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Recent technology for food and beverage quality assessment: a review

Wei keong tan, zulkifli husin, muhammad luqman yasruddin, muhammad amir hakim ismail.

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Revised 2022 Mar 13; Accepted 2022 Mar 16; Issue date 2023 Jun.

Food and beverage assessment is an evaluation method used to measure the strengths and weaknesses of a food and beverage system to make improvements. These assessments had become crucial, especially in the issues of adulteration, replacement, and contamination that happened in artificial adjustment relating to the quality, weight and volume. Thus, this review will examine and describe features recently applied in image, odour, taste and electromagnetic, relevant to the food and beverages assessment. This review will also compare and discuss each technique and provides suggestions based on the current technology. This review will deliberate technology integration and the involvement of deep learning to enable several types of current technologies, such as imaging, odour and taste senses, and electromagnetic sensing, to be used in food evaluation applications for inspection and packaging.

Keywords: Food and beverage assessment, Recent technology, Imaging technology, Odour and taste sensing technology, Electromagnetic sensing technology

Introduction

Nowadays, food and beverage safety has been a global common health concern, especially in food hygiene and food quality. Food is a global necessity to consume every day for energy and development, health and disease prevention. Hence, it is important to ensure that only safe and qualified food products are supplied to consumers. However, in reality, consumers are facing difficulty in choosing the legal food products due to the poor quality of food, poor hygiene, food adulteration, food impurity, expired food and others issues.

Food adulteration is one of the major consumer issues in developing countries as it has a direct impact on human health. Food adulteration occurs due to decreased production costs and greater market demand than supply, especially for recent COVID-19 pandemic conditions. It is difficult for consumers to detect adulterated food through the human senses and can only go through laboratory equipment because the food has been substituted or mixed with other permitted or prohibited substances. Therefore, the development of food and beverage assessments is essential and should be a priority to ensure food safety and public health. Several methodological procedures and technologies have been developed for food and beverage assessment, including imaging, odour, taste, electromagnetic sensing, and others. (Abasi et al. 2018 ).

Examples of reviews in food quality analysis and detection of food adulteration include the analysis of meat and its products, milk, and fruits that have been introduced using several technologies. The imaging technologies, especially for hyperspectral imaging, are focused on the colour, shape and texture of substances. Odour and taste sensing technology (Quartz Crystal Microbalance (BAW), Metal Oxide Semiconductor (MOS-based electronic nose), and Electrochemical biosensors are focused on the specific components of an aroma or solution and analyses their chemical composition by contact with its headspace and immersed in sample respectively, whereas electromagnetic sensing technology measures the electromagnetic wave transmission coefficient using the frequency, polarization, and angle of incidence of the electromagnetic wave, as well as the object's permittivity and conductivity. (Mustafa et al. 2019 ; Wei et al. 2018 ).

The motivation for this work originated from studying research papers in the area of technology integration, which stated that technology integration generally outperforms independent systems in terms of classification and quality evaluation. Thus, this work anticipates that signals from various techniques can be integrated using appropriate fusion and deep learning algorithms to provide results closer to mammalian sensory systems. This review will introduce the principles, advantages and disadvantages of the current in evaluating the quality of food and beverages, as well as the differences among this technique.

Assessment method using imaging technology

Imaging technology utilizes imaging processing technique to create or display two-dimensional or three-dimensional image. With the advancement of technology nowadays, the functionality of cameras and the clarification of image enable us to explore the external and internal structure of food products, which increase the accuracy and sensitivity in food quality analysis especially in agricultural-related rural products. Current food analysis devices which using imaging technology (as Fig.  1 ) including hyperspectral imaging, x-ray imaging, odour imaging as well as digital and analogue imaging devices.

Dedicated device based on Imaging Technology, that is including a Hyperspectral Imaging System with output mapping. (Li et al. 2018 ), b Colorimetric Sensor System with the output image. (Chen et al. 2014 ), and c Digital Imaging (Computer Vision) System with output processed image (Liu et al. 2018 ) d X-ray Imaging System (Papachristodoulou et al. 2018 )

Hyperspectral imaging (HSI)

HSI is a technique that combines spectroscopic and imaging approaches into a single system that provides both spectral and spatial data. HSI may use this combined technique to detect various components inside a product and measure their spatial distribution to compute the product's compositional gradient. HSI technique can scan a whole sample inside an image, capturing readings ranging from hundreds to millions of pixels (depending on sample size and camera spatial resolution), and calculating average nutritional values and/or a compositional gradient from these readings. (Tahmasbian et al. 2021 ).

HSI shows its abilities to analyse and predict food freshness (Suktanarak and Teerachaichayut 2017 ), chemical composition (Jamshidi et al. 2016 ; Barbin et al. 2013 ), and quality attributes (Kamruzzaman et al. 2016 ; Li et al. 2018 ). In food freshness, (Suktanarak and Teerachaichayut 2017 ) assessed the freshness of an egg by correlating a Standard HU value (using calculation on the weight of the egg and average height of the albumen) with the colour image captured by 900–1,700 nm Near-Infrared (NIR) hyperspectral imaging technique using Partial Least Square Regression (PLSR) model.

In chemical content, Barbin et al. ( 2013 ) constructed an experiment to determine the chemical composition of intact and minced pork using NIR hyperspectral imaging. This experiment used spectra extracted from hyperspectral image and perform the analysis using PLSR with a reference value of moisture, protein and fat contents from Smart Trac (CEM Corporation, Matthews, North Carolina, USA) and LECO FP-428 Nitrogen Determinator (LECO Instruments Ltd., Stockport, UK). In the detection of diazinon in pesticide residue on cucumber, Jamshidi et al. ( 2016 ) created a predictive model using PLSR algorithm to correlate the presence of pesticides and images captured by 450–1000 nm Visible Near-Infrared (VNIR) spectroscopy combined with chemometrics. The experimental results showed excellent execution of the framework planned in the assurance of pesticide residue and the overall health states of the cucumber grouping.

In quality attributes, Kamruzzaman et al. ( 2016 ) constructed a Multiple Linear Regression (MLR) model by choosing a set of feature wavelengths from a 400–1000 nm VNIR hyperspectral imaging system, which is aimed to correlate with the CIE L*a*b* colour space of fresh beef, lamb, and pork meat from the colourimeter. The integration of PLSR models (Li et al. 2018 ) with the image captured from 600–975 nm VNIR and 865–1610 nm short-wave infrared (SWIR) hyperspectral imaging to predict the plum quality in terms of colour (L*, a* and b*) and SSC.

HSI application showed potential in food and beverage quality assessment. However, the HSI application currently available in market are large size of the equipment, expensive, and difficult to manage and mostly used in laboratories. Furthermore, due to the design of mechanically moving components and frame rates limitation, the existing hyperspectral imaging cameras are only able to scan one line at a time. This limitation requires further study for better improvement especially in time usage (Schneider and Feussner 2017 ).

X-ray imaging

X-ray imaging is a non-contact sensor, which records the remaining of an x-ray beam transmission after passing through the body of an object. It's generally employed in medical diagnostics, item inspection, and even agricultural items to discover interior imperfections. Energy-dispersive X-ray fluorescence spectroscopy (EDXRF) is one of the X-ray imaging technologies used to assess the quality of foods and beverages. It is used to determine the concentration of chemical elements such as K, Ca, Fe, Zn, Br, Rb, Cl, Cu, Mg, P, S, Se, Sr in milk powder (Rossmann et al. 2016 ; Papachristodoulou et al. 2018 ) and fat content in the green pork hams by combining Ultrasonic velocity (υ) and X-ray absorption (de Prados et al. 2015 ). Multivariate statistical methods, (Rossmann et al. 2016 ; Papachristodoulou et al. 2018 ) was used for close monitoring in milk powder production to ensure good manufacturing practices and stable infant formula quality.

Compared with conventional method, X-ray imaging technology is more effective in the detection of the metallic contaminant and other foreign non-metallic material such as bone, glass, wood, plastic, and rocks. The non-destructive features especially in viewing samples' interior features to detect hidden defects or contaminants make the X-ray imaging technology to become more popular. However, the usage of X-ray imaging technology require a relatively high cost and high voltage power supply, as well as the need of radiation shielding and the risks inherent in using radiation. (Haff and Toyofuku 2008 ).

Odour imaging

Currently, there is a cutting-edge technology for non-visible matter (odour) detection, which is an odour imaging-based colorimetric sensor array. The fundamental principle of odour imaging technology is based on colorimetric sensors, which utilizes the shading change brought about by the response between unstable substances and a progression of artificially responsive colours after chemo-responsive dyes (as main sensing unit of colorimetric sensor) detect and distinguish chemical vapours and then express response information in the form of imaging. The odour imaging-based colorimetric sensor array technology is comprised of a sensor array, a computer or controller, and a scanner. The sensor array acquired the sensor response value from the chemical vapour and converted it into colorimetric data. Before being processed by a computer or controller, the colorimetric data is transformed into an image using a scanner. (Rodríguez-Pulido et al. 2017 ).

There are several experiments conducted to prove the relationship between the concentration or presence of chemical vapour and food and beverage quality (Morsy et al. 2016 ; Chen et al. 2014 , 2017 ; Bordbar et al. 2018 ). Firstly, colorimetric sensor array technique (Chen et al. 2014 ) is used to evaluate the freshness of chicken by using orthogonal linear discriminant analysis (OLDA) and adaptive boosting (AdaBoost) algorithm, namely AdaBoosteOLDA. Morsy et al. ( 2016 ) used non-destructive approaches and sensors for fish decay evaluation by assessing sixteen chemo-sensitive compounds (Alizarin, Bromocresol Green, Bromocresol Purple, Bromothymol Blue sodium salt, Bromophenol Blue, Xylenol Blue, Chlorophenol Red, Cresol Red, Crystal Violet Lactone, Reichardts dye, 2,6-dichloro-4-(2,4,6-triphenyl-1-pyridinio) phenolate, Phenol Red, Rosolic acid, Methyl Red, Curcumin and Carminic acid), mixes consolidated in a cluster for colorimetric recognition of common deterioration mixes (trimethylamine, dimethylamine, cadaverine, and putrescine). The experiment also effectively assessed the signal intensity recorded with the colorimetric exhibit according to fish decay time, as well as demonstrated the relationship between fish decay time and the adjustment of thiobarbituric acid, total volatile nitrogen, pH, and oxygen concentration. Next, Chen et al. ( 2017 ) developed a low-cost solution by repurposing the food's barcode as a colorimetric sensor cluster to monitor chicken aging and quality by using a smartphone camera. The experiment also collected the measurement of VOC from Nile red and Zn-TPP and pH from Methyl red and the result showed that colour change in pH and VOC responsive dyes are a clear indication of food aging under various temperature conditions. On the other hand, Bordbar et al. ( 2018 ) developed an alum and synthetic acetic acid detection and determination for fraud detection in pickle by using unsupervised by using unsupervised pattern recognition methods such as Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) and PLSR through image analysis. This research showed the satisfied result by acquiring 0.469 and 0.446 for alum and also 1.34 and 0.933 for acidic corrosive in Root Mean Square Error for adjustment and expectation respectively.

As a summary, the colorimetric sensor array based on odour imaging can detect some analytes effectively. This technology has the potential for mass production and deployment due to its ease of fabrication, lightweight and compact and easy integration with cameras. However, it is difficult to analyse large data sets of RGB values to classify the individual components of a mixture. (Kangas et al. 2016 ).

Digital and analogue image processing

Computer Vision System (CVS) is a framework that incorporates a lighting arrangement, camera, and image investigation programming utilizing a PC. It has been widely used in the food industry and as it is known to be quick, prudent, steady, precise and non-intrusive (Husin et al. 2012 ; Zareiforoush et al. 2016 ). Numerous undertakings have been made to expand the utilization of CVS in the agricultural field, such as spicy powder quality assessment (Shenoy et al. 2015 ), red meat colour, marbling score (Sun et al. 2018 ), imperfection (Chmiel and Słowiński 2016 ) and intramuscular fat rate (IMF%) prediction and quality evaluation (Liu et al. 2018 ). (Liu et al. 2018 ) used stepwise regression and support vector machine models to estimate pork intramuscular fat rate (IMF%) by collecting RGB, HSI, and L*a*b* colour space, and the accuracy results were obtained 0.63 and 0.75 for regression models and support vector machine, respectively. (Sun et al. 2018 ) had developed a CVS to determine the colour and marbling score of pork loin using vector machine forecast model and obtained the prediction accuracy of 92.5% and 75.0%, for measured colour and marbling score respectively. (Chmiel and Słowiński 2016 ) had proven the usefulness of CVS to distinguish meat imperfections of m. longissimus lumborum (LL) by measuring the colour of the meat in CIEL*a*b* and obtained the highest accuracy of 82.6%. According to (Shenoy et al. 2015 ), digital colour imaging method (DCI)can be used for assessing the mixture quality of spice powder, as it showed a good trend with the salt concentration method where there is colour difference between the powders.

CVS able to extract various characteristics, such as colour, image texture, shape and scale. With accuracy, objectivity and speed, these simple appearance characteristics allow task-relevant analysis and interpretation. These appearance characteristics can correlate well with several physical, chemical and sensory food quality indicators. These quality attributes are often related to characteristics that can be assessed directly by non-destructive frameworks. Since quality features are related to physicochemical properties, several methods of image processing have been developed, making a significant contribution to the industrial requirements for automated inspection and grading. However, higher resolutions and faster processing of features are needed for digital image processing, since a large amount of data needs to be processed in a short period or in real-time. (Valous and Sun 2012 ).

Assessment method using odour and tasting sensing technology

The sensation of smell and taste is one of the analytical tools used in food industry for the early detection of quality changes in food products. However, the cost of hiring tangible professionals is high and limited by the fact that our sense of smell and taste is subjective and gets tired easily. Different confinements of tangible evaluation incorporate the reproducibility of the outcomes and low reproducibility, which makes tangible evaluation impossible to provide quantitative research (Majchrzak et al. 2018 ). As such, is absolutely necessary to have an instrument that can mimic the human sense of smell and taste and to be used in routine industrial applications. Gas chromatography is one of the great inventions used to determine the physicochemical properties of products. In order to promote this technology to industrial application, several instruments are created for the purpose of quality evaluation of food and beverages as shown in Fig.  2 . (Peris and Escuder-Gilabert 2016 ).

Dedicated device based on odour and taste Technology, that is including a Metal Oxide Semiconductor System (Wijaya et al. 2017 ), b Quartz Crystal Microbalance Sensor System (Debabhuti et al. 2019 ), and c Electrochemical sensor System (Di Rosa et al. 2017 )

Metal-oxide semiconductor (MOS)

This MOS has been more widely used to make arrays for odour measurement than any other class of gas sensors. It has a gas-sensitive film consisting of tungsten oxide or tin oxide. The most widely used material in the film is tin dioxide (SnO 2 ) doped with a small amount of a catalytic metal such as palladium or platinum. When the gas (oxygen) reaches the sensor under normal circumstances, the gas reacts and is absorbed into the film and combines with electrons, thus causing the blocking of electron flow and the sensor remains unpowered. However, in the presence of a reducing gas, the gas (oxygen) is absorbed by the gas molecules, resulting in zero electron attraction, resuming the electron flow and activating the sensor. Also, by changing the choice of catalyst and operating conditions, tin dioxide resistive sensors have been developed for a range of applications, especially in food and beverage assessment. Food and beverage normally released several volatile organic compounds (VOCs) that belong to certain chemical groups such as sulphur and aliphatic (methane, ethane, propane and butane). By using the MOS abilities and characteristics of VOCs from food and beverage, several kinds of research have been accomplished performing food and beverage assessment, in terms of freshness (Wijaya et al. 2017 ; Du et al. 2015 ), classification (Heidarbeigi et al. 2015 ), and content prediction (Li et al. 2016 ).

In classification, (Heidarbeigi et al. 2015 ) used electronic nose to classify various kinds of saffron. A sensor array of six MQ-type metal oxide semiconductors (HANWEI Electronics Co., Ltd., Henan, China) is used in the electronic nose and the sensor data collected from a data acquisition card (NI USB-6009, National Instrument), for classification purpose (PCA and Backpropagation Neural Network, BPNN). The experiment result showed that 86.87% success rate among classification of saffron and different percentage mixture with dyed corn stigma and yellow style, and 100% success rate between classification saffron and different percentage of safflower, using BPNN algorithm. In content prediction, (Li et al. 2016 ) implemented pork freshness with different packaging methods using PEN3 E-nose (an array of 10 different metal oxide sensors) together with PCA and MLR algorithm to correlate the total viable counts (TVC) and total volatile basic nitrogen (TVBN). This study showed that the increase of TVBN in meat samples is related to the decomposition activity of spoilage bacteria and endogenous enzymes, which is producing many volatile organic compounds such as alcohols, ketones, hydrogen sulfide, aldehydes, and organic acid.

In freshness, a portable electronic nose device system was developed by (Wijaya et al. 2017 ), to monitor the beef freshness which consist of a combination between 10 MQ-type gas sensors and Arduino Mega SDK microcontroller and K-Nearest Neighbour algorithm. The experimental results showed the system is perfectly distinguished fresh and spoiled beef by achieving classification accuracy for binary, three classes, and four classes classification with 93.64%, 86.00%, and 85.50%, respectively. (Du et al. 2015 ) employed six tin oxide sensors (Figaro Engineering Inc.) with PCA and Fisher Linear Discriminant as the classifier to determine shrimp freshness. The sensory evaluation and the content of Total Volatile Basic Nitrogen (TVBN) were performed to indicate the freshness of the shrimp and the result showed that the discriminant rates were 98.3% for 120 modeling sample data, and 91.7% for 36 testing sample data.

The utilities of MOS sensor in food and beverage assessment is high, due to its high sensitivity to chemicals in a wide range of VOCs, reliability, and reproducibility. However, its ability to operate in high temperature require more power supply, and make it susceptible to humidity which makes it to prone to drift. (Örnek and Karlik 2012 ).

Quartz crystal microbalance (QCM)

QCM is a highly sensitive mass sensing technique that can detect changes in mass in the nanogram range. This means that QCM sensors can detect changes in mass as tiny as a fraction of a monolayer or a single atom layer across sensor crystal. High sensitivity and real-time monitoring of mass changes in sensor crystal make QCM an attractive method for gas sensors. Several researchers employed QCM sensors to collect volatile gas data for food and beverage assessment, in terms of freshness (Mohareb et al. 2016 ) and classification (Kodogiannis 2018 ; Sharma et al. 2015 ; Debabhuti et al. 2019 ).

In freshness assessment, (Mohareb et al. 2016 ) constructed efficient tools for beef freshness to correlate the population of selected microbial groups, namely total viable counts (TVC), Pseudomonas spp., B. thermosphacta, Enterobacteriaceae, and lactic acid bacteria, to the responses of the electronic nose sensors from an electronic nose (LibraNose, Technobiochip, Napoli, Italy), sensory score and Ensemble-based support vector machines algorithm (bagging and boosting). The result showed that overall prediction was also increased in the case of regression models for bacterial species count prediction from 76.5% to 85.0%.

In classification, (Kodogiannis 2018 ) distinguished fresh, semi-fresh, and spoiled beef using a QCM sensor (Libra enose, eight 20-MHz AT-cut quartz crystal microbalances positioned in a measurement chamber) and a Multi-Input Multi-Output (MIMO) Clustering Fuzzy Wavelet Neural Network (CFWNN). The result showed that the model overall achieved a 95.7% correct classification, and 100%, 87.5% and 100% for fresh, semi-fresh and spoiled meat samples, respectively. (Debabhuti et al. 2019 ) and (Sharma et al. 2015 ) used six and eight QCM sensors respectively to collect the aroma released by mango and black tea and the sensor output is checked progressively utilizing NI PCI6602 data acquisition card as well being stored in the personal computer. Research results on black tea fermentation and mango maturity using the PCA algorithm showed that the QCM sensor cluster is suitable for real-time, field-deployable and accurate techniques to observe the maturity stage of mango and aging time of black tea.

The popularity of QCM sensor in food and beverage assessment was due to its high accuracy, detection of wide range of active element and low cost of production. However, the QCM sensor consists of complicated electronics with high sensitivity, poor signal-to-noise ratio, humidity and temperature sensitivity. (Guz 2019 ).

Electrochemical sensor

The electronic tongue or electrochemical sensor is a taste sensor system linked to the model recognition apparatus to analyse the complex fluid media, such as food and beverages. The techniques used in electrochemical techniques included potentiometry (Zhang et al. 2015 ) and cyclic voltammetry (Pauliuc et al. 2020 ; Li et al. 2015 ; Apetrei and Apetrei 2016 ).

The potentiometry method is implemented for measuring the potential between two electrodes in the absence of current. The measured potential can be utilised to identify the analyte of interest, especially on the concentration of particular solution components. (Zhang et al. 2015 ) implemented the TS-5000Z electronic tongue sensor system (Insent Inc., Japan, consisting of a bitterness sensor (SB2C00), umami sensor (SB2AAE), saltiness sensor (SB2CT0), sourness sensor (SB2CA0), and astringency sensor) and PCA algorithm to evaluate meat quality based on taste assessment, recognition and correlation with meat chemical composition. The result showed that fat content had the highest positive correlation with sourness ( r  = 0.8002, P  < 0.001) while was negatively correlated with umami ( r  =  − 0.9086, P  < 0.001) and saltiness ( r  =  − 0.8197, P  < 0.001).

A voltammetry method collects the Faradic current and capacitive current when the electrodes are immersed in the tested solution and there are compounds in the solution that are electrochemically active at the applied potential. The voltammetry method has been used in a variety of studies in food and beverage evaluation, including milk adulteration, honey authentication, and ammonia detection. (Apetrei and Apetrei 2016 ) created a Partial Least Squares-Discriminant Analysis (PLS-DA) model to detect putrescine and ammonia in beef samples using data from the Biologic SP 150 potentiostat/galvanostat (Bio-Logic Science Instruments SAS, France). The validation of the PLS-DA model was performed using the leave-one-out fully cross-validation method, obtaining in all cases more than 96% levels of correct classification with higher than 97% sensitivities and more than 96% specificities. The PCA model was built by (Pauliuc et al. 2020 ) and (Li et al. 2015 ) to authenticate Romanian honey and examine the milk contamination with urea, respectively using data from the voltammetric electronic tongue (electrochemical station CHI660E, Shanghai Chenhua Organization; PGSTAT 204 with FRA32M module, Metrohm, Filderstadt, Germany). The studies demonstrated the capability of the voltammetry technique to perform a quick representation of urea-corrupted milk segregation and nectar test. (Kundu et al. 2019 ).

Electrochemical sensors have shown their potential advantages in food and beverage assessment, including high accuracy and high sensitivity to chemical constituents, together with low power consumption. However, the ability of electrochemical sensor decreases with time due to the degradation of the electrode catalyst and eventually polluted in-process applications by process gases. Moreover, the electrochemical sensor only operates with a limited temperature range and has mild selectivity. (Manjavacas and Nieto 2016 ).

Assessment method using electromagnetic sensing technology

This electromagnetic sensing technology depends on a planar electromagnetic sensor with radio recurrence excitation and utilized PC for calculation to achieve online quality monitoring. Planar electromagnetic sensing is a non-destructive technique and evaluation based on inductive, capacitive or electromagnetic approaches, which depends on material dielectric properties as well as the electrode and material geometry affect the capacitance and the conductance between the two electrodes. This characteristic is gaining popularity in several applications, including material permittivity analysis, gas detection, and even food inspection. Online sensing systems suitable for the food and beverage industry need to have some key characteristics and qualities to meet the requirements, including cost feasibility, high reliability in terms of estimation accuracy and estimation speed. At the same time, the sensor technology must be able to estimate volumetric permeability in order to measure performance throughout the product, which can be achieved by using planar electromagnetic detection technology as shown in Fig.  3 (Gooneratne et al. 2005 ). The example of planar electromagnetic sensing technology is planar interdigital sensing, planar meander sensing, and planar microstrip ring sensing.

Dedicated device based on electromagnetic sensing Technology, that is including a Experimental setup for food analysis(Abdullah et al. 2016 ), b planar Interdigital sensor design (Mukhopadhyay and Gooneratne 2007 ), and c planar microstrip ring sensor design (Jilani et al. 2014 ) and d planar meander sensor design (Gooneratne et al. 2005 )

In planar interdigital sensing, (Mukhopadhyay and Gooneratne 2007 ) developed a non-destructive novel interdigital biosensor for measuring fat content in pork using the characteristics of the generation of AC source and electromagnetic field generated from two electrodes. The experiment also conducted a reference analysis for fat content analysed by Soxhlet extraction of the homogenized sample (including the skin) using petroleum ether and the result showed that they are quite distinctive among different parts of pork meat in terms of impedance value. In sugar content measurement, (Siriporn et al. 2018 ) compared the measurement from a planar interdigital sensor with the readings on a refractometer and the results showed that correlation coefficient (R 2 ) was obtained at 0.9805.

In microstrip ring sensing, (Jain and Mishra 2019 ) microstrip ring dampness sensor was used in determining the moisture of rice grain by utilizing stove drying technique and measured by the vector network analyzer (Model No. Field fox N9925A). (Jilani et al. 2016 ) also successfully proposed a solution for determining the moisture of broiler chicken meat using microwave ring resonator sensor and measured by using Anritsu MS2034B vector network analyzer over the range of 0–4 GHz, which is showing the significant changes when the corresponding capacitance decreases 30% in the early ageing (0D–7D) period.

For planar meander sensing, (Abdullah et al. 2016 ) proposed a detecting adulteration system that can differentiate between beef and pork meat. The experiment is collected S21 measurement and impedance for different parts of beef and pork and the result showed that the pork has a higher value of S21 (dB), higher resonance frequency (2.76 GHz) and impedance (Ω) compared to beef.

The ability of electromagnetic sensing technology including capacitive and dielectric properties to investigate functional relationships with impedance, frequency, fat content, soluble solid content, moisture content and other processing parameters would greatly useful in food and beverage quality assessment. This technology's responsiveness to structural alterations that may emerge during heating or other physical interactions should be improved because of the size of the detected sample or the various samples needing distinct structural designs. (Khaled et al. 2015 ).

Conclusion and future trends

As can be seen from the above studies, it is noted that the technology used in food and beverage assessment still requires further research to investigate and study the more specific elements that could be used to improve the quality of evaluation. It is critical to prevent food adulteration as a result of inadequate food supply for the increasing population. Recently, people pay more and more attention to food and beverage quality, which urge the demand of dedicated portable non-destructive equipment. The characteristics of low cost, lightweight, user-friendliness and quick inspection are particularly concentrated in such instruments A survey of the literature indicates that researchers have recently begin to design and develop portable and/or handheld devices on food and beverage assessment. Artificial intelligence technology was encouraged to incorporated into detection technologies in order to reduce the human resource and human error.

It should be pointed out that the recommendation made for the integration between image, odour, taste and electromagnetic technology using appropriate fusion and deep learning algorithm that can provide results closer to mammalian sensory systems for the food and beverage assessment. It is because each method acts as a part of the human body, just as the imaging method acts as the human eye, the smell method acts as the human sense of smell, followed by the taste method acts as the human tongue. Last, the electromagnetic effect acts like human skin. Each method has its own advantages and disadvantages. Each method has its own advantageous and disadvantageous as shown in Table 1 . When one of the methods failed to perform, there are still other methods can perform to cover the fault. A decision-making system is necessary to make the right decision to perform the collaborative between each technique. Currently, deep learning is a promising technique, which the performance is much better than machine learning. The deep learning applications use a layered structure of algorithms called an artificial neural system, which is motivated by the organic neural system of the human mind, prompting a procedure of discovering that is unmistakably more able than that of standard AI models. The summary of this review article is presented in Table 2 .

Comparison between electronic senses, sensory analysis and conventional laboratory instruments features. (Di Rosa et al. 2017 )

Application of dedicated devices on food assessment

Acknowledgements

The authors acknowledge the financial support from Universiti Malaysia Perlis (UniMAP) and Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme (FRGS) number: FRGS/1/2019/TK04/UNIMAP/02/7.

Authors’ contributions

WKT: conceptualization, investigation, software, writing—original draft. MLY methodology, writing—review and editing, investigation. MAHI: visualization, investigation. ZH: validation, Writing—review and editing, Supervision.

We acknowledge the financial support from the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme (FRGS) number: FRGS/1/2019/TK04/UNIMAP/02/7; all of which enabled us to carry out this study.

Code availability

Not applicable.

Availability of data and material

Declarations, conflict of interest.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Contributor Information

Wei Keong Tan, Email: [email protected].

Zulkifli Husin, Email: [email protected].

Muhammad Luqman Yasruddin, Email: [email protected].

Muhammad Amir Hakim Ismail, Email: [email protected].

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The Best Diet: Quality Counts

• Dietary guidelines have changed over the years as research becomes more accurate in determining what we should eat to attain optimal health and weight. The strongest evidence to date shows that calories matter, but focusing on food quality is an equally important part of preventing weight gain and promoting weight loss.
• Focus on eating high-quality foods in appropriately sized portions.

Consider quality, not just calories

  “A calorie is a calorie” is an oft-repeated dietary slogan, and not overeating is indeed an important health measure. Rather than focusing on calories alone, however, emerging research shows that quality is also key in determining what we should eat and what we should avoid in order to achieve and maintain a healthy weight. Rather than choosing foods based only on caloric value, think instead about choosing high-quality, healthy foods, and minimizing low-quality foods.

• High-quality foods include unrefined, minimally processed foods such as vegetables and fruits, whole grains, healthy fats and healthy sources of protein – the foods recommended in the Healthy Eating Plate .
• Lower-quality foods include highly processed snack foods, sugar-sweetened beverages, refined (white) grains, refined sugar, fried foods, foods high in saturated and trans fats, and high-glycemic foods such as potatoes.

There isn’t one “perfect” diet for everyone, owing to individual differences in genes and lifestyle.

Quality counts

One study analyzed whether certain foods were more or less likely to promote weight gain. This type of research examining specific foods and drinks allows us to understand whether “a calorie is a calorie,” or if eating more higher-quality foods and fewer lower-quality foods can lead to weight loss and maintenance.

Researchers in the Department of Nutrition at Harvard School of Public Health show us that quality is in fact very important in determining what we should eat to achieve and maintain a healthy weight, and that the notion of “a calorie is a calorie” does not tell the whole story.

• In a study of over 120,000 healthy women and men spanning 20 years, researchers determined that weight change was most strongly associated with the intake of potato chips, potatoes, sugar-sweetened beverages, and both processed and unprocessed red meats. The researchers concluded that consumption of processed foods higher in starches, refined grains, fats, and sugars can increase weight gain.
• Foods shown to be associated with weight loss were vegetables, whole grains, fruits, nuts, and yogurt.
• Researchers did not discount the importance of calories, instead suggesting that choosing high-quality foods (and decreasing consumption of lower-quality foods) is an important factor in helping individuals consume fewer calories. ( 23 )

View the HSPH news release , “Changes in specific dietary factors may have big impact on long-term weight gain: Weight-loss Strategy to Only ‘Eat Less, Exercise More” May be Overly Simplistic’”

Managing macronutrients: Does it matter?

With the proliferation of macronutrient-based diets over the past several decades, from low-fat to low-carbohydrate, discussion of the three main macronutrients – carbohydrates, proteins, and fats – has become standard when talking about optimal diets. Researchers have begun comparing these “macronutrient management”-style diets to one another in order to determine which is most effective, but thus far evidence is largely inconclusive.

One study, published in JAMA in 2007, compared four weight-loss diets ranging from low to high carbohydrate intake. This 12-month trial followed over 300 overweight and obese premenopausal women, randomly assigning them to either an Atkins (very low carbohydrate), Zone (low carbohydrate), LEARN (high carbohydrate), or Ornish (very high in carbohydrate) diet.

• After one year, weight loss was greater for women in the Atkins diet group compared with the other diet groups.
• This study also examined secondary outcomes focused on metabolic effects (such as cholesterol, body fat percentage, glucose levels and blood pressure), and found that those for the Atkins group were comparable with or more favorable than the other diet groups.
• There was no significant difference in weight loss among the other three diets (Zone, LEARN, and Ornish).
• This study does raise questions about about long-term effects and mechanisms, but the researchers concluded that a low-carbohydrate, high-protein, high-fat diet may be considered a feasible recommendation for weight loss. ( 24 )

Another study, published in The New England Journal of Medicine in 2009, challenged the above study’s findings by testing four different types of diets and producing results that showed comparable average weight loss among the different diets.

• The study followed 800 people over 2 years, assigning subjects to one of four diets: Low-fat and average-protein, low-fat and high-protein, high-fat and average-protein, and high-fat and high protein.
• Researchers concluded that all of the diets resulted in meaningful weight loss, despite the differences in macronutrient composition.
• The study also found that the more group counseling sessions participants attended, the more weight they lost, and the less weight they regained. This supports the idea that not only is what you eat important, but behavioral, psychological, and social factors are important for weight loss as well. ( 25 )

An additional study, published in The New England Journal of Medicine in 2010, looked at the role of protein and glycemic index upon weight loss maintenance. Researchers first implemented a low-calorie diet to produce weight loss, then examined whether protein and glycemic index impacted weight loss maintenance.

• The study population was made up of nearly 800 overweight adults from European countries who had lost at least 8% of their initial body weight with a low-calorie diet. Participants were then assigned one of five diets to prevent weight regain over a 26-week period: A low-protein and low-glycemic-index diet, a low-protein and high-glycemic-index diet, a high-protein and low-glycemic-index diet, a high-protein and high-glycemic-index diet, or a control diet.
• The low-protein-high-glycemic-index diet was associated with subsequent significant weight regain, and weight regain was less in the groups assigned to a high-protein diet than in those assigned to a low-protein diet, as well as less in the groups assigned to a low-glycemic-index diet than in those assigned to a high-glycemic-index diet.
• These results show that a modest increase in protein content and a modest reduction in the glycemic index led to an improvement in maintenance of weight loss. ( 26 )

The results from these three studies suggest that there may be some benefits to a macronutrient-based dietary approach, but research also shows that while a particular diet may result in weight loss for one person, it may not be effective for another person due to individual differences in genes and lifestyle. For those seeking the “perfect” one-size-fits-all diet, then, there isn’t one! The great news is that everyone can follow The Healthy Eating Plate guidelines and choose healthy, flavorful foods to create a diet that works best for you.

23. Mozaffarian, D., et al., Changes in diet and lifestyle and long-term weight gain in women and men . N Engl J Med , 2011. 364(25): p. 2392-404. 24. Gardner, C.D., et al., Comparison of the Atkins, Zone, Ornish, and LEARN diets for change in weight and related risk factors among overweight premenopausal women: the A TO Z Weight Loss Study: a randomized trial. JAMA , 2007. 297(9): p. 969-77. 25. Sacks, F.M., et al., Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates . N Engl J Med , 2009. 360(9): p. 859-73. 26. Larsen, T.M., et al., Diets with high or low protein content and glycemic index for weight-loss maintenance . N Engl J Med , 2010. 363(22): p. 2102-13.

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Food is Medicine: A Project to Unify and Advance Collective Action

The White House Conference on Hunger, Nutrition, and Health — held in September 2022 — renewed national attention and issued a call to action to end hunger and reduce the prevalence of chronic disease in the United States by 2030.  

Food is Medicine approaches that focus on integrating consistent access to diet- and nutrition- related resources are a critical component to achieve this goal. The approaches are increasingly present across many communities and systems. There’s also increasing federal investment and action to support Food is Medicine approaches in a variety of settings. 

Building on this collective energy, the Department of Health and Human Services (HHS) developed a Food is Medicine initiative in response to a congressionally funded initiative in fiscal year 2023. This congressional action directed the Secretary of HHS, in consultation with other federal agencies, to develop and implement a federal strategy to reduce nutrition-related chronic diseases and food insecurity to improve health and racial equity in the United States. This includes diet-related research and programmatic efforts that will increase access to Food is Medicine initiatives.

Go to Food Is Medicine

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Almost half of the US is experiencing drought. How that can affect the food industry.

The dryness could impact the quality of many fall harvest crops, experts say.

The U.S. is experiencing the driest fall on record, which could potentially impact the quality of upcoming autumn harvests, experts told ABC News.

About 77% of the mainland U.S. is abnormally dry, and almost half of the country is experiencing drought, according to the U.S. Drought Monitor . The spatial pattern of the dry conditions varies widely across the continent, Josue Medellin-Azuara, a professor of civil and environmental engineering at the University of California Merced, told ABC News.

MORE: Florida's farmlands, iconic orange groves recovering following back-to-back hurricanes

Improvement in the drought is not expected for most of the South, the Plains and parts of the Upper Midwest due to expected La Nina conditions this winter that would further reinforce the dryness, according to forecasts by the National Oceanic and Atmospheric Administration.

However, a lot of the crops in these regions that harvest in the fall had good growing conditions throughout the summer and are in the process of being harvested, meaning overall output should not be heavily impacted, Joseph Glauber, senior research fellow at the International Food Policy Research Institute and former chief economist for the U.S. Department of Agriculture, told ABC News.

Some summer crops are even expected to see record outputs, according to the latest report from USDA’s National Agricultural Statistics Service . Record yields for both corn and soybean -- at 183.8 bushels per acre and 53.1 bushels per acre, respectively -- are expected.

The drought conditions are a relatively recent development. As of June 2024, drought coverage in the U.S. stood at a four-year low, according to the USDA , citing U.S. Drought Monitor statistics.

MORE: More than half of water from Colorado River used for agriculture industry, report finds

Drought conditions in the continental U.S. increased from 12% in June 2024 to 45% in October 2024, according to the U.S. Drought Monitor. July was "good," but the dryness really started to ramp up in August, Glauber said.

The dryness could impact the quality of many fall harvest crops, such as the test weights of the yields, Glauber said. The sudden turn toward dry weather has promoted a rapid pace of summer crop maturation and harvesting, according to a statement provided to ABC News by the USDA. By Oct. 20, more than 81% of the U.S. soybeans and 65% of the corn had already been harvested, compared to the respective five-year averages of 67% and 52%.

"Anytime you stress a plant, you risk plant problems that could develop," Glauber said.

A fall drought can also encourage a ripple effect throughout the following seasons, Precious Tshabalala, an economist with the Food & Environment program at the Union of Concerned Scientists, told ABC News.

MORE: Food prices could increase further due to climate change's effect on inflation around the world: Study

The USDA Economic Research Services is predicting a less than 2% rise in food prices in the near future, but if the food in question is used to feed livestock, a domino effect of increasing prices -- for dairy and meat -- could occur, she said,

"Any disruptions in the water supply during the critical phases harvesting or even the growing season could translate to lower yields," Tshabalala said.

In addition, there has been some recent degradation of rangeland and pastures, as well as a lack of soil moisture for the establishment of fall-sown crops, including winter wheat, according to the USDA. By Oct. 20, nearly half (48%) of the U.S. rangeland and pastures were rated in very poor to poor condition.

MORE: North America experienced an unprecedented 'hot drought' in the last century, new research shows

Places like California that have high variability in precipitation are used to these conditions, Medellin-Azuara said. They typically rely on the melting of the winter snowpack, which then flows into rivers that are irrigated into agricultural fields.

"At this point, we're not as affected by drought," he said. "We produce most of the crops in the summer."

Despite the impacts of drought, food prices are not expected to be affected by much, Glauber said, adding that it is usually the global market -- such as the outbreak of the war in Ukraine's impact on wheat production -- that causes prices to rise drastically.

"The price of the typical groceries in the food store -- only 25% of that is farm value," Glauber said. "The rest is post-farm, so transportation costs and distribution costs, and even things like wage rates, which have all gone up since the pandemic."

MORE: How the agriculture industry must adapt to megadrought in the West: Experts

Tshabalala warned that as global warming worsens, so will the variability of precipitation and the impact on farmers and food prices.

"These catastrophic weather events will lead to temperature and rain variations, increasing the risk for the farmer and in turn, affecting food availability and ultimately food prices," she said. "We've seen this in the past before, so the trend is still the same, if not getting worse."

ABC News' Max Golembo contributed to this report.

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Cite this chapter

• Iuliia V. Ugarova   ORCID: orcid.org/0000-0002-3312-4398 13 ,
• Elena N. Bolkhovitina   ORCID: orcid.org/0000-0002-5901-8446 13 &
• Alla Yu. Gorbunova 14  

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Between 2010 and 2018, Russian public catering market has overcome several falls and rises of the market due to certain trends and special features. The paper aims to define the key factors that constrain the growth of public catering regarding regional features and specifying feasible growth drivers for the business sector. The paper compares regional features with national and world trends in catering by employing analytical reviews and statistics from national and regional statistical offices. The formal questionnaire for Altai Krai residents helped to define regional features. The research employed analysis techniques, comparison, statistical techniques, expert evaluation approach, etc. The article presents the findings which reflect regional features and show the most attractive public catering formats for the residents: cafes, bars, and fast food restaurants. The regional consumers show low attendance records for public catering places and have a low average bill. The paper also reveals a conflict between the consumer expectations and real components of quality of service in public catering within the region. In conclusion, the article states major drivers for public catering in the region. Soon one of them will be the format of fast food restaurants. To develop other formats, the region will need to shape some eating choices. The crisis of 2020 has finally shaped another feasible driver in the sector—“ RTE Meals delivery. ”

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Polzunov Altai State Technical University, Barnaul, Russia

Iuliia V. Ugarova & Elena N. Bolkhovitina

Altai State University, Barnaul, Russia

Alla Yu. Gorbunova

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Correspondence to Iuliia V. Ugarova .

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Svetlana G. Maximova

Department of Radiophysics and Theoretical Physics, Altai State University, Barnaul, Russia

Roman I. Raikin

Steppe Institute of the Ural Branch, Russian Academy of Sciences, Orenburg, Russia

Alexander A. Chibilev

Biological Sciences, Faculty of Biology, Altai State University, Barnaul, Russia

Marina M. Silantyeva

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Ugarova, I.V., Bolkhovitina, E.N., Gorbunova, A.Y. (2023). Public Catering Market: Regional Features and Key Growth Drivers. In: Maximova, S.G., Raikin, R.I., Chibilev, A.A., Silantyeva, M.M. (eds) Advances in Natural, Human-Made, and Coupled Human-Natural Systems Research. Lecture Notes in Networks and Systems, vol 234. Springer, Cham. https://doi.org/10.1007/978-3-030-75483-9_15

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DOI : https://doi.org/10.1007/978-3-030-75483-9_15

Published : 17 March 2023

Publisher Name : Springer, Cham

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Online ISBN : 978-3-030-75483-9

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