust more and more for new code—and C and C++ less and less. Ultimately maybe never.

All that old C and C++ code that’s already kicking around won’t vanish; it’ll remain in use, likely for many decades. But if Rust becomes the common way to write new code that needs to be fast and bare-metal, we could begin to notice that—very gradually, year by year—our software landscape will grow more and more reliable: less crash-prone, less insecure. 

That would astonish no one more than Hoare. “Most languages,” he says, “just die on the vine.”

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Computer Science > Programming Languages

Title: rust: the programming language for safety and performance.

Abstract: Rust is a young programming language gaining increased attention from software developers since it was introduced to the world by Mozilla in 2010. In this study, we attempt to answer several research questions. Does Rust deserve such increased attention? What is there in Rust that is attracting programmers to this new language? Safety and performance were among the very first promises of Rust, as was claimed by its early developers. Is Rust a safe language with high performance? Have these claims been achieved? To answer these questions, we surveyed and analyzed recent research on Rust and research that benchmarks Rust with other available prominent programming languages. The results show that Rust deserves the increased interest by programmers, and recent experimental results in benchmarking research show Rust's overall superiority over other well-established languages in terms of performance, safety, and security. Even though this study was not comprehensive (and more work must be done in this area), it informs the programming and research communities on the promising features of Rust as the language of choice for the future.

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Original research article, corrosion performance and rust conversion mechanism of graphene modified epoxy surface tolerant coating.

• 1 School of Petrochemical Engineering, Changzhou University, Changzhou, China
• 2 Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
• 3 Hubei Huaqiang Technology Co., Ltd., Yichang, China

A graphene modified epoxy surface tolerant coating was prepared, and the corrosion performance and rust conversion mechanism of the prepared composite coating on rusty carbon steel substrate was investigated. Scanning electron microscope (SEM), X-ray powder diffractometer (XRD), and infrared (IR) spectrum were used to confirmed the iron rust conversion performance by the reaction of phytic acid and rust. electrochemical impedance spectroscopy (EIS), polarization curve, and salt spray test were used to evaluate the corrosion resistance of low surface treatment coatings. Results indicated most of the rust were dissolved and transformed with the reaction of phytic acid and rust on the rusty carbon steel; graphene could effectively improve the compactness and protective performance of the epoxy surface tolerant coating.

Introduction

Heavy anticorrosive coating technology is the most economical and popular protection technology to slow down the corrosion rate of marine steel structures ( Arukalam et al., 2018 ; Zhu et al., 2020 ). However, in order to ensure the anticorrosive quality of the coating, the steel substrate needs to be sandblasted or shot blasted before construction, and in most cases, the surface cleanliness after treatment is required to meet the surface treatment level Sa2.5 specified in ISO 8501-1988. Sandblasting not only brings a lot of dust and noise pollution but also increases the construction cost. Due to the influence of construction conditions, coating conditions, and the changeable coastal weather, the marine steel structure cannot be coated immediately after sandblasting or can only be coated with rust ( Lei et al., 2021 ; Oliveira et al., 2021 ). In particular, some dead corners of complex steel structures cannot be treated by traditional sand blasting; besides, in the actual outdoor coating construction, it is impossible to completely and thoroughly sandblast steel. Even after sandblasting, the steel surface still has various degrees of rust and is often in a high degree of moisture. Therefore, it is particularly important to develop a simple and efficient anticorrosion coating with low surface treatment for long-term anticorrosion of equipment in the marine environment ( Liao and Lee, 2016 ; Feng and Yuan, 2020 ).

Low surface treatment coating is also called surface tolerance coating, which is an anticorrosive coating that can be applied on the corroded surface of steel with simple surface treatment or without treatment. Low surface treatment coating has excellent adhesion, wettability, permeability, and rust conversion. Good wetting and permeability are the basis of low surface treatment coatings ( Figueroa et al., 2020 ; Marano et al., 2020 ). On the one hand, the low surface treatment coatings contain active antirust pigments or rust conversion agents, which can transform active corrosion products, generate stable iron chelate, and become a part of the complete paint film as a way of inert fillers. On the other hand, adding chelating agent and corrosion inhibitor to rust primer can improve the passivation performance of metal substrate ( Jiang et al., 2020 ; Chang et al., 2021 ).

Phytic acid (PA) molecule has six phosphate groups which can combine with metal cations; it is an environmentally friendly rust inhibitor. Graphene (G) is the thinnest two-dimensional (2D) carbon material; its own unique nanostructure endows its perfect impermeability to any atoms and molecules under ambient conditions, and so G could be used as an excellent functional filler in anticorrosion coatings ( Gu et al., 2015 ; Bai et al., 2021 ; Mu et al., 2021 ). In our previous research, we have confirmed that the original iron ions absorbed on rusty carbon steel surfaces could be transformed by PA, and a dense film was formed with the reaction of PA and rust ( Xu et al., 2021 ). In this research, we prepared a G modified epoxy surface tolerant coating using PA as a rust conversion agent and G as a functional filler. The corrosion performance of as-prepared surface tolerant coating on rusty steel was studied by means of electrochemical measurements in 3.5 wt% NaCl solution. The results of this paper may provide an insight on providing a simple and efficient protection technology for corroded metals in the marine environment.

Experimental

All reagents including PA solution (PA content: 70 wt%) were purchased from Sigma-Aldrich and Aladdin and used without further purification unless otherwise noted. Epoxy resin (EP), C 12–14 alkyl glycidyl ether (AGE), and polyamide curing agent were purchased from Hubei Greenhome Materials Technology, Inc. G powder (5–10 layers, 10–200 μm diameter, 5–15 nm thickness, 99.5 wt% purity) was purchased from Ningbo Morsh Technology. Co., Ltd. Carbon steel (1 cm × 1 cm × 1 cm) was purchased from Yuxin Technology Co., Ltd. The polyo-phenylenediamine was prepared and used as G dispersant ( Cui et al., 2019 ).

The rusty carbon samples were prepared by dropping 3.5 wt% NaCl solution onto the clean sample and allowing it to react for 30 days at ambient temperature. Some loose corrosion products were formed on the surface of carbon steel (namely, rusty carbon steel).

Preparation of Graphene Modified Epoxy Surface Tolerant Coating

Firstly, 0.5 g G power was ultrasonically dispersed by 0.01 g polyo-phenylenediamine in 20 ml xylene solvent, and the mixture was stirred for 30 min, then 0.12 g PA, 20 ml AGE, and 30 g EP were added to the above mixture and ground until paint fineness reached 50 μm. Finally, 20 g polyamide curing agent was added, and the mixture was stirred for 30 min. The prepared composite coating (PA/G/EP) was applied to the rusty carbon steel cured at room temperature for 48 h; the coating thickness was 60 ± 2 μm. In the same way, a pure epoxy coating (EP) and PA with EP (PA/EP) were prepared and coated on rusty carbon steel at the same thickness.

Material Characterization

The rust and the PA chelate were analyzed by Intelligent Fourier Infrared Spectrometer (NICOLET 6700 FTIR) and X-ray powder diffractometer (Bruker-AXS D8 XRD). The cross-section surfaces of EP, PA/EP, and PA/G/EP were observed by scanning electron microscope (FEG 250 SEM). To prepare the cross-section surfaces, firstly, the coating was cured at 80°C for 24 h, and then the coating was quickly broken in a liquid nitrogen environment. Cross-section surfaces of different coatings were immediately treated with gold spraying to increase their conductivity (the thickness of the gold-plated layer was only 5–8 nm, which did not change the cross-section morphology of the prepared coatings), and at last the prepared cross-section surface samples were put in a vacuum chamber for SEM observation. The electrochemical test was performed at the electrochemical workstation (CHI-660E, China) using the three-electrode system. A platinum electrode was used as an auxiliary electrode, a calomel electrode was used as a reference electrode, and a carbon steel with 1 cm 2 exposed area was used as a working electrode. The corrosive medium was 3.5 wt% NaCl solution. The electrochemical impedance spectroscopy (EIS) curves after different immersion times were measured at an open circuit potential with an interference signal amplitude of 20 mV and a frequency range of 100,000–0.01 Hz. Electrochemical impedance fitting was performed using Zview software for data analysis. Three coating/electrode systems were prepared for each electrode, and the electrochemical test was repeated three times.

Results and Discussion

Transformation performance of pa on rusty carbon steel.

To investigate the transformation mechanism of PA on rusty carbon steel, infrared (IR) and XRD spectra of the rusty carbon steel, PA dropped on rusty carbon steel, and PA/G coating coated on rusty carbon steel are presented in Figures 1 , 2 , respectively. In the IR spectrum of rusty carbon steel ( Figure 1A ), the peaks at 883 and 787 cm −1 belonged to the bending vibration of -OH in α-FeOOH. The band of 682 cm −1 belonged to the bending vibration of -OH in β-FeOOH, and the band around 745 cm −1 was due to the bending vibration of -OH in γ-FeOOH. When the 5 wt% PA solution was dropped on the rusty carbon steel for 4 h, the characteristic peaks of rusty carbon steel almost disappeared, and some new characteristic peaks located at 1,004 and 2,847 cm −1 appeared ( Figure 1B ), which corresponded to the P-O stretching vibration and the stretching vibration of OH in the P-OH group, indicating that PA could reacted with rust and has been absorbed on rusty carbon steel. When the PA/G/EP was coated on rusty carbon steel ( Figure 2C ), most of the characteristic peaks of rusty carbon steel cannot be detected. Some new absorption peaks at 1,657 and 1,543 cm −1 came from the carbon skeleton vibration of the G ( Xu et al., 2021 ).

FIGURE 1 . The IR spectra for rusty carbon steel (A) , PA dropped on rusty carbon steel (B) , and PA/G/EP coating coated on rusty carbon steel (C) .

FIGURE 2 . The XRD spectra for rusty carbon steel (A) , 5 wt% PA solution dropped on rusty carbon steel (B) , and PA/G coating coated on rusty carbon steel (C) .

It can be found in the XRD (see Figure 2A ) pattern that the rust mainly contained diffraction peaks of NaCl (PDF 05-0628), FeOCl (PDF 39-0612), Fe 2 O 3 (PDF 16-0653), and Fe (PDF 50-1275). After adding PA, only NaCl characteristic peak was left, indicating that most rust was converted by PA ( Figure 2B ). No obvious rust characteristic peak was found in Figure 2C . In order to investigate the change of surface morphology of rusty carbon steel after the reaction between PA and rust, 5 wt% PA solution was directly dropped on the surface of rusty carbon steel. It could be seen that many corrosion pits appeared on the surface of rusty carbon steel ( Figure 3A ); when the PA reacted with the rust for 24 h, the corrosion pits almost disappeared and the surface roughness significantly decreased ( Figure 3B ), indicating that the PA has excellent rust conversion performance.

FIGURE 3 . SEM images of rusty carbon steel (A) and rusty carbon steel reacted with 5 wt %PA solution for 24 h (B) .

Generally, coatings with good physical barrier properties have excellent protective properties, and the dispersion state of fillers in composite coatings has a significant impact on the physical barrier properties of coatings ( Liu et al., 2013b ). In order to observe the dispersion state of G and PA in the composite coating, SEM was used to observe the dispersion performance of G in xylene solvent and the cross-section surface morphology of the coating, and the results are shown in Figures 4 , 5 , respectively. Figure 4 showed that the sheet structure of G was dispersed uniformly by polyo-phenylenediamine in xylene solvent, and no obvious agglomeration of G could be found.

FIGURE 4 . SEM images of dispersed G in xylene solvent at low magnification (A) and high magnification (B) .

FIGURE 5 . The SEM cross-section images of prepared coatings, (A) pure EP, (B) PA/EP, and (C) PA/G/EP.

The cross-section surface of pure EP was relatively smooth, and there were fluvial cracks parallel to the direction of crack propagation on the surface ( Figure 5A ), which was typical of brittle thermosetting polymers section characteristics. After adding PA in pure EP ( Figure 5B ), the crack of PA/EP coating section was reduced compared with that of pure EP, and some small holes were observed in the coating. When the PA and well-dispersed G slurry were added in EP ( Figure 5C ), the cross-section of the PA/G/EP coating was smooth; no obvious agglomeration of G or small holes could be observed, indicating that G could effectively improve the compactness of the EP coating.

Corrosion Performance of the G Modified Epoxy Surface Tolerant Coating

Figure 6 presents the open circuit potential ( E OCP ) variation of rusty carbon steel, EPPA/EP, and PA/G/EP coated on rusty carbon steel as a function of immersion time in 3.5% NaCl solution. The E OCP of rusty carbon steel was kept at −0.782 V and was basically unchanged. The E OCP of all coatings decreased to different degrees after the fluctuation at initial time and then remained basically unchanged after 240 h. Compared with pure EP, PA/EP and PA/G/EP exhibited much more enhanced E OCP . After 288 h immersion, compared to EP, the positive shift of E OCP as 0.11 V for PA/G/EP indicated that well-dispersed G has obvious corrosion inhibition, and this similar phenomenon has been reported by other researchers ( Cui et al., 2019 ). In our previous research, we confirmed that commercial G without dispersion was found to have almost no corrosion inhibition ( Liu et al., 2016 ).

FIGURE 6 . The open circuit potential curves of rusty carbon steel (A) , EP (B) , PA/EP (C) , and PA/G/EP (D) immersed in 3.5% NaCl solution after 240 h.

Nyquist and Bode plots are shown in Figure 7 for bare rusty carbon steel, EP, PA/EP, and PA/G/EP coated on rusty carbon steel after different immersion times in 3.5 wt% NaCl solution, as EIS is one of the most intensive and nondestructive testing techniques for investigation and prediction of the anticorrosion performance of organic coating in aqueous solution ( Liu et al., 2013a ; Liu et al., 2013b ). To quantitative analyze the corrosion resistance of these four systems, two appropriate equivalent circuits ( Figure 8 ) were used to fit the EIS data, and the fitting corrosion parameters are listed in Table 1 ; ( Xia et al., 2020 ). In Figure 6 , R s is the solution resistance, and R c and CPE -1 represent the coating resistance and coating capacitance, respectively. R ct and CPE -2 represent the charge-transfer resistance and double-layer capacitance, respectively ( Wang et al., 2021 ; Cui et al., 2018 ). Figure 8A was used to fit the EIS data for PA/G/EP during the 96-h immersion, and Figure 8B was used to fit the EIS data which have two time constants ( Pan et al., 2020 ).

FIGURE 7 . The EIS of rusty carbon steel (A) , EP (B) , PA/EP (C) , and PA/G/EP (D) immersed in 3.5 wt% NaCl solution after different times.

FIGURE 8 . The equivalent circuit used to fit the EIS data. (A) used for one time constant in EIS, (B) used for two time constants in EIS.

TABLE 1 . Electrochemical corrosion parameters fitted from the equivalent circuit.

Generally, the impedance modulus at the lowest frequency (|Z| 0.01Hz ) in Bode diagram can be used to evaluate the protective performance of the coatings. For the EIS results with two time constants, the time constant at the high frequencies corresponds to the capacitive behavior of the coating (or rust), and the time constant at the medium and low frequencies is assigned to the corrosion response of the metal substrates ( Liu et al., 2012 ).

For the bare rusty carbon steel ( Figure 7A ), the radius of the two capacitive arcs decreased gradually, and the impedance modulus at low frequency domain |Z| 0.01Hz decreased with time, indicating that the corrosion rate of rusty carbon steel increased in 3.5 wt% NaCl solution. Without coating protection, the rusty carbon steel would corrode and fail in a short time in 3.5% NaCl solution.

When the pure EP was coated on rusty carbon steel without surface treatment ( Figure 7B ), the porous rust in epoxy coating may reduce the compactness of paint film, form water-vapor channel, and then decrease its anticorrosion performance. The |Z| 0.01Hz of pure EP was only 3.56 × 10 5  Ω cm 2 after 240 h immersion in 3.5 wt% NaCl solution. Due to the water penetration and ionic species movement through the pure EP, the EP coating conductivity increased. The coating capacitance ( CPE -1 ) increased from 50.22 to 1,023 nF cm −2 , and the coating resistance ( R c ) decreased from 0.86 to 0.23 MΩ cm 2 during 240 h of immersion in 3.5% NaCl solution.

When the PA/EP is coated on rusty carbon steel ( Figure 7C ), the PA could react with rust, reduce the porosity and increase the adhesion of the coating to the rusty carbon steel, and then increase the compactness of paint film. The radius of two capacitive reactance arcs was doubled compared to pure EP. However, there were still two time constants during the whole immersion times; the coating resistance ( R c ) of PA/EP decreased from 18.6 to 1.56 MΩ cm 2 after 240 h immersion, indicating that water resistance of the PA/EP needs to be improved.

For PA/G/EP ( Figure 7D ), only one time constant was observed at the initial stage of 96 h immersion (Stage I), and then two time constants appeared after 240 h of immersion (Stage II). When the well-dispersed G is added into the EP, G can fill the structural and pinhole porosity of the EP and decrease the electrolyte diffusion towards the rusty carbon steel substrate, and the water diffusion coefficient is decreased greatly by the tortuous diffusion path ( Liu et al., 2016 ). However, water molecules would gradually penetrate the coating with the extension of immersion time and accelerate the corrosion of the metal. Thus, two time constants (or two capacitive arcs) appeared after 240 h of immersion.

The pure EP and PA/EP coatings exhibit two time constants in short-term immersion, while the PA/G/EP remains one time constant in a high frequency range during 96-h immersion. The impedance modulus at low frequency (|Z| 0.01Hz ) can represent the corrosion protection of coating/metal system, which is in inverse proportion to the corrosion rate. The |Z| 0.01Hz of the PA/G/EP-coated rusty carbon electrode was 5.9 × 10 8  Ω cm 2 after 240-h immersion ( Figure 6D ), which was far larger than that of pure EP (2.1 × 10 5  Ω cm 2 ) and PA/EP (7.3 × 10 6  Ω cm 2 ) coated rusty carbon electrodes after 240-h immersion ( Figures 6B, C ). These results indicated that PA/G/EP exhibited better corrosion protection for the rusty carbon steel than other coatings. The increase in impedance for PA/G/EP can be attributed to the hydrophobicity and barrier effects of G well dispersed in EP. Moreover, PA/EP protects the rusty carbon steel against corrosion better than the pure EP does, mainly due to the passivation capabilities of the PA molecules.

Figure 9 presents the polarization curves of rusty carbon steel, EP, PA/EP, and PA/G/EP coated on rusty carbon steel immersed in 3.5 wt% NaCl solution after 240 h at room temperature (∼25°C). The corrosion parameters calculated from the Tafel regions are listed in Table 2 ( Zhao et al., 2014 ). The corrosion current densities ( i corr ) calculated from Tafel regions of rusty carbon steel, EP, PA/EP, and PA/G/EP were 13.2, 0.813, 0.195, and 0.031 μA cm −2 , respectively. Compared to the bare rusty carbon steel, when the EP, PA/EP, and PA/G/EP were coated on rusty carbon steel, both of the absolute values of β a and β c increased, suggesting that the anodic oxidation and cathodic reduction reaction of rusty carbon steel were inhibited. It is important to note that the PA/G/EP exhibited more positive potential (−0.624 V) as compared to the rusty carbon steel (−0.778 V), and the i corr value of PA/G/EP (0.031 μA cm −2 ) was almost two orders of magnitude less than that of the rusty carbon steel (3.2 μA cm −2 ). The remarkably improved anticorrosion performance of PA/G/EP can be attributed to the synergistic effect of passivation performance of PA and physical barrier properties of G in the EP coatings .

FIGURE 9 . The polarization curves of rusty carbon steel (A) , EP (B) , PA/EP (C) , and PA/G/EP (D) immersed in 3.5 wt% NaCl solution after 240 h.

TABLE 2 . Corrosion parameters of rusty carbon steel, EP, PA/EP, and PA/G/EP immersed in 3.5 wt% NaCl solution after 240 h.

Salt Spray Tests

Figure 10 shows photographs of PA/G/EP after different exposure times (0, 24, 120, and 240 h) in neutral salt spray chamber. To accelerate the damage of salt spray to the paint film, a single-edged knife was used to cut “×” on the surface of the coating. PA/G/EP compactly absorbed on the metal substrate and little corrosion was observed after 24 h ( Figure 10B ). It could be seen that some white sodium chloride deposited on the surface of the PA/G/EP film, and a few yellow rusty spots were observed near the scratches after 120 h ( Figure 10C ). After the PA/G/EP was kept in the salt spray chamber for 240 h ( Figure 10D ), yellow rust on the scratches increased; however, the PA/G/EP was intact without obvious corrosion or foaming phenomenon in the blank area. This phenomenon can be explained in that, on the one hand, G can improve the compactness of the PA/G/EP, making it difficult for the corrosion media (mainly including chloride ions and water molecules) to penetrate into the coating. On the other hand, the PA/G/EP has a good self-healing ability, the PA in the coating has a good rust conversion effect of the coating, and PA can inhibit metal corrosion even at the scratches of PA/G/EP. The salt spray test results indicated the good anticorrosion performance of PA/G/EP coating.

FIGURE 10 . Photographs of PA/G/EP coating immersed in salt spray chamber after different times. (A) : 0 h; (B) : 24 h; (C) : 120 h; (D) : 240 h.

1) A graphene modified epoxy surface tolerant coating was prepared by adding G and PA in epoxy coating. Most of the rust was dissolved and transformed with the reaction of PA and rusty carbon steel. The well-dispersed G could inhibit the thermal shrinkage and improve the compactness of EP.

2) The |Z| 0.01Hz of the PA/G/EP-coated rusty carbon electrode was 5.9 × 10 8  Ω cm 2 after 240-h immersion, which was far larger than that of pure EP (2.1 × 10 5  Ω cm 2 ) and PA/EP (7.3 × 10 6  Ω cm 2 ) coated rusty carbon electrodes after 240-h immersion.

3) When the PA/G/EP was coated on rusty carbon steel, both of the anodic oxidation and cathodic reduction reaction of rusty carbon steel were inhibited in 3.5 wt% NaCl solution. The salt spray test results indicated the good anticorrosion performance of PA/G/EP coating.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding authors.

Author Contributions

Conceptualization, XG; methodology, HX; formal analysis, XG and JY; data curation, XG and JP; writing-original draft preparation, XG and SL; writing-review and editing, XG, CY, and SL; supervision, CY and SL; funding acquisition, JP. All authors have read and agreed to the published version of the manuscript.

The authors gratefully appreciate the financial support provided by National Science and Technology Major Project (2017-VII-0012-0107) and Zhejiang Key Research and Development Program (2019C03093).

Conflict of Interest

Author JY is employed by Hubei Huaqiang Technology Co., Ltd.

The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: corrosion, surface tolerant coating, graphene, rusty, EIS

Citation: Guo X, Xu H, Pu J, Yao C, Yang J and Liu S (2021) Corrosion Performance and Rust Conversion Mechanism of Graphene Modified Epoxy Surface Tolerant Coating. Front. Mater. 8:767776. doi: 10.3389/fmats.2021.767776

Received: 31 August 2021; Accepted: 11 October 2021; Published: 12 November 2021.

Reviewed by:

Copyright © 2021 Guo, Xu, Pu, Yao, Yang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Chao Yao, [email protected] ; Shuan Liu, [email protected]

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Advances in Materials Toward Anti-Corrosion and Anti-Biofoulings

• Open access
• Published: 14 February 2023

Fighting wheat rusts in China: a look back and into the future

• Jie Zhao   ORCID: orcid.org/0000-0001-5932-6708 1 &
• Zhensheng Kang 1  

Phytopathology Research volume  5 , Article number:  6 ( 2023 ) Cite this article

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Wheat rusts, including stripe, leaf, and stem rusts, are severe wheat diseases and cause huge yield loss in China annually. Benefiting from utilizing the genetic resistance wheat varieties, wheat stem rust has been effectively controlled since the 1970s; however, the wheat stripe and leaf rusts are still threating the wheat production in China due to lack of effective agricultural regulations. This review summarizes the research advances on wheat rust physiology, epidemiology, and fungicide resistance in China. In addition, the corresponding field management strategies for the integrated control of rust diseases are also discussed.

Wheat is one of the four staple crops in China. Stripe, leaf, and stem rusts are the three dominant rust diseases on wheat, which are caused by three Puccinia species in phylum Basidiomycota. Historically, the three wheat rust diseases caused severe epidemic incidents and significant wheat yield loss in China. Currently, stripe rust is the most devastating disease on wheat among the three in China. Several excellent reviews have summarized the occurrence and management of wheat stripe and leaf rusts in China (Shen and Wang 1962 ; Wang et al. 1988 ; Wu and Niu 2000 ; Li and Zeng 2002 ; Zeng and Luo 2006 ; Wan et al. 2007 ; Song et al. 2010 ; Wang et al. 2010 ; Chen et al. 2013 ; Kang et al. 2015 ; Ma 2018 ; Zhao et al. 2016a ,  2018 ; Zeng et al. 2022 ), but the research advances of wheat stem rust in China have not been comprehensively reviewed yet. Recently, many exciting progresses related to the wheat rust disease controls have been achieved in China. Here, we reviewed the history of the wheat rust in China and proposed the future perspective for the disease control from following aspects: the economic importance, epidemiology, fungicide resistance, and integrated managements.

Historical and current status of wheat rusts

Common wheat ( Triticum aestivum L.) is one of the most important staple cereal crops, the rice, corn, wheat, and potato. China is the largest wheat-producing and consuming country, which produces an annual yield of over 128 million metric tons, accounting for approximately 17.5% of the global wheat production based on the 10-year’s data from 2011 to 2020 (FAOSTAT 2020 ). In 2021, the total planting area of wheat is 23.6 million hectares, which produces approximately 137 million tons of wheat ( http://www.stats.gov.cn/ ). Therefore, wheat is of extremely and economically important crop in China. Currently, the major wheat-planting regions are distributed in five provinces, Shandong, Hebei, Henan, Jiangsu, and Anhui, which is also known as ‘the Huang-Huai-Hai winter wheat areas’ (Wan et al. 2007 ).

Wheat rusts, including stripe rust (or yellow rust) (Fig.  1 ), leaf rust (or brown rust) (Fig.  2 ), and stem rust (or black rust) (Fig.  3 ), are the dominant wheat fungal diseases. These wheat diseases significantly limit the yield reduction. Wheat rust is an ancient disease. The recorded occurrence of wheat rusts in China can be tracked back to as early as 4000 years ago, the time of the introduction of wheat into Hexi Corridor in Gansu during the Shang Dynasty (Li and Zeng 2002 ; Yang et al. 2016 ; Wei 2021 ). It was first documented in detail in a Chinese ancient agricultural book, Qimingyaoshu 《齐民要术》 by the author Sixie Jia during AD 533 to 544 in the Beiwei Dynasty. In this book, it was documented that wheat was vulnerable to ‘jaundice’ disease (actually stripe rust) and the disease was figuratively described as ‘jaundice’ because it resembled the color of newly born infants. Currently, wheat stripe rust is the most destructive disease among the three wheat rust diseases in China. It mainly prevails in the northwest and southwest China. Because of the severe epidemics, the stripe rust disease is listed in first class crop diseases management in the 333th bulletin by Ministry of Agriculture and Rural Affairs of the People’s Republic of China on September 15, 2020 ( http://www.moa.gov.cn/govpublic/ZZYGLS/202112/t20211224_6385489.htm ).

Single stripe signs of uredia between leaf veins of wheat stripe rust ( a ) and a nursery field showing severe stripe rust infection on wheat plants at elongation stage in Mianyang, Sichuan on March 18, 2011 ( b )

Symptoms of leaf rust on wheat leaves. a A few uredia at early stage of the development. b Numerous uredia produced on a leaf at late stage of the development

Symptoms of stem rust in wheat fields. a Uredia on a diseased stem. b Uredia on awns and glumes of a wheat head

Wheat leaf rust usually takes place in the North China Plain, the middle-lower reaches of the Yangtz River, southwestern and northeastern regions of China (Liu and Chen 2012 ). Wheat leaf rust has been well controlled in China in the last decades, but the epidemic of the disease has often occurred in many wheat-growing provinces, especially in ‘Huang-Huai-Hai regions’ recently (Zhao et al. 2008 ; Zhang et al. 2018 , 2020b ; Wang et al. 2022b ). The increasing incident of wheat leaf rust has potentially threatened the wheat production in these regions, and is a major rust disease after stripe rust in China.

Wheat stem rust primarily occurred in the northeastern spring wheat-growing region of China (Zeng et al. 1963 ; Li and Zeng 2002 ). This disease has been problematic in China prior to the 1970s. However, the disease rarely occurs in China nowadays (Han et al. 2010 ; Li et al. 2017 ), which benefits from extensive application of wheat cultivars that carry the stem rust-resistant gene Sr31 since the 1970s (Li and Zeng 2002 ). Although Ug99 (race TTKSK) and its variants that successfully overcome the resistance of Sr31 and have widely spread from the origin of Uganda to many other African and Asian countries ( https://rusttracker.cimmyt.org/?page_id=260 ), Ug99 has not been detected in China yet (Cao et al. 2007 ). However, most of tested Chinese native wheat cultivars (98.3% out of 118 varieties) are highly susceptible to Ug99. Ug99 also overcomes Sr21 and Sr38 that are two key resistance genes to stem rust in China. Therefore, invasion of Ug99 lineage races to China is of significantly potential risk. Regulations to prevent the invasion of Ug99 races are necessary.

Severe impacts recorded in the last 70 years

Prior to 1949, several severe epidemic incidents of wheat stripe rust were reported in Sichuan and Fujian provinces in 1939–1940, which resulted in a yield reduction up to 15% and 60%, respectively. In the 1940s, the disease severely occurred in the middle regions (Guanzhong plain) of Shaanxi Province, especially in the years of 1942, 1946, 1948, and 1949 (Li and Zeng 2002 ). Since 1950, China has encountered five nationwide severe wheat stripe rust epidemics, which took place in 1950, 1964, 1990, 2002, and 2017, respectively. These epidemics resulted in the wheat rust outbreak in a total of 550 million hectares, leading to the yield loss up to 13.8 million metric tons (Li and Zeng 2002 ; Ma 2018 ). The most sever epidemics occurred in 1950 and 1964, which affected the growing area over 13.33 million hectares, with a yield loss of 6 million and 3.2 million metric tons, respectively (Li and Zeng 2002 ). From 1972 to 1983, several severe stripe rust epidemic events occurred in the key oversummering (Qinghai, Gansu) and overwintering regions, which are distributed in Sichuan, Shaanxi, Henan, and Hubei provinces. Each incident resulted in the infection of wheat areas approximately 1.33 million to 2.0 million hectares (Li and Zeng 2002 ). In addition, large-scale epidemics caused by the disease occurred in 1975, 1983, and 1985, resulting in an estimated crop yield reduction up to 0.865 million, 1.074 million, and 0.85 million metric tons, respectively. In 1991, an extremely severe nationwide epidemic took place in Gansu, Ningxia, Shaanxi, Henan, Hubei, and Shandong provinces, which destroyed approximately 6.53 million hectares of wheat and caused a conspicuous crop yield loss of 0.434 million metric tons, although the fungicides were timely applied (Li and Zeng 2002 ). Based on the data acquired from 2006 to 2015, the average yield reduction caused by wheat stripe rust is approximately 0.159 million metric tons annually (Liu et al. 2016 ). The most recent large scale of stripe rust epidemic occurred in 2019, which is believed infecting two million hectares of wheat. Notably, no significant yield loss was observed due to the application of fungicides.

Serious epidemics caused by wheat leaf rust have been reported in winter wheat-growing areas of northern China and spring wheat-growing areas of northeastern China. This disease has led to a disastrous decrease in yield during the 1950s–1980s (Hu and Roelfs 1985 ; Li and Zeng 2002 ; Zhou et al. 2013 ; Peng et al. 2016 ). In this period, four moderate epidemics of leaf rust occurred in the north winter wheat-planting areas in 1969, 1973, 1975, and 1979, respectively, which also resulted in a huge yield reduction (Li and Zeng 2002 ). Since the late 1990s, five severe leaf rust epidemics in China have been documented in the year of 2008, 2009, 2012, 2012, and 2015 (Zhou et al. 2013 ; Zhang et al. 2015 , 2020b , 2020c ; Wu et al. 2019 ), and the most severe epidemic of leaf rust occurred in Anhui, Gansu, Henan, Sichuan, and Shanxi provinces in 2012. It damaged more than 15 million hectares of wheat growing area and caused a yield reduction near 3 million metric tons (Zhou et al. 2013 ; Wu et al. 2019 ).

Wheat stem rust is known as a serious issue in wheat-growing regions before the 1970s, especially in spring wheat growing regions of northeastern China, where nine severe epidemics were reported from 1923 to 1964 (Li and Zeng 2002 ). Two most severe wheat stem rust epidemics occurred in 1923 and 1948, which caused a massive yield reduction of 7.4 million and 5.6 million metric tons, respectively (Wu et al. 2020b ). In 1956, 1958, and 1964, the moderate and severe large-scale epidemics occurred in ‘Jiang-Huai region’ (also known as ‘Yangtz-Huaihe region’), from 1949 to 1966. Each epidemic caused a massive yield loss. For instance, in 1956, the epidemic in Jiangsu and Anhui provinces caused a noteworthy yield loss up to 1.0 million metric tons (Li and Zeng 2002 ). Since the 1970s, wheat stem rust has not been a notable issue and the pathogen is considered as opportunistic pathogen and cannot cause a serious threat to wheat production. Therefore, wheat stripe rust is the most destructive rust disease and more attentions should be paid to control this disease.

The causal agents

Stripe rust, leaf rust, and stem rust on wheat are caused by different Puccinia species in Pucciniaceae family of phylum Basidiomycota. Wheat stripe rust is caused by Puccinia striiformis Westendorp f. sp. tritici Eriksson ( Pst ) [syn. P. glumarum (Schumacher) Erichsen et Hennings] (Fig.  4 a, b). Traditionally, P. striiformis f. sp. tritici is one of five different formae speciales (f. sp., pl.) of P. striiformis (Eriksson 1894 ; Stubbs 1985 ). Whereas, based on morphological and genomic data, P. striiformis (stripe rust agents of wheat, Aegilops , Elymus, and barley) were clustered into the same clade. Therefore, they were all re-designated as P. striiformis (Liu and Hambleton 2010 ). Wheat leaf rust is caused by P. triticina Eriksson ( Pt ) (syn. P. recondite Roberge ex Desmaz f. sp. tritici Eriksson et Hennings) (Mains 1932 ) (Fig.  4 c, d); while wheat stem rust is caused by P. graminis f. sp. tritici Eriksson et Hennings ( Pgt ) (Fig.  4 e, f). The differences are also reflected by the distinct uredia and urediospores of three rust species, where they exhibit differences in color, spore size and cause different symptoms on the hosts.

Urediospores and teliospores of the wheat stripe, leaf, and stem rust fungus. a , b Urediospores ( a ) and teliospores ( b ) of Puccinia striiformis f. sp. tritici . c , d Urediospores ( c ) and teliospores ( d ) of Puccinia triticina . e , f Urediospores ( e ) and teliospores ( f ) of Puccinia graminis f. sp. tritici

Primary hosts and alternate hosts

Primary hosts (uredial host).

The wheat rusts Pst , Pt , and Pgt are obligate parasites. These pathogens primarily infect wheat, other cereal crops, and grasses. By infecting these hosts, they go through the uredial or telial stages (Stubbs 1985 ). The monocot plants Triticum , Aegilops , Agropyron , Bromus , Elymus , Hordeum , and Secale are all vulnerable to Pst (Stubbs 1985 ). In fact, many approaches have been made to determine the susceptibility of grass plants to Pst , Pt , and Pgt (Ling 1945 ; Lu et al. 1958 ; Peng and Chen 1987 ; Wang et al. 1987 ; Niu et al. 1991a , 1991b ; Yuan et al. 1994 ; Wei et al. 2021 ; Qin et al. 2022 ; Li and Zeng 2002 ). Currently, 88 grass species (including varieties) from 16 genera in the family Poaceae could serve as uredinial hosts or accessory hosts for Pst (Li and Zeng 2002 ). However, Pt isolated from leaf rust of six grass species, Agrimonia Pilosa , Bromus inermis , Elymus dahuricus , E. sibiricus , Roegneria penduline , and R. ciliaris , could infect wheat (Wang et al. 1987 ), suggesting that these plants assist the wheat leaf rust prevailing in field.

Alternate host (aecial host)

The pathogens Pgt , Pt , and Pst are known to be heteroecious and macrocyclic. The have to infect alternate hosts to complete the sexual reproduction. For Pgt and Pt , their alternate hosts were discovered over a century ago (de Bary 1866 ; Jackson and Mains 1921 ); however, the alternate hosts for Pst remained to be mysterious till 2010 (Jin et al. 2010 ). Now it is known that Berberis and Mahonia are the alternate common hosts for Pgt and Pst (Roelfs 1985 ; Jin et al. 2010 ; Zhao et al. 2013 ; Cheng et al. 2022 ). Notably, there are some differences for Berberis and Mahonia species or subspecies when they serve as alternate hosts for Pgt and Pst . For example, Berberis circumserrata could be an alternate host for Pst but not for Pgt (Roelfs 1985 ; Zhao et al. 2013 ). There are 215 endemic Berberis and 36 endemic Mahonia species in China, while there are 500 Berberis and 60 Mahonia species around the world (Ying and Chen 2001 ). So far, more than forty Chinese Berberis species and four Mahonia species/subspecies have been reported to serve as alternate hosts for Pst (Zhao et al. 2013 , 2016b , 2018 ; Du et al. 2019 ; Zhuang et al. 2019 ; Cheng et al. 2022 ). However, only one endemic Berberis species, the B. amurensis Rupr., was identified as an alternate host for Pgt in China (Zeng et al. 1963 ). Under field conditions, Pgt infects five Berberis species, B. aggregata , B. brachypoda , B. potaninii , B. shensiana , and B. soulieana , and sexual reproduction of this rust is completed during the infection of these hosts (Zhao et al. 2015 ). These observations clearly indicated that the above mentioned Berberis species are alternate hosts for Pgt .

Although many Thalictrum , Isopyrum , and Clematis species in Ranunculaceae family, and a few Anchusa and Echium species in the Boraginaceae family have been identified as alternate hosts for Pt (Chester 1946 ; Sibilia 1960 ; d’Oliveira and Samborski 1966 ), only four meadow rue ( Thalictrum ) species are the native alternate hosts in China. These species were identified as T. minus L., T. petaloideum L., T. minus var. hypoleucum , and T. baicalense recently (Zhao et al. 1994 , 2021 ).

Life cycle of the rusts

Pst , Pgt , and Pt are the heteroecious, macrocyclic rust fungi. They complete their life cycle with five different types of spores on two unrelated hosts (Fig.  5 ). Their full life cycle includes asexual and sexual stages. Under favorable conditions, basidiospores generate from teliospores. After germination, it can infect an alternate host to produce pycnia and pycniospores, as well as receptive hyphae (trichogyne) and paraphyses. With these mating type and receptive hyphae, they complete their sexual life cycle and consequently produce aecial clusters from abaxial leaves, where the aeciospores generate inside of the aecial clusters. Once the aecial clusters broke, aeciospores are released from aecial clusters and spread by wind to infect primary hosts, wheat and grasses. Urediospores are produced after aeciospores infect the primary hosts. However, teliospores are primarily formed in wheat host tissues at a late wheat growth stage.

Life cycle of Puccinia striiformis f. sp. tritici

Wheat rust epidemiology

The wheat stripe rust epidemic in China can be divided into different epidemiological regions. In fact, the epidemiological regions of the disease are consistent (Li and Zeng 2002 ) till 1995, when Zeng and the colleagues proposed that the Chinese epidemiological region of wheat stripe rust can be divided into three regions (Zeng and Sun 1995 ). Based on a combined method of large-scale and long-term field surveillances, geographic information system (GIS) system and molecular data, they divided the epidemiological regions into oversummering region (for the autumn spores), winter Pst -reproducing region that for the spring spores, and spring epidemic region (Chen et al. 2013 ). Later, Zeng and Luo ( 2006 ) proposed to subdivide China’s main stripe rust epidemiological region into 15 epidemiological zone according to the geographic features, crop cultivation modes, the regularity for pathogen oversummering and overwintering, and the frequency of stripe rust epidemics. It is worth to mention that because of the unique geography, the Yunnan epidemiological region is relatively independent because the pathogen can complete the disease cycle and over-summering and over-wintering without traveling to other regions (Li and Zeng 2002 ). As a result, this epidemiological region is almost isolated from other regions. However, recent studies revealed that the Yunnan epidemiological region and other southwestern epidemiological regions are also involved in wheat stripe rust epidemics in China (Awais et al. 2022 ; Huang et al. 2022 ; Ju et al. 2022 ; Zhan et al. 2022a ). In addition to Yunnan region, Tibet and Xinjiang also developed to be the independent stripe rust epidemiological regions (Li and Zeng 2002 ; Hu et al. 2017 ; Awais et al. 2022 ). Importantly, Xinjiang and other Chinese provincial Pst populations are all isolated from that of Pakistan due to extremely high genetic divergence (Awais et al. 2023 ). Chen et al. ( 2013 ) considered that Chinese stripe rust epidemiological regions include oversummering regions, winter- Pst reproductive regions, and spring epidemic regions. The oversummering regions include Gansu (area of Longnan, Tianshui, Dingxi, Linxia, Pingliang, Qingyang, and Gannan), Ningxia (Guyuan), Qinghai (Haidong), Shaanxi (Baoji), and Sichuan (Ganzi, Aba, and Liangshan area). However, the winter- Pst reproductive regions include low mountain, valley, mountain dam, and plain areas in Sichuan, South Shaanxi, Northwest Hubei, Yunnan, Guizhou, and Chongqing. While, the spring epidemic regions are the most of winter wheat-growing regions, including the ‘Huang-Huai-Hai Plain’, the regions of Beijing, Tianjin, Hebei, Henan, Shandong, Jiangsu, Anhui, the Guanzhong Plain of Shaanxi, and mid-lower reaches of Yangtz River.

For wheat stem rust, spring wheat-growing regions of Northeast China and Inner Mongolia, Northwest China, and wheat-growing regions of South Yunnan Province (Dehong, Honghe, Wenshan, and Simao regions) are important epidemiological areas. Weak winter wheat-growing regions of middle and lower reaches of Yangtz River and Sichuan (Ganzi) are regular epidemiological areas. Wheat-growing regions of Fujian Province and Southeastern coastal regions (Guangdong and Guangxi provinces) are also epidemiological areas (Wu and Huang 1987 ; Cao and Chen 2009 ).

Wheat leaf rust frequently occurs in wheat-growing regions of Southwest China and the mid-lower reaches of Yangtz River, but many of them appear in Yangtz River reaches, ‘Huang-Huai-Hai Plain’, and southwestern China. Occasionally, severe epidemics can occur in wheat-planting regions of North and Northeast China, and even Northwest China (Jin et al. 2017 ; Zhou et al. 2013 ).

The disease cycle of Puccinia species

Puccinia species are obligate pathogens when they infect wheat, where they fully depend on this living host to complete disease cycle. Temperature is the key factor for their disease cycle, and the rust diseases require different temperature for their growth. Wheat stem rust prefers higher temperature (opt. 30°C) than wheat leaf rust (opt. 25°C) and wheat stripe rust (opt. 12–15°C) (Roelfs et al. 1992 ). Cool and humid weather favor the development of wheat stripe rust. By contrast, high temperature inhibits the disease development (Rapilly 1979 ). In China, wheat stripe rust complete disease cycle by windborne urediospore infection, including oversummering and overwintering spores and the spores of infected autumn-sown wheat (Li and Zeng 2002 ). In susceptible hosts, the temperature for Pst oversummering period cannot exceed 23°C (max. aver. Temp. of a 10-day duration) in July and August, the two hottest months (Li and Zeng 2002 ; Zeng and Luo 2006 ). In general, the lowest altitude for Pst oversummering is over 1600 m above sea level, where the highest average temperature is typically below 23°C. Urediospores in oversummering areas are spread to autumn-sown wheat seedlings by wind in the local and overwintering areas, where the pathogen infects the plants and develops the stripe rust. In addition, the lowest temperature for Pst overwintering period is −6°C to −7°C from December to next January which are the coldest months. However, as long as the wheat seedlings are covered by snow, these pathogens can safely overwinter even if temperature drops to −10°C (Fig.  6 ) (Li and Zeng 2002 ). Pst usually overwinters in infected wheat tissues in the form of hyphae. In these regions, wheat grows slowly in autumn and winter, which is usually warmer than other regions. Under such circumstances, Pst continuously grow on infected wheat plants during winter and subsequently develop as the Pst -reproducing regions. South Henan, North Hubei, Longnan of South Gansu, South Shaanxi, and Sichuan Basin are the primary overwintering regions (Li and Zeng 2002 ; Chen et al. 2013 ). In spring, the pathogens in overwintering regions are transmitted to wide wheat-growing regions in East China and other regions to cause inter-regional epidemics.

Autumn-sown winter wheat seedling leaves showing developing stripe rust infection underneath snow patches in Baoji, western of Shaanxi Province in China, based on field observations on December 14, 2015

Importantly, Chinese researchers found that in spring of the Northwest oversummering areas, such as Qinghai, Gansu, Western Shaanxi, and Tibet, Pst basidiospores can infect susceptible barberry to complete their sexual cycle (Zhao et al. 2013 , 2022 ; Wang et al. 2016 ; Chen et al. 2021a ; Liu et al. 2021 ; Du et al. 2022 ). In some regions, such as Qinghai, Shaanxi, and Gansu, susceptible barberry released basidiospores are the major source of infection, and often cause the epidemics of wheat stripe rust (Chen et al. 2021a ; Liu et al. 2021 ; Zhao et al. 2022 ). Nevertheless, it was found recently that in Tibet, Pst can infect susceptible barberry to complete their sexual reproduction in autumn (Du et al. 2022 ), but whether susceptible barberry is related to stripe rust infection on wheat is unknown.

Unlike other rusts, wheat leaf rust has wider oversummering and overwintering areas in China. In particular, in some places, Pt urediospores can continuously infect the young wheat stumps after harvesting and are preserved in the local for oversummering. In autumn, the pathogens further infect the winter wheat seedlings that are sown in autumn season to cause leaf rust and overwinter in the infected wheat tissues in the form of hyphae. Generally, the frequency of overwintering in warmer regions is higher than that in cold regions, and the frequency of overwintering is positively correlated to the level of wheat leaf rust epidemic in the coming spring. The epidemic is mainly attributed to the continuous re-infection via the windborne urediospores.

In contrast, wheat stem rust has narrow overwintering areas due to the nature of urediospores that are sensitive to cold. As such, the pathogens overwinter in southeastern regions (i.e. Fujian, Guangdong) and South Yunnan rather than in north wheat-producing regions. The rust can parasitize wheat plants in overwintering areas in which the average minimum temperature in December to next January is above 10°C (Huang et al. 1993 ). Pgt can attack autumn-sown wheat seedlings in Shandong Peninsula and ‘Xuhuai regions’ of Jiangsu Province. However, they cannot survive the cold winter in most of these regions. Although few pathogens may successfully overwinter in these regions, they contribute inconsiderably to wheat stem rust epidemics (Huang et al. 1993 ). In spring and summer, spores in overwintering areas spread from south to north and west via the Yangtz River reaches, the North China Plain and reach spring wheat-producing regions in Northeastern and Northwestern China as well as Inner Mongolia. Thus, the dispersal of the pathogen causes vast wheat stem rust epidemics. Pgt urediospores mostly oversummer on late-maturing spring wheat and wheat stump in Northwestern and Southwestern China, and also on volunteer winter wheat in the plains of Jiaodong of Shandong Province and Huaibei of Jiangsu Province (Huang et al. 1993 ).

The race evolution of the pathogens

In nature, pathogens can rapidly evolve. The rule is also seen in the three wheat rust pathogens. Indeed, wheat rust pathogens can evolve to new virulent races with a high frequency in the field. New races often overcome the resistance of wheat varieties and cause disease. Some of the races dominate epidemics in the field by overcoming a certain resistance gene and evolve as the emerging new races.

The Pst races

Race identification of Pst in China was commenced in the 1940s by Fang ( 1944 ), who identified nine races from isolates in southwestern of China. These pathogen races are mostly from Yunnan Province (Fang 1944 ). Later, Lu et al. ( 1956 ) identified 10 isolates that were collected from seven provinces in 1951 as 5 races which were used by Gassner and Straib on wheat cultivars Carsten V, Michigan Amber, Spaldings Prolific, Blé rouge Décosse, and Heines Kolbens (Gassner and Straib 1930 ). Based on the maximum scores of reaction on the differentials including Early Premium, Nongda 3, Bima 1, Bima 4, Liying 3, and Yupi, fifty Pst isolates collected in 1953–1955 were determined as 16 races, and 8 of which were recovered from Elymus sibiricus , E. chinense , and Agropyron spp. (Lu et al. 1956 ). Since 1957, CY (CY = Chinese yellow) series were assigned to Chinese Pst races, and later CYR (CYR = Chinese yellow rust) series designation for races of this rust has been used till nowadays. In addition, pathotypes that are virulent to a certain genotype of Chinese differential sets, such as Hybrid 46 (Hy46) pathotype, Suwon 11 (Su11) pathotype, Lovrin 10/13 (Lv10/13) pathotype, Guinong 22 (G22) pathotype, and Jubilejina 2 (Ju2) pathotype, were also determined as Pst races that were not designated to CYR series. Since the designation of physiological CYR series races (CYR1 to CYR34) (Table 1 ), it has been designated according to the race with an outbreak frequency higher than 10% and a continuous prevalence in China (Lu et al. 1963 ; Liu et al. 2017 ). During 1957–1961, 10 CYR races (CYR1–CYR10) were identified from 325 Pst isolates. Among the races, three of which, the CRY1, CYR8, and CYR3 were widespread (Lu et al. 1963 ). During 1963–1966, CYR1 and CYR10 were the dominant races, while CYR10 displayed the highest outbreak frequency in 1964, but CYR8 decreased to rare race. CYR13 was firstly found in Lintao County of Gansu Province in 1962 and it exhibited an increasing frequency from 6.4% to 16.3% during 1964–1966. By contrast, during 1971–1979, CYR1, CYR8, CYR10, and CYR13 displayed a decreasing frequency and were not detected any more after 1975. Meanwhile, CYR17, CYR18 (virulent to Abbondanza), and CYR19 rapidly developed into major races. CYR17 caused an epidemic in Shaanxi Province in 1965. It gradually developed to be dominant race during 1974–1976 in North and East China; whereas, CYR18 that was founded for the first time in Gangu County in Gansu Province exhibit an extremely low frequency of outbreak. At the same time, in Sichuan Province, CYR18 was prevalent, but CYR17 was not. In Gansu Province, however, CYR18 was conspicuous and CYR17 had a high frequency of epidemic. Both races showed high outbreak frequency in Shaanxi Province (Wang et al. 1986 ). Since 1975, the outbreak frequency of CYR17 and CYR18 remarkably decreased, but CYR19 rapidly increased as a major race, where the outbreak frequency reached the highest of 81.1% in all the countrywide races in 1977 after the first appearance in Qingsheng County of Sichuan Province in 1972 (Wang et al. 1986 ). During 1980–1985, the CYR19 was proved as a complex of races, which was further separately designated as CYR23 (previously 19-1); however, CYR24 (previously 19-3), CYR25 (previously 19-4), CYR26 (previously 19-2), CYR23, CYR25, and CYR26 were prevalent races, and CYR25 was predominant race (Wang et al. 1986 ). CYR20 was first found virulent to the wheat variety Fengchan 3 in Shaanxi Province in 1971 (SXIPP 1976 ). CYR21 was initially detected in the Pingliang of Gansu Province in 1975. However, both CYR20 and CYR21 were not developed to be the dominant races (Wang et al. 1986 ). In 1982, Su11 pathotypes that are virulent to wheat genotype Suwon 11 were first detected in an experimental field at Qinghai Academy of Agricultural Sciences (Li 1983 ; Wang et al. 1986 ). CYR22 was first detected in Tianshui of Gansu Province in 1975, which then developed to be the dominant race in Gansu and Shaanxi provinces with the outbreak frequency of 25.5% and 22.7% in 1983, respectively. Lv10 and Lv13 pathotypes that are virulent to wheat genotypes Lovrin 10/13 ( Yr9 ) were initially detected in Longnan of Gansu Province in 1975 and 1979, respectively (Kang and Li 1984 ; Kang et al. 1987 ). CYR27, also known as pathotype 82-1, was first detected in Xihe County of Gansu Province in 1980. Later, it reached a high outbreak frequency in 1983. The trend was promptly decreased in 1984 in the provinces Gansu, Shaanxi, Sichuan, Yunnan as well as eastern regions of China, including Shanxi, Hebei, Shandong, Henan, Jiangsu, Anhui, Hebei, Hunan, and Inner Mongolia (CNWRCG 1985 ; Wang et al. 1986 ). CYR28 is a Lv10 pathotype complex and CYR29 is also known as Lv13-1. Both races are the members of Lv10/13 pathotypes. They were first detected in 1983 and 1985, respectively (CNWRCG 1987 ). During 1986–1990, CYR29 rapidly became the top outbreak frequency race over others in 1988, and reached the maximum frequency of 40.3% in 1989. The frequency remained the highest in the following 2 years (Wu et al. 1993 ). Meanwhile, Lv10/13 pathotypes rapidly developed into a prevalent pathotype. Due to rapid development of CYR29 and Lv10/13 pathotypes, the susceptible wheat which was planted about 8.8 million hectares in 1990 and accounted for 62.7% of the total planted areas in that year, was suffered with severe wheat stripe rust epidemic (CNWRCG 1991 ). In contrast, CYR28 remained low outbreak frequencies consistently. During the same period, the outbreak frequency of CYR23, CYR25, and CYR26 races were rapidly decreased (CNWRCG 1991 ). In 1991–1996, CYR29 kept prevailing and emerged as the most dominant race till 1995, but it became inconsiderable to the rust epidemic since 1996. Although CYR25 ever developed as a second dominant race during 1991–1992, its outbreak frequency was low. CYR30, previously names as race 91-1, is virulent to the genotypes Hybrid 46 ( Yr3b , Yr4b , and YrH46 ). Similarly, CYR31 previously named as race 93-1, is virulent to genotypes Hybrid 46 and Suwon 11 ( YrSu ). CYR30 and CYR31 were first detected in Sichuan in 1991 and in Gansu in 1993, respectively; both pathogens have a broad virulence spectrum than CYR28 and CYR29. As a result, CYR 30 and CYR31 rapidly became third and second prevalent races during 1993–1995. In particular, CYR31 ever emerged as the top prominent race in 1996 (Wang et al. 1996 ; Wan et al. 1999 ). Notably, Hy46 and Su11 became the major pathotypes during 1994–1996, and they were further classified to 9 and 12 sub-pathotypes, respectively, based on their virulence differentiation (Wan et al. 1999 ). CYR32, a previous name Hy-3, is designated in 2002 and is more virulent than CYR30 and CYR31. This race was first detected in the wheat cultivar Red Abbondanza in Huangzhong of Qinghai Province in 1994 (Wan et al. 2003 ). The outbreak frequency of this race is comparable to that of CYR31, which are about 11.7% in 2000. However, in 2001, the outbreak frequency reached incredibly to 28.8% (Wan et al. 2003 ). CYR33 (also known as Su11-14 previously) is virulent on Suwon 11, which was designated in 2008. This race was detected in 1997 with an outbreak frequency less than 1%, but the frequency unbelievably jumped to 26.72% in 2007 (Chen et al. 2009 ). Since 2000, CYR32 and CYR33 become the dominant races (Wan et al. 2003 ; Liu and Chen 2012 ; Wang et al. 2014 ; Li et al. 2016b ; Wang et al. 2017 ; Jia et al. 2018a , 2021 ); with an exception of CYR33 that exhibited a remarkably low frequency (< 5%) in Gansu in 2018 (Jia et al. 2021 ). Based on the annual reports from 2010 to 2011, CYR32 and CYR33 were mostly detected in Gansu, Shaanxi, and Sichuan provinces (Liu et al. 2012 ). There are 133 races and pathotypes were identified from 1014 isolates that are collected from 14 provinces. Thirteen of which are CYR races, including CYR17, CYR20, CYR21, CYR23, CYR25, CYR26, CYR27, CYR28, CYR29, CYR30, CYR31, CYR32, and CYR33. The remaining 115 isolates were known pathogens (Liu et al. 2012 ), which increases 35 pathotypes than that of identified before 2004 (Wan et al. 2004 ). Su11 pathotypes include 586 isolates (57.8% of the total) and is followed by Hy46 pathotypes that consist 273 isolates (26.9% of the total). G22 pathotypes, known to be virulent on genotype Guinong 22 which harbors resistance gene Yr26 , Yr24 , and Yr10 , are spreading since the first detection of the sub-pathotype 9 (G22-9) in Pi County of Sichuan Province in 2009 (Liu et al. 2010 ). Due to rapid spreading, the outbreak frequency of G22-9 increased from 0.11% in 2009 to 10.56% in 2015. As the result, the sub-pathotype G22-9 promptly developed to be the dominant pathotype and therefore was designated as CYR34 in 2016 (Liu et al. 2017 ). Currently, CYR34, CYR33, CYR32, and G22 pathotypes are dominate races/pathotypes (Han et al. 2016 ; Li et al. 2016b ; Jia et al. 2018a , 2021 ). Meanwhile, more attention should be paid on monitoring the emerging pathotypes. For instance, the ZS pathotype, which is virulent to wheat genotype Zhong 4 (ZS). This pathotype was first detected from wheat cultivar Baomai in Taibai County of Shaanxi Province in 2003. It exhibits a similar virulence spectrum on 19 Chinese wheat varieties in addition to Zhong 4. (Li et al. 2016b ). However, a pathotype ZS-1 suddenly caused epidemics in Gansu Province during 2017–2018 (Jia et al. 2021 ). A rising concern is the high virulence pathotypes that have broken the fence of the resistance gene Yr-5 that exists in the genotype Triticum aestivum subsp. spelta var. album . This pathotype displays similar virulence to the widely distributed CYR32 and CYR34 races and currently has evolved to generate the same lineage pathotypes (Zhang et al. 2020a , 2022 ). Recently, more Pst races have been sporadically identified in a few provinces since 2012. Race identification of Pst is very important to understand temporal dynamics, and can guide Yr gene deployment in the epidemiological regions. It is equally important for managing wheat stripe rust and race-targeted wheat breeding program.

The Pt races

Pt race identification in China started from 1940 by professor Huanru Wang who temporarily worked at the Institute of Agricultural Research, Tsinghua University in Kunming, Yunnan Province (Wang 1947 ). He identified three races, the race 1, 63, and 123 from Yunnan isolates that were collected in 1940–1942 using the same international differential hosts applied by Mains and Jackson ( 1926 ). Later, Kening Wang identified 417 Pt isolates collected from 1949 to 1951 using the international differential hosts set; however, the differentials was not suitable for identifying Pt races of China (Wang 1961 ). Until the early 1970s, the uniform differential hosts set, including eight wheat cultivars, viz. Lovrin 10, 6068, INR66-331, Redman, Dongfanghong3, Fengchan 3, Baiyoubao, and Taishan 4, were used as Chinese differentials to differentiate Pt races. Meanwhile, local wheat cultivars were added to the differential hosts. Therefore, the non-uniform names of Pt races, such as Zhi, Chun, Yu, and Lu series, were used in designating isolates in different regions of China (Wang et al. 1982 ). By 1977, a uniform nomenclature was determined to designate Chinese Pt races with CL (CL = China leaf rust) plus a hyphen and a number (also Chinese Yezhong) series. Using this nomenclature rule, 1237 Pt isolates were identified annually from 18 provinces during 1974–1979, and finally were identified as 11 races by the Institute of Plant Protection, Chinese Academy of Agricultural Sciences, the College of Plant Protection, Hebei Agricultural University, and the Institute of Plant Protection, Heilongjiang Provincial Institute of Agricultural Sciences. Three out of 11 prevalent races were renamed as CL-1 (Yezhong 1), CL-2 (Yezhong 2), and CL-3 (Yezhong 3). The remaining 8 races, including Zhi 2 to Zhi 7, Zhi 13, and Shandong A, were not uniformly determined (Wang et al. 1982 ). In 1981, a combination of original standard differentials and additional eight wheat cultivars (Taishan 1, Zhong 5, Rulofen, Lovrin 12, Predgornaia 2, Avrora, Kavkez, and Kangyin 655) was used to differentiate Pt races. In 1986, 16 races, CL-4, CL-38, CL-34, CL-7, CL-2, CL-44, CL-3, CL-19, CL-29, CL-12, and CL-17, and 5 unnamed races with additional virulence patterns were identified from 113 isolates using eight Chinese differentials. Among them, CL-4 was the most prevalent race in China, with a highest 29% outbreak frequency (Hu and Roelfs 1989 ). It is worth to mention that Hu and Roelfs ( 1989 ) used 16 Thatcher near-isogenic lines to identify Pt races in China. They detected a virulence frequency of 84% to 95% on Lr2c , Lr14a , Lr14b , Lr21 , Lr17 , and Lr3 . Unified designated race 13, with virulence on Lr1 , Lr2a , Lr2c , and Lr3 , was prevalent across China. From 1996, 48 races, viz. CL-1 to CL-48 (also Yezhong 1 to 48), were identified in China. During 1976–1996, the dominant races, CL-1, CL-2, CL-3, CL-29, CL-38 (Yezhong series), and Lovrin 10 pathotypes (virulent to wheat cv. Lovrin 10, including CL-4, 34, 46, 19, and 45) have been detected annually (Yuan et al. 1983 , 1991 ; Yuan 1984 ; Chen et al. 1994 ; Yuan and Zhu 1995 ). In 1997, PHT (virulent to Lr1 , Lr2c , Lr3 , Lr3ka , Lr11 , Lr16 , Lr17 , Lr26 , and Lr30 ), PCR (virulent to Lr1 , Lr2c , Lr3 , Lr3ka , Lr11 , Lr26 , and Lr30 ), and THT (virulent to Lr1 , Lr2a , Lr2c , Lr3 , Lr3ka , Lr11 , Lr16 , Lr17 , Lr26 , and Lr30 ) were dominant races among 41 races identified from 110 isolates collected from nine provinces (Qin et al. 1998 ). During 1998–2000, four out of 162 races, the FHB, PHT, FHG, and THT, were identified from 479 Pt isolates and exhibit an outbreak frequency much higher than other races. Races TTJ, TRT, THD, FCJ, FCD, FHD, KHD, THB, and PHB in Shanghai, FHB in Hebei, PHT in Shandong, FHJ, FHG, FRG, and KRB in Shaanxi, and FHT, NHJ, PHJ, and THT in Yunnan were dominant races in the corresponding regions. In contrast, although the outbreak frequency of races FHB, PRF, and TMG were higher than 36 other races identified from 43 isolates in Jiangsu Province, only three isolates were detected among all isolates, and there were no dominant races in this region (Yang et al. 2002 ). Isolates with virulence to Lr2c , Lr3 , Lr2b , Lr16 , Lr26 , Lr10 , Lr37 , and Lr14b exhibited an outbreak frequency over 80%, and isolates displaying virulent to Lr1 , Lr2a , Lr9 , Lr11 , Lr14a , Lr29 , Lr18 , Lr14ab , Lr17 , and Lr28 showed a frequency around 50%. Notably, increasing number of isolates show virulence to Lr2a , Lr2b , Lr3 , Lr9 , Lr19 , Lr24 , Lr28 , and Lr29 , but there are also decreasing numbers with virulence to Lr1 , Lr3ka , Lr15 , Lr14B , Lr6 , Lr7 , and Lr30 in the 3 years (Yang et al. 2002 ). In addition, 79 races were identified from 613 Pt isolates during 2000–2006. The races PHT, THT, PHJ, and THJ were prominent in the field and were virulent to Lr1 , Lr2c , Lr3 , Lr11 , Lr16 , Lr17 , and Lr26 . An increasing virulence diversity has been seen in those years, although no pathotypes showed virulence to Lr9 and Lr24 (Liu and Chen 2012 ). In 2007, 96 isolates from Shaanxi, Hebei, and Sichuan provinces were discovered that, PHST and FHST in Shaanxi, THQT, THQS, THQR, THQN, and PHSP in Hubei, and THTT in Sichuan were dominant races, respectively. The outbreak frequency of isolates with virulence to Lr2c , Lr3 , Lr3bg , LrB , Lr11 , Lr14a , Lr14b , Lr16 , Lr25 , Lr26 , and Lr33 accounted for over 70% in the three provinces, and those isolates displayed avirulence to Lr9 , Lr24 , and Lr38 were null (Wu et al. 2009 ). To make a conveniently comparison for Pt races between countries, a set of wheat Thatcher genetic background-based near-isogenic lines with Lr1 , Lr2a , Lr2c , Lr3 , Lr9 , Lr16 , Lr24 , Lr26 , Lr3ka , Lr11 , Lr17 , and Lr30 was suggested to use (Jin et al. 2008 ). During 2009–2010, three races, the FCBQQ, PCGLN, and PCGLL, which are the three out of 48 races identified from 155 Pt isolates collected from seven provinces were determined to be prevalent races. Almost all isolates, except for four isolates, showed virulence to Lr26 , and none of them was virulent to Lr18 and Lr24 (Kolmer 2015 ). During 2011–2015, 158 Pt races were identified from isolates collected from 18 provinces. Six races, the THTT, THTS, PHTT, THJS, and THJT are the most prominent. In particular, THTT and THTS were widely spread (Zhang et al. 2020b , 2020c ). Over 90% of the isolates (2296) collected from 18 provinces in 2011–2013 were virulent to Lr1 , Lr2c , Lr3 , Lr3bg , Lr10 , Lr14a , Lr14b , Lr16 , Lr17 , Lr26 , Lr33 , Lr37 , Lr50 , and LrB (Zhang et al. 2020c ). More than 80% of the isolates (1143) from 15 provinces in 2014–2015 showed virulence to Lr1 , Lr2a , Lr2b , Lr2c , Lr3 , Lr3bg , Lr10 , Lr11 , Lr14a , Lr14b , Lr16 , Lr17 , Lr26 , Lr32 , Lr33 , Lr50 , and LrB (Zhang et al. 2020b ). In 2017, 52 races were identified from 1407 Pt isolates collected from nine provinces using 16 Thatcher near-isogenic lines ( Lr1 , Lr2a , Lr2c , Lr3 , Lr9 , Lr16 , Lr24 , Lr26 , Lr3ka , Lr11 , Lr17 , Lr30 , LrB , Lr10 , Lr14a , and Lr18 ), where THTT, THTS, PHTT, THKT, PHTS, THKS, and THJT were the dominant races. THTT, PHTT, and THTS in Sichuan, THTT, THKT, and THJT in Shandong, THTT and PHTT in Hebei, THTT and THTS in Hubei, Henan, and Gansu, and THTS and THTT in Anhui and Jiangsu provinces were the prevalent races, respectively (Jia et al. 2018b ).

The Pgt races

In China, Tu ( 1934 ) first identified six Pgt races in Guangdong Province in 1934, and subsequently, Yin ( 1947 ) identified fifteen races from Pgt isolates collected from twelve provinces in 1947. Later, the race 1 was detected in 15 sampling sites in Northeast China and race 2 was identified in Jiangsu, Hebei, and Shandong provinces (Wang et al. 1950 ). Wu and Huang ( 1987 ) summarized that, during 1959–1965 and 1973–1985, sixteen races, including 17, 19, 21, 21C1, 21C2, 21C3, 34, 34C1, 34C2, 34C3, 34C4, 40, 116, 194, 207, and Ketai 1 were detected from 10068 Pgt isolates in China. Of these races, race 21 and 34, and their race group (C series) were dominant. These races were virulent to Sr resistance genes Sr7a , Sr7b , Sr8 , Sr9a , Sr12 , Sr14 , Sr17 , Sr23 , and Sr29 , but avirulent to Sr11 , Sr15 , Sr21 , Sr22 , Sr24 , Sr26 , Sr27 , SrTmp , and SrTt-2 (Wu and Huang 1987 ). During 1956–1961, six races, the race 1 to race 6, were identified on a set of differential hosts that consisted of 12 wheat cultivars, viz. Hezuo 6, Songhuajiang 1, Songhuajiang 2, Gansu 96, Mailiduo, Tubuqi, Manggou 335A-531, Khapli, Fule, Einkorn, Reliance, and Kehua (Zeng et al. 1963 ). Three of which, race1, 2 and 3, were identified from 1700 Pgt isolates. However, race 1 was dominant race, and race 3 was rarely discovered (Zeng et al. 1963 ). In addition, race 4 and 5 were recovered from aecia produced on B. amurensis via artificial inoculation (Zeng et al. 1963 ). Based on rust tests using standard (international) differentials that are comprised of the wheat varieties Little Club, Marguis, Reliance, Kota, Arnautka, Mindum, Spelmar, Kubanka, Acme, Einkorn, Uernal, and Khapli, with additional wheat cultivars (Mianzi 52/Mianzi49) as accessory differentials hosts. As a result, 26 and 334 isolates, collected in Liaoning Province in 1960 and 1961 respectively, were determined as six races including 17, 21, 34, 40, 21C1 (C = Chinese), and 34C1 (Wu et al. 1964 ). The race 116 was first detected during 1952–1957 by the team of Institute of Northeast Agricultural Sciences and Institute of Applied Fungi, Chinese Academy of Sciences, but not recorded pathogenicity on wheat genotypes. This race was detected and identified from samples collected on wheat cultivar Mentana in Huaihua County in Hunan Province in 1982. This race was detected late than the race 40. However, both races were highly virulent to the wheat cultivar Vernal (Huang et al. 1984b ). Race 34C3, detected on the wheat cultivar Orofen that was introduced into China in 1970s and used as resistance germplasm against wheat stem rust, was avirulent to the wheat cultivar Rulofen that was introduced as a resistance germplasm to wheat leaf rust (Huang et al. 1984a ). By 1977, race 34C4 (provisionally 34CR), virulent to Orofen and Rulofen, was detected based on reactions on a set of differential hosts including Reliance, Mianzi 52, M2761, Huadong 6, Rulofen and Orofen (Huang et al. 1984a ). During 1990 to 1994, 19 races (pathotypes) that are 21C3CKH, 21C3CKR, 21C3CTR, 21C3CTH, 21C3CPH, 21C3CPR, 21C3CFH, 21C3CFR, 34C2MKH, 34C2MKR, 34C2MKK, 34C2MFK, 34C2MFR, 34MKG, 34MFG, 34MFK, 34C1MKH, 34C1MKR, and 34C1MFH were identified among 1224 Pgt isolates from 18 provinces (Yunnan, Fujian, Sichuan, Guizhou, Hunan, Hubei, Zhejiang, Shanghai, Jiangsu, Shaanxi, Henan, Hebei, Gansu, Inner Mongolia, Jilin, Liaoning, Heilongjiang, and Qinghai) of China (Yao et al. 1997 ). Among those races, race 21C3 and race 34C2 were dominant ones (Yao et al. 1997 ). The new race (or pathotype) 21C3CTR that is virulent to Sr11 was first detected in Emeishan of Sichuan Province in 1993, and later it reached an outbreak frequency as high as 31.0% by widely spreading in Sichuan, Yunnan, Hubei, Henan, Hebei, and Gansu provinces (Yao et al. 1996 ). During 2007–2008, four races 21C3CTH, 21C3CFH, 21C3CPH, and 34MKG were identified from 59 Pgt isolates in Heilongjiang, Sichuan, and Yunnan provinces. Of which, 21C3CTH was prevalent with high outbreak frequency of 72.9% (Han et al. 2010 ). During 2012–2013, 13 races (pathotypes), 21C3CTHTM, 21C3CTQSM, 21C3CTTSC, 21C3HTTTM, 34MKGQM, 34MRGQM, 34MRGSM, 34MTGSM, 34Oroll-MTGSM, 34Oroll-MRGQM, 34C3RTGQM, 34C3RKGQM, and 34C3RKGSM, were identified from 23 Pgt isolates collected from wheat plants and 30 from Berberis species. Two of which, 34C3RTGQM and 34Oroll-MRGQM, were prominent races. Six of these races, 34MRGQM, 34MRGSM, 34MTGSM, 34Oroll-MTGSM, 34Oroll-MRGQM, and 34C3RTGQM, emerged recently and were first detected with a combined virulence to Sr5  +  Sr11 (Cao et al. 2016 ). Over the past decade, many dominant races have decreased in the field. However, there is an exception that 21C3 and 34C2 have remained prominent with a consistently high outbreak frequency so far (Wu et al. 1964 ; Yao et al. 1993 ; Han et al. 2010 ; Cao et al. 2016 ).

Variable oversummering and overwintering regions for the pathogens

Variable oversummering regions of pst.

Intriguingly, many studies showed that most of the new Pst races in China were originally uncovered in northwestern regions and some of southern regions, especially in Longnan of Gansu Province and northwestern of Sichuan Province, such as CYR13, CYR17, CYR18, CYR19, CYR21, CYR22, CYR27, CYR28, CYR29, CYR30, CYR31, CYR32, and CYR34 (Wang et al. 1986 , 1996 ; Wan et al. 2003 ; Liu and Hambleton 2010 ; Liu et al. 2017 ). Due to the emergence of new Pst races, the resistance of wheat cultivars was often overcome in these regions. Molecular studies revealed that the Pst population in Gansu, especially in the Longnan region, had a high level of genetic diversity (Shan et al. 1998 ; Zheng et al. 2005 ; Duan et al. 2010 ; Lu et al. 2012 ). Therefore, the regions mentioned above are considered as the most important Pst genetic variation regions, and are also the origins of new Pst races. These races in turn provide vast Pst inoculum to the wheat plants grown in eastern regions. The formation of Pst genetically variable region is not known until recently. So far, more than 40 barberries ( Berberis spp.) and four Mahonia spp. that are native in China have been identified as alternate hosts for Pst and more than 10 Berberis species and at least two Mahonia spp. are widely distributed in Pst oversummering regions (Zhao et al. 2013 , 2016b ; Zhuang et al. 2019 ; Du et al. 2019 ; Li et al. 2021 ; Cheng et al. 2022 ) (Fig.  7 ). Importantly, it has been demonstrated that under natural conditions, sexual cycle of Pst in China occurs more frequently based on known and new races of Pst isolates that were recovered from naturally-rusted barberry (Zhao et al. 2013 ; Li et al. 2016a ; Wang et al. 2016 ), and Mahonia (Cheng et al. 2022 ). Accordingly, wide distributed Berberis spp. and frequent occurrence of sexual cycle of Pst resulted in the latently genetic recombination and the continual generation of new races, which represents the formation of oversummering Pst genetically variable regions in China.

The map showing extensive distribution of most of Chinese Berberis spp. and Mahonia spp. serving as alternate hosts for Puccinia striiformis f. sp. tritici in North-western area of oversummering areas, and a few Berberis spp. for P. graminis f. sp. tritici in Gansu, Shaanxi and Tibet in China based on data collections of field investigations during 2010–2020 (Zhao et al. 2013 , 2015 , 2016b ; Wang et al. 2016 ; Du et al. 2019 ; Li et al. 2021 ; Zhuang et al. 2019 ; Cheng et al. 2022 ). Geographic outline of oversummering areas were redraw according to a review by Wan et al. ( 2007 ) and Tibet of oversummering area was added. 1 North-western area. 2 South-western area. 3 Xinjiang area. 4 Northern area. 5 Tibet area. Map resource: http://bzdt.ch.mnr.gov.cn/ . Data resource: Information on barberry data in Northeast China from Yuanyin Cao’s laboratory at Shenyang Agricultural University, Shenyang, Liaoning Province

Pgt genetically variable regions

Based on the studies of Pgt isolates in 1963–1967 and 1973–1992, Yunnan, Sichuan, and, Guizhou provinces are known as Pgt genetically variable regions. In these regions, new virulent races emerge and accumulate more rapidly than other regions. One of the reasons is that the pathogens can oversummer and overwinter to complete their disease cycle locally (Huang et al. 1993 ).

Pt genetically variable regions

Although many Pt genetically variable regions in China have not been designated due to the lack of evidence, an increasing number of high genetic and virulence diversity have been found in the pathogen population habitats distributed in Hebei, Henan, Shandong, Sichuan, Yunnan, Gansu, and Shaanxi provinces (Xu et al. 2013 ; Ge et al. 2015 ; Kolmer 2015 ; Ma et al. 2020 ). However, these regions are considered unlikely the potentially variable regions for Pt in China due to low clonal population (Kolmer 2015 ).

High temperature-tolerant isolates

Temperature is a key factor that affects wheat rust fungi growth and development. Relatively, Pst requires the lowest high temperatures, which is lower than Pt and Pgt (Roelfs et al. 1992 ), as high temperature restricts the development of Pst . When the average 10-day temperatures are above 23°C in July and August, which is the two hottest months, can halt the development of the disease (Roelfs et al. 1992 ; Li and Zeng 2002 ). The data of global land–ocean temperature index indicate that the annual average temperature has arisen 0.85°C in 2021 ( https://climate.nasa.gov/vital-signs/global-temperature/ ). In China, especially the Central and East regions, it has increased 0.97°C (CMA 2021 ). Recently, studies on high-temperature tolerance have been investigated using a Chinese Pst population consisting of 126 isolates from 12 provinces. Results showed that the Chinese Pst population had a remarkable adaptation to high temperature and the average ET 50 values, a temperature that is required to obtain 50% of the maximum effect, were 24.1°C with a range of 18.46–27.01°C, which has passed the highest temperature limitation of 23°C (Zhang et al. 2013 ). Moreover, genetic diversity of Pst population had a nicely negative correlation with average ET 50 values as well as a significantly positive correlation with the coefficient of ET 50 variation, but there was no correlation with genetic diversity (Lian et al. 2016 ). Field investigations revealed that Pst can oversummer during 23–25°C in Pingliang of Gansu Province (Wang 2009 ), and that Pst can overwinter in high altitude with higher temperature and oversummer in lower altitude with lower temperature. The over-wintering altitudes can be seen in Tianshui of Gansu Province from 1800 m up to 2080 m, and oversummering altitude can be the place of 1650 m down to 1450 m. While, in Yunnan Province which is at a higher altitude, the oversummering altitude for Pst ranges from 2300 to 1950 m (Pan et al. 2011 ). Therefore, under high temperature conditions (> 23°C), high temperature-tolerant Pst isolates have greater potential to complete the disease cycle than high temperature-sensitive ones. The potential influence of high temperature-tolerant Pst isolates on wheat stripe rust occurrence should be under consideration. Recently, in the eastern coastal epidemiological regions of Zhejiang and Jiangsu provinces, wheat stripe rust is usually an ignorable issue because it normally develops slowly and sometimes stops infection in early April; however, it is not a severe issue until early May in 2019 (Ju et al. 2022 ). The outbreak is possibly due to the warmer weather where the high temperature-tolerant isolates prevailed. Following the global warming, the race dynamics of high temperature-tolerant Pst isolates should be paid more attention and taken necessary measures to manage wheat stripe rust in China.

Fungicide resistance of Puccinia species

There are a variety of fungicides used to control Puccinia species pathogen infection. One of the key fungicides triazole plays an important role in preventing wheat from rust disease infection. In China, fungicide application for wheat rust control can be tracked back to the 1950s (Ou and Meng 1958 ; Lu et al. 1962 ). Now, more than ten chemicals are used as fungicides to control this disease, such as sodium sulfanilate and fluorides; however, wheat often suffers from yield lose when severe epidemic hits (Wang et al. 1988 ). Nevertheless, those chemicals had been extensively applied to control wheat rust diseases in the 1960s–1970s, and made a considerable success (Wang et al. 1988 ). Notably, the fungicide triadimefon was introduced into China in 1976 and was locally synthesized by Institute of Elemental Organic Chemistry of Nankai University (Wang et al. 1988 ). This fungicide effectively controlled wheat rust infection by seed treatment and foliar spray inoculation (Wang et al. 1988 ). Additionally, other triazole fungicides, such as tebuconazole and hexaconazole, have been developed to control wheat rusts. Triazole type of fungicides has maintained high efficiency in controlling the wheat rusts for 5 decades. A worrisome situation is that following the long duration use of triazole type of fungicides, especially triadimefon, the insensitive and anti-fungicide isolates have been found in Chinese wheat rust populations (Cook et al. 2021 ; Zhan et al 2022b ). A recent study by Zhan et al. ( 2022b ) showed that there are about 7% of Pst isolates in total of 446 isolates collected from winter-producing regions and northwest oversummering regions exhibiting triadimefon resistance and cross-resistance to triadimefon, tebuconazole, and hexaconazole. However, the majority of the resistance isolates are from southwestern of China. The isolates in Xinjiang and Tibet epidemic regions are still high sensitive to triadimefon. Compared with the Pst isolates from Europe, United States, Ethiopia, and Chile, Chinese Pst isolates have a high percentage of fungicide-resistant mutants (Cook et al. 2021 ). Genetic analyses revealed that single-site mutation by Y134F substitution in the target gene of demethylase inhibitor (DMI; Cyp51 ) resulted in fungicide resistance in Chinese Pst population (Cook et al. 2021 ; Zhan et al. 2022b ).

Notably, fungicide-resistance has also been detected in Chinese Pgt population recently. A study by Wu et al. ( 2020a ) reported that low to moderate triadimefon-resistance had been detected in 29 Pgt isolates accounting for ~ 32.6% in the tested 89 Pgt isolates that were sampled from wheat and barberry in Heilongjiang, Liaoning, Sichuan, and Shaanxi provinces during 2013–2015. Chinese Pgt population had a positive correlation between resistance to triadimefon and carbendazim, and no cross-resistance to triadimefon, thiophanate-methyl, and kresoxim-methyl. In addition, triazole type of fungicides have been consistently used to control wheat leaf rust in China since the late 1970s. While, isolates of Pst and Pgt with the resistance to triazole fungicides have emerged in China. Although no evidence to demonstrate Pt isolates are resistant to fungicides, it is plausible to propose that the risk of anti-fungicide of Pt against triazole type of fungicide may need to be investigated.

Emergence of new rust races

Although wheat cultivars carrying resistance genes have been effectively used to control the three rusts, new races often overcome the resistance of these wheat cultivars and cause disease. As a result, many of which developed to be the prevalent races and cause huge yield reduction annually. The emergence and rapid accumulation of new pathogenic rust races are usually accompanied with the high level of threatening to wheat production. Due to the emergence of new pathogenic races, the resistance of many cultivated varieties are facing danger than ever before, where they turn to be vulnerable to the new emerged races. It has been observed that a few new strip rust races quickly diffused to other wheat-growing regions that are far away from their origin sites. These new races caused a severe interregional wheat stripe rust epidemic. So far, eight main cultivated wheat cultivars across China have been displaced (Li and Zeng 2002 ; Wan et al. 2007 ; Han et al. 2016 ). Recently, a newly-emergence race, named TSA-6 which is virulence to Yr5, has been identified in Shaanxi Province (Zhang et al. 2020a ). Later, it was detected in Qinghai Province (unpublished data). The Yr5 -virulent race and its mutant TSA-9 possess similar pathogenicity with dominant Pst races CYR34 and CYR 32, which are pathogenic to most of the 165 tested Chinese wheat cultivars (Zhang et al. 2022 ). Historically, in China, a new race could develop into a prevalent race within 6–9 years, and sometimes within the frame of 3–5 years after initial emergence (Lu et al. 1963 ; Wang et al. 1986 ; Wu et al. 1993 ; Jiang et al. 1996 ; Wan et al. 2003 , 2004 ; Li et al. 2016b ; Liu et al. 2017 ). Thus, the enhanced surveillance on the dynamics of new emerging Pst isolates should be taken in consideration.

New races of Chinese Pgt population have been intensively reported for nearly 5 decades since the 1970s. Dominant 21C3 and 34C0 race families have been existed for many years. However, during 2009–2015, three new races, 21C3CTTTM and 34C0MRGSM identified from wheat, and 34C3MTGQM identified from Berberis species become the dominant races in China (Zhao et al. 2013 , 2015 ; Li et al. 2018 ; Cao et al. 2019 ).

Recent studies have reported that although new races of China Pt population emerged over the past years, occurrence frequencies of new races were extremely low and new races were somewhat different from surveillance years (Zhang et al. 2020b , 2020c ). Generally, leaf rust epidemics are thought to be closely related to the appearance of new races, but the outbreaks of wheat leaf rust in China during 2011–2015 were considered as a result of climatic and host conditions instead of new races (Zhang et al. 2020b , 2020c ). Since 2011, no case with regard to new races developing to be prevalent races to cause wheat leaf rust epidemics in China during these years have been reported.

Invasion risk of alien races

Wheat rusts are air borne diseases where the fungal spores can spread with a long distance. Theoretically, the wind can help the spores travel across regions and even continents. In particular, human activities accelerate the spread by the travel between continents. In fact, the inter-continental spread of wheat rusts have become a major disease propagation means. Over the past 30 years, stripe rust has spread to Australia in 1979 (O’Brien et al. 1980 ; Wellings et al. 2003 ; Wellings 2007 ), New Zealand in 1980 (Beresford 1982 ), and South Africa in 1996 (Pretorius et al. 1997 ). A recent well known case is the spread of the Pgt race Ug99 (TTKSK) lineage that traveled from Uganda in 1999, and finally landed in Iran in 2019, demonstrating the incredible long-distance travel of wheat rusts (Fig.  8 ; relabeled based on data information from https://rusttracker.cimmyt.org/?page_id=22 ).

The re-labelled map sketch illustrating origin (Uganda indicated by red-dotted circle), evolution and dispersal of the Puccinia graminis f. sp. tritici race TTKSK (Ug99) lineage and potential invasion risk to China. Data resource: CIMMYT, September 2021 at https://rusttracker.cimmyt.org/?page_id=22

In China, since 1970s, wheat stem rust has been effectively controlled for 5 decades because of the cultivation of stem rust-resistant wheat cultivars. Notably, Pgt races have been found to mutate at a low frequency in the field, and two race groups, 21C3 and 34C, finally become dominant for nearly 5 decades since the 1970s (Wu and Huang 1987 ; Yao et al. 1998 ; Cao et al. 2016 ). However, the new Pgt race TTKSK (previously TTKS, also known as Ug99) breaks the resistance of Sr31 , a resistance gene that maintains a long-lasting protection from wheat stem rust infection for over a half century and introduced to most of the wheat variety worldwide. This race was first detected in Uganda in 1998 (Pretorius et al. 2000 ). Currently, Ug99 has developed to 15 Ug99 lineage variants through somatic recombination (Li et al. 2019b ), and each has a combined virulence not only to Sr31 but also to some of the eight important Sr genes, which are Sr 21, Sr24 , Sr30 , Sr36 , Sr38 , Sr9h , SrTmp , and Sr8155B1 . Since Ug99 race group has invaded Iran, much attention should be paid as they are geographically not far from China, although Ug99 and its variants have not been detected in China yet. In fact, only two (~ 1.7%) wheat varieties out of 118 in the tested Chinese wheat varieties are moderately resistant or fully resistant to the Ug99 race (Singh et al. 2006 ). Therefore, wind-borne spores of Ug99 lineage have a strong potential to be spread to China.

Discovery of the sexual cycle of the rusts

The sexual stage of Pgt has been known for a long time. The finding of susceptible barberry serving as alternate host has greatly pushed our understanding of Pst sexual cycle forward. It was recognized that susceptible barberry plays an important role in providing rust spores that cause primary stem rust infection of wheat in United States (Roelfs 1982 ). In China, although attempts were made to verify the role of barberry relating to occurrence of wheat stem rust under field conditions over the past decades (Wang 1955 ; Zhang et al. 1957 ; Wang et al. 1958 ; Zeng and Xue 1963 ), they all failed. Until recently, the existence of sexual cycle of Pgt in the fields has been discovered in China (Zhao et al. 2015 ). However, the role of susceptible barberry in a wheat stem rust epidemic is still not fully understood. Further work should be focused on this issue in China.

Since many Chinese barberry ( Berberis spp.) and Mahonia spp. were identified as alternate hosts for Pst , the occurrence of Pst sexual cycle has been intensively investigated under field conditions. Chinese researchers demonstrated that Pst could infect susceptible Berberis and Mahonia spp. which are native in China to complete the sexual cycle in spring (Zhao et al. 2013 , 2022 ; Wang et al. 2016 ; Liu et al. 2021 ; Chen et al. 2021a ; Cheng et al. 2022 ), and that Pst could infect endemic Berberis to achieve sexual reproduction in autumn in Tibet (Du et al. 2022 ). In regions such as Qinghai and Shaanxi provinces, where susceptible Berberis spp. and wheat grow adjacently, under this situation, barberry provides aeciospores as inoculum to cause stripe rust infection on wheat (Chen et al. 2021a ; Zhao et al. 2022 ). In addition, whether susceptible Mahonia spp. is involved in providing aeciospores as inoculum to trigger stripe rust outbreak on wheat also needs further investigation.

Attempts have also been made to demonstrate the relationship between Thalictrum spp. as alternate hosts of Pt and leaf rust on wheat and grasses, but the relationship remains obscure. In 1960s, Guichao Huang at Institute of Agricultural Sciences in Jiamusi, testified that rusts on Thalictrum spp. were related to leaf rust on Agropyron instead of leaf rust on wheat (Wang et al. 1987 ). In 1980s, Wang et al. ( 1987 ) reported that, in the Baishitougou village of Inner Mongolia, leaf rust on Agrostis spp. can complete sexual cycle on T. petaloideum ; however the aeciospores from T. minus , T. minus var. stipellatum , T. minus var. hypoleucum , and/or T. petaloideum failed to cause wheat leaf rust by artificial inoculation. Although a few Chinese Thalictrum spp. have been identified as alternate hosts for Pt , the role of Thalictrum spp. in the occurrence of leaf rust on wheat under natural conditions remains unknown. Sequence alignment of internal transcribed space (ITS) indicated that more than 20 aeciospores from susceptible T. baicalense plants had 95–96% of sequence similarity with P. triticina (Zhao et al. 2021 ). However, inoculation experiment of aeciospores on susceptible wheat cultivars were not conducted to justify the potential infection by Pt urediospores in fields.

Sources of Pst teliospores for alternate host infection

Teliospores are essential for infecting alternate hosts ( Berberis and Mahonia ) to invoke sexual cycle. Under favorable conditions, basidiospores, which germinate from teliospores, infect alternate hosts to initiate sexual reproduction in the three wheat rusts. Therefore, vigorous teliospore sources are associated with sexual stage of the three rust pathogens. Field investigations and laboratory experiments demonstrate that Pst teliospores can be produced at all growth stages and possess germination capacity in field. However, the teliospore production and germination rate are dependent of the fungi growth stage, weather condition, and locations (Chen et al. 2021b ). In addition, wheat straw stacks of diseased tissues are the harbor of Pst teliospores in oversummering regions, such as Gansu and Qinghai provinces (Chen et al. 2021b ). A study by Qin et al. ( 2022 ) reported that grass residues can harbor the overwintering Pst for the primary infection in the coming spring. Survival of Pst teliospores on grasses after overwintering can also serve as the potential source to infect alternate hosts of Pst .

Wheat stripe rust management

Planting rust-resistant wheat cultivars has been considered as an effective, economical, and green strategy to control wheat rust diseases. In China, comprehensive application of wheat cultivars carrying Sr resistance genes has been successful for long-term disease control. By deploying an integrated management strategy for wheat stripe rust, the disease has been effectively controlled in most wheat-producing areas since 2004 in China (Chen et al. 2013 ). After the year 2010, wheat stripe rust has led to the infection around 2.67 million hectares perennially, and caused annual yield loss around 0.17 million metric tons (Huang et al. 2018 ). One of the key reasons is that the resistance genes in wheat cultivars were frequently overcome by the emerging new races, resulting in the wheat cultivars to be vulnerable within a short period after released in the fields. Therefore, an integrated strategy should be considered to slow down the new rust race emergence.

Mining novel resistance genes for durable control

At present, 83 wheat stripe rust (yellow rust) resistance genes ( Yr ), viz. Yr81 - Yr83 , have been designated (McIntosh et al. 2017 ; Li et al. 2020 ). Of the 83 Yr genes, only Yr15 , Yr45 , and Yr61 possess effective resistance to prevalent Chinese Pst races (Zhang et al. 2020a ; Feng et al. 2022 ). Moreover, unnamed new Yr genes from current wheat varieties or other Triticum species, such as YrElm , YrElm1-4 , YrElm4 , YrLm2 , YrM97 , and YrM852 from Elymus mollis (Yang et al. 2009b , 2010 ; He et al. 2010 ; Xu et al. 2012 ; Bai et al. 2013 ; Zhang et al. 2014 ), YrHua , YrHy, YrH122, YrH9014 , YrH9020a , YrHua9020 , and YrHu from Psathyrostachys huashanica (Cao et al. 2005 ; Liu et  al. 2008 ; Yao et al. 2010 ; Tian et al. 2011 ; Ma et al. 2013 , 2015a , b , 2016 ; Liu et al. 2014 ), YrV1 , YrHV , YrWV , and YrV3 from Haynaldia villosa (Zhou et al. 2008 ; Hou et al. 2009 , 2013 ; Wang et al. 2011a ), YrCH5383 , YrL693 , and YrCH5026 from Thinopyrum intermedium (Hou et al. 2015 ; Huang et al. 2014 ; Zhan et al. 2014b ), and YrM8003 from rye (Xu et al. 2010 ), have been identified. In addition, 12 meta-quantitative trait loci (MQTL), including both quantitative resistance loci (QRL) and major resistance genes, were discovered from 194 QRL that have been identified previously (Cheng et al. 2019 ), which can be used for breeding stripe rust-resistant wheat cultivars by marker-assisted selection (MAS).

So far, 63 wheat stem rust resistance genes ( Sr ) have been identified worldwide (Mago et al. 2022 ). In China, eight Sr genes, including Sr9e , Sr26 , Sr31 , Sr33 , Sr37 , Sr38 , Sr47 , and SrTt3 , are still resistant to local Pgt races. Nevertheless, much attention should be paid to those races with combined virulence to the resistances Sr5 and Sr11 (Cao et al. 2016 ). The stem rust resistance genes have been confirmed to be effective against the dominant races 34MKGQM, such as Sr9e , Sr10 , Sr11 , Sr13 , Sr14 , Sr17 , Sr18 , Sr19 , Sr20 , Sr21 , Sr23 , Sr25 , Sr26 , Sr30 , Sr31 , Sr32 , Sr33 , Sr34 , Sr35 , Sr36 , Sr37 , Sr38 , Sr47 , Srdp-2 , SrTmp , SrTt3 , and SrWld-1 . The resistant genes against the dominant race 21C3CTHSM include Sr5 , Sr9e , Sr19 , Sr20 , Sr21 , Sr22 , Sr23 , Sr25 , Sr26 , Sr27 , Sr30 , Sr31 , Sr32 , Sr33 , Sr36 , Sr37 , Sr38 , Sr47 , and SrTmp (Han et al. 2018 ). Fifteen Sr genes, viz. Sr9e , Sr19 , Sr20 , Sr21 , Sr23 , Sr25 , Sr26 , Sr30 , Sr31 , Sr32 , Sr36 , Sr37 , Sr38 , Sr47 and SrTmp exhibited resistance to both predominant races. Li et al. ( 2019a ) reported that 83 Heilongjiang wheat cultivars, carrying Sr2 , Sr24 , Sr25 , Sr26 , Sr31 , and Sr38 based on molecular detection, were resistance to three prevalent races 21C3CTHQM, 34MKGQM, and 34C3RTGQM, respectively. Field adult-plant resistance to all three prevalent Pgt races 21C3CTH, 21C3CFH, and 34MKG were identified in 56 out of 78 (71.79%) alien Ug99-resistance wheat varieties (lines) that were introduced from International Maize and Wheat Improvement Center (CIMMYT), and 72 out of 142 (50.7%) domestic wheat varieties from 15 provinces of China (Han et al. 2013 ). Wu et al. ( 2020b ) identified the wheat lines from CIMMYT carrying Sr9e , Sr21 , Sr26 , Sr33 , Sr35 , Sr37 , Sr38 , Sr47 , and SrTt3 resistance genes against Ug99, and the lines possessing resistance genes against the prevalent Pgt races 21C3CTTTM, 34C0MRGSM, and 34C3MTGQM in China. Those Sr genes are important resistance germplasm resources for wheat breeding.

Currently, over 100 wheat leaf rust resistance genes ( Lr ) have been identified worldwide, and 80 of which have been officially named (McIntosh et al. 2017 ; Kumar et al. 2021 ). Wu et al. ( 2020a ) reported that, based on resistance of 100 Chinese cultivars that challenged with 20 prevailing Pt isolates, nine Lr genes, viz. Lr9 , Lr18 , Lr19 , Lr24 , Lr28 , Lr29 , Lr47 , Lr51 , and Lr53 , exhibited a broad resistance spectrum to all tested isolates. It is worth to mention that the Lr genes can be utilized for leaf rust-resistant wheat breeding, but Lr genes, including Lr2c , Lr3 , Lr16 , Lr17 , LrB , Lr3bg , Lr14b , Lr23 , and Lr39 , should be avoided since they are high susceptible to the 20 prevailing Pt isolates in the fields (Wu et al. 2020a ). In addition, six Lr genes, Lr1 , Lr33 , Lr34 , Lr45, and Lr46 , were identified in 37 Chinese wheat cultivars. Of which, 29 cultivars carrying Lr34 and Lr46 , and exhibit adult-plant resistance to leaf rust (Wu et al. 2020a ). Chinese cultivar Shanghai 7 displays high resistance to Ug99, but it is difficult to identify the Ug99-resistance gene in this cultivar due to the unknown genetic background of this wheat variety (Singh et al. 2006 ). Currently, over 70 quantitative trait loci (QTL) against wheat leaf rust have been identified, and 11 of which possess pleiotropic resistance to the disease (Zhang et al. 2016 ; Liu and Li 2019 ; Yan et al. 2022 ).

Pyramiding multi-gene resistance to wheat rusts

Pyramiding rust-resistant genes is an important strategy to breed wheat resistance cultivars. Previously, 1BL/IRS translocation lines that carry the stem rust gene Sr31 , and the stripe rust gene Yr9 were widely used in stem rust-, and stripe rust-resistant wheat breeding. Chinese wheat cultivars carrying both genes play an important role in controlling stripe and stem rust. Wheat cultivars with multi-resistance genes exhibit a broader resistance spectrum. Multi-gene pyramiding strategy therefore has been verified to be practicable for durable control of wheat rusts. By pyramiding Yr15 and Yr64 to the resistance wheat line RIL- Yr64 / Yr15 , a wider spectrum and durable resistance wheat variety was obtained (Qie et al. 2019 ). Zhang and Zhang ( 2016 ) introduced both YrSM139-1B and YrSM139-2D into the wheat cultivar Shaanmai 139, which increased the reception wheat with a broad resistance to wheat rusts remarkably. Zeng et al. ( 2015 ) reported that wheat cultivars carrying multi- Yr genes displayed stripe rust resistance in adult plant. However, pyramiding multi- Lr or  Sr  genes to a wheat cultivar has not been reported in China yet. Notably, the wheat variety carrying tandem resistance genes, such as Sr24 - Lr24 and Lr37-Yr17-Sr38 , can simultaneously resist the three wheat rusts, which is a good donor germplasm for wheat breeding.

Deployment of wheat cultivars carrying rust resistance genes

The deployment of wheat varieties carrying resistance genes in epidemiological regions can theoretically control disease outbreak. Wheat varieties with whole growth stage resistance have been grown in epidemiological regions now. In 1965, wheat varieties Abbondanza and Fengchan 3 were widely grown in South Shaanxi and central Shaanxi Province to control wheat stripe rust for 9 years (SXIPP 1976 ). In the 1970s, breeding and application of stem rust-resistant wheat cultivars, especially those carrying Sr31 , play a significant role in controlling the rust disease outbreak in China. Since then, wheat stem rust has been a sporadic-occurring disease in China (Cao et al. 1994 ; Wang et al. 2010 ). One of the suggestions regarding the deployment of resistance genes is to cultivate the wheat varieties carrying multi-resistance genes but not a single resistance gene at a large scale or in epidemiological region.

Regulation of alternate hosts

Alternate hosts and vigorous teliospores are required for wheat rusts to complete the sexual stage. Sexual genetic recombination of wheat rusts can conceive high virulence progenies of the pathogen. Some techniques have been employed to reduce possibility of the new race generation by controlling the pathogen’s sexual reproduction on alternate hosts, which largely reduced the potential emergence of new races generated in the habitat of barberry species. Some useful tips are recommended: (1) triazole fungicides (i.e. triadimefon) should be frequently used on alternate host plants; (2) eradicating alternate host plants close to wheat fields; (3) reducing overwintering teliospore levels by removing wheat straw.

Use of fungicides

Chemical fungicides, such as Flutriafol, hexaconazole, diniconazole, propiconazole, tebuconazole, and triadimefon, have been registered and applied in China. However, long-term and intensive application of triazole fungicides has led to the emergence of anti-fungicide Pst and Pgt races in China (Wu et al. 2020a ; Zhan et al. 2022b ). The trouble is that the fungicide-resistant isolates are continuously emerging. Therefore, exploring new fungicides or alternative utilization of fungicides is an issue on table.

Biocontrol of the rust disease

Mycoparasitism mechanism is common in rust fungi, especially in the genus of Puccinia , which can be a useful and environmental-friendly method to control the rust diseases in addition to the fungicides. To date, approximately 30 genera of fungi are able to hyper-parasitize rust fungi. However, only five fungal species, Lecanicillium lecanii , Typhula idahoensis , Microdochium nivale (Littlefield 1981 ), Cladosporium cladosporioides (Zhan et al. 2014a ), and Alternaria alternata (Zheng et al. 2017 ), have been reported to infect and kill Pst urediospores. Likewise, hyper-parasitism of two Verticillium spp., V. psalliotae and V. tenuipes , on P. triticina (syn. P. recondita ), and Aphanocladium album on P. graminis have been reported (Koc et al. 1981 ; Leinhos and Buchenauer 1992 ). In addition, the biocontrol agent Pseudomonas aurantiaca was reported to have a potential control effect on wheat leaf rust (Wang et al. 2011b ). However, effects of hyper-parasitic mycoparasites and biocontrol agents on three wheat rusts were observed under laboratory conditions. Application of hyper-parasites and biocontrol agents in fields to control wheat rusts is on the way.

Monitoring and forecasting wheat rust epidemics

Monitoring and forecasting dynamics of crop disease can help to manage crop diseases. These field managements include pathogen spore volume, the planting area of susceptible host plants, and environmental conditions. By monitoring race dynamics, virulence variation, and pathogen population structure, we can obtain valuable information of the pathogen dynamics which will determine how and why to deploy the agricultural regulations. A classical case is that in 1958, a monitoring and forecasting method was employed to control wheat stripe rust. Based on the pathogen volume in winter and the coming early spring, the susceptible wheat cultivars planted, and the climatic factors, it predicted the epidemics of wheat stripe rust in 1964, 1973, and 1977. By 1977, more than 30 monitoring and forecasting stations were established national wide. This prediction method was proved to be reliable and it still is adopted nowadays. For instance, monitoring and forecasting wheat stripe rust was carried out in 14 individual years during 1960–1979, 8 epidemics were successfully predicted (Wang et al. 1988 ). Later, the computer-based models to predict the mid/long term epidemics of wheat stripe and leaf rusts were established and successfully applied (Yucheng Plant Protection Station 1979 ; Zeng et al. 1981 ; Xiao et al. 1983 ; Dong et al. 1987 ; Wu et al. 1991 ; Cao et al. 1995 ; Jiang et al. 1996 ; Pu et al. 2012 ). For the short-term prediction, overwintering inoculum and weather conditions during/after overwintering are predicted to be associated with the occurrence of wheat rust epidemics. In addition, high virulence frequency of a single dominant race and a few other races, the virulence spectrum, parasite fitness, and susceptible wheat cultivars planted can be used to predict epidemics of wheat rusts. For instance, the 1990s severe nationwide epidemic of wheat stripe rust was predicted in advance based on the high virulence frequency of the race CYR29 (up to 40.3%) and 6.7 million planting areas of susceptible wheat cultivars in 1989 (Wu et al. 1991 ). Currently, a series of internet-based devices or technologies, such as inoculum trapping, remote sensing, geographic information system (GIS), Global positioning system (GPS), atmospheric circulation modelling, and Internal of Things (IoT), have been developed and applied to manage crop diseases including wheat rusts (Hu et al. 2022 ). The modern agricultural technologies will undoubtedly enable us to precisely monitor and predict the development of wheat rusts and other crop diseases, and as a result to control the wheat rusts.

Planting wheat variety mixtures

Monoculture often fosters compatible pathogen accumulation. Growing a mixture of different wheat varieties can effectively control epidemics in fields. Many studies indicated that planting multi-wheat variety mixtures is an effective approach to reduce wheat stripe and leaf rusts outbreak in field. The low density susceptible wheat plants, such as 3:1 (resistant: susceptible) ratio, will decline disease development in wheat variety mixtures (Cao and Zeng 1994 ; Shen et al. 2008 ; Lü et al. 2014 ; Wang et al. 2022a ). However, it is not determined if increasing of wheat variety can further reduce the occurrence of wheat rusts. Nevertheless, the mixing planting of distinct wheat varieties to reduce rust infection is worth of further filed practicing.

Intercropping

Intercropping of wheat and other crops can also decrease wheat rust occurrence. For example, intercropping of rust-resistant wheat cultivars with faba bean can reduce wheat stripe rust infection by 22–100% according to 1-year field trial (Xiao et al. 2005 ). Likewise, Yang et al. ( 2009a ) reported that, based on 6 years trials, intercropping of wheat and faba bean can decrease 30.4–63.55% wheat stripe rust occurrences with an increase of 0.28–0.63 metric tons per hectare of crop yields. In addition, intercropping of wheat and faba bean, namely the Yumai 1(wheat)/Yuxi (local bean variety) and Qiekuina (wheat)/Yuxi (local bean variety), achieve 38.7–39.6% of control to wheat leaf rust (Yang et al. 2003 ).

The outlook to the future

Due to the emerging new rust pathogens, there is a potential risk that the new rust pathogens would overcome the resistance of currently-growing wheat cultivars and cause a large scale of epidemics. Therefore, the work that monitoring and analyzing the emerging rust races in field should be strengthened to avoid wheat rust outbreaks. On the other hand, monitoring the effectiveness of wheat rust resistance genes will help to guide the rust managements, such as the deployment and introducing of new resistance genes. Mining of new wheat rust resistance genes would always promote our capability to fight against these devastating pathogens.

New technologies, especially the novel biotechnology, will assist to defend wheat rusts. The techniques, such as the molecular-assisted selection, and gene-editing technology have been applied to help breed disease resistant wheat cultivars, including wheat stripe rust (Li et al. 2022 ; Wang et al. 2022b ). MAS breeding is not only shortening the breeding procedure but also can rapidly locate the resistance genes for further pyramiding multi-resistance genes in a given variety. Multi-resistance gene wheat cultivars possess the merit of broad disease resistance spectrum, which can be generated by introducing the all-stage resistance genes.

In addition, management of alternate hosts is important for reducing the generation of new wheat rust races. Eradication of barberry bushes has been confirmed as an effective long-term control of wheat stem rust in the United States (Roelfs 1982 ). In China, the barberry species are abundant and widespread and are often observed in spring, even autumn-wheat planting regions (Du et al. 2022 ). Therefore, controlling the barberry rust infection by applying fungicides timely prior to the early stage of pycnial development has been successful in interrupting sexual cycle of rust pathogens.

Investigation of the avirulence genes in rust pathogens is essential for understanding the pathogenesis variation of the wheat rusts and for the targeted wheat breeding. Although some avirulence genes have been cloned in Pgt , such as AvrSr27 , AvrSr35 , and AvrSr50 (Chen et al. 2017 ; Salcedo et al. 2017 ; Upadhyaya et al. 2021 ), none of the avirulence genes in Pst and Pt has been cloned so far. Therefore, identification of avirulence genes of Pst and Pt and more avirulence genes of Pgt should be taken into consideration.

Conclusions

Wheat stripe, leaf, and stem rusts are destructive fungal diseases on wheat in China. Their spores can travel a long distance by wind. Severe epidemics of the three wheat rust diseases frequently occurred and have resulted in huge yield and economic losses. Strategies for the management of the wheat rusts have been made, which has achieved the effective control on wheat rusts in China, especially the wheat stem rust. Recently, new research progresses have been achieved on the control of wheat rusts. Herein, we summarized the rust epidemics, fungicide-resistance and the agricultural managements in China. With the aids of new bio-technologies, we are confident to fully control the wheat rust epidemics in China in the near future.

Availability of data and materials

Not applicable.

Abbreviations

Puccinia graminis f. sp. tritici

Puccinia striiformis f. sp. tritici

Puccinia triticina

Chinese yellow rust

Formae specialis

Yellow rust

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This study was financially supported by the National Key Research and Development Program of China (2021YFD1401000), the National Natural Science Foundation of China (32072358, 31871918, 32272507, and 31071641), the Earmarked Fund for CARS-03, the Natural Science Basic Research Plan in Shaanxi Province of China (2020JZ-15), and National ‘111 Plan’ (BP0719026).

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Zhao, J., Kang, Z. Fighting wheat rusts in China: a look back and into the future. Phytopathol Res 5 , 6 (2023). https://doi.org/10.1186/s42483-023-00159-z

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• Published: 14 September 2015

Research investment implications of shifts in the global geography of wheat stripe rust

• Jason M. Beddow 1 , 2 , 3 ,
• Philip G. Pardey 1 , 2 , 3 ,
• Yuan Chai 1 ,
• Terrance M. Hurley 1 , 2 , 3 ,
• Darren J. Kriticos   ORCID: orcid.org/0000-0003-2599-8105 1 , 3 ,
• Hans-Joachim Braun 4 ,
• Robert F. Park 5 ,
• William S. Cuddy 6 &
• Tania Yonow 1 , 3  

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Breeding new crop varieties with resistance to the biotic stresses that undermine crop yields is tantamount to increasing the amount and quality of biological capital in agriculture. However, the success of genes that confer resistance to pests induces a co-evolutionary response that depreciates the biological capital embodied in the crop, as pests evolve the capacity to overcome the crop's new defences. Thus, simply maintaining this biological capital, and the beneficial production and economic outcomes it bestows, requires continual reinvestment in new crop defences. Here we use observed and modelled data on stripe rust occurrence to gauge changes in the geographic spread of the disease over recent decades. We document a significant increase in the spread of stripe rust since 1960, with 88% of the world's wheat production now susceptible to infection. Using a probabilistic Monte Carlo simulation model we estimate that 5.47 million tonnes of wheat are lost to the pathogen each year, equivalent to a loss of US$979 million per year. Comparing the cost of developing stripe-rust-resistant varieties of wheat with the cost of stripe-rust-induced yield losses, we estimate that a sustained annual research investment of at least US$32 million into stripe rust resistance is economically justified.

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Acknowledgements

We thank R. Singh for technical guidance. In addition, attendees of the Borlaug Global Rust Initiative (BGRI) meetings at New Delhi (August 2013) and Obregon, Mexico (March 2014) and the Second International Wheat Stripe Rust Symposium at Izmir, Turkey (April 2014) provided valuable comments and feedback. A substantial portion of the funding was provided by the Wheat CRP by way of the International Maize and Wheat Improvement Center (CIMMYT) with additional support from the University of Minnesota's MnDRIVE Global Food Ventures Initiative and the International Science and Technology Practice and Policy (InSTePP) Center. R.F.P. and W.C. received support from the Australian Grains Research and Development Corporation.

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International Science and Technology Practice and Policy (InSTePP) Center in the Department of Applied Economics at the University of Minnesota, 1994 Buford Ave, 248 Ruttan Hall, Saint Paul, 55108, Minnesota, USA

Jason M. Beddow, Philip G. Pardey, Yuan Chai, Terrance M. Hurley, Darren J. Kriticos & Tania Yonow

Stakman-Bourlaug Cereal Rust Center at the University of Minnesota, 495 Borlaug Hall, 1991 Upper Buford Circle, Saint Paul, 55108, Minnesota, USA

Jason M. Beddow, Philip G. Pardey & Terrance M. Hurley

Commonwealth Scientific and Industrial Research Organization (CSIRO), GPO Box 1700, Canberra, 2601, Australian Capital Territory, Australia

Jason M. Beddow, Philip G. Pardey, Terrance M. Hurley, Darren J. Kriticos & Tania Yonow

International Maize and Wheat Improvement Center (CIMMYT), El Batán, Texcoco, Edo. de México, 56237, Mexico

Hans-Joachim Braun

Plant Breeding Institute at the University of Sydney, Private Bag 4011, Narellan, 2567, Sydney, New South Wales, Australia

• Robert F. Park

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Contributions

P.G.P., J.M.B. and T.M.H. designed the study and methods; D.J.K., J.M.B., Y.C., R.F.P., H.J.B., T.Y. and W.S.C. compiled and interpreted distribution data and developed the species niche model; Y.C. and T.M.H. undertook the probabilistic assessment; J.M.B. implemented the spatial assessment; P.G.P., J.M.B., T.M.H., Y.C., R.F.P. and W.S.C. wrote the paper.

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Correspondence to Jason M. Beddow .

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Beddow, J., Pardey, P., Chai, Y. et al. Research investment implications of shifts in the global geography of wheat stripe rust. Nature Plants 1 , 15132 (2015). https://doi.org/10.1038/nplants.2015.132

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Received : 28 April 2015

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Published : 14 September 2015

DOI : https://doi.org/10.1038/nplants.2015.132

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Roland Rust Directory Page

Roland Rust

Distinguished University Professor

David Bruce Smith Chair in Marketing

Executive Director, Center for Excellence in Service

Ph.D., Business Administration, University of North Carolina at Chapel Hill

Roland T. Rust is Distinguished University Professor and David Bruce Smith Chair in Marketing at the Robert H. Smith School of Business at the University of Maryland, where he is founder and Executive Director of the Center for Excellence in Service. He is VP of Publications for the American Marketing Association, in charge of policy and editor selections for AMA’s five journals. A recent research.com study named him one of the top 100 “Best Scientists in Business and Management,” worldwide across all business disciplines, based on research impact. His lifetime achievement honors include the AMA Irwin/McGraw-Hill Distinguished Marketing Educator Award, the EMAC Distinguished Marketing Scholar Award, Fellow of the INFORMS Society for Marketing Science, the Paul D. Converse Award, Fellow of the American Statistical Association, as well as the top career honors in service marketing, marketing research, marketing strategy, and advertising, and honorary doctorates in economics from the University of Neuchatel (Switzerland) and the Norwegian School of Economics. He was one of the inaugural honorees in the American Marketing Association’s Marketing Legends video series, and one of the inaugural AMA Fellows. Awards for his publications include four best article awards from the Journal of Marketing , as well as the Berry/AMA Book Award for the best book in marketing. He served as Editor-in-Chief of the Journal of Marketing , founded the annual Frontiers in Service Conference, was founding Editor-in-Chief of the Journal of Service Research , and served as Editor-in-Chief of the International Journal of Research in Marketing (IJRM) . He has consulted with many leading companies worldwide, including such companies as American Airlines, AT&T, Comcast, Dow Chemical, DuPont, Eli Lilly, FedEx, Hershey, Hewlett-Packard, IBM, Lockheed Martin, Microsoft, NASA, NCR, Nortel, Procter & Gamble, Sears, Sony, Starwood, Tata, Unilever, and USAA. A national class distance runner in his collegiate days, he has been inducted into the DePauw University Athletic Hall of Fame. He has coached Olympic Trials qualifiers, and national and world age group champions in track and triathlon.

Honors and Awards

Lifetime achievement awards.

Ranked 24th top researcher all-time in Marketing (and top active researcher in any field at the Smith School) by an extensive international study: Ioannidis JPA, Baas J, Klavans R, Boyack KW (2019) A standardized citation metrics author database annotated for scientific field . PLoS Biol 17(8): e3000384. Ranked within the top one-fifth of 1% of marketing researchers worldwide.

Buck Weaver Award, INFORMS Society for Marketing Science, 2020. The award honors distinguished scholars and practitioners who have excelled in the achievement of rigor and relevance in marketing science. I am one of only nine people who have won both of INFORMS ISMS' two top career awards—the Buck Weaver Award and ISMS Fellow.

Honorary Doctorate, Norwegian School of Economics, 2017.

EMAC Distinguished Marketing Scholar Award, 2017. This is the top career honor from the European Marketing Academy. One of only three people ever to win the top academic career award from both the American Marketing Association and the European Marketing Academy.

Featured on AMA's Marketing Legends Video Series, 2017, as one of the inaugural group of interviewees.

Global Scholar of the Year, awarded by the Global Alliance of Marketing & Management Associations, 2016.

Fellow of the American Marketing Association, one of the inaugural class of AMA Fellows, 2015.

Fellow of the European Marketing Academy, 2015.

AMA Irwin/McGraw-Hill Distinguished Marketing Educator Award, 2012. This is the top career honor in academic Marketing.

Paul D. Converse Award, 2012. This award, established by the American Marketing Association, honors "individuals who have made outstanding contributions to marketing scholarship."

Honorary Doctorate in Economics from the University of Neuchatel, Switzerland, for "intellectual leadership … in terms of research on services, which have led to the updating, if not the entire rewriting, of contemporary textbooks on management and marketing," 2010.

Fellow of the INFORMS Society for Marketing Science, one of the first 16 people to receive this honor, 2010.

Mahajan Award for Lifetime contribution to Marketing Strategy Research, awarded by the American Marketing Association's Marketing Strategy Special Interest Group, 2010.

PhD Alumni Merit Award, awarded by the Kenan-Flagler Business School at the University of North Carolina at Chapel Hill, 2008.

Distinguished University Professor, the highest honor awarded by the University of Maryland, the first business school professor ever to receive this honor, 2008.

CUTCO/Vector Distinguished Marketing Educator Award, awarded by the Academy of Marketing Science, 2007.

Elsevier Distinguished Scholar Award, for "exceptional scholarly achievements," awarded by the Society for Marketing Advances, 2005.

American Marketing Association Career Contributions to the Services Discipline Award, recognizing "the greatest long-term impact on the development of the services discipline," awarded by the AMA Services Special Interest Group, 2002.

American Marketing Association Gilbert A. Churchill Award, for lifetime achievement in marketing research, awarded by the AMA Marketing Research Special Interest Group, 2000.

Fellow, American Statistical Association, elected "for significant statistical contributions in marketing, advertising, quality management, and psychometrics; and for service to the profession," 1997.

Henry Latané Distinguished Doctoral Alumnus Award, awarded by the Kenan-Flagler Business School at the University of North Carolina at Chapel Hill, 1995.

"Outstanding Contribution to Advertising Research" lifetime achievement award, awarded by the American Academy of Advertising, 1994.

Best Article & Book Awards

Sheth Foundation JAMS Best Article Award, 2022, for the 2021 article, “A Strategic Framework for Artificial Intelligence in Marketing (with Ming-Hui Huang).

Finalist, Sheth Foundation/Journal of Marketing Award, 2021, for "Brand Buzz in the Echoverse," (with Kelly Hewett, William Rand, and Harald van Heerde). The award honors the article published in the Journal of Marketing that has made long-term contributions to the field of marketing. An article is eligible for this award in the fifth year after its publication. The criteria for selection include the quality of the article's contribution to theory and practice, its originality, its technical competence, and its impact on the field of marketing.

Finalist, IJRM Steenkamp Long-Term Impact Award, 2021, for "Agent-Based Modeling in Marketing: Guidelines for Rigor" (with William Rand), IJRM 2011.

Finalist, IJRM Steenkamp Long-Term Impact Award, 2021, for "Will the Frog Change into a Prince: Predicting Future Customer Profitability" (with V. Kumar and Rajkumar Venkatesan), IJRM , 2011.

AMA SERVSIG Best Service Article Award, 2019, for "Artificial Intelligence in Service," in the Journal of Service Research, 2018, (with Ming-Hui Huang).

JSR Best Article Award, 2019, for "Artificial Intelligence in Service," in the Journal of Service Research, 2018, (with Ming-Hui Huang).

Finalist, AMA SERVSIG Best Service Article Award, 2018, for "Return on Service Amenities" in the Journal of Marketing Research, 2017 (with Rebecca Hamilton, Michel Wedel and Chekitan Dev).

Finalist, AMA SERVSIG Best Service Article Award, 2018, for "Technology-Driven Service Strategy" in the Journal of the Academy of Marketing Science, 2017 (with Ming-Hui Huang).

Finalist, MSI/H. Paul Root Award, 2017. The award recognizes the Journal of Marketing article that made the greatest contribution to the advancement of the practice of marketing, for the 2016 article, "Brand Buzz in the Echoverse" (with Kelly Hewett, William Rand and Harald van Heerde).

Sheth Foundation Best Paper Award for the year's best article in the Journal of the Academy of Marketing Science, 2017, for the 2016 article, "Adaptive Personalization Using Social Networks" (with Tuck Siong Chung and Michel Wedel)

Best Published Paper Award, Oxford Centre for Corporate Reputation, 2017, for "Brand Buzz in the Echoverse," (with Kelly Hewett, William Rand and Harald van Heerde), Journal of Marketing, 2016. "The award recognises the exceptional quality of your article and its potential to affect future research on corporate reputation. It carries a prize of £1,000 to be shared among the authors."

Runner-up, 2014 INFORMS Service Science Section Best Paper Award, for "Adaptive Personalization Using Social Networks," (with Tuck Siong Chung and Michel Wedel).

Article named 7th most impactful marketing article from 1982 - 2003 based on a survey of marketing managers (Roberts et al, IJRM 2014), recognized for "Return on Quality (ROQ): Making Service Quality Financially Accountable," (Journal of Marketing, 1995, with Anthony J. Zahorik and Timothy L. Keiningham).

Article named one of the 10 most impactful marketing articles in the Journal of Marketing from 2004 - 2012, based on number of citations (Roberts et al, IJRM 2014), recognized for "Return on Marketing: Using Customer Equity to Focus Marketing Strategy," (Journal of Marketing 2004, with Latherine N. Lemon and Valarie A. Zeithamal).

Article named one of the 10 most impactful articles in Marketing Science from 2004 - 2012, based on number of citations (Roberts et al, IJRM 2014), recognized for "Marketing Models of Service and Relationships," (Marketing Science, 2006, with Tuck Siong Chung).

Finalist, IJRM Best Article Award, 2012, for the 2011 article, "Will the Frog Change into a Prince?: Predicting Future Customer Profitability," (with V. Kumar and Rajkumar Venkatesan).

Finalist, Paul E. Green Award, 2011. The award recognizes "the best article in the Journal of Marketing Research that demonstrates the greatest potential to contribute significantly to the practice of marketing research," for the February 2010 article, "Customer Satisfaction and Consumer Spending Growth," (with Claes Fornell and Marnik Dekimpe). The award winners are chosen by the Journal of Marketing Research's Editorial Review Board.

Second Place Winner, 2010, INFORMS Service Science Section Best Paper Award, for "Optimizing Service Productivity" (with Ming-Hui Huang).

Sheth Foundation/Journal of Marketing Award, 2009, for the JM article with the greatest long-term impact for his article "Return on Marketing: Using Customer Equity to Focus Marketing Strategy" (with Kay Lemon and Valarie Zeithaml).

Finalist, William O'Dell Award, 2010. The award recognizes the article that "has made the most significant, long-run contribution to marketing theory, and/or methodology, and/or practice," for the November 2005 Journal of Marketing Research article, "Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing," (with Debora Viana Thompson and Rebecca Hamilton). The award winner is chosen by the Journal of Marketing Research's Editorial Review Board.

Donald R. Lehmann Award, 2007, (co-author and dissertation chair), awarded by the American Marketing Association Marketing Research SIG for the Best Dissertation-Based Research Article for the November 2005 Journal of Marketing Research article, "Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing," (with Debora Viana Thompson and Rebecca Hamilton).

IBM Best Article Award, Journal of Service Research, 2007, for the 2006 article, "The Path to Customer Centricity," (with Denish Shah, A. Parasuraman, Richard Staelin, and George Day). The award winner is selected by the journal's editorial review board.

Highly Commended Paper Award, 2006, awarded for the 2005 International Journal of Service Industry Management article, "The Business Value of E-Government for Small Firms," (with Debora Thompson and Jeffrey Rhoda). The award, chosen by the journal's editorial review board, is given to the top four articles of the year.

MSI/H. Paul Root Award, 2005, awarded for the January 2004 Journal of Marketing article, "Return on Marketing: Using Customer Equity to Focus Marketing Strategy," (with Katherine N. Lemon and Valarie A. Zeithaml). The award recognizes the article that made the greatest contribution to the advancement of the practice of marketing. The award winner is chosen by the Journal of Marketing's Editorial Review Board.

Robert D. Buzzell Best Paper Award, 2003, awarded for the paper, "Driving Customer Equity: Linking Customer Lifetime Value to Strategic Marketing Decisions" (with Katherine N. Lemon and Valarie A. Zeithaml). Previously known as the MSI Best Paper Award, the Buzzell Award is awarded by the Marketing Science Institute to honor papers that have made a significant contribution to marketing practice and thought. It also serves to signal the kind of writing and research that is of lasting value to corporate marketing executives.

MSI/H. Paul Root Award, 2003, awarded for the October 2002 Journal of Marketing article, "Getting Return on Quality: Revenue Expansion, Cost Reduction or Both?" (with Christine Moorman and Peter Dickson). The award recognizes the article that made the greatest contribution to the advancement of the practice of marketing. The award winner is chosen by the Journal of Marketing's Editorial Review Board.

Berry-AMA Book Prize, 2002, awarded for the book, Driving Customer Equity, co-authored by Valarie A. Zeithaml and Katherine N. Lemon (Free Press 2000). The award is given by the American Marketing Association to the best book in marketing from the most recent three year period. The award recognizes "exceptional marketing books that have set the standard for excellence" and "whose innovative ideas have had significant impact on marketing and related fields." Anthologies, textbooks and manuals are not eligible for the award. The award is selected by current and past Executive Directors of the Marketing Science Institute.

Marketing Science Institute Best Paper Award, 2002, awarded for the paper, "Getting Returns from Service Quality: Is the Conventional Wisdom Wrong?" (with Christine Moorman and Peter Dickson). The award recognizes papers that have made the most significant contribution to marketing practice and thought. It also signifies the kind of writing and research that is of lasting value to corporate marketing executives.

Donald R. Lehmann Award, 2001, (co-author and dissertation chair), awarded by the American Marketing Association Marketing Research SIG for the Best Dissertation-Based Research Article for the November 2000 Journal of Marketing Research article, "Modeling Fuzzy Data in Qualitative Marketing Research," (with Sajeev Varki and Bruce Cooil).

Finalist, Paul E. Green Award for the Journal of Marketing Research article with the most potential to contribute significantly to the practice of marketing research and research in marketing, for the November 2000 article, "Modeling Fuzzy Data in Qualitative Marketing Research," (with Sajeev Varki and Bruce Cooil). The award is chosen by the Journal of Marketing Research Editorial Board.

Second Place Winner, 1999 William R. Davidson Award for the best paper published in the Journal of Retailing two years previously, for "Customer Delight: Foundations, Findings, and Managerial Insight," (with Richard L. Oliver and Sajeev Varki). The award is chosen by the Journal of Retailing Editorial Board.

Best Services Article Award, AMA Services Special Interest Group, 1998, for "Customer Satisfaction, Productivity, and Profitability: Differences Between Goods and Services," Marketing Science, 1997 (2) (with Eugene W. Anderson and Claes Fornell).

Finalist, John D.C. Little Best Article Award for the best 1997 marketing article in Marketing Science or Management Science, for "Customer Satisfaction, Productivity, and Profitability: Differences Between Goods and Services," (with Eugene W. Anderson and Claes Fornell). The award is chosen by the officers of the INFORMS College on Marketing and the Editorial Review Boards of Marketing Science and Management Science.

Alpha Kappa Psi Foundation Award for the article in the 1995 Journal of Marketing that had the greatest contribution to the advancement of the practice of marketing. Awarded for "Return on Quality (ROQ): Making Service Quality Financially Accountable," (with Anthony J. Zahorik and Timothy L. Keiningham). The award is chosen by members of the Journal of Marketing Editorial Review Board.

"Best Article Award for 1993" from the Journal of Retailing for the article, "Customer Satisfaction, Customer Retention, and Market Share," (with Anthony J. Zahorik). The Best Article, selected by a vote of the Editorial Board, is one judged to have contributed most significantly to the development of retailing theory and/or practice.

Winner, Best Article Award in the 1993 Journal of Advertising for the article, "Emotional Feelings and Evaluative Dimensions of Advertising: Are They Related?" (with Patricia Stout).

Selected Publications

Huang, Ming-Hui and Roland T. Rust, “A Framework for Collaborative Artificial Intelligence in Marketing,” Journal of Retailing, forthcoming. 

Huang, Ming-Hui and Roland T. Rust, “AI as Customer,” Journal of Service Management, 33 (2), 210-220.

Rust, Roland T., William Rand, Ming-Hui Huang, Andrew Stephen, Gillian Brooks and Timur Chabuk (2021), "Real-Time Brand Reputation Tracking Using Social Media," Journal of Marketing , 85(4), 21-23.

Huang, Ming-Hui and Roland T. Rust (2021), "A Strategic Framework for Artificial Intelligence in Marketing," Journal of the Academy of Marketing Science, 49 (1), 30-50.

Huang, Ming-Hui and Roland T. Rust (2021), "Engaged to a Robot: The Role of AI in Service," Journal of Service Research, 24 (1), 30-41.

Rust, Roland T. (2020), "The Future of Marketing," IJRM, 37 (1), 15-26.

Huang, Ming-Hui, Roland T. Rust and Vojislav Maksimovic (2019), "The Feeling Economy: Managing in the Next Generation of AI," California Management Review, 61 (4), 43-65.

Huang, Ming-Hui and Roland T. Rust (2018), "Artificial Intelligence in Service," Journal of Service Research, 21 (2), 155-172.

• Hamilton, Rebecca J., Roland T. Rust, Michel Wedel and Chekitan Dev (2017), "Return on Service Amenities," Journal of Marketing Research, 54 (February), 96-110.
• Finalist, AMA SERVSIG Best Service Article Award, 2018.
• Huang, Ming-Hui and Roland T. Rust (2017), "Technology-Driven Service Strategy," Journal of the Academy of Marketing Science, 45 (6), 906-924.
• Finalist, Sheth Foundation Best Paper Award for the year's best article in the Journal of the Academy of Marketing Science, 2018.

Hamilton, Rebecca J., Roland T. Rust and Chekitan Dev (2017), "What Features Retain Customers?" MIT Sloan Management Review, 58 (2), 79-84.

Hewett, Kelly, William Rand, Roland T. Rust and Harald J. van Heerde (2016), "Brand Buzz in the Echoverse," Journal of Marketing, 80 (3), 1-24.

Rust, Roland T., Christine Moorman and Jacqueline van Beuningen (2016), "Quality Mental Model Convergence and Business Performance," IJRM, 33 (1), 155-171.

Mithas, Sunil and Roland T. Rust (2016), "How Information Technology Strategy and Investments Influence Firm Performance: Conjecture and Empirical Evidence," MISQ, 40 (1), 223-245.

Chung, Tuck Siong, Michel Wedel and Roland T. Rust (2016), "Adaptive Personalization Using Social Networks," Journal of the Academy of Marketing Science, 44 (1), 66-87.

Chung, Tuck Siong, Michel Wedel and Roland T. Rust, "Adaptive Personalization Using Social Networks," Journal of the Academy of Marketing Science, forthcoming.

Rust, Roland T. and Ming-Hui Huang (2014), "The Service Revolution and the Transformation of Marketing Science," Marketing Science, 33 (2), 206-221.

Huang, Ming-Hui and Roland T. Rust (2013), "IT-Related Service: A Multidisciplinary Perspective," Journal of Service Research, 16 (3), 251-258.

Rust, Roland T. and Ming-Hui Huang (2012), "Optimizing Service Productivity," Journal of Marketing, 76 (2), 47-66.

• Finalist, Harold H. Maynard Award, 2013.
• Second Place Winner, 2010 INFORMS Service Science Section Best Paper Award.

Arens, Zachary and Roland T. Rust (2012), "The Duality of Decisions and the Case for Impulsiveness Metrics," Journal of the Academy of Marketing Science, 40 (3), 468-479.

Rust, Roland T., V. Kumar and Rajkumar Venkatesan (2011), "Will the Frog Change into a Prince?: Predicting Future Customer Profitability," International Journal of Research in Marketing, 28 (4), 281-294.

• Finalist, IJRM Best Article Award.

Rand, William and Roland T. Rust (2011), "Agent-Based Modeling in Marketing: Guidelines for Rigor," International Journal of Research in Marketing (IJRM), 28 (3), 181-193.

Huang, Ming-Hui and Roland T. Rust (2011), "Sustainability and Consumption," Journal of the Academy of Marketing Science, 39(1), 40-54.

Fornell, Claes, Roland T. Rust and Marnik G. Dekimpe, (2010), "The Effect of Customer Satisfaction on Consumer Spending Growth," Journal of Marketing Research, 47 (February), 28-35.

• Finalist, Paul E. Green Award, 2011. The award recognizes "the best article in the Journal of Marketing Research that demonstrates the greatest potential to contribute significantly to the practice of marketing research." The award winners are chosen by the Journal of Marketing Research's Editorial Review Board.

Rust, Roland T., Christine Moorman and Gaurav Bhalla, (2010), "Rethinking Marketing," Harvard Business Review, 88(1), 94-101.

Hanssens, Dominique M., Roland T. Rust and Rajendra K. Srivastava, (2009), "Marketing Strategy and Wall Street: Nailing Down Marketing's Impact," Journal of Marketing, 73 (6), 115-118.

Chung, Tuck Siong, Roland T. Rust and Michel Wedel (2009), "My Mobile Music: An Adaptive Personalization System for Digital Audio Players," Marketing Science, 28(1), 52-68.

Rust, Roland T. and Tuck Siong Chung (2006), "Marketing Models of Service and Relationships," Marketing Science, 25 (6), 560-580 (followed by seven invited commentaries).

• Article named one of the 10 most impactful marketing articles in Marketing Science from 2004-2012, based on number of citations (Roberts et al, IJRM 2014).

Rust, Roland T., Debora Viana Thompson, and Rebecca Hamilton (2006), "Defeating Feature Fatigue,"Harvard Business Review, 84 (2), 98-107. Also published in the Chinese Harvard Business Review, (February 2006), 90-101.

Shah, Denish, Roland T. Rust, A. Parasuraman, Richard Staelin, and George S. Day (2006), "The Path to Customer-Centricity," Journal of Service Research, 2007.

• IBM Best Article Award, Journal of Service Research, 2007. The award winner is selected by the journal's editorial review board.

Thompson, Debora Viana, Rebecca Hamilton and Roland T. Rust, (2005), "Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing," Journal of Marketing Research, 42 (November), 431-442.

• Finalist, William O'Dell Award, 2010. The award recognizes the article that "has made the most significant, long-run contribution to marketing theory, and/or methodology, and/or practice." The award winner is chosen by the Journal of Marketing Research's Editorial Review Board.
• Donald R. Lehman Award, 2007, (co-author and dissertation chair), awarded by the American Marketing Association Marketing Reearch SIG for the Best Dissertation-Based Research Article.

Rust, Roland T. and Peter Verhoef, (2005) " Optimizing the Marketing Interventions Mix in Intermediate-Term CRM ," Marketing Science, 24(3), 477-489.

Rust, Roland T., Tim Ambler, Gregory S. Carpenter, V. Kumar and Rajendra K. Srivastava, (2004), "Measuring Marketing Productivity: Current Knowledge and Future Directions," Journal of Marketing, 68 (4), 76-89.

Rust, Roland T., Katherine N. Lemon and Valarie A. Zeithaml (2004), "Return on Marketing: Using Customer Equity to Focus Marketing Strategy," Journal of Marketing, 68 (1), 109-127.

• Sheth Foundation/Journal of Marketing Award, 2010. The award is chosen by the editorial board and a committee of former editors of the Journal of Marketing for the JM article published between 2000 and 2004 that has had the most long-term impact on the discipline of marketing.
• MSI/H. Paul Root Award, 2005. The award recognizes the article that made the gretest contribution to the advancement of the practice of marketing. The award winner is chosen by the Journal of Marketing's Editorial Review Board.
• Robert D. Buzzell Best Paper Award, 2003, awarded for an earlier version of the paper, entitled, "Driving Customer Equity: Linking Customer Lifetime Value to Strategic Marketing Decisions." Previously known as the MSI Best Paper Award, the Buzzell Award is awarded by the Marketing Science Institute to honor papers that have made a significant contribution to marketing practice and thought. It also serves to signal the kind of writing and research that is of lasting value to corporate marketing executives.
• Article named one of the 10 most impactful marketing articles in the Journal of Marketing from 2004-2012, based on number of citations (Roberts et al, IJRM 2014).

Rust, Roland T., Christine Moorman and Peter R. Dickson, (2002), "Getting Return on Quality: Cost Reduction, Revenue Expansion, or Both?" Journal of Marketing, 66 (October), 7-24. Previously presented at the AMA Frontiers in Services Conference, October 2001.

• MSI/H. Paul Root Award, 2003. The award recognizes the article that made the greatest contribution to the advancement of the practice of marketing. The award winner is chosen by the Journal of Marketing's Editorial Review Board.
• Marketing Science Institute Best Paper Award, 2002, awarded for an earlier draft of the paper, "Getting Returns from Service Quality: Is the Conventional Wisdom Wrong?" Established in 1993, the award recognizes the authors of papers that have made the most significant contribution to marketing practice and thought. It also signifies the kind of writing and research that is of lasting value to corporate marketing executives. To allow sufficient time to assess the impact of the work, this year's winners were selected from papers issued in 2000.

Varki, Sajeev, Bruce Cooil, and Roland T. Rust, (2000), "Modeling Fuzzy Data in Qualitative Marketing Research," Journal of Marketing Research, 37 (November), 480-499.

• Winner, Donald R. Lehmann Award (co-author and dissertation advisor) for the outstanding dissertation-based article in marketing research.
• Finalist, Paul E. Green Award for the Journal of Marketing Research article with the most potential to contribute significantly to the practice of marketing research and research in marketing. The award is chosen by the Editorial Review Board of the Journal of Marketing Research.

Simester, Duncan I., John R. Hauser, Birger Wernerfelt, and Roland T. Rust, (2000), "Implementing Quality Improvement Programs Designed to Enhance Customer Satisfaction: Quasi-experiments in the U.S. and Spain," Journal of Marketing Research, 37 (February), 102-112 (2000).

Moorman, Christine and Roland T. Rust, (1999), "The Role of Marketing," Journal of Marketing, JM/MSI Special Issue on Fundamental Issues in Marketing, 63 (Special Issue), 180-197.

Rust, Roland T., J. Jeffrey Inman, Jianmin Jia, and Anthony Zahorik, (1999), " What You Don't Know About Customer-Perceived Quality: The Role of Customer Expectation Distributions ," Marketing Science, 18 (1), 77-92. Also summarized in Scientific American.

Anderson, Eugene W., Claes Fornell, and Roland T. Rust, (1997), " Customer Satisfaction, Productivity, and Profitability: Differences Between Goods and Services ," Marketing Science, (2), 129-145.

• Best Services Article Award of 1997, AMA Services Special Interest Group.
• Finalist, John D.C. Little Best Article Award for the best 1997 marketing article in Marketing Science or Management Science. The award is chosen by the officers of the INFORMS College on Marketing and the Editorial Review Boards of Marketing Science and Management Science.

Cooil, Bruce and Roland T. Rust, (1995), "General Estimators for the Reliability of Qualitative Data," Psychometrika, 60 (June) 199-220. Previously presented at the ASA Joint Statistical meetings, August 1994.

Rust, Roland T., Anthony J. Zahorik, and Timothy L. Keiningham, (1995), "Return on Quality (ROQ): Making Service Quality Financially Accountable," Journal of Marketing, 59 (April) 58-70.

• Winner of the Alpha Kappa Psi Foundation Award for the 1995 article in the Journal of Marketing that had the greatest contribution to the advancement of the practice of marketing.

Rust, Roland T., Duncan Simester, Roderick J. Brodie, and V. Nilikant, (1995), "Model Selection Criteria: An Investigation of Relative Accuracy, Posterior Probabilities, and Combinations of Criteria," Management Science, 41 (February) 222-233.

Rust, Roland T. and Naveen Donthu, (1995), "Capturing Geographically Localized Misspecification Error in Retail Store Choice Models," Journal of Marketing Research, (February), 103-110.

Cooil, Bruce and Roland T. Rust, (1994), "Reliability and Expected Loss: A Unifying Principle," Psychometrika, 59 (June), 203-216.

Rust, Roland T. and Bruce Cooil, (1994), "Reliability Measures for Qualitative Data: Theory and Implications," Journal of Marketing Research, 31 (February), 1-14.

Rust, Roland T., Donald R. Lehmann, and John U. Farley, (1990), "Estimating Publication Bias in Meta-Analysis," Journal of Marketing Research, (May) 220-226.

Fornell, Claes and Roland T. Rust, (1989), "Incorporating Prior Theory in Covariance Structure Analysis: A Bayesian Approach," Psychometrika, (June), 249-259.

Donthu, Naveen and Roland T. Rust, (1989), " Estimating Geographic Customer Densities Using Kernel Density Estimation ," Marketing Science, (Spring), 191-203.

Rust, Roland T., (1988), "Flexible Regression," Journal of Marketing Research, (February), 10-24.

Rust, Roland T. and David C. Schmittlein, (1985), " A Bayesian Cross-Validated Likelihood Method for Comparing Alternative Specifications of Quantitative Models ," Marketing Science, (Winter), 20-40.

Rust, Roland T. and Mark I. Alpert, (1984), " An Audience Flow Model of Television Viewing Choice ," Marketing Science, (Spring), 113-124.

Rust, Roland T. and Robert P. Leone, (1984), "The Mixed Media Dirichlet Multinomial Distribution: A Model for Evaluating Television-Magazine Advertising Schedules," Journal of Marketing Research, (February) 89-99.

Huff, David L. and Roland T. Rust, (1984), "Measuring the Congruence of Market Areas," Journal of Marketing, (Winter), 68-74.

Rust, Roland T. and Elizabeth O. Bornman, (1982), "Distribution-Free Methods of Approximating Nonlinear Marketing Relationships," Journal of Marketing Research, (August), 372-374.

Rust, Roland T. and Jay E. Klompmaker, (1981), "Improving the Estimation Procedure for the Beta Binomial TV Exposure Model," Journal of Marketing Research, (November), 442-448.

Headen, Robert S., Jay E. Klompmaker, and Roland T. Rust, (1979), "The Duplication of Viewing Law and Television Media Schedule Evaluation," Journal of Marketing Research, (August), 33-340.

Editorships

• Former Editor-in-Chief: IJRM
• Former Editor-in-Chief: Journal of Marketing
• Founding Editor: Journal of Service Research
• Editorial Review Boards: Journal of Marketing ; Journal of Marketing Research; Journal of Service Research ; JAMS; Service Science
• Rust, Roland T. and Ming-Hui Huang (2021), The Feeling Economy: How Artificial Intelligence Is Creating the Era of Empathy , New York: Palgrave Macmillan.
• Roland T. Rust and Ming-Hui Huang, Eds. (2014). Handbook of Service Marketing Research , Cheltenham, U.K.: Edward Elgar.
• Customer Equity Management Roland T. Rust, Kay N. Lemon & Das Narayandas, 2005 Prentice Hall.
• E-Service Roland T. Rust and P.K. Kannan, 2002, M.E. Sharpe
• Driving Customer Equity: How Customer Lifetime Value is Reshaping Corporate Strategy, Roland T. Rust, Valarie A. Zeithaml and Katherine N. Lemon, 2000, The Free Press
• Service Marketing Roland T. Rust, Anthony J. Zahorik and Timothy L. Keiningham, 1996, Harper Collins
• Readings in Service Marketing Roland T. Rust, Anthony J. Zahorik and Timothy L. Keiningham, 1996, Harper Collins
• Return on Quality Roland T. Rust, Anthony J. Zahorik and Timothy L. Keiningham, 1994, Irwin Publishing
• Service Quality Roland T. Rust and Richard L. ("Rich") Oliver, 1994, Sage Publishing
• Advertising Media Models Roland T. Rust, 1986, Lexington Books
• Welcome to the Feeling Economy
• The Rise of Women in the Feeling Economy
• AMA Marketing Legends Video with Roland Rust
• Artificial Common Sense
• Education for the Feeling Economy
• When Machines Can Feel
• Comedy Classes for Geeks and Nerds
• Investigating Discrimination in the Service Industry using Agent-Based Modeling
• An Introduction to Agent-Based Modeling & Computational Methods

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