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Precision agriculture technology adoption: a qualitative study of small-scale commercial “family farms” located in the North China Plain

• Open access
• Published: 12 September 2021
• Volume 23 , pages 319–351, ( 2022 )

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• Helen Kendall 1 ,
• Beth Clark   ORCID: orcid.org/0000-0002-9828-6806 1 ,
• Wenjing Li 1 , 2 , 3 ,
• Shan Jin 1 ,
• Glyn. D. Jones 2 ,
• Jing Chen 4 ,
• James Taylor 5 ,
• Zhenhong Li 6 &
• Lynn. J. Frewer 1  

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Precision agriculture (PA) technologies offer a potential solution to food security and environmental challenges but, will only be successful if adopted by farmers. Adoption in China lags behind that in some developed agricultural economies despite scientifically proven benefits of PA technologies for Chinese agriculture. Adoption is dependent on farmer attitudes and perceptions towards PA technologies. An exploratory qualitative study using in-depth interviews was conducted with Chinese arable farmers (n = 27) to explore their perceptions towards and adoption intentions of PA technologies in two Chinese provinces (Hebei and Shandong). A thematic analysis revealed five central themes to have emerged from the data, these were: “socio-political landscape”, “farming culture”, “agricultural challenges”, “adoption intentions (barriers/facilitators” and “practical support mechanisms” . All were likely to influence the level and rate of adoption of PA technologies amongst family farmers in China. The research revealed an openness to the potential of PA technologies amongst family farmers, although there was heterogeneity in the perceptions of PA technology and willingness to adopt. Improved rates of adoption will be achieved by reducing the barriers to adoption, including the need for low-cost PA applications that can be applied at small scale, improved information provision, financial support mechanisms including more accessible subsidies and credit, and reliable, regulated and affordable service provision.

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Introduction

Precision agriculture (PA) is being implemented globally as an agricultural data management strategy across many agronomic contexts. It is an approach that takes account of temporal and spatial variability to support management decision-making to enable improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production (International Society of Precision Agriculture, no date). The use of PA technologies in particular is aimed at ensuring sustainable intensification across all aspects of agricultural production, whilst reducing its environmental impacts (Gebbers & Adamchuk, 2010 ; Li et al., 2020 ). Their utility in relation to improved food security and environmental protection has been well documented (Cheema & Khan, 2019 ; Gebbers & Adamchuk, 2010 ; Mikula et al., 2020 ; Phillips, 2014 ). PA can be viewed as a ‘toolkit’ from which farmers choose what they (perceive to) need (Lowenberg-DeBoer & Erickson, 2019 ). Although a clear definition of what technologies are included in PA is still required (Lowenberg-DeBoer & Erickson, 2019 ; Say et al., 2018 ) broadly technologies can be classified into: data collection technologies, including, global satellite positioning (GNSS: see Stombaugh, 2018 ); remote sensing technologies (Wachowiak et al., 2017 ), soil sampling and mapping, data processing and decision-making technologies e.g., geographical information systems (GIS) and sensor networks (Jawad et al., 2017 ), and; application technologies, including, variable rate technologies (VRT) (Wandkar et al., 2018 ).

PA technologies are designed to deliver three fundamental benefits to farmers and society: (1) economic benefits through reductions in farm expenditure via the controlled application of agricultural inputs (Tey et al., 2017 ); (2) increased production levels due to targeted management of in-field (or intra-animal) variability (Schimmelpfennig, 2016 ) and; (3) environmental benefits through the precise application of agrichemical applications (such as fertilisers, pesticides or antimicrobials), which will also increase compliance with national/global environmental legislation (Ma et al., 2014 ). Technology uptake in low resource economies falls behind more advanced agricultural economies despite their considerable potential to increase efficiencies in production, inclusion and participation in global markets and improve rural livelihoods (Deichmann et al., 2016 ; Pathak et al., 2019 ). There is scope for the adoption of small, low-cost PA technologies and there are examples of PA uptake in Argentina, Brazil, India and South Africa ( inter alia (Finger et al., 2019 ; Say et al., 2018 )). Rates of PA adoption vary considerably globally, with uptake in China recognised to fall significantly behind Europe and Australia (Chen et al., 2014 ; Say et al., 2018 ). The culmination of social, environmental, political and production pressures identify China as a country with significant potential to benefit from the adoption of PA technologies and make the country an interesting and timely example for their adoption (Li et al., 2019 , 2020 ).

The potential of precision agricultural technologies in China

Intensification of production has historically dominated Chinese agriculture policy (Hauptman, 2018 ). Chinese agricultural production is subject to interacting pressures including, inter alia ; dwindling natural resources, environmental degradation, climate change, and over-reliance on agrichemicals (Cui et al., 2014 ; Hauptman, 2018 ). Social pressures include population growth, rapid urbanisation and increasing socio-economic rural urban divides, and changing consumer preferences (Cui et al., 2018 ; Qian et al., 2016 ).

A variety of policy initiatives have been introduced over the last 50 years to address China’s food security pressures and modernise its approach to agriculture (Zhong & Zhu, 2017 ). These include reducing the ecological impacts of farming by introducing a cap on fertiliser usage (Lin, 2020 ). Widespread agricultural technology adoption is recognised as having a fundamental role to play in the modernisation process, and will contribute to securing China’s future economic growth (Liu et al., 2013 ). It represents a key component of China’s latest 13th, Five-Year Plan that represents the countries social and economic development initiatives, and features in the national 863 Programme (State High-Tech Development Plan). PA is currently concentrated on large-scale commercial agricultural operations, which only account for 0.0007% of all farms in China (Clark et al., 2018 ). This may be in part due to lack of IT infrastructure to support PA technologies, coupled with a lack of capacity both within the industry and intended population, to exploit their potential at scale (Li et al., 2019 ).

Agricultural landscape in China

The Chinese agricultural landscape is characterised by the fragmentation of farmland and a preponderance of small subsistence farms (Table 1 ). This is a legacy of the former Household Responsibility System (HRS) which represented a move away from collective farming and gave individual households autonomy over allocated plots for substance farming, commonly known as responsibility land (Table 2 summarises key Chinese agricultural policy reforms and their impacts). Agricultural policy reforms introduced in the 1990s and early 2000s aimed to radically transform the agricultural landscape by creating formalised markets for land transfer to facilitate larger scale, commercial farming to meet food demand (Sausmikat, 2015 ). In creating land markets, the value of agricultural land and the agri-business sector increased, whilst also increasing the suitability of the land for the adoption of advanced agricultural technologies. This provided an opportunity for some farmers to leave agricultural production and pursue alternative employment, whilst for others, renting land from others provided a means of producing commercially. “Family farms” in this sense are farms that operated at commercial scale but are predominantly operated by a single family. Land comprises of a family’s responsibility land plus land they have tenanted from others. In 2016, 30.7 million ha (460 million mu) of land had been transferred in this way, accounting for more than a third of all total agricultural land area. This indicates that small non-commercial farming is diminishing and there is an observable growth in the number of larger “family farms” (Xinhuanet, 2020 ), although still only accounting for a small proportion of total agricultural holdings (approximately 0.33%) (Xinhuanet, 2020 ).

Whilst land transfer policies have been a fundamental component of China’s agricultural modernisation planning (Table 2 ), for famers that have acquired land it creates additional challenges and presents further barriers to PA adoption. For example, farmers are managing land to which they have no historic connection or may be farming fragmented and discontinuous plots rather than larger management zones. This hinders the adoption of more sophisticated PA technologies that are currently designed for large continuous land areas, making application on small plots challenging (Clark et al., 2018 ; Kendall et al., 2017 ; Li et al., 2019 ). Moreover, the creation of land markets has aided socio-economic trends, including increased levels of rural to urban migration, allowing farmers to transfer responsibility land to others to pursue higher earning employment opportunities in cities (He & Ye, 2014 ; Liang & Wu, 2014 ; Liu, 2014 ). The result of which has been increased ageing demographics in rural communities, reduced agricultural labour pools and increased associated labour costs.

Adoption motivations and the importance of stakeholder engagement

The adoption of PA technologies requires farmers to change their existing and often historic agricultural practices. There is a broad literature that has explored the factors influencing farmer adoption of PA technologies, although much of the research conducted to date has explored drivers of uptake in developed agricultural economies, predominantly North America, Europe and Australia (for reviews see for example Hasler et al., 2017 ; Pathak et al., 2019 ; Tey & Brindal, 2012 ). Limited research has been conducted to understand the adoption trajectories of PA technologies in developing agricultural economies and to the best of the authors knowledge, this includes research conducted with Chinese farmers to explore their attitudes towards, and the factors influencing, more widespread adoption in Chinese agriculture. An overview of research that has sought to identify the factors influencing farmer and landowner uptake of PA technologies is provided in Table 3 and highlights three primary factorial influences (internal, external and technology) and geographical region where research has been identified to influence adoption.

It is unlikely that farmer adoption motivations are influenced by one single factor, rather they are driven by a combination of each of these three aforementioned influences which are also likely to be context specific and subject to change over time. Adoption is also potentially dependent on the level of behavioural change required by the adopter, i.e., the extent to which a new technology is “disruptive” requiring a fundamental change to their existing behaviour, or “continuous” requiring incremental behaviour change or offering benefits that complement existing farming practice (Hasler et al., 2017 ). Continuous technologies are more easily integrated into existing practices as they do not require significant behaviour change (Clark et al., 2018 ; Kendall et al., 2017 ).

Research has been conducted to develop PA applications and evidence their benefits for Chinese agriculture (see for example Gao et al., 2017 ; Han et al., 2019 ; Huang et al., 2018 ; Jihua et al., 2014 ; Peng et al., 2014 ; Zhao et al., 2017 )). However, there is limited social research conducted in China that specifically explores the factors influencing the adoption of PA technologies, the extent to which existing factors apply in the Chinese agronomic, policy and cultural contexts. This research therefore adopted an interpretivist approach, using in-depth qualitative interviews to explore the views of Chinese family farmers, generate nuanced understandings of their perceptions of, and attitudes towards, PA and identify the factors that promote or inhibit adoption. The qualitative approach permitted a comparative exploration of factors and concepts that have been shown to influence uptake globally (Table 3 ) and explore the extent to which these have relevance for the Chinese context. Adoption of technologies, particularly where current levels of adoption are low, requires the inclusion of stakeholders in the research and development process (Galindo et al., 2012 ; Raley et al., 2016 ). This ensures that technologies align with the needs, priorities and preferences of end-users, avoids any unintended consequences, and increases adoption (Clark et al., 2018 ). Understanding the factors influencing adoption from the end-user perspective is therefore important for scientists, researchers, educators, agricultural extension services providers designing, trailing and suppling PA to Chinese family farmers. It also has wider relevance to those with an interest in developing agricultural economies and small-scale farming. This will support the development of PA approaches and the design of initiatives that promote widespread uptake (Wossen et al., 2015 ).

Three primary research aims were identified for exploration in the qualitative study:

To identify current agricultural challenges and the corresponding solutions from the perspective of Chinese farmers;

To understand Chinese farmers’ perceptions of, and attitudes towards, different PA technologies and;

To explore the barriers to, and facilitators of, Chinese farmers’ adoption of agricultural technologies and services.

Methodological approach

Research development.

Qualitative in-depth interviews were chosen for their ability to explore participant experiences. This method is suited to exploratory studies and the method is recognised to have cross cultural validity (see Kendall et al., 2017 ; Lofland & Lofland, 1971 ). Whilst the approach does not allow for the generalisation of findings to wider populations, it does provide opportunity to deeply engage with potential end-users and unpick the factors that motivate, support, or inhibit adoption (Bryman, 2016 ). An initial discussion guide informed by the literature and theories of technology adoption was developed. The study protocol was also informed by exploratory qualitative research conducted by the lead authors with Chinese farmers and Chinese agricultural policy makers, with both used to develop an understanding of contextual issues for more detailed exploration (Kendall et al., 2017 ). Interviews were semi-structured and conducted in English and simultaneously translated into Mandarin or the local dialect. A semi-structured approach provided both focus on core topics and flexibility based on participant responses, and is particularly useful when multiple researchers are conducting interviews to ensure consistency (Bryman, 2016 ). Ethical approval for the project was granted by Newcastle University Ethics Committee (March 2018) and for the pilot (July 2016).

A discussion guide was piloted with ten Chinese farmers located in the Beijing region in November 2017 to check the accuracy, suitability of the question areas and comprehension of meaning and interview timing. The pilot revealed that participants found it particularly difficult to discuss in any detail commonly available PA technologies owing to their limited awareness and experience of them. Pilot interviews were dominated by discussion of demographics, farming practices and agronomic challenges. In order to ensure construct validity, these findings were used in conjunction with the study aims (Yin, 2014 ) to prepare a revised (final) discussion guide for data collection (April 2018). The discussion guide focused on several key concepts identified within the literature to potentially impact adoption of agricultural technologies including: the challenges faced by family farmers in China, their level of existing technology adoption, perceived level of technology adoption readiness and potential mechanisms to support PA technology adoption amongst family farmers. Contextual demographic farm information was collected by questionnaire prior to commencing the interview. The final discussion guide contained five broad question areas (Table 4 ).

Question probes were included to prompt further inquiry, and interviewers were encouraged to investigate interesting lines of enquiry verbally. Prompt cards were used as discussion aids, specifically in the “Technology adoption” and “Mechanisms to support uptake” sections of the discussion guides. The cards were particularly useful in helping to familiarise participants with a range of technologies from simple to more advanced PA technologies e.g., Remote sensing, GIS and VRT). All materials were translated from English to Mandarin and back translated. Each interview lasted approximately 1 h. All interviews were recorded verbatim and were translated from Mandarin to English for analysis.

Recruitment and sample

Data were collected in two primary locations, Hebei (Shijiazhuang) and Shandong (Zibo). These represented regions in the North China Plain predominated by family farms and were locations in which project partners had demonstration sites. Recruitment and translational support were also provided by project partners NERCITA. Purposeful sampling was adopted to identify “family farmers” that would be able to talk with experience in relation to the study aims (Palinkas et al., 2015 ). Selection criteria ensured that participants were, (1) part of the farming community in Hebei (Shijiazhuang) and Shandong (Zibo); (2) were the principle farmer of their land (i.e., farm manger); (3) had at least 1 year’s farming experience within these locations, and; (4) their farm was classified as a ‘family farm’ (i.e., operating at a commercial scale but managed and primarily operated by a single family). Consistent with the exploratory nature of the study the final sample consisted of n = 27 arable farmers across the two study locations. All participants were remunerated for their time and contribution to the research, this was in line with local practice. Consistent with methodological recommendations interviews were conducted until data saturation was reached (Bryman, 2016 ).

Data analysis

Field notes were taken by the lead researchers (HK, BC) during and after the interviews were conducted. These included thoughts on the interview content and reflections on the interview and the research process itself. Thematic data analysis was supported by qualitative analysis software Nvivo ( 2016 ), and followed a three-stage process. First, interview transcripts were open-coded (Glaser & Strauss, 1971 ) and an initial coding framework was developed by the lead author (HK). Second, the coding framework was refined. Three members of the research team (HK, BC and SJ) independently coded a selection of the transcripts and compared codes against the framework. This inter-coder reliability process followed three iterations until there was agreement that the categories within the framework reflected the data. The third stage of analysis involved three members of the research team coding the full data set into the coding framework (HK, BC and SJ). Overarching themes emerging from the data were discussed and finalised.

Twenty-seven interviews were conducted from 12th to 19th April 2018 (n = 16 farmers with one of these also acting as research hub manager/farmer in Zibo, Shandong Province; n = 11 farm managers in Shijiazhuang, Hebei Province) (Table 5 ). The sample comprised of 18 males and 9 female participants (age range from 41 to 67 years). Participants had a median of 30 years farming experience (range between 3 and 50). The median farm size was 200 mu (approx. 13 hectares: range between 10 and 1400 mu). One farmer (participant 10) had moved to the Shandong region to establish an ecological farming business, although this was not typical of the sample. The remainder farmed responsibility land alongside land that had been transferred from other farmers. For most farmers, increases in farm size through land transfer had occurred within the last decade. Two farmers specialised in horticulture in greenhouses in addition to arable farming. Farmers planted staple crops, predominantly wheat and maize with small proportion also planting soybean, a lower yielding but higher market value crop. A small number of farmers had diversified into the production of fruits and vegetables for which higher market values could be obtained.

Emergent themes

Five central themes emerged from the data “socio-political landscape”, “farming culture”, “agricultural challenges”, “adoption intentions (barriers/facilitators)” and “practical support mechanisms” (Fig. 1 ). These themes were representative of a mix of internal, external and technological factors that were all likely to influence the level and rate of adoption of PA technologies amongst family farmers. The findings are discussed under these theme headings and linkages between the respective themes explored supported by illustrative quotes from participants which have been adjusted, to correct English whilst maintaining meaning.

Themes and subthemes from the interview data

Socio-political landscape

Societal and political influences were shown to shape Chinese agriculture and influence awareness and adoption of PA technologies amongst participants. Despite policy directives aimed at modernising the nations approach to agricultural production, including those aimed at increasing production efficiencies and reducing the environmental impacts of production, limited consideration was given to the wider environmental impacts of agricultural production by participants with limited reflection given to the personal responsibilities of farmers to reduce the environmental impact of farming. Farmers were production orientated, welcoming opportunities to increase farm scale and intensify production to counter low market values for yields. All participants had benefitted from the opportunity to transfer land, noting this to have increased the scale of their production significantly over the last decade.

Participants recognised that ‘in practical terms it [acquiring land through transfer] is not that easy’ (participant 19). Competing Chinese government policy agendas were identified to affect farming communities with implications recognised for the rate of land transfer, farm size growth and impact upon prosperity that could be derived from agricultural production. In parallel with the need to increase agricultural productivity and sustainability, the Chinese government is committed to reducing the environmental impacts of agricultural production by significantly reducing the countries usage of agri-chemicals alongside mitigating the degradation of the nation’s forests (a consequence of a result of rapid population growth). Many respondents noted government policies aimed at forest conservation and restoration of forest ecosystems that have been initiated (e.g., Sloping Land Conversion Program (SLCP) and the National Forest Protection Program (NFPP)) (Bennett, 2008 ; Rodríguez et al., 2016 ; Wenhua, 2004 ). Through the SLCP scheme public payments are available to rural households to convert agricultural land to ‘ecological forests’ (for timber production), ‘economic forests’ (orchards or forests with medicinal value) or to grassland:

Our country wants farmers to cultivate forests, so they don’t have very much field to cultivate [crops] (participant 22) You are not able to expand it [farm land]. You know… look at my geographic location, now it is all covered with trees, [I] cannot transfer anymore [land]. (participant 25)

Participants located in Shijiazhuang noted the impact of these schemes on their ability to increase farm size, with many farmers choosing to convert land to forest conservation, as the subsidies received were greater than profits that could be made from agriculture. This reduced land availability increased the costs of land available for transfer and, was noted to contribute to the fragmentation of farm plots. This policy initiative was identified to be a primary factor preventing farmers from increasing farm size and the scale of production. Farm scale was noted to be a significant barrier to the suitability, applicability and likely adoption of PA technology on farm.

You can earn more than 1000 yuan for planting trees on 1 mu [of land] but only hundreds for crops. (participant 26)

Farming culture

Despite increased farm size, farmers maintained traditional low-level mechanisation farming methods and operated short-term management plans for their farms with none exceeding 5 years. This was possibly attributable to the short length and informality of land transfer contracts. Most farmers demonstrated productionist orientations and were driven primarily by the need to increase the profitability of their farms, in direct response to market challenges. Economic drivers and incentives to increase farming profits were important motivators behind decisions made on farm, including decisions regarding the adoption of PA technologies. Decisions to increase land ownership and the scale of farm operations via land transfer were driven by the need to increase profitability given the broad recognition that you “you earn very little in agriculture” ( participant 23 ) . A small proportion of farmers had diversified production, producing speciality produce that commanded higher market values. The diversity of crops grown across a region was identified to present challenges to technology design and logistical challenges in relation to delivering agri-extension support services.

Farmers just grow crops that have a higher market value. So this may, bring a big challenge to agricultural extension services. Because the crops planted in this region might vary…so for agricultural extension and service providers, it means that there isn't a uniform technology that can be provided. It's quite fragmented (participant 27)

Farmers only made links to the production efficiencies and economic benefits of PA technologies with limited consideration of the potential environmental co-benefits. There was limited evidence of active environmentally regenerative farm and land management practices and equally limited recognition of the potential role that PA could play helping farmers to improve the environmental impact of agricultural production and meet incoming national legislation and agri-chemical usage targets. Participants showed limited awareness of future policy initiatives and legislation, including the cap on agrichemical use and conversely reported significant increases in their usage, necessitated by the need to guarantee yields to improve economic prosperity from farming.

Agricultural challenges

Various interlinked challenges acted as barriers to PA adoption but also represented opportunities for the development of PA applications to address farmer needs. Challenges were linked to economic, socio-demographic, political, landscape-related, infrastructural and environmental factors. Low economic returns combined with steadily increasing input and labour costs were further confounded by difficulties in accessing markets. The socio-demographic composition of rural communities had changed in recent decades, as a direct consequence of significant economic growth in urban conurbations, which had resulted in considerable rural–urban migration of younger members of the community for educational and employment opportunities. Others had used land transfer legislation as an opportunity to rent out their responsibility land and had sought higher paid employment in cities.

it’s not worth it to farm just 1 or 2 mu of land. The younger generation would just leave the village and find jobs outside, especially the men…So, of course young people don’t want to farm… Farming is hard and you can’t make much money out of it (participant 23). It takes time and investment to achieve high levels of mechanization. Now we face many challenges in terms of land transfer…Given another 10 to 15 years, it would be easier to gather farmland because few people of the next generation will engage in farming. (participant 19)

The average age of farmers, as well as the scarcity of agricultural workers, increased the cost of labour, particularly at peak periods of the agricultural calendar (i.e. harvest).

The changes have been huge. I have engaged in agriculture for over 30 years. A prominent change in the past ten years has been the increase in labour costs. Seeds as well (participant 19)

Environmental challenges were primarily associated with climatic uncertainties. Many reported droughts impact due to limited underground water supplies, inadequate well facilities and the reliance on inefficient and outdated irrigation methods, exaggerated by inefficient irrigation solutions. Lodging in conditions of rain, hail and wind was also reported resulting in significant crop loss, exacerbated by a lack of space for, and the cost of, storing crops.

“One of the biggest problems is irrigation. Suppose there was a heavy rain in the fields, I don’t need to irrigate for a period of time. But when you discover it needs irrigating, the crops are already in drought.’ (participant 19) One of worst natural disasters here is of course the wind, and also the hail, hailstones…usually the wheat, wheat suffers the most from hail. (participant 24) The biggest problem is not having space for crop storage. When the weather is bad, the crops get wet and turn bad. It’s rather problematic. (participant 21)

Land reforms resulted in many farming larger farms including land which they had no historic connection, often a collection of variable small holder plots fragmented across villages. This reduced the suitability of many precision farming technologies (typically designed for larger continuous areas):

“On my farm, I have 50-mu chunks or 40-mu chunks. But for theirs [other farmers], many fields are fragmented, 1 mu over here and 1 mu over there. That’s impossible to work on.’ (participant 23).

Land fragmentation occurred because of responsibility land farmers being unwilling to rent their land to others (commonly referred to as ‘nail houses’) or farmers adhering to policy pressures and cultivating their land for alternative purposes e.g. converted to forestry or grassland. Rapid farmland expansion created additional problems linked to the ability to invest in adequate infrastructure, such as storage for harvested crops, and more efficient methods of irrigation as noted. There was an underlying perception that investments made on farm were not recouped in profits and short-term tenancies resulted in a reluctance to invest in farm infrastructure, and supported a culture of intensification. Further challenges, such as the placement of transport infrastructure, were beyond farmers control and impacted their ability to increase farm size and the potential suitability of PA technologies were reported.

We are confined by the landscape. 600 mu is upper bound. We have high speed roads running along the south and the north border of the farm. There is not much space to expand. (participant 19)

Adoption intention (barriers/facilitators)

Farmers showed a willingness to consider technological solutions to the agricultural challenges faced. Intention to trial and subsequently adopt PA technologies was shaped by five factors (sub-themes) discussed below.

Awareness and adoption of PA technology varied according to individual farmer attributes and PA applications. Farmers with formal agricultural education showed greater awareness and engagement with PA technologies and were incentivised to keep up to date in technology developments. Formally educated farmers had a broader knowledge of PA applications and understanding of the suite of PA technologies available. Interestingly some farmers perceived themselves to be more innovative than their behaviours revealed.

One farmer reported that proximity to a demonstration farm had given them first-hand experience of PA applications. However, adoption of PA was not sustained beyond the duration of the demonstration project. The majority of farmers in the sample were aware of Global Navigation Satellite Systems (GNSS) (i.e., GPS) although none owned machinery on which this was enabled. Regional promotion had resulted in the widespread awareness and adoption of some PA applications, for example. UAV’s were used for spot spraying of pesticides, with awareness generated through regional promotion initiatives as a resource efficient means of agri-chemical application. Participants considered this technology to be an inexpensive and financially accessible for most small-scale farmers. Awareness of more advanced PA technologies, i.e., VRT such as remote sensing and hyperspectral imaging, was extremely limited amongst participants. Where farmers demonstrated an awareness of these technologies information was gained through informal peer-based networks, facilitated by widespread adoption of smart phones (e.g. farmers’ group chat via cooperative membership, peer networks and WeChat, a Chinese messaging, social media and payment app) and television, rather than through more formal mechanisms such as research institutes, companies or agronomy services providers.

I have seen drones [UAV’s] used for pesticide applications but I haven’t used them in my field… [I use] tractor… for ploughing and planting seeds (participant 22) Actually, I knew of it [UAV’s] a long time ago. (Interviewer: where do you get the information? what format was this information in?) Some information was via my smartphone, sometimes this was posted by my friends’ in their moments on WeChat, and I also watch television programmes that have provided me with information 7 (participant 10).

Awareness had not translated into engagement via trial or adoption for most PA technologies. Farmers relied predominantly on traditional farming machinery, i.e., tractors, and seeding machines, that were rented through machine cooperatives. The cost of technology and low profitability of farming were the primary reported barriers to trial and adoption. Farmers were unsure about where to access technologies and formal information provision mechanisms (i.e., agronomists) beyond the information and technologies that were promoted by government sponsored annual training programmes and demonstration projects, and perceived there to be an absence of local agricultural extension agents.

The use of UAV’s for agrochemical applications was an exception with adoption common, particularly amongst farmers in Hebei, which had been a government sponsored demonstration area where UAV’s had been promoted for time and labour efficiencies. Promotion had been effective in initiating farmer engagement. Participants considered UAVs to be affordable (comparable to other technologies) and easy to implement requiring limited operator skills or training. For other technologies, uptake had not extended beyond trial within demonstration projects, with cost cited as the primary barrier to long-term adoption alongside the lack of commercial service providers.

Drone spraying here is used when the crops sprout. It’s used in winter, autumn and in spring. Maize as well, it’s sprayed after sprouting. (participant 23) That drone, I have two. (Interviewer: Do you provide drones to other farmers?) Yes. (participant 25)

In the absence of commercial service providers, there was evidence of collaboration and informal rental markets emerging via peers for those that could not afford to invest directly in technologies. For example, one farmer (participant 19) had adopted laser land levelling technology on his own farm and, in the absence of a company/agronomy service provider, had established a company providing this service to farmers in his region. However, this level of innovation was not typical:

I have been doing laser levelling for four years, I am the first in Hebei… When I went to the United States for an agricultural inspection in 1992, I had the impression that on the irrigated land there, the water flowed neatly. When I encountered this problem, I spoke to someone and later found out about laser levelling. Then I searched it online and found that there was a company named Tianbao selling laser levellers in China at that time. [….] The company is in Beijing. I bought two levellers from this company and have used them in my experimental field. (participant 19)

Perceived benefits

The perceived benefits centred around PA’s potential for economic advantages through the reduction of inputs (e.g., time, labour and seeds and agrochemicals) whilst simultaneously increasing yield. Improvements to crop quality were considered to increase profits via the market appeal and value of products. PA technologies were recognised as time saving, reducing labour expenditure and allowing farmers to engage in alternative farm management activities at appropriate times. For example, drip irrigation was recognised to improve efficiency, allowing farmers to quickly respond to variations in weather and soil moisture. Broader factors that might influence adoption were mentioned, although economic benefits predominated discussions.

We can see the advantages of the machines…I want all machine operations including seeding, pesticide spraying and harvesting in line with the field size. They can improve farming efficiency. I’ve been looking for GPS so that I can make the field banks straight. (participant 20)

Wider land management and environmental benefits of PA were not considered, including the potential of PA to reduce pesticide, fertiliser and herbicide application. The primary focus on farm profitability, and the lack of consideration of the wider environmental and land management benefits, aligns with the issues explored within the theme ‘farming culture’, particularly the productivity focused identities and the short-term orientation of family farmers in China.

Perceived risks

The perceived risks associated with the adoption of PA technologies represented a barrier to adoption. Although there was some appreciation of the potential benefits that PA could deliver, the capital investment that such technologies require, and the perceived lack of cost/benefit information to support decision-making of adoption, represented important risks.

Just the investment is big… Too much investment. (participant 6) Nothing could be done without money…I couldn’t use the new technology if I don’t get loans. (participant 22) I want [to adopt]. But I have no money. We don’t have things like this here. Drones [UAV’s] are quite advanced here. (participant 26)

Participants were aware of government subsidies to support adoption. However, access was limited by: farm size; whether subsidies covered the full cost of adoption; the prescribed nature of subsidies issued to landowners and not managers (i.e., to the owners of responsibility land and not for land rented), and; only permitted farmers to purchase technologies that were approved by the government.

Concerns were raised about the performance and reliability of technology and whether it could deliver the claims made. For example, many farmers with UAV’s highlighted issues with battery life and size, chemical holding capacity and concerns around chemical evaporation.

So the bottleneck now is, for drones [UAV’s], we need a breakthrough regarding the battery issues…The battery life sucks; so far the bottleneck hasn’t been resolved. Apart from that…the battery takes up the space, right…adds to the weight, so the loading capacity suffers (participant 10).

Farmers had limited awareness about the sourcing and appropriateness of more advanced PA technologies. Many had not observed or trialled these technologies so benefits were difficult to quantify. Farmers were concerned about their ability to learn new systems, operate machinery and interpret data, and did not consider there to be adequate practical support available to aid the integration of technologies into existing practice. Farmers questioned their ability to financially benefit from technology adoption, based on demographic factors including age and the reduced likelihood of intergenerational succession as a consequence of migration trends.

”It [UAV’s] is surely is great if I knew how to use it.’ (participant 21) (Interviewer: Have you ever thought of buying one yourself?) Maybe. But it’s not suitable. I’m old’ (participant 26)

Concerns were also expressed about the potential for mechanical failure, lacking the knowledge and skills to fix machinery or having this available locally, and the unforeseen costs that this might incur.

of course, there are risks…for example, like mechanical malfunction… things like that. (participant 10)

Openness towards technology and level of adoption readiness varied. Some farmers demonstrated characteristics from which they could be considered ‘innovators’ (Rogers, 1962 ), specialising in production methods including ecological farming and greenhouse horticulture (in addition to arable faming) (participants 10 and participant 12) and developing close relationships with those developing technologies (laser land levelling) to address farming problems (Participant 19). Others perceived readiness to adopt did not align with their actual level of engagement with technology. Many perceived themselves to be ‘innovators’ characterised by taking an active role in understanding new technologies and willing to try innovations despite unproven benefits and with some risk that adoption might be unprofitable (Clark et al., 2018 ; Rogers, 1962 ). However, this was contradicted by their (low) level of engagement with technology and limited awareness and knowledge of both established and emerging PA technologies. Farmers did not want to be early adopters yet were aware of the risks of being left behind and were persuaded to adopt technologies after the benefits of technologies have been proven (Rogers, 1962 ). These farmers were less likely to adopt technologies that required significant change to their existing practice and were more likely to consider adopting technologies that could be incorporated easily into their existing farm management practices.

‘would use the new technology when I see others use it [first]. If you wait to see the benefits, everybody would like to use it for sure. I am willing to try new technologies. (participant 21) The one I bought [UAV] was a decision made from seeing others use it; that’s why I bought one for myself as well (participant 1)

Adoption mechanisms

Farmers were enthusiastic about being involved in the research and development of technologies. Whilst “co-production” has been advocated in scientific communities (Clark et al., 2018 ; Cui et al., 2014 ), farmers expressed difficulties engaging with researchers beyond expected attendance at annual government training initiatives and supported visits to demonstration farms. Despite willingness to engage, farmers had limited knowledge of how best to engage and consequently reported waiting for information and technologies to reach them. Information was shared informally, via peer-based networks including hearing and seeing neighbours adopting new approaches. Participants recognised the need for more professional and effective platforms for information exchange; including a role for local extension agents, to provide more comprehensive and targeted information and build trust.

Policy support. The government has invested a lot of money to build high-quality farmland, and I think there should be policy in place to guide the process. I think it would be great if the policy can promote the use of land levelling and soil quality improvement in this region. (participant 19)

Participants expressed a need for policy to address the economic barriers which prohibit on-farm investment. Flexibility of government subsidies to include a wider range of technologies, reducing the limitations on farm size, as well as private low interest borrowing options to support investment in technologies were commonly cited.

We have subsidies for growing quality seeds and the crops-farming. But the subsidies only go to owners of the land, not people who actually farm the land. (participant 21)

From a policy perspective, farmers appreciated the fundamental role played by land reforms although suggested improvements to accelerate this, including: more formalised mechanisms for recording land transfer; improvements to contractual arrangements to increase farmer tenancy stability, and; facilitating long-term farm management planning and policy interventions to reduce land fragmentation.

Discussion and policy implications

This study found Chinese family farmers to be open to the potential of PA technologies, although heterogeneity in farmer perceptions of PA technology, willingness, and readiness to adopt were apparent. Awareness and use of the PA technologies was shown to be influenced by a combination of internal (i.e., farm and farmer characteristics) and external characteristics (i.e., observability, trialability and support), as well as those of the technologies themselves. Many of the internal and external factors, consistently shown within the literature (summarised in Table 3 ) to influence PA adoption globally, influenced adoption in this context. Although, several dimensions of these factors were specific to the Chinese agricultural context (see also Clark et al., 2018 ).

Farm size, land fragmentation and farming discontinuous plots was considered a fundamental obstruction to the modernisation of farming practice, including adoption of PA technologies. The socio-political landscape specifically, the land reforms in China, as well as policy tensions surrounding land use (i.e., conflicts between environmental, food management policies and agricultural modernisation) had impacted farmer’s ability to increase farm size. The Chinese government may need to consider the trade-offs made by farmers because of policies in different domains (i.e., agricultural and environmental). Coherence across policies and improvements to the land transfer market to reduce fragmentation and uncertainties associated with tenancies, would allow for more long-term farm management planning and reduce the risks associated with making financial investment on farm. This would have multiple benefits, broadly helping to achieve agricultural modernisation goals, improve the suitability of existing PA technologies to small-scale farming as well as obtaining environmental co-benefits (Qian et al., 2016 ).

The suitability of technology for small scale farming is a fundamental barrier to adoption identified in other developing agricultural economies, e.g., India (Mondal & Basu, 2009 ), and indicates the need for low-cost PA technologies better suited to small-scale farms that will benefit both farmers and the environment (Cheema & Khan, 2019 ). Galindo et al. ( 2012 ) argue that site-specific agriculture is usually associated with high levels of technology, although demonstrate that providing approaches following the “observe-interpret- evaluate-implement” principles enables more low-tech approaches that are suitable and beneficial to smallholder farmers, supporting the arguments for improved understanding of the challenges faced by family farmers to support the design of and increase the relevance of PA applications, Future research should look to: (1) create technologies suited to small-scale, fragmented farmland; (2) look to adapt the provision of existing technologies to suit the identified challenges, and (3) have greater involvement from end-users alongside experts throughout the development process (Galindo et al., 2012 ).

Despite recognised and proven potential, and notable attempts made by the Chinese government over the last two decades to promote PA technology (e.g., via the establishment of demonstration centres), awareness, engagement, trial and adoption opportunities to engage with research and demonstration activities were perceived to be limited. The exception to this was the use of UAV for spot agri-chemical application. Here the economic benefits were quantifiable, and awareness and adoption had been facilitated through peer observation and more informal knowledge networks. Drones have more typically been utilised for data (image) gathering exercised in more developed agricultural economies. This difference is also more widely facilitated through the regulatory environment which allows for the use of UAV’s for agrichemical application in China. Widespread adoption here reiterates the importance of information, observation and trial and knowledge exchange opportunities for increasing awareness and facilitating adoption (external factors). Research findings suggest that farmers who engage with and adopt PA technologies are more likely to consider adopting additional technologies (Winstead et al., 2010 ), there is a need therefore, for more targeted informational and educational opportunities alongside more frequent demonstration and field-days that specifically address the challenges faced by family farmers and stimulate initial trial (Heiniger et al., 2002 ). Future research should look to quantify the effect of different forms of knowledge provision and exchange on PA technology adoption, to identify those most suited to encouraging and importantly sustaining update, ensuring that heterogeneity in farm and farmer characteristics are acknowledged. The following paragraphs provide some suggestions for avenues to explore.

Findings identified two categories of farmers: (1) those who are pioneers and enthusiastically engage with and invest in PA technologies, although these were less typical of the sample, and; (2) those who were interested, although needed reassurances from observing others adopt, were not able to invest in technology directly, but were interested in service provision options. This suggests that market segmentation to differentiate adoption profiles would be useful to identify those most likely to lead adoption within communities and enable improved product positioning and targeting of local extension agents in disseminating information (Li et al., 2020 ). Care needs to be taken to ensure a more objective measure of this, given that participants often reported higher levels of perceived technology readiness than their behaviours characterised.

In the absence of formal and regular educational opportunities, farmer awareness was typically gained via peer networks such as mobile phone platforms (WeChat), and observation of the benefits obtained by other farmers illustrated by the widespread adoption of UAV’s as well as motivated by concerns about “being left behind”. This highlights the importance of peer-to-peer support mechanisms and illustrates the value of supporting farmers to engage with these networks (Heiniger et al., 2002 ; Kernecker et al., 2020 ). Widespread adoption of mobile phone technology has been shown to reduce information asymmetry amongst farmers in developing agricultural economies (Aker, 2010 ; Ma et al., 2018 ). In the Chinese context, widespread adoption and reported reliance on internet and smartphone technology as a primary information sharing mechanism, has consequences for how technologies are disseminated though family farm communities. Providing there is the appropriate network coverage infrastructure in rural communities, smartphone and internet-based technology represents an opportunity to improve communication between researchers, agricultural policy makers, local extension agents and farmers (Aker, 2010 ; Ma et al., 2018 ). Although, differences in digital competencies amongst end-users must be recognised to avoid divisions within rural communities (Galindo et al., 2012 ).

Informal mechanisms for education and support should be coupled with more formal educational opportunities, with the level of engagement with PA also influenced by education level, with greater efforts to engage demonstrated by those with formal agricultural educations. Research indicates that encouraging skilled agricultural graduates back to rural communities can support the dissemination of PA technologies within rural communities. Therefore, there is an important role for relevant stakeholders is to acknowledge the value of both formal and informal education mechanisms to improve dialogue with end-users and in so doing improve current innovation trajectories (Clark et al., 2018 ; Heiniger et al., 2002 ; Qian et al., 2016 ).

Despite a low awareness and knowledge and PA technologies, farmers were principally motivated by the potential economic benefits that the adoption of PA technologies could bring, including improved profits and livelihoods from farming. This is unlike developed countries, such as the US, where evidence suggests farmers consider a broader range of benefits in addition to financial incentives, including, environmental benefits and increased convenience to the farmer when deciding to adopt (Thompson et al., 2019 ). However, whilst recognising the protential economic benefits farmers were inherently risk adverse and cautious about investing in technologies where the benefits were difficult to quantify, return on investment uncertain and adoption required end-users to make fundamental, and expensive changes to their farming practice (see also Hasler et al., 2017 ). This aversion to risk was compounded by the short-term approach to farm management planning by farmers, influenced by tenancy rather than land ownership, the informality of land contracts between and the low profitability of farming as well as demographic characteristics including age and succession status (Adesina & Baidu-Forson, 1995 ). All of these have been shown to influence confidence and security in making on farm investment (Dean & Damm-Luhr, 2010 ; Gao et al., 2017 ).

It is important to provide farmers with cost/benefit analysis data particularly in the decision-making stage to mitigate farmer concerns and reduce the perceived barriers related to economic risks. Future research is required to evidence the economic benefits PA adoption including economic studies that demonstrate that PA technologies can increase farm profitability (i.e., through resource efficacies) (Daberkow & McBride, 2003 ; Schimmelpfennig & Ebel, 2016 ). A further policy recommendation would be to consider reforms to the land transfer policies, providing market-based mechanisms for land purchase and ownership which is recognised to incentivise farmer investment in land improvements and technologies that may have multiple farm efficacies (Wainaina et al., 2016 ).

Finally, limited and poor access to information regarding financial support mechanisms such as subsidies and low interest credit further contributed to the perceived risk of adoption. Improved information and access across a spectrum of financial support mechanisms including credit, rental and affordable full-service provision and contractor options would reduce the economic barriers to adoption (Wossen et al., 2015 ). Agri-tech service providers have a vital role to play in reducing the influence of cost as a barrier to adoption by alleviating the need for long-term capital investments and the need for knowledge and skills acquisition by farmers by acting as professional consultants. In lieu of such services and as a means of improving farm profitability, farmers were shown to have established informal service provision networks. This finding illustrates the arguments presented regarding the importance of social capital as a determinant of technology adoption in low resource economies, and the importance of community networks to facilitate uptake in the absence of formal financial support and credit access. It also further demonstrates a demand and role for formal PA service provision, and raises concerns around the unregulated adoption of PA technologies, for example, the unregulated use of UAV’s could carry risks to operators and bystanders. Farmers were open to, and recognised, a role for a top-down approach form the Chinese government to support adoption, with farmers acknowledging that for many, unless regulated, adoption of modern farm management mechanisms including precision technologies will be very slow to occur.

Recommendation and limitations

Research, policy and education supporting the adoption of PA technologies in developing agricultural economies should explicitly include farmers and end-users as key stakeholders in the process, from initial idea conception through the research and development process to product commercialisation as is advocated by institutions such as UK Research and Innovation the European Commission. This requires the role of farmers and end-users as the target market for PA technologies to be reframed and for them to be included as co-developers of technology. This approach is consistent with the principles of ‘Responsible Research and Innovation’ (RRI) advocated by the European Commission and within the domain of PA (Clark et al., 2018 ).

Adoption success is influenced by a broad range of stakeholders in addition to farmers and end-users, including but not limited to, local policy makers, rural community members, agronomists and service providers. Future research should incorporate the views of these stakeholders in addition to farmers and end-users. The findings relate specifically to the experiences of family farmers in the North China plain, whilst our research highlights several themes likely to be similar across China, e.g., impact of agricultural policies, financial and information constraints, future research should consider the perspectives of farmers in other regions of China which may be exposed to different contextual factors.

Economic cost–benefit analysis and information regarding specific technologies is necessary to help mitigate the principle barrier to adoption (cost) including evidencing the long-term economic advantages to adoption, and improved translations and communication to support farmer decision making and improve uptake. Resources should be allocated for knowledge building, including demonstration, extension and information provision tailored to smallholder farmers, and is required to acknowledge the importance of utilising formal and informal educational channels, alongside technological development. Finally, differences in perceived readiness to adopt were identified, future research could quantitatively explore differences in farmer adoption characteristics to understand communication preferences and support more targeted communication with local farming communities.

Conclusions

Incentivising adoption to meet the ‘ubiquitous’ adoption ambitions of the Chinese government, requires consideration of the unique factors influencing adoption in the Chinese context. Whilst land reforms have provided the facilitating conditions for more widespread adoption, they have also created additional challenges (i.e., land fragmentation) that have acted as a barrier to uptake. Increasing rates of adoption requires clear understanding of these challenges and the unmet needs of farmers to reduce adoption barriers. A clear role for PA and untapped market opportunities for the researchers, developers and agronomic service providers of PA technologies in China was highlighted. Limited awareness of suitable and affordable technologies was identified as an important barrier to adoption, highlighting the need for small scale, low cost PA applications, improved information provision, finical support mechanisms including more accessible subsidies, and service provision, as well as, reliable implementation and aftercare support.

Data availability

All data is available from the corresponding author on request.

Code availability

Not applicable.

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Acknowledgements

This work was conducted as part of the PAFIC—Precision Agriculture for Family-farms in China project, funded by the UK China Research and Innovation Partnership Fund (Newton Programme, STFC Ref.: ST/N006801/1; NSFC Ref.: 61661136003).

This research was funded by the UK-China Research and Innovation Partnership Fund (Newton Programme: PAFIC—Precision Agriculture for Family-farms in China project, NSFC Ref.: 61661136003 & STFC Ref.: ST/N006801/1).

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Kendall, H., Clark, B., Li, W. et al. Precision agriculture technology adoption: a qualitative study of small-scale commercial “family farms” located in the North China Plain. Precision Agric 23 , 319–351 (2022). https://doi.org/10.1007/s11119-021-09839-2

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• v.28(5); 2021 May

Perception of organic farmers towards organic agriculture and role of extension

Bader alhafi alotaibi.

a Department of Agricultural Extension and Rural Society, King Saud University, Riyadh 11451, Saudi Arabia

Edgar Yoder

b Department of Agricultural Economics, Sociology and Education, Pennslavyna State University, University Park, PA 16802, USA

Mark A. Brennan

Hazem s. kassem.

The sustainability of organic agriculture is associated with the farmers’ experience, quality of information provided, management of risks, and compliance with legislation. The objectives of this study were to identify the sources used by the organic farmers to gain information related to organic production, and to assess organic farmers’ perceived attitudes towards extension services. To address the research objectives, in-depth semi-structured interviews were conducted with 10 organic farmers in central Pennsylvania. The interviews were digitally recorded and transcribed verbatim, categorized and coded, then thematically analyzed using an interpretive description methodology. The results showed that the extension services were not identified as a primary source of information that was frequently used by the organic farmers. Other organic farmers and organizationa for organic agriculture were the two primary sources of informaiton. The organic farmers were very adept at building social capital in seeking informaiton to address their issues and problems. The primary challenges faced by the organic farmers were the control of insects and weeds, and weather-related issues. The results highlighted that in addition to identifying viable information sources, factors such as adaptive capacities to climate change and certification were key to successful production in organic systems. The present study provides rich and deep information on how farmers perceive organic agriculture and extension services. The outcome of the research undertaken will enable planners, policy makers and the related Cooperative Extension personnel to better understand perceptions of the farmers to devise viable and workable policies and plans that address the concerns and challenges of the farmers.

1. Introduction

Organic agriculture is the fastest growing agricultural sector in the United States. The Certified Organic Survey documented that organic farmers and ranchers sold around $7.6 billion in organic products in 2016, which is a 23% increase compared to 2015 sales ( USDA, 2017 ). Third party regulators typically manage the organic certification and labeling process. Growers desiring to have their proucts officially labeled as organically grown are required to complete the certification process ( Mosier and Thilmany, 2016 ). The organic market is expanding because there is high demand driven by perceptions and beliefs among consumers, and there is also increased general public support for organic producers and their products ( Nguyen et al., 2019 , Soroka and Wojciechowska-Solis, 2019 ).

Organic agriculture production and sales of organic food have expanded rapidly, and agricultural extension has the opportunity to develop and deliver organic educational programs for organic farmers to ensure information is available to all farmers, both conventional and organic farmers ( Parker and Lillard, 2013 ). However, there are many challenges for extension agents desiring to reach organic growers which include limted engagement with organic farmers, limited information on organic agriculture, and limted training among extension workers ( Constance and Choi, 2010 , Lillard et al., 2013 , Farmer et al., 2014 ). Extension has a role as a source of information for farmers that can play an important role to support sustainable agriculture and providing information on OA ( Allahyari, 2009 ).

Previous research has documented there is a need for extension and organic agriculture related research to support organic agriculture ( Alotaibi et al., 2019 , Barbercheck et al., 2012 , Marsh et al., 2017 ). This research can elucidate the barriers to communication with organic farmers, and additionally, knowledge of the organic farmers’ perceptions would be tremendously useful in developing stronger extension programs to support organic agriculture. Because of challenges that are facing farmers, understanding and assessing farmers’ perception regarding OA and extension services are important to the development of OA in central Pennsylvania. The aim of this study was to understand and examine organic farmers’ perceptions toward organic agriculture information sources and the role of extension. This aim was accomplished by achieving the following objectives; to identify the sources that organic farmers use to gain organic production information and to explore the organic farmers’ perceived attitudes towards extension as an information source.

2. Materials and methods

2.1. study approach and location.

A qualitative approach was used to gain a deeper understanding of the perceptions of organic farmers. Qualitative data may be especially useful to educators who desire to understand how and why people act in their particular settings ( Sutton and Austin, 2015 ). The study was conducted from March to July 2018 in Central Pennsylvania. Information from self-identified organic farmers was collected through the use of semi-structured interviews.

2.2. Selection of organic farmers respondents

In qualitative research, selection of participants at each site is one of the most important task a researcher can undertakes. According to Lune and Berg (2016) , a site is where access to potential study participants is possible. Because potential risk exists regarding confidentiality and/or anonmity for interviewees in qualitative research, the researcher must develop and build trusting relationships with those who participate in the study. The Central Pennsylvania organic farmers were recruited for study participation in Centre County Pennsylvania. The Organic farmers were selected based on the following criteria: sell their organic produce in farmers markets in the Centre County area; has practiced organic agriculture production for more than five years; grow fruits and vegetables, and agree to participate in the study interview as descirbed in an informed consent letter provided before the interview.

Ten organic farmers (male and female) in the Centre County area in PA agreed to participate. The number of a sample interviewees fits between the range of 6–25 participants as suggested by Morse, 1994 , Patton, 2001 for qualitative approaches. In order to reach these farmers, some facilitators helped to make contacts at three farmers markets: the Downtown State College farmers market, the Boalsburg farmers market, and the North Atherton farmers market.

2.3. Interview process

The study used semi-structured, open-ended interviews to collect the data. Open-ended semi-structured interviews were designed to ensure open conversations with organic farmers. Interview participants voluntarily agreed to participate after they were informed about the study. The interview questions were ordered based on the research questions and were audibly recorded as well after participants’ permissions were obtained. There are certain steps for conducting the interview, according to Creswell (2007a) . The first step is to ensure the research questions are asked in an open-ended manner. Second, interviewees must be identified, and the type of interview such as face-to-face or telephone interviews must be determined. Next, when conducting face-to-face interviews, the researcher must make sure to have adequate recording procedures. Step four is to use an interview protocol.

Interviews were conducted at farmers’ market locations and ranged from 10 to 20 min. According to Creswell (2007b) , time is important when collecting qualitative interview data, and he recommends conducting one or two trial interviews so the investigator can determine the apprroximate amount of time needed to obtain the information. Based on those trial interviews it was determined the investigator would need 45-60 minutes to conduct each interview. The researcher worked with each organic farmer to determine the time and location for the interviews. The farmers all preferred to conduct the individual farmers interview on site at the respective farmer market location at the end of the day between 4 and 5 pm because of the decrease in number of customers. Finally, after the interviews were conducted and recorded, the interview data were transcribed. Data management procedures were used to ensure participants’ anonymity and confidentiality.

As shown in Fig. 1 , four areas of information were collected to reflect the farmers’ Information: namely, farmers’ demographic attributes (experience, scope of operation, farm family, experience with the organic certification process, and marketing channels), information sources, role of cooperative extension, and challenges recently faced in organic farming and its effect.

Conceptual model of the study.

The study framework was conceptually based in adult education learning theory ( Franz, 2007 , Boyle, 1981 , Merriam et al., 2007 , Norris, 2003 ), communication theory ( Bettman, 1979 , McGuire, 1984 ) and behavior change thoery ( Ajzen, 1985 , Prochaska et al., 1992 ). Adults such as organic producers, are self-directed learners that often are focused on solving and managing their problmes that want to be actively engaged in a problem-solving learning environment. Communication theory substantiates that adults learn well through dialogue with others and reach outside their immediate realm for relevant information and information sources. Behavior change models demonstrate that individuals typically go through five stages as they contemplate adopting a new behavior of new technology. Franz (2007) specifically addresses how the conceptual theories of adult learning help us understand adult learners in relation to informing Cooperative Extension's transformation to a more issues-based programming approach in an effort to address the needs of new audiences.

2.4. Data analysis

The process of data analysis followed basic principles of content analysis ( Neuendorf, 2017 ). The data were stored, categorized, and labeled with an open code/label. Strauss (1990) indicate once phenomena in data are identified, then the researcher may group concepts. This grouping process is called categorizing. The qualitative coding process used the framework developed by Saldaña (2016) . A descriptive code name was developed for each code based on the research questions and farmers’ responses. Once the open coding process was completed, then axial coding work was completed on the data. Strauss and Corbin, 1990a , Strauss and Corbin, 1990b define axial coding as “a set of procedures whereby data are put back together in new ways after open coding, by making connections between categories” (p. 96). The 10 individual overall cases were coded in this way as well as the nested cases. These embedded cases were analyzed against each other to see differences and similarities and to draw conclusions to support the larger single case study analysis. Data tables were developed using the transcribed interviews and themes were pulled from these tables. Finally, a peer review process was utilized in the data analysis phase. Two peer reviewers analyzed the coding tables and were asked to comment on the results of the data analysis.

• 2.5 Verifying the quality of the information

According to Dooley (2002) the case study method is effective at verifying the quality of the study and to strengthen the findings of the research. This triangulation of data, or “establishing converging lines of evidence” will add to the quality of the study ( Yin, 2012 ). The researcher utilized interviews, document review, member checking and a peer review process in the coding process to enhance the reliability of the data. These activities support Creswell’s (2007b) “ characteristics of a “good “qualitative study ” (p. 45). Creswell’s characteristics include utilizing multiple forms of data, utilizing evolving design methods that understand the unique discovery nature of qualitative research design, using an appropriate approach to qualitative research, seeking to understand core ideas based on the research questions, outlining and using detailed research methods, using multiple levels of data analysis, writing the study in a clear and engaging manner, positioning the researcher in the study, and finally engaging in an ethical study that has appropriate input from the institutional review board ( Creswell, 2007b ).

3.1. Profile of the farmers interviewed

Interview participant demographics regarding gender, years of organic experience, organic production, crops, farm family, certification and marketing are summarized in Table 1 . Several questions were to gain a context of the farmers' experience growing organic production, crops and participated in theorganic certification process. The sample of farmers in organic farming households included 8 male farmers and two females. Farmers reported a history growing organic ranging from 5 years to 40 years. All of the organic farmers produce croups such as vegetables and/or fruit.

Summary profile of the organic farmers interviewed.

3.2. Farmer Information Sources

Each organic farmer was asked to describe the sources of information they use to gain general information regarding the production of their organically produced products.

All farmers indicated networking was a frequent and important source of information. Farmers indicated networking meant direct face-to-face interactions with other organic producers including family members and friends. The following statements capture the essence of direct networking with trusted peers as an effective information source for gaining information.

“In general. Often it is through connections with other farmers that also are farming organically. So, it would be networking.” Farmer 3

“I get a lot of my information from speaking with my peers.” Farmer 7

Sometimes the initial network contact doesn’t provide information regarding organic agriculture; however, that contact provides a link to an unknown peer farmer that subsequently provides the desired information. Farmer 4 indicated that his contact with a family member (his son) led to a subsequent contact with a peer farmer.

“He (his son) talks to other farmers, particularly ones who have already been practicing organic agriculture”. Farmer 4

Thus by direct contact with a family member the farmer expanded his network to include other peers. Referrals by word-of-mouth appear to be commonplace and a trusted and credible source of information.

Farmer 5 indicated another key source of network contact included providers of organic farming product supplies including sales personnel. Farmer 5 during the past 15 years has transitioned from a dairy farm operation to a 26 acre organic vegetable production operation. His prior dairy experience and interactions with sales personnel may have contributed to his/her being the only farmer to mention sales personnel.

Organizations, organic certification agencies and marketing associations were identified as an important and valuable source of information. Not surprisingly these organizations sponsor a variety of conferences, educational exhibits and materials, workshops, demonstrations, and, in some cases, social activities. Their outreach activities are varied and relatively easy to access. The following excerpts reflect the value organic farmers place on two organizations and associations identified as primary source of information.

“In Pennsylvania, there's a certifying agency called Pennsylvania Certified Organic (PCO). You can search on the internet and you can Google that and it'll come up with plenty of information about organic production.” Farmer 10

“I became associated with the organic protocols through Pennsylvania Certified Organic, who was the certifier of that farm. So that's how I mainly learned and got the base knowledge. If I ever have a question now about organic practices, I usually call PCO or look it up online.” Farmer 6

Pennsylvania Certified Organic’s USDA PCO is a non-profit organization (thrid party certifier) that educates and certifies organic operations based in Pennsylvania, Delaware, Maryland, New Jersey, New York, North Carolina, Ohio, Virginia, West Virginia and the District of Columbia. PCO provides education, inspection and certification for organic farmers ( https://www.paorganic.org/ ).

“We do go to some conferences and meetings that we like. PASA Conference would be one.” Farmer 2 and Farmer 3 and Farmer 4 reported literally the same comment.

PASA (Pennsylvania Association for Sustainable Agriculture) represents a network of local peer farmers that openly share their knowledge via conferences, research based literature and workshops. PASA conducts a farm based, participatory oriented approach to research. PASA also sponsors farmer training and development programs. The mission of PASA is “We're a community of farmers and supporters, focused on education and evidence-based research, for the purpose of building a more economically-just, environmentally-regenerative, and community-focused food system”. ( https://pasafarming.org/ ) Organic certification, and the cooperative spirit, are the common links between our farms. Two other organizations were identified as sources of information.

Farmer 4 indicated he also is a member of Tuscarora Organic Growers. and receives some information from them. Tuscarora Organic Growers is a farmer cooperative and with organic certification and the cooperative spirit being the common links between the farmer members ( https://www.tog.coop ). Additionally, Farmer 1 indicated “Usually I pick up most of the information for these practices from attending the meetings put on by the extension service and vegetable conference we attend every winter at Hershey, the Mid-Atlantic Vegetable Conference.

Organic farmers interviewed exhibited characteristics of being self-directed learners through their descriptions of participating in non-formal education activities to gain information and knowledge they desired. These non-formal education activities were grouped into accessing information in two forms. First they accessed information in traditional print formats, and second they accessed information using current internet technology.

All farmers engaged in a variety of self-directed, non-formal learning using traditional published materials including books, magazines, articles, catalogues and bulletins. Additionally two farmers specifically indicated that they “try things on their own and personally experiment” by themselves. The following excerpts illustrate the types of printed materials they accessed.

Farmer 9 indicated “Well, sometimes I read magazines and that sort of thing,”

“Okay. That is probably just little magazines that we get in the mail. We're small as it is, mainly out of the house, family-type operation. Yeah, no big publications”. Farmer 2

“I get some information from reading periodicals.” I read Organic Farming and Gardening, and I read Acres USA. Farmer 7

“So, in those days, it was largely through books… There wasn't even the internet back in 1988. So that was how we did it mostly was through word of mouth and by books that had been written by people that were participating or experts in the field”. Farmer 8

“From my thumb, (personal experimentation) and also, newspapers such as organic articles in newspapers or in organic magazines. I rely on that quite a bit.” Farmer 5

“I'm just self-educating on this topic, so whatever information I learn I try to make note of that and incorporate that when I can.” Farmer 1

Only three of the farmers specifically indicated they used internet technology to access organic agriculture information. These three farmers were males with one being a recent college graduate. The other two farmers had been growing organically for 26 years and 40 years with operations exceeding 25 acres of organic production. One of these two farmers serves on an advisory board for a college of agriculture. The following are their rather succinct comments regarding their use of the internet.

Farmer 6 was succinct, “I look it up online”.

“And I get a little bit of information off the internet“. Farmer 7

And you can search on the internet and you can Google that and it'll come up with plenty of information about organic production.” Farmer 10

3.3. Role of Cooperative Cxtension

University resources includes workshops, formal courses, internships and the resources provided through the Cooperative Extension System at Land Grant Universities. Only one farmer indicated a family member had completed an internship. His son had completed an internship at a 250 acre organic farm in south central Pennsylvania, and the son’s experience in completing the internship was and continues to be a valuable source of knowledge and information. Additionally Farmer 6 indicated that upon graduating from an agricultural college he worked for three (3) years on an organic farm and that “provided a base knowledge regarding organic (farming) and the organic certification protocols.” Through his college experiences he became aware of the organic farm where he worked.

The Cooperative Extension system personnel were not frequently mentioned as a direct source of information regarding organic farming or organic agriculture. Only two farmers indicated they had made direct contact with extension personnel in seeking information regarding organic farming questions. Typically the farmers indicated “never” and “rarely” in describing their direct interaction with extension personnel. Farmer 4 indicated that on one occasion he/she did contact an extension agent about a raspberry problem and a gooseberry problem, and the agent was “very helpful. That is the one time the most help is with raspberries.” Farmer 6 indicated he/she made contact with a master gardener. The farmer viewed the master gardener personnel as the “face of extension for responding to a question. They have a hotline that you can call into. And they are the ones that will help answer my questions.”

So why is there limited direct interaction with extension agents? Several reasons emerged. First, there appears to be a common perception that local extension personnel do not have current and reliable information regarding organic agriculture practices. The following statements reflect the general views of organic farmers.

Farmer 3 indicated “Well if they do, they don’t come across that way to me.”

“And we found that most of them (local extension personnel) do not know very much about organic practices or organic agriculture. We don’t contact them because we know that they are not going to be able to help us with organic.” Farmer 4

“I know several of the local extension people. Extension is not very involved in organic agriculture. I don’t think they (Extension) have enough people to be involved in everything.” Farmer 10

Several farmers provided their perspectives on why local extension personnel may be perceived as not being a primary direct source of information for organic agriculture. One view is that land grant university leadership and other personnel and extension leadership did not take organic agriculture as an important initiative in the early years of the organic agriculture movement. Farmer 7 commented in the following:

I think it was a lack of knowledge, a lack of understanding and perhaps a lack of interest. I think for a long time organic was looked down upon by the conventional ag establishment as being perhaps wasteful or fine in small applications. For instance, oh organic, that is affine way to garden. But really to be honest, the ag establishment has been very slow to be really supportive of organic agriculture, but they’re coming.”

Farmer 8 adds to the perspective that organic farmers that embraced organic agriculture developed sources of information before land grant universities and extension developed educational materials and programs targeting organic agriculture farmers.

I (Farmer 8) started before extension had embraced organic agriculture. I never relied on them, so I kind of went out just on my own, very independent. So I really never got used to using them (local extension personnel).

Farmer 3 indicated Rodale had a well established reputation and credible resources, including publications, in organic agriculture. Rodale was an established player in organic agriculture before land grant institutions and Cooperative Extension.

The value of extension as a source for information reaches beyond direct interaction with extension personnel. Seven of the 10 farmers reported using either online or printed materials developed by extension. The following descriptions in farmers’ own words reflects the resources used and the value of those resources.

Farmer 1 ‘Well I have vegetable production guide put out by extension. It’s very descriptive of all the problems….Sometimes I go online and lookup information…there is a good website”.

“They have great publications…and they have how to do onions organic, scallions organic, and potatoes organic. They have not only how to grow them but how to sell them and market them. And, I think that’s phenomenal!” Farmer 8.

“The information that is available (from extension), is crucial. One of the publications I use is Fruit Production for the Home Gardener which is put together by extension.” Farmer 6.

“ I read their (extension agents) articles in Lancaster Farmer or magazines where they write in.” Farmer 5.

3.4. Primary Challenges faced by organic farmers

The majority of the organic farmers did not apply for participation in the organic certification because of the high cost of organic certification, increased inspections on their farms, and rigorous standards, and also they sell their products to people who trust them and are regular customers in the farmers’ markets in State College. However, one large organic farmer was worried about the standards for certification being lowered because he felt that capitalist society wanted to lower the standards of organic agriculture in order to make it easier to sell organic products, and he perceived that organic standards are currently being lowered.

The majority of recent challenges perceived by organic farmers can be categorized as insects, pest control, weeds, and weather. These challenges may have contributed to a lack of products. Extension agents have been unhelpful because organic famers believed they know more than the extension agents about organic agriculture. Marketing was not a barrier to organic farmers because small scale farmers sell their organic products to local customers. The challenges in the next five years identified by organic farmers are price competition, sinking prices, insect control, climate change, and the government regulators allowing lower standards that organic farmers think are questionable.

4. Discussion

The study reported here set out to understand organic farmers’ perceptions towards extension and organic agriculture. The information provided by organic farmers reflects their capacity and adeptness of building social capital in addressing their issues and problems related to organic agriculture. The results of this study provide evidence that organic farmers view PASA, networking, and Pennsylvania Certified Organic as primary OA information sources. Networking was mentioned by organic farmers as the primary source of information, and also the number one way in which these organic farmers learned new practices. The results demonstrate that organic farmers use and recognize networking and interactions with others farmers as ways to manage their business practices, and also social learning between groups was an important factor impacting practices. These results are similar to those of previous studies ( Crawford et al., 2015 , Millar and Curtis, 1999 ). The literature ( Blackstock et al., 2010 , Pierrette Coulibaly et al., 2021 ) documents the importance of interaction or contact from a trusted source for achieving behavior change. Gernerally, the more credible the source in the eyes of the farmer the more likey the information will be considered and/or used. There are two concepts that contribute to source credibility-trustworthiness and expertise. For farmers, relevant experience and occupation are important factors that convince them regarding reliablity of information. Organic farmers are no different than many other farmers. Access to similar and/or trusted networks is likely to enhance message uptake and the building of socail capital. Moreover, all farmers reflect the importance of self-learning in enhancing their knowledge about organic agriculture via reading different materials and using internet. It could be concluded that adults have traditionally been viewed as self-directed learners ( Kearsley, 2010 , Knowles, 1984 ).

The results also indicated that extension was viewed by organic farmers as a supplementary source rather than a primary source for gaining information related to organic agriculture. Organic farmers viewed extension as more useful to conventional farming operators. Lack of dedicated organic extension programs has led organic farmers to feel that they know more about organic practices than extension professionals, and also farmers were not willing to pay for extension. These findings demonstrate that currently extension does not have a primary role in organic agriculture, but there is nevertheless potential that extension agents can increase their role in involvement in organic agriculture. There have been several efforts to rethink the role of extension and transform the system to effectively move from a rural, expert-based transfer of knowledge system to one that has the capacity to respond quickly to emerging issues thus making extension and land-grant partnership more accessible, meaningful, and accountable. For extension personnel at the local level, there may be an emerging role as a paticiatory educational broker bringing together the organic farmer, the distributor and the consumer in identifying problems/issues and developing action plans aimed at achieving sustainable organic production learning communities. According to Kucińska et al. (2009) to enhance extension role in organic agriculture, extension agents and organic farmers should engage in open discussion to share the challenges they face and work together to develop the curriculum of organic programs for small organic farmers and any audience interested in organic practices.

According to interview responses, organic farmers adopted organic agriculture because of sales in markets, bio-diversity, health reasons, protecting the environment, and preferring not to use chemicals in their food. Their perceptions regarding organic agriculture were positive because they practiced organic agriculture based on what they learned from their experiences. These findings are in line with previous research ( Oyesola and Obabire, 2011 , Läpple, 2013 ).

The study also attempted to identify challenges regarding organic agriculture. In short, organic farmers face challenges such as pest control, weeds, and weather. These challenges may have contributed to a lack of products. The lack of organic programs among organic farmers might worsen these challenges. In this context, Brzezina et al. (2016) argued that implementation of organic food production principles in practice and continuous improvement is depended on farmers’ adaptive capacity to climate change. Furthermore, fluctuation of prices is another challenge viewed by organic farmers as high risky. Stable prices and positive consumer perception is necessary to enable sustainable organic production ( Bouttes et al., 2019 )

This study has some limitations regarding selection of farmers. First, although organic farmers were encountered at farmers markets around State College, it is possible that the experiences and views of these individuals did not reflect the views of the organic farmers in the region. Second, there is a heterogeneity of the scale of production among the farmers interviewed. This is might affect credibility of some results identified during data analysis.

5. Conclusions

This qualitative study provides rich and deep information on how farmers percept organic agriculture. This study identifies that farmers continue to grow organic crops, amongst other things, because of perceived profitability, preserving bio-diversity of good insects, protecting health, preserving the environment, and not wanting to use chemicals that pose a risk to themselves and customers. Farmers mainly learned about organic agriculture through meeting with other farmers, news, publications, PASA, PCO, and reading. The study recommends that extension professionals should present themselves and provide organic programs in PASA and PCO, focus more on personal relationships with farmers, and include a networking approach as their priority in order to increase organic farmers’ knowledge. Future research is recommended to determine barriers to adopting organic agriculture, and also it would be worthwhile to conduct research to determine the role of extension agents in organic agriculture and also the barriers perceived by extension agents regarding their role in the organic agriculture arena.

Declaration of Competing 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.

Acknowledgments

This research was funded by the Deanship of Scientific Research, King Saud University, Saudi Arabia, through the Research Group No. RGP –1441-511. Moreover, the authors thank the Deanship of Scientific Research and RSSU at King Saud University for their technical support.

Peer review under responsibility of King Saud University.

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Article Contents

1. introduction, 2. analytical framework, 3. literature search, 5. discussion, 6. conclusion, acknowledgement.

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Research impact assessment in agriculture—A review of approaches and impact areas

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Peter Weißhuhn, Katharina Helming, Johanna Ferretti, Research impact assessment in agriculture—A review of approaches and impact areas, Research Evaluation , Volume 27, Issue 1, January 2018, Pages 36–42, https://doi.org/10.1093/reseval/rvx034

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Research has a role to play in society’s endeavour for sustainable development. This is particularly true for agricultural research, since agriculture is at the nexus between numerous sustainable development goals. Yet, generally accepted methods for linking research outcomes to sustainability impacts are missing. We conducted a review of scientific literature to analyse how impacts of agricultural research were assessed and what types of impacts were covered. A total of 171 papers published between 2008 and 2016 were reviewed. Our analytical framework covered three categories: (1) the assessment level of research (policy, programme, organization, project, technology, or other); (2) the type of assessment method (conceptual, qualitative, or quantitative); and (3) the impact areas (economic, social, environmental, or sustainability). The analysis revealed that most papers (56%) addressed economic impacts, such as cost-effectiveness of research funding or macroeconomic effects. In total, 42% analysed social impacts, like food security or aspects of equity. Very few papers (2%) examined environmental impacts, such as climate effects or ecosystem change. Only one paper considered all three sustainability dimensions. We found a majority of papers assessing research impacts at the level of technologies, particularly for economic impacts. There was a tendency of preferring quantitative methods for economic impacts, and qualitative methods for social impacts. The most striking finding was the ‘blind eye’ towards environmental and sustainability implications in research impact assessments. Efforts have to be made to close this gap and to develop integrated research assessment approaches, such as those available for policy impact assessments.

Research has multiple impacts on society. In the light of the international discourse on grand societal challenges and sustainable development, the debate is reinforced about the role of research on economic growth, societal well-being, and environmental integrity ( 1 ). Research impact assessment (RIA) is a key instrument to exploring this role ( 2 ).

A number of countries have begun using RIA to base decisions for allocation of funding on it, and to justify the value of investments in research to taxpayers ( 3 ). The so-called scientometric assessments with a focus on bibliometric and exploitable results such as patents are the main basis for current RIA practices ( 4–6 ). However, neither academic values of science, based on the assumption of ‘knowledge as progress’, nor market values frameworks (‘profit as progress’) seem adequate for achieving and assessing broader public values ( 7 ). Those approaches do not explicitly acknowledge the contribution of research to solving societal challenges, although they are sufficient to measure scientific excellence ( 8 ) or academic impact.

RIA may however represent a vital element for designing socially responsible research processes with orientation towards responsibility for a sustainable development ( 9 , 10 ). In the past, RIAs occurred to focus on output indicators and on links between science and productivity while hardly exploring the wider societal impacts of science ( 11 ). RIA should entail the consideration of intended and non-intended, positive and negative, and long- and short-term impacts of research ( 12 ). Indeed, there has been a broadening of impact assessments to include, for example, cultural and social returns to society ( 13 ). RIA is conceptually and methodologically not yet sufficiently equipped to capture wider societal implications, though ( 14 ). This is due to the specific challenges associated with RIA, including inter alia unknown time lags between research processes and their impacts ( 15–17 ). Independent from their orientation, RIAs are likely to influence research policies for years to come ( 18 ).

Research on RIA and its potential to cover wider societal impacts has examined assessment methods and approaches in specific fields of research, and in specific research organizations. The European Science Foundation ( 19 ) and Guthrie et al. ( 20 ) provided overviews of a range of methods usable in assessment exercises. They discuss generic methods (e.g. economic analyses, surveys, and case studies) with view to their selection for RIAs. Methods need to fit the objectives of the assessment and the characteristics of the disciplines examined. Econometric methods consider the rate of return over investment ( 21 ), indicators for ‘productive interactions’ between the stakeholders try to capture the social impact of research ( 22 ), and case study-based approaches map the ‘public values’ of research programmes ( 8 , 23 ). No approach is generally favourable over another, while challenges exist in understanding which impact areas are relevant in what contexts. Penfield et al. ( 6 ) looked at the different methods and frameworks employed in assessment approaches worldwide, with a focus on the UK Research Excellence Framework. They argue that there is a need for RIA approaches based on types of impact rather than research discipline. They point to the need for tools and systems to assist in RIAs and highlight different types of information needed along the output-outcome-impact-chain to provide for a comprehensive assessment. In the field of public health research, a minority of RIAs exhibit a wider scope on impacts, and these studies highlight the relevance of case studies ( 24 ). However, case studies often rely on principal investigator interviews and/or peer review, not taking into account the views of end users. Evaluation practices in environment-related research organizations tend to focus on research uptake and management processes, but partially show a broader scope and longer-term outcomes. Establishing attribution of environmental research to different types of impacts was identified to be a key challenge ( 25 ). Other authors tested impact frameworks or impact patterns in disciplinary public research organizations. For example, Gaunand et al. ( 26 ) analysed an internal database of the French Agricultural research organization INRA with 1,048 entries to identify seven impact areas, with five going beyond traditional types of impacts (e.g. conservation of natural resources or scientific advice). Besides, for the case of agricultural research, no systematic review of RIA methods exists in the academic literature that would allow for an overview of available approaches covering different impact areas of research.

Against this background, the objective of this study was to review in how far RIAs of agricultural research capture wider societal implications. We understand agricultural research as being a prime example for the consideration of wider research impacts. This is because agriculture is a sector which has direct and severe implications for a range of the UN Sustainable Development Goals. It has a strong practice orientation and is just beginning to develop a common understanding of innovation processes ( 27 ).

The analysis of the identified literature on agricultural RIA (for details, see next section ‘Literature search’) built on a framework from a preliminary study presented at the ImpAR Conference 2015 ( 28 ). It was based on three categories to explore the impact areas that were addressed and the design of RIA. In particular, the analytical framework consisted of: ( 1 ) the assessment level of research; ( 2 ) the type of assessment method; and ( 3 ) the impact areas covered. On the side, we additionally explored the time dimension of RIA, i.e. whether the assessment was done ex ante or ex post (see Fig. 1 ).

Analytical framework for the review of non-scientometric impact assessment literature of agricultural research.

Agricultural research and the ramifications following from that refer to different levels of assessment (or levels of evaluation, ( 29 )). We defined six assessment levels that can be the subject of a RIA: policy, programme, organization, project, technology, and other. The assessment level of the RIA is a relevant category, since it shapes the approach to the RIA (e.g. the impact chain of a research project differs to that at policy level). The assessment level was clearly stated in all of the analysed papers and in no case more than one assessment level was addressed. Articles were assigned to the policy level, if a certain public technology policy ( 30 ) or science policy, implemented by governments to directly or indirectly affect the conduct of science, was considered. Exemplary topics are research funding, transfer of research results to application, or contribution to economic development. Research programmes were understood as instruments that are adopted by government departments, or other organizational entities to implement research policies and fund research activities in a specific research field (e.g. programmes to promote research on a certain crop or cultivation technique). Articles dealing with the organizational level assess the impact of research activities of a specific research organization. The term research organization comprises public or private research institutes, associations, networks, or partnerships (e.g. the Consultative Group on International Agricultural Research (CGIAR) and its research centres). A research project is the level at which research is actually carried out, e.g. as part of a research programme. The assessment of a research project would consider the impacts of the whole project, from planning through implementation to evaluation instead of focusing on a specific project output, like a certain agricultural innovation. The technology level was considered to be complementary to the other assessment levels of research and comprises studies with a strong focus on specific agricultural machinery or other agricultural innovation such as new crops or crop rotations, fertilizer applications, pest control, or tillage practices, irrespective of the agricultural system (e.g. smallholder or high-technology farming, or organic, integrated, or conventional farming). The category ‘other’ included one article addressing RIA at the level of individual researchers (see ( 31 )).

We categorized the impact areas along the three dimensions of sustainable development by drawing upon the European Commission’s impact assessment guidelines (cf. ( 32 )). The guidelines entail a list of 7 environmental impacts, such as natural resource use, climate change, or aspects of nature conservation; 12 social impacts, such as employment and working conditions, security, education, or aspects of equity; and 10 economic impacts, including business competitiveness, increased trade, and several macroeconomic aspects. The European Commission’s impact assessment guidelines were used as a classification framework because it is one of the most advanced impact assessment frameworks established until to date ( 33 ). In addition, we opened a separate category for those articles exploring joint impacts on the three sustainability dimensions. Few articles addressed impacts in two sustainability dimensions which we assigned to the dominating impact area.

To categorize the type of RIA method, we distinguished between conceptual, qualitative, and quantitative. Conceptual analyses include the development of frameworks or concepts for measuring impacts of agricultural research (e.g. tracking of innovation pathways or the identification of barriers and supporting factors for impact generation). Qualitative and quantitative methods were identified by the use of qualitative data or quantitative data, respectively (cf. ( 34–36 )). Qualitative data can be scaled nominally or ordinally. It is generated by interviews, questionnaires, surveys or choice experiments to gauge stakeholder attitudes to new technologies, their willingness to pay, and their preference for adoption measures. The generation of quantitative data involves a numeric measurement in a standardized way. Such data are on a metric scale and are often used for modelling. The used categorization is rather simple. We assigned approaches which employed mixed-method approaches according to their dominant method. We preferred this over more sophisticated typologies to achieve a high level of abstraction and because the focus of our analysis was on impact areas rather than methods. However, to show consistencies with existing typologies of impact assessment methods ( 19 , 37 ), we provide an overview of the categorization chosen and give examples of the most relevant types of methods.

To additionally explore the approach of the assessment ( 38 ), the dimensions ex ante and ex post were identified. The two approaches are complementary: whereas ex ante impact assessments are usually conducted for strategic and planning purposes to set priorities, ex post impact assessments serve as accountability validation and control against a baseline. The studies in our sample that employed an ex ante approach to RIA usually made this explicit, while in the majority of ex post impact assessments, this was indicated rather implicitly.

This study was performed as a literature review based on Thomson Reuters Web of Science TM Core Collection, indexed in the Science Citation Index Expanded (SCI-Exp) and the Social Sciences Citation Index (SSCI). The motivation for restricting the analysis to articles from ISI-listed journals was to stay within the boundaries of internationally accepted scientific quality management and worldwide access. The advantages of a search based on Elsevier’s Scopus ® (more journals and alternative publications, and more articles from social and health science covered) would not apply for this literature review, with regard to the drawbacks of an index system based on abstracts instead of citation indexes, which is not as transparent as the Core Collection regarding the database definable by the user. We selected the years of 2008 to mid-2016 for the analysis (numbers last updated on 2 June 2016) . First, because most performance-based funding systems have been introduced since 2000, allowing sufficient time for the RIA approaches to evolve and literature to be published. Secondly, in 2008 two key publications on RIA of agricultural research triggered the topic: Kelley, et al. ( 38 ) published the lessons learned from the Standing Panel on Impact Assessment of CGIAR; Watts, et al. ( 39 ) summarized several central pitfalls of impact assessment concerning agricultural research. We took these publications as a starting point for the literature search. We searched in TOPIC and therefore, the terms had to appear in the title, abstract, author keywords, or keywords plus ® . The search query 1 filtered for agricultural research in relation to research impact. To cover similar expressions, we used science, ‘R&D’, and innovation interchangeably with research, and we searched for assessment, evaluation, criteria, benefit, adoption, or adaptation of research.

We combined the TOPIC search with a less strict search query 2 in TITLE using the same groups of terms, as these searches contained approximately two-thirds non-overlapping papers. Together they consisted of 315 papers. Of these, we reviewed 282 after excluding all document types other than articles and reviews (19 papers were not peer-reviewed journal articles) and all papers not written in English language (14 papers). After going through them, 171 proved to be topic-relevant and were included in the analysis.

Analysis matrix showing the number of reviewed articles, each categorized to an assessment level and an impact area (social, economic, environmental, or all three (sustainability)). Additionally, the type of analytical method (conceptual, quantitative, and qualitative) is itemized

In the agricultural RIA, the core assessment level of the reviewed articles was technology (39%), while the other levels were almost equally represented (with the exception of ‘other’). Generally, most papers (56%) addressed economic research impacts, closely followed by social research impacts (42%); however, only three papers (2%) addressed environmental research impacts and only 1 of 171 papers addressed all three dimensions of sustainable development. Assessments at the level of research policy slightly emphasized social impacts over economic impacts (18 papers, or 58%), whereas assessments at the level of technology clearly focused primarily on economic impacts (46 papers, or 68%).

The methods used for agricultural RIA showed no preference for one method type (see Table 1 ). Approximately 31% of the papers assessed research impacts quantitatively, whereas 37% used qualitative methods. Conceptual considerations on research impact were applied by 32% of the studies. A noticeable high number of qualitative studies were conducted to assess social impacts. At the evaluation level of research policy and research programmes, we found a focus on quantitative methods, if economic impacts were assessed.

Overview on type of methods used for agricultural RIA

a Mix of conceptual and qualitative methods.

b Mix of conceptual, qualitative, and quantitative methods.

Additionally, 37 ex ante studies, compared to 134 ex post studies, revealed that the latter clearly dominated, but no robust relation to any other investigated characteristic was found. Of the three environmental impact studies, none assessed ex ante , while the one study exploring sustainability impacts did. The share of ex ante assessments regarding social impacts was very similar to those regarding economic impacts. Within the assessment levels of research (excluding ‘others’ with only one paper), no notable difference between the shares of ex ante assessments occurred as they ranged between 13 and 28%.

The most relevant outcome of the review analysis was that only 3 of the 171 papers focus on the environmental impacts of agricultural research. This seems surprising because agriculture is dependent on an intact environment. However, this finding is supported by two recent reviews: one from Bennett, et al. ( 40 ) and one from Maredia and Raitzer ( 41 ). Both note that not only international agricultural research in general but also research on natural resource management shows a lack regarding large-scale assessments of environmental impacts. The CGIAR also recognized the necessity to deepen the understanding of the environmental impacts of its work because RIAs had largely ignored environmental benefits ( 42 ).

A few papers explicitly include environmental impacts of research in addition to their main focus. Raitzer and Maredia ( 43 ) address water depletion, greenhouse gas emissions, and landscape effects; however, their overall focus is on poverty reduction. Ajayi et al. ( 44 ) report the improvement of soil physical properties and soil biodiversity from introducing fertilizer trees but predominantly measure economic and social effects. Cavallo, et al. ( 45 ) investigate users’ attitudes towards the environmental impact of agricultural tractors (considered as technological innovation) but do not measure the environmental impact. Briones, et al. ( 46 ) configure an environmental ‘modification’ of economic surplus analysis, but they do not prioritize environmental impacts.

Of course, the environmental impacts of agricultural practices were the topic of many studies in recent decades, such as Kyllmar, et al. ( 47 ), Skinner, et al. ( 48 ), Van der Werf and Petit ( 49 ), among many others. However, we found very little evidence for the impact of agricultural research on the environment. A study on environmental management systems that examined technology adoption rates though not the environmental impacts is exemplarily for this ( 50 ). One possible explanation is based on the observation made by Morris, et al. ( 51 ) and Watts, et al. ( 39 ). They see impact assessments tending to accentuate the success stories because studies are often commissioned strategically as to demonstrate a certain outcome. This would mean to avoid carving out negative environmental impacts that conflict with, when indicated, the positive economic or societal impacts of the assessed research activity. In analogy to policy impact assessments, this points to the need of incentives to equally explore intended and unintended, expected and non-expected impacts from scratch ( 52 ). From those tasked with an RIA, this again requires an open attitude in ‘doing RIA’ and towards the findings of their RIA.

Another possible explanation was given by Bennett, et al. ( 40 ): a lack of skills in ecology or environmental economics to cope with the technically complex and data-intensive integration of environmental impacts. Although such a lack of skills or data could also apply to social and economic impacts, continuous monitoring of environmental data related to agricultural practices is particularly scarce. A third possible explanation is a conceptual oversight, as environmental impacts may be thought to be covered by the plenty of environmental impact assessments of agricultural activities itself.

The impression of a ‘blind eye’ on the environment in agricultural RIA may change when publications beyond Web of Science TM Core Collection are considered ( 53 ) or sources other than peer-reviewed journal articles are analysed (e.g. reports; conference proceedings). See, for example, Kelley, et al. ( 38 ), Maredia and Pingali ( 54 ), or FAO ( 55 ). Additionally, scientific publications of the highest quality standard (indicated by reviews and articles being listed in the Web of Science TM Core Collection) seem to not yet reflect experiences and advancements from assessment applications on research and innovation policy that usually include the environmental impact ( 56 ).

Since their beginnings, RIAs have begun to move away from narrow exercises concerned with economic impacts ( 11 ) and expanded their scope to social impacts. However, we only found one sustainability approach in our review that would cover all three impact areas of agricultural research (see ( 57 )). In contrast, progressive approaches to policy impact assessment largely attempt to cover the full range of environmental, social, and economic impacts of policy ( 33 , 58 ). RIAs may learn from them.

Additionally, the focus of agricultural research on technological innovation seems evident. Although the word innovation is sometimes still used for new technology (as in ‘diffusion of innovations’), it is increasingly used for the process of technical and institutional change at the farm level and higher levels of impact. Technology production increasingly is embedded in innovation systems ( 59 ).

The review revealed a diversity of methods (see Table 2 ) applied in impact assessments of agricultural research. In the early phases of RIA, the methods drawn from agricultural economics were considered as good standard for an impact assessment of international agricultural research ( 39 ). However, quantitative methods most often address economic impacts. In addition, the reliability of assessments based on econometric models is often disputed because of strong relationships between modelling assumptions and respective results.

Regarding environmental (or sustainability) impacts of agricultural research, the portfolio of assessment methods could be extended by learning from RIAs in other impact areas. In our literature sample, only review, framework development (e.g. key barrier typologies, environmental costing, or payments for ecosystem services), life-cycle assessment, and semi-structured interviews were used for environmental impacts of agricultural research.

In total, 42 of the 171 analysed papers assessed the impact of participatory research. A co-management of public research acknowledges the influence of the surrounding ecological, social, and political system and allows different types of stakeholder knowledge to shape innovation ( 60 ). Schut, et al. ( 36 ) conceptualize an agricultural innovation support system, which considers multi-stakeholder dynamics next to multilevel interactions within the agricultural system and multiple dimensions of the agricultural problem. Another type of participation in RIAs is the involvement of stakeholders to the evaluation process. A comparatively low number of six papers considered participatory evaluation of research impact, of them three in combination with impact assessment of participatory research.

Approximately 22% of the articles in our sample on agricultural research reported that they conducted their assessments ex ante , but most studies were ex post assessments. Watts, et al. ( 39 ) considered ex ante impact assessment to be more instructive than ex post assessment because it can directly guide the design of research towards maximizing beneficial impacts. This is particularly true when an ex ante assessment is conducted as a comparative assessment comprising a set of alternative options ( 61 ).

Many authors of the studies analysed were not explicit about the time frames considered in their ex post studies. The potential latency of impacts from research points to the need for ex post (and ex ante) studies to account for and analyse longer time periods, either considering ‘decades’ ( 62 , 63 ) or a lag distribution covering up to 50 years, with a peak approximately in the middle of the impact period ( 64 ). This finding is in line with the perspective of impact assessments as an ongoing process throughout a project’s life cycle and not as a one-off process at the end ( 51 ). Nevertheless, ex post assessments are an important component of a comprehensive evaluation package, which includes ex ante impact assessment, impact pathway analysis, programme peer reviews, performance monitoring and evaluation, and process evaluations, among others ( 38 ).

RIA is conceptually and methodologically not yet sufficiently equipped to capture wider societal implications, though ( 14 ). This is due to the specific challenges associated with RIA, including inter alia unknown time lags between research processes and their impacts ( 15–17 ). Independent from their orientation, RIAs are likely to influence research policies for years to come ( 18 ).

However, in the cases in which a RIA is carried out, an increase in the positive impacts (or avoidance of negative impacts) of agricultural research does not follow automatically. Lilja and Dixon ( 65 ) state the following methodological reasons for the missing impact of impact studies: no accountability with internal learning, no developed scaling out, the overlap of monitoring and evaluation and impact assessment, the intrinsic nature of functional and empowering farmer participation, the persistent lack of widespread attention to gender, and the operational and political complexity of multi-stakeholder impact assessment. In contrast, a desired impact of research could be reached or boosted by specific measures without making an impact assessment at all. Kristjanson, et al. ( 66 ), for example, proposed seven framework conditions for agricultural research to bridge the gap between scientific knowledge and action towards sustainable development. RIA should develop into process-oriented evaluations, in contrast to outcome-oriented evaluation ( 67 ), for addressing the intended kind of impacts, the scope of assessment, and for choosing the appropriate assessment method ( 19 ).

This review aimed at providing an overview of impact assessment activities reported in academic agricultural literature with regard to their coverage of impact areas and type of assessment method used. We found a remarkable body of non-scientometric RIA at all evaluation levels of agricultural research but a major interest in economic impacts of new agricultural technologies. These are closely followed by an interest in social impacts at multiple assessments levels that usually focus on food security and poverty reduction and rely slightly more on qualitative assessment methods. In contrast, the assessment of the environmental impacts of agricultural research or comprehensive sustainability assessments was exceptionally limited. They may have been systematically overlooked in the past, for the reason of expected negative results, thought to be covered by other impact studies or methodological challenges. RIA could learn from user-oriented policy impact assessments that usually include environmental impacts. Frameworks for RIA should avoid narrowing the assessment focus and instead considering intended and unintended impacts in several impact areas equally. It seems fruitful to invest in assessment teams’ environmental analytic skills and to expand several of the already developed methods for economic or social impact to the environmental impacts. Only then, the complex and comprehensive contribution of agricultural research to sustainable development can be revealed.

The authors would like to thank Jana Rumler and Claus Dalchow for their support in the Web of Science analysis and Melanie Gutschker for her support in the quantitative literature analysis.

This work was supported by the project LIAISE (Linking Impact Assessment to Sustainability Expertise, www.liaisenoe.eu ), which was funded by Framework Programme 7 of the European Commission and co-funded by the Leibniz-Centre for Agricultural Landscape Research. The research was further inspired and supported by funding from the ‘Guidelines for Sustainability Management’ project for non-university research institutes in Germany (‘Leitfaden Nachhaltigkeitsmanagement’, BMBF grant 311 number 13NKE003A).

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The exact TOPIC query was: agricult* NEAR/1 (research* OR *scien* OR "R&D" OR innovati*) AND (research* OR *scien* OR "R&D" OR innovati*) NEAR/2 (impact* OR assess* OR evaluat* OR criteria* OR benefit* OR adoption* OR adaptation*)

The exact TITLE query was: agricult* AND (research* OR *scien* OR "R&D" OR innovati*) AND (impact* OR assess* OR evaluat* OR criteria* OR benefit* OR adoption* OR adaptation*)

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The Implications for Qualitative Researchers as Professionalization Transforms U.S. Agriculture

By Mary Ann Smith-Janas, President, Marketry, Inc., Birmingham, Alabama, [email protected]

In the Amazon streaming series Clarkson’s Farm , the UK’s Top Gear host, Jeremy Clarkson, takes over the management of his farm. While the series is mostly comedic, it does illustrate one of the great accomplishments of the last century—the professionalization of the global agricultural industry.

In previous generations, a farmer without any knowledge or experience would have utterly failed. But today, Clarkson can mitigate his inexperience by taking advantage of modern resources. For example, he’s invested in German and Italian equipment technologies. He’s also surrounded by neighboring farmers and consultants who work hard to teach him the innovations and efficiencies that contribute to a successful operation.

Like Clarkson’s Oxfordshire, U.S. agriculture is also being transformed by the professionalization trend. The strength of U.S. agriculture used to be a widely distributed and decentralized system of small farms. However, since 1980, there has been a huge increase in consolidation and centralization. Farms in nearly every commodity and livestock category have grown larger. Meanwhile, the number of distinct farming operations has fallen by 16.7 percent in this period. 1

In this article, I’ll explain how the Ag industry’s transformation is generating new opportunities for qualitative researchers. I’ll also explain the essential methods and skills required to successfully compete for project work in the near term.

Importantly, I could not have written the following without the inspiring conversations and generous contributions from several agriculture experts I interviewed for this article. (Please note: Most of the experts requested that their company and identity remain private.)

Key Challenges for U.S. Agriculture

Farm Labor Shortage According to the July 2021 update of the Purdue Center for Commercial Agriculture Ag Economy Barometer report (2021), nearly two-thirds of the farmers surveyed said they either had “some” or “a lot of difficulty” in hiring adequate labor. Only one year earlier, just three out of 10 respondents reported this level of difficulty.

Rising Costs According to the U.S. Department of Agriculture’s (USDA) Farm Sector Income & Finances report, farm production expenses for 2022 were expected to increase by 17.8 percent, representing the largest year-to-year dollar increase on record. The rise is outpacing high inflation due to a confluence of factors, including transportation costs, interest expenses, and the spike in fertilizer prices, which has been triggered largely by sanctions on the major fertilizer producers—Russia and Belarus.

Globalization In an article on the impact of globalization on U.S. Ag, Time magazine 2 quoted the chief economist from the American Farm Bureau on problems with agricultural products flooding the market and bringing prices paid to farmers down: “Globalization brought more farmers into the international market for crops, flooding the market with soybeans and corn and cattle and milk, and with increased supply comes lower prices. Global food production has increased 30 percent over the last decade,” according to John Newton, chief economist of the American Farm Bureau. “If that’s a good thing for feeding the planet, it also reduces what comes back to producers, whose costs don’t fall with prices.”

Adapting to Challenges: The Professionalization of U.S. Agriculture

While the above challenges seem daunting, technology is offering some effective solutions.

Automation Solves for Labor Shortages As labor becomes more costly and less available, manufacturers and other companies are racing to develop automation, robotics, and artificial intelligence (AI). Automated machinery can take care of the more mundane tasks on the farm (even milking cows), freeing up extra time for farmers to focus on more complex tasks or take a break.

Technology Boosts Sustainability and Profits Technology is revolutionizing farming and allowing farmers to be more productive and sustainable. Precision farming (“smart farming”) can help farmers quickly identify and address issues like weeds, pests, and other challenges by using sensors and machines. Advanced irrigation systems can help farmers save water by monitoring soil moisture. Drones and other aerial imaging can give farmers an overhead view of their fields. The Internet of Things (IoT) can help farmers automate and track their operations. By using technology, farmers can reduce their reliance on chemicals and water, increase crop yields, and protect fragile ecosystems. As technology continues to evolve, the possibilities for farmers to become more efficient and sustainable grow exponentially.

Qual’s Main Role: Better Innovation-related Decisions

The above challenges clearly require innovation, but the risks of poorly performing initiatives are huge. Most farms are a single bad season away from going out of business.

Qualitative market research is critical for identifying the real problems and pain points farmers face and what innovations have the best chances for success.

That’s why qual research is in such high demand today by equipment manufacturers and seed, chemical, and technology companies. An industry business analyst explains, “The Ag industry, for all those who are involved, is a rewarding way of life, but also a high-stakes, high-responsibility, burdensome way of life as well. Farmers crave new technology to make their way of life easier, but new technology has to actually break even and be more profitable for the farmer. Ag industry companies need help from research vendors to actually find what problem the farmer has, so we can build a solution to meet that need.”

Another adds, “What’s at stake is so much bigger compared to a lot of other technologies. If your gaming app that’s really cool doesn’t work, yes, it’s a problem. If your sprayer doesn’t work, then you have ruined land, profits, and maybe your future. There’s so much more at stake when we ask them to take a leap (on new technology or products).”

One equipment manufacturer expert values the role that marketing research plays in building their brand for the future. “The Ag industry is being flooded with new technology, but sometimes new technology doesn’t solve a customer need. Marketing research lets us hear the problems the customer has. Then we can build tech to solve that need. It’s a lot less risky than building the new tech just because we can.”

Changing Demographics of Ag Respondents in Qual

According to the USDA, the majority of farmers are men from the Baby Boomer generation, with an average age just shy of 60. Like the rural communities they inhabit, they tend to be disproportionately Caucasian.

However, there’s been a notable rise in farmers younger than 35 years old, and most new producers have at least one female decision-maker in the farm’s management. The industry has also seen increasing levels of education and technological literacy, reflecting the changing demographics in rural America.

Ultimately, the implication for Ag researchers is evolving recruitment from current leaders of the farm to include more of the up-and-coming generation. Here are some key criteria to consider:

First, it’s important to remember that not all “farms” are the same. From a half-acre backyard in the suburbs of a major metro to thousands of acres in the heartland, the size of a farm can vary greatly. The types of crops also vary greatly. While some farms are growing and thriving, others are merely surviving.

Each of these factors has a massive influence on the farm’s need for innovation and professionalization. Therefore, accurately collecting these criteria when qualifying participants is critical to helping clients gather insights.

Tips to Ensure Recruiting Accuracy and Success

Collaborate with a Specialist Recruiter Recruiting partners is always critically important to a successful qual practice; this is even more true for Ag research. Reach out to specialized recruiters you will find in GreenBook and Quirk’s, such as Revelations Research Solutions, Klein Market Test Inc., and CFR.

Consider Using Customized Panels With their Ag Access insights community with over 400,000 people, one company, CFR, has established relations to help researchers target respondents with specific equipment ownership, operation type, and occupation details.

Be Creative Quick online searches and hashtag searches on social media can produce great yields. Need recent tractor purchasers but have no list? On Instagram and Facebook, local dealerships often thank new customers by name and show them with their new equipment. Looking for organic farms across the U.S.? You can find members on organicfarmersassociation.org or in articles like Food & Wine’s “The Best Farms in Every State.”

Avoid the Busiest Times of the Year The USDA website or statewide cooperatives provide calendars to help you plan your research around planting and harvest times.

Ideal Methodologies for This Unique Respondent Group

Working on this article, I reached out to client-side industry experts to hear about the best approaches to collect and tell the farmers’ stories to their organizations. Their responses point to the full toolkit of qualitative researchers.

Telephone Interviews When it comes to conducting Ag research, telephone interviews remain a popular choice due to the work with early hours, late nights, and geographic spread of many farms.

Video Interviews The addition of a video element to these interviews can greatly benefit everyone involved. Through visual observation, moderators can read subtle cues in the body language or environment of the interviewee that are often lost over the phone. Additionally, video can capture the facial expressions or physical reactions of the interviewee as they discuss certain topics or questions.

In the words of one client-side researcher, “Boy, do we love video because it is so much more compelling. Anytime we can add media to something is good.” So, why not leverage the power of video to make your next interview more authentic and engaging for all parties? With the right technology, you can make a big impact.

On-farm Ethnographies, Virtual Ethnographies, Focus Groups Another client-side business analyst explains that getting as close as possible to farmers, whether through ethnographies or virtual self-ethnographies and focus groups is critical for his stakeholders.

“When our corporate team members sit in an office and try to solve problems for our customers, we often do so with bias and with our own experiences that are most likely one, two, or three decades or more in the past. Additionally, corporate teams in the Ag industry are often global, and many of the team members do not know how farming is done in different regions around the world. To be able to go out and observe the participant and learn directly from them on their property is one of the best methods for us to discover and begin to solve problems for the customer. As a brand in the Ag industry, we sometimes want to hear from the customer, and we want them to think about problems and begin to generate ideas of how they think they could solve them.”

Ongoing Advisory or Discussion Groups Ongoing advisory or discussion groups (longitudinal research) are another great way to build a relationship and to gain rich information about the market and the farmers. This type of research focuses on gathering data over an extended period, say from planning and planting to harvesting the soybeans, with the aim of understanding changes, trends, and developments over time.

You can track the successes and failures of the farmers, as well as identify any new needs, wants, or concerns they might have along the way. In a recent project, a soybean farmer stood in the same spot in a field every month to capture a video that shared the journey—how the crop was growing, what they were doing, how he was feeling, what he struggled with, and what came next. We saw stormy nights with too much rain, infestations that needed treatment, and, in the end, a crop yield that was the highest in the farm’s 40-year history.

Regardless of the methodology chosen, it’s important to ensure that the farmers feel comfortable and relaxed. Pay attention to their body language and facial expressions to get an idea of their level of comfort and understanding. Ask them to provide examples and stories to help bring their experiences to life. Don’t be afraid to try a projective exercise.

With well-executed qualitative market research, you can gain a deeper understanding of the market and the farmers, leading to better-informed decisions by clients racing to develop the next tractor, technology, or chemical.

The Skills and Talents That Lead to Success in U.S. Agriculture Research

There are certain truths about this important group that qual researchers should keep in mind.

Must Demonstrate Respect and Enthusiasm for Farming While the industry has been transformed by professionalization, one key cultural element remains as one expert explains, “This is a relationship business.” The most valuable commodity in doing agriculture research is trust. Trust-building can happen by association and will enable you to go deeper faster. This could be a referral from a trusted vendor or a neighboring farm.

One great way to demonstrate respect is to get the story of their operation first and, if you are in person on the farm, take a tour and weave your questions in as you walk.

Must Acquire Substantial Knowledge About Farming Clients hire “research partners with expertise in the market—those with knowledge (and even better, empathy) of the farmer’s day-to-day and ways of working that respect their time and know-how. You are going to be overwhelmed with technical language and phrases you’ve never heard before. If you show real ignorance of these very technical topics, the quality of your research will suffer.”

A great way to learn about the industry is to explore various online magazines, including Farm Journal , Progressive Farmer , and Successful Farming.

Conclusion: Agriculture Is a Uniquely Rewarding Specialization for Qualitative Researchers

Farmers are proud of their work and their lifestyle, and they’re glad to share, so you can learn all about why they do the things they do. On top of all that, farmers are often incredibly generous and willing to help in any way they can.

A client-side researcher describes her experiences: “I’m not a farmer. I didn’t grow up on a farm. I’ve also never had people more willing to teach me and talk to me about something. So, you go in earnestly, and I’ve done it a million times, saying, ‘I don’t know a thing about poultry. Please tell me what this process is.’ They love talking about it. Do some homework, be open and friendly, and they will teach you.”

If you’ve ever experienced the exhilaration of watching the sun rise over a Napa Valley vineyard as you prepare for an early morning interview or the humbling feeling of the hustle and bustle of harvest day in a farmer’s combine, you know that farmers are some of the best people you’ll ever meet. They are smart and passionate about their work. For them, the farm is a place of work, of home, and of the family’s future. It’s also a powerful connection to generations of hardworking people who came before them.

When a skilled moderator is helping to evoke their stories, we see positive outcomes for not just the farmers, but the companies creating the products and technologies that they will use.

In her presentation at the 2023 QRCA Conference in Charlotte, Reflections of a Researcher , Malena Donas explored the ways our work as QRCs impacts us as consumers. Certainly, I have been changed by my work in agriculture—I have a greater appreciation for the tradition of farming and never miss a stop at a local produce stand or a farmers’ market. It’s a win-win situation, creating a better future for all of us. Ultimately, it provides researchers and organizations with better-informed decisions in this critical and ever-changing industry.

• U.S. Department of Agriculture, www.ers.usda.gov/data-products/ag-and-food-statistics-charting-the-essentials/farming-and-farm-income/#:~:text=In%20the%20most%20recent%20survey,million%20acres%20ten%20years%20earlier (accessed May 12, 2023)
• Time magazine, https://time.com/5736789/small-american-farmers-debt-crisis-extinction
• agribusiness
• agriculture industry research; qualitative research in agriculture; ag research; agriculture
• agriculture research
• innovation research
• longitudinal research
• professionalization

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