A proposed framework for accelerating technology trajectories in agriculture: a case study in China

doi:10.15302/J-FASE-2018244

Front. Agr. Sci. Eng.

2018, Vol. 5

Issue (4) : 485-498 https://doi.org/10.15302/J-FASE-2018244

RESEARCH ARTICLE

A proposed framework for accelerating technology trajectories in agriculture: a case study in China

Beth CLARK¹, Glyn D. JONES^1,², Helen KENDALL¹(

), James TAYLOR¹, Yiying CAO³, Wenjing LI^1,⁴, Chunjiang ZHAO⁵, Jing CHEN⁶, Guijun YANG⁵, Liping CHEN⁵, Zhenhong LI⁷, Rachel GAULTON⁷, Lynn J. FREWER¹

¹. School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK
². FERA Sciences Ltd., National Agri-Food Innovation Campus, Sand Hutton, Yo41 1LZ, UK
³. RSK ADAS, Leeds, LS15 8GB, UK
⁴. School of Economics and Management, China University of Geosciences, Wuhan 430074, China
⁵. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
⁶. Chinese Academy of Agricultural Science, Beijing 100081, China
⁷. School of Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK

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Abstract

Precision agriculture (PA) technologies have great potential for promoting sustainable intensification of food production, ensuring targeted delivery of agricultural inputs, and hence food security and environmental protection. The benefits of PA technologies are applicable across a broad range of agronomic, environmental and rural socio-economic contexts globally. However, farmer and land-manager adoption in low to middle income countries has typically been slower than that observed in more affluent countries. China is currently engaged in the process of agricultural modernisation to ensure food security for its 1.4 billion population and has developed a portfolio of policies designed to improve food security, while simultaneously promoting environmental protection. Particular attention has been paid to the reduction of agricultural inputs such as fertilisers and pesticides. The widespread adoption of PA technologies across the Chinese agricultural landscape is central to the success of these policies. However, socio-economic and cultural barriers, farm scale, (in particular the prevalence of smaller family farms) and demographic changes in the rural population, (for example, the movement of younger people to the cities) represent barriers to PA adoption across China. A framework for ensuring an acceptable and accelerated PA technology trajectory is proposed which combines systematic understanding of farmer and end-user priorities and preferences for technology design throughout the technology development process, and subsequent end-user requirements for implementation (including demonstration of economic and agronomic benefits, and knowledge transfer). Future research will validate the framework against qualitative and quantitative socio-economic, cultural and agronomic indicators of successful, or otherwise, PA implementation. The results will provide the evidence upon which to develop further policies regarding how to secure sustainable food production and how best to implement PA in China, as well as practical recommendations for optimising end-user uptake.

Keywords precision agriculture farmer adoption technological innovation

Corresponding Author(s): Helen KENDALL

Just Accepted Date: 22 October 2018 Online First Date: 07 November 2018 Issue Date: 19 November 2018

Cite this article:

Beth CLARK,Glyn D. JONES,Helen KENDALL, et al. A proposed framework for accelerating technology trajectories in agriculture: a case study in China[J]. Front. Agr. Sci. Eng. , 2018, 5(4): 485-498.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2018244
https://academic.hep.com.cn/fase/EN/Y2018/V5/I4/485

Factors influencing adoption	Overview	References
Cost (i.e., financial investments)	Capital costs associated with PA technologies can be high, particularly in times of low commodity prices. The high costs of these technologies may disproportionately favor larger farms that have the capital to invest in the associated technologies. In addition to the costs of the technology, there are additional costs of extension services required to interpret data and formulate management plans. Moreover, while the costs are clear, it is difficult for farmers to identify the financial benefits of PA technology	[⁸,²⁵–²⁷]
Level of mechanisation within a farming system	Many technologies are aimed at mechanised operation and are not suitable for manual operations. E.g., yield mapping in processing tomatoes using a mechanised harvest system is possible. However, mechanisation is not possible when farming market tomatoes	[²⁶]
Skills	The adoption of PA technologies requires farmers to invest in learning a new skill, using information systems and interpreting data outputs which can require significant time investments. PA technologies may be perceived to be complex and difficult to use. Moreover, agricultural workers may give low prioritisation to the analysis of data over more practical tasks (i.e., harvesting). It is also recognized that the identification of in-field management zones requires longitudinal data collection and staff retention or at least acquisition of new staff with appropriate skills. Trained and skilled agricultural workers may also be difficult to find in rural areas	[⁸,²⁶,²⁸–³⁰]
Socio-demographics	Farm size influences adoption, with larger farms being more likely to adopt PA technologies owing to increased levels of awareness. Access to information and ability to invest may also be more problematic on smaller farms, where farmers may be less well informed about PA and are less likely to be adopters	[²⁹] [³⁰] [²⁷] [⁸] [²⁷] [²⁹]
	Farmer education level influences adoption; farmers educated to degree level are more likely to adopt PA technologies, training in which has become part of agricultural education at universities	[⁸,²⁶]
	Younger farmers are potentially more highly educated and more willing to innovate; older farmers may be more reluctant to engage owing to the reduced likelihood of paying off investments in technology and lowered time periods over which they can witness accrual of benefits	[²⁸]
Technology compatibility	Incompatibility of software and hardware from different PA manufacturers may present a barrier to adoption	[²⁶,²⁹]
Perceived benefit	The primary benefits of PA may be difficult for the farmer to quantify	[²⁶,²⁹]
Perceived risk	There may be a perceived risk within rural communities for negative impacts in relation to traditional cultures, and socio-demographic composition	[²⁵]
	New technological innovations are likely to be perceived as being riskier than traditional practices	[²⁸]
Data security	Due to potential interpretation complexity and time commitments linked to PA, analysis of data collected on farm is often outsourced to consultants or contractors. Outsourcing of farm data carries concerns relating to data insecurity, and fears of misuse	[²⁶,²⁹]
Advisory service (farmer support)	Better advisory services, more information and better training opportunities are required to support the adoption of PA technologies particularly during the introductory stages of adoption, and to aid with the interpretation of data	[²⁶]
	Farm advisory specialists and agronomy advisors may represent a limited resource in terms of availability and/or lack knowledge and training in specialist approaches to PA, and are therefore unable to provide adequate support to farmers regarding technology adoption	[⁸,²⁶]
	There is currently a lack of industry wide protocols for the application PA techniques	[³⁰]
Farming subsidies	High levels of farming subsidies can reduce incentives to farmers to manage farms based on maximum profitability, and eliminate farmer motivation to consider economising technologies such as PA	[²⁶]
Farm demonstrations	There has been a decline in the number of farm demonstrations of PA which provide information to farmers and support proficiency in the use of technology	[³¹]

Tab.1 Factors influencing the adoption of precision farming technologies

Tab.2 Characterization of Chinese farms at different scales

Fig.1 How effective co-design is predicted to accelerate technology adoption

RRI framework element	RRI framework requirement	Stakeholders and timing (i.e., who should be engaged and at what point in the TRL development process)	Research methods	Analysis	Expected effect on development/adoption	Evidence for future policy
Socio-economic barriers to adoption on small farms and relevant communities	Identification of relevant stakeholders and qualitative and quantitative evidence	Early and ongoing engagement with range of stakeholders (TRL1–9 and post adoption) that are the intended beneficiaries of PA technologies (i.e., farmers and end-users), those with influence over introduction and adoption (i.e., policymakers at all levels including national, regional and local) and community leaders	Qualitative methods (incl.): - In-depth interviews - Focus groups - Stakeholder engagement workshops Quantitative methods: - Surveys of end-users and stakeholders	- Thematic analysis using qualitative methodologies - Quantitative analysis to distinguish requirements across different end-user stakeholder groups - SEM modeling to assess the relationship between attitude and intention to adopt	- Identification of on farm challenges influencing technology needs and capacity for adoption - Ensuring that technology development aligns with farmer needs - Developing technologies to at least minimum performance needs - Recommendations and translational inputs into policy development	Design measures to overcome barriers to adoption. e.g., - Integrated education and dissemination activities. - Restructure implementation to take account of demographic factors e.g., aging rural population with more women who may not have received technical educations
Identification of socio-economic facilitators of adoption on family farms and relevant communities					- Focus on desired design features that address on farm challenges and farmer needs - Identification of end-user/communities readiness to adopt technologies - Identification of mechanisms to support adoption (i.e., subsidies, agronomic service provision)	- Community/government support regarding technology introduction (e.g., loans/subsidies to communities/farms to purchase/buy in to technology)
Assessing ethical issues, including the principal of fairness or equitable access to PA technologies across farm scales					- Appreciation of ethical impacts on local communities (i.e., impacts on rural migration trends, marginalization of poorest farmer, loss of traditional knowledge and farming practices)	- Developing policies to ensure ‘fairness’ or equitable access to PA technologies - Developing policies to preserve traditional farming practice
Economic impacts of PA technology adoption	Comprehension of the range and variance in economic benefits (costs) in differing farm systems and drivers of benefit/cost	Economic assessments of farmer practice made over the duration of the research project. Baseline through to post implementation assessment and future predictions. Scenario-based assessments of economic impacts under different market conditions Wider economic and quality of life assessments of impact of adoption on rural communities, e.g., impacts on rural livelihoods, access to health care and education	On farm partial budget (simplest method which considers effects of varying one input per unit area) to general equilibrium (most difficult and time consuming which considers varying multiple inputs and system wide effects)		- Objective analysis of economic benefits to end users disseminated in optimal fashion - Identification of key financial attributes that drive economic benefits such as farm profitability - Prediction of impact on adoption trajectories under varying market conditions	Key financial attributes that drive economic benefits. For example, cost of PA adoption, impacts on short- and long-term agronomic goals, linked to increased yield and reduced inputs. This can be estimated at earlier technology stages and more formally assessed when the technology is being applied (for example, in developer field trials or during later beta test phases, i.e., TRL6–9)
Economic impacts of PA technology adoption
Agronomic experiments and interventions to determine impact of PA	Implementation of PA technology solutions aimed at trailing innovations and demonstrating the capacity and benefits of PA technologies on farms and in ‘real world’ environments	Collaboration between scientists and farmers from inception through to prototype trials and final testing (TRL1–9). Experimental testing in a range of farm environments including demonstration farms on working farms post TRL9	Technology dependent; specific experiments designed to determine impacts of PA interventions on yield and environmental impacts of farming practices at different farm scales. Assessment of agronomic and environmental impacts of PA adoption in ‘real world’ environments	Quantitative analysis of improved yields, reduced disease and pest incidence, reduced inputs	- Ensuring the development and promotion of PA technology solutions that are problem focused and align with the needs of farmers - Demonstration of the applied benefits of given technology in a ‘real world’ setting - Opportunity for end-user trial and feedback on design and implementation of technology - Opportunity for adaptions to design to be made post trail to improve adoption rates and time to peak adoption - Assessment of the impacts of PA on existing and emerging environmental policies	- Evidence of reduced agronomic inputs (fertiliser, pesticides, water etc.) following PA adoption - Compliance with emerging environmental standards relating to agricultural production

Tab.3 An example RRI framework for accelerated PA development and equitable adoption applied to PA adoption in family farms in China

Fig.2 Application of the RRI framework for accelerated PA development and equitable adoption on small farms in China

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