Perceptions of Agricultural Experts towards Barriers to the Adoption of Precision Agriculture
محورهای موضوعی : Education and training
1 - گروه مهندسی آب و مدیریت کشاورزی، دانشکده علوم کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران
2 - گروه مهندسی آب و مدیریت کشاورزی، دانشکده علوم کشاورزی و منابع طبیعی، دانشگاه محقق اردبیلی، اردبیل، ایران
کلید واژه: barriers, Ardabil, Perception, precision agriculture, agricultural experts,
چکیده مقاله :
Precision agriculture holds significant potential for increasing crop yield, reducing costs, and ensuring environmental protection. However, the adoption of these technologies is impeded by certain barriers that need to be acknowledged. This survey aimed to investigate the perceptions of agricultural experts (n=142) regarding the barriers to adopting precision agriculture in Ardabil province, Iran. Data were collected through a questionnaire administered to the participants. The research tool was validated by a group of university staff, and its reliability was confirmed through a pilot study involving 30 experts, which yielded a high alpha value. Due to the prevailing COVID-19 situation, data collection was conducted virtually. The findings indicated that the surveyed experts possessed a relatively good understanding of precision agriculture. Five factors, namely lack of knowledge, economic constraints, inadequate extension-farmer interactions, data security concerns, and limited accessibility, collectively accounted for 73.34 percent of the total variance in barriers to adopting precision agricultural technologies. Due to the lack of knowledge and poor farmer-extension interaction, extension courses are needed to improve farmers' knowledge and awareness of precision agriculture. Regarding the economic barriers, allocating the facilities and credits for developing and applying these technologies is necessary. Concerning the barriers to data security and lack of access, the government and related organizations should support farmers in solving internet access problems. Also, training and necessary facilities to maintain data security should be provided. Considering the effect of perception of usefulness on attitude, it is necessary to provide in-service training to improve experts' knowledge and perceptions about these technologies' usefulness. Precision agriculture demonstration farms in research stations or farmers' farms with the interaction of experts can be effective.
کشاورزی دقیق پتانسیل بالایی برای افزایش محصولات کشاورزی، کاهش هزینه و حفظ محیطزیست دارد، ولی پذیرش این فناوریها با موانعی مواجه است که لازم مورد توجه قرار گیرد. با استفاده از نمونهای متشکل از 142 کارشناس کشاورزی، این پیمایش برای شناسایی ادراک کارشناسان نسبت به موانع کشاورزی دقیق دراستان اردبیل، ایران انجام شد. ابزار جمع آوری دادهها پرسشنامهای بود که روایی آن توسط گروهی از اساتید دانشگاه تایید گردید. یک مطالعه راهنما به کمک 30 کارشناس انجام شد که مقدار آلفا بیانگر پایایی بالای ابزار تحقیق بود. به علت شیوع کووید 19 جمعآوری دادهها بصورت مجازی انجام شد. نتایج نشان داد که کارشناسان دانش خوبی نسبت به کشاورزی دقیق داشتن. پنج عامل فقدان دانش، موانع اقتصادی، فقدان تعامل بین کشاورزان- ترویج، مساله امنیت دادهها، و فقدان دسترسی، 34/73 درصد از واریانس موانع پذیرش فناوریهای کشاورزی دقیق را تبیین کردهاند. باتوجه به فقدان دانش و تعامل ضعیف کشاورز – مروج، لازم است فعالیتهای آموزشی ترویجی برای ارتقای آگاهی کشاورزان در زمینه کشاورزی دقیق صورت گیرد. جهت رفع موانع اقتصادی لازم است تسهیلات و اعتبارات لازم برای توسعه و کابرد این فناوریها تخصیص یابد. در خصوص موانع امنیت دادهها و عدم دسترسی، دولت و سازمانهای وابسته باید در رفع مشکلات دسترسی به اینترنت اقدام نمایند. همچنین، آموزش و امکانات لازم برای حفظ امنیت دادهها به کشاورزان ارایه گردد. با توجه به تاثیر ادراک سـودمندی بر نگـرش، لازم است آموزشهای ضمن خدمت بـرای اصلاح دانش و ادراک کارشناسـان نسبت به سـودمندی این فناوریهـا ارایه شـود. مزارع نمایشی کشاورزی دقیق در مراکز تحقیقاتی یا مزارع کشاورزان با تعامل کارشناسان میتواند موثر باشد
Adrian A.M., Norwood S.H., & Mask P.L. (2005). Producers’ perceptions and attitudes toward precision agriculture technologies. Computers and Electronics in Agriculture 48, 256–271.
Allahyari, M.S., Mohammadzadeh, M. & Nastis, S.A. (2016). Agricultural experts’ attitude towards precision agriculture: Evidence from Guilan agricultural organization, Northern Iran. Information Processing in Agriculture, 3, 183-189.
Arayesh, M.B. & Sabouri, M.S. (2016). Educational Requirements of using Precision Agriculture from the viewpoint of Agricultural Researchers of Ilam Province. Journal of Agricultural Education and Administration Research, 7 (35), 35-54 (In Persian).
Aubert, B.A., Schroeder, A., & Grimaudo, J. (2012). IT as enabler of sustainable farming: an empirical analysis of farmers’ adoption decision of precision agriculture technology. Decision Support System 54, 510–520.
Barnes, A. P., Soto, I., Eory, V., Beck, B., Balafoutis, A., Sanchez, B., & et al. (2019). Exploring the adoption of precision agricultural technologies: A cross-regional study of EU farmers. Land Use Policy, 80, 163–174, https ://doi.org/10.1016/j.landu sepol .2018.10.004.
Bogdanski, A. (2012). Integrated food-energy systems for climate-smart agriculture. Agriculture and Food Security, 1, 9. https://doi.org/10.1186/2048-7010-1-9
Bolfe, E.L., Jorge, L.A.C., Sanches, I.D., Júnior, A.L., Costa, C.C., Victoria, D.C., Inamasu, R.Y., Grego, C.R., Victor Rodrigues Ferreira, V.R., & Ramirez, A.R. (2020). Precision and digital agriculture: Adoption of technologies and perception of Brazilian farmers, Agriculture, 10, 1-16, doi: 10.3390/agriculture10120653.
Bosompem, M. (2020). Predictors of Ex-Ante adoption of precision agriculture technologies by Cocoa farmers in Ghana, Journal of Sustainable Development in Africa, 21 (4), 89-110.
Busse, M., Doernberg, A., Siebert, R., Kuntosch, A., Schwerdtner, W., Koenig, B., & Bokelmann, W. (2014). Innovation mechanisms in German precision farming. Precision Agriculture, 15, 403–426.
Cullen, R., Forbes, S.L., & Grout, R. (2013). Non-adoption of environmental innovations in wine growing. New Zealand Journal of Crop and Horticultural Science, 41, 41–48. DOI: 10.1080/01140671.2012.744760
Daberkow, S.G., McBride, W.D. (2003). Farm and operator characteristics affecting the awareness and adoption of precision agriculture technologies in the US. Precision Agriculture 4, 163–177. https://doi.org/10.1023/A:1024557205871
Demestichas, K., Peppes, N. & Alexakis, T. (2020). Survey on security threats in agricultural IoT and smart farming. Sensors, 20, 6458; doi:10.3390/s20226458.
Eidi, A., Kazemiyeh, F., Zarifian, Sh., & Mirloo, S. (2020). analysis of precision agricultural problems from the viewpoint of agricultural jihad experts in Urmia. Journal of Agricultural Science and Sustainable Production, 30 (1), 211-223. (In Persian)
Eidt, C., Hickey, G., Curtis, M., 2012. Knowledge integration and the adoption of new
agricultural technologies: Kenyan perspectives. Food Secrity 4, 355e367.
Faber, A., & Hoppe, T. (2013). Co-constructing a sustainable built environment in the Netherlands dynamics and opportunities in an environmental sectoral innovation system. Energy Policy, 52, 628–638.
Gandorfer, M., Schleicher, S., & Erdle, K. (2018). Barriers to adoption of smart farming technologies in Germany. Proceedings of the 14th International Conference on Precision Agriculture June 24 – June 27, 2018, Montreal, Quebec, Canada.
Griffin, T.W., Shockley, J.M., & Mark, T.B. (2018). Economics of precision farming, in: Precision Agriculture Basics, 221–230. Shannon, D.S., Clay, D.E., Kitchen, N.R. (Eds.). DOI:10.2134/precisionagbasics
Hair, J.F., Anderson, R.E., Tatham, R.L., & Black, W.C. (1998). Multivariate data analysis. 5th ed. Prentice Hall, Upper Saddle River, NJ, USA.
Homayoun, K. & Yazdanpanah, M. (2019). An analysis of the benefits and challenges of precision agriculture, National conference on agricultural industry and commercialization, Khuzestan University of Agriculture and Natural Resources - Khuzestan Industry, Mining and Trade Organization https://civilica.com/doc/981407 (In Persian).
Jensen, H. G., Jacobsen, L.-B., Pedersen, S. M., & Tavella, E. (2012). Socioeconomic impact of widespread adoption of precision farming and controlled traffic systems in Denmark. Precision Agriculture, 13, 661–677.
Karimi-Takanlou, Z., Ranjpour, R., Motafakkerazad, M.A., Assadzadeh, A. & Bagherzadeh-Azar, R. (2018). A New Approach for Estimating the food security level in Iran with the GFSI index and studying the Influence of price indexes and Population on it. Agricultural Economics and Development, 26(101), 181-218 (In Persian).
Koutsos, T. & Menexes, G. (2019). Economic, agronomic, and environmental benefits from the adoption of precision agriculture technologies: A systematic review. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 10 (1), 40-56. doi:10.4018/IJAEIS.2019010103.
Lambert, D. M., English, B. C., Harper, D. C., Larkin, S. L., Larson, J. A., Mooney, D. F., et al. (2014). Adoption and frequency of precision soil testing in cotton production. Journal of Agricultural and Resource Economics, 39(1), 106–123.
Lawson, L. G., Pedersen, S. M., Sørensen, C. G., Pesonen, L., Fountas, S., and Werner, A. & et al., 2011. A four nation survey of farm information management and advanced farming systems: A descriptive analysis of survey responses. Computers and Electronics in Agriculture, 77, 7-20. doi:10.1016/j.compag.2011.03.002
Long, T., Blok, V. &, Coninx, I (2015). Barriers to the adoption and diffusion of technological innovations for climate-smart agriculture in Europe: evidence from the Netherlands, France, Switzerland and Italy, Cleaner Production, http://dx.doi.org/10.1016/j.jclepro.2015.06.044.
Mitchell, S., Weersink, A. & Bannon, N. (2020). Adoption barriers for precision agriculture technologies in Canadian crop production. Canadian Journal of Plant Science, 101(3), 412-416. https://doi.org/10.1139/cjps-2020-0234
Montalvo, C. (2008). General wisdom concerning the factors affecting the adoption of cleaner technologies, a survey 1990–2007. Cleaner Production, 16, 7–13.
O’brien, R.M. (2007). Caution regarding rules of thumb for variance inflation factors. Quality and Quantity 41, 673-690.
Ofori, E., Griffin, T. & Yeager, E. (2020). Duration analyses of precision agriculture technology adoption: what's influencing farmers' time-to-adoption decisions? Agricultural Finance Review, 80(5), 647-664.
Paustian, M. & Theuvsen, L. (2016). Adoption of precision agriculture technologies by German crop farmers. Precision Agriculture, 18(5), 701–716.
Pickthall, T. & Trivett, E. (2017). An investigation into the barriers that prevent the adoption of precision
farming technologies in combinable cropping in the UK. In: Aspects of Applied Biology 135: Precision
systems in agricultural and horticultural production, I. Grove and R. Kennedy (Eds.), p. 29-37. https://
www.aab.org.uk/product-page/aspects-135-precision-systems-in-agricultural-and-horticultural-production.
Pierpaoli, E., Carlia, G. Pignatti, E. & Canavari, M. (2013). Drivers of Precision agriculture technologies adoption: A literature review. Procedia Technology, 8, 61–69.
Pivoto, D., Barham, B., Dabdab, P., Zhang, D. & Talamini, E. (2019). Factors influencing the adoption of smart farming by Brazilian grain farmers. International Food Agribusiness Management Review. 22, 571–588.
Reichardt, M., & Jürgens, C. (2009). Adoption and future perspective of precision farming in Germany: Results of several surveys among different agricultural target groups. Precision Agriculture, 10, 73–94 doi:10.1007/s11119-008-9101-1.
Robert, P.C. (2002). Precision agriculture: a challenge for crop nutrition management. Plant and Soil, 247, 143-149.
Robertson, M., Isbister, B., Maling, I., Oliver, Y., Wong, M., Adams, M., Bill Bowden, B. & Tozer, P. (2007). Opportunities and constraints for managing within-field spatial variability in Western Australian grain production. Field Crops Research, 104 (1-3), 60–67.
Rogge, E., Evens, F., & Gulinck, H. (2007). Perception of rural landscapes in Flanders: looking beyond aesthetics. Landscape and Urban Planning, 82, 159-174.
Sabouri, M.S. & Farshidnia, Z. (2018). The feasibility of using precision farming technology in the poultry industry from the viewpoint of Semnan Agricultural Jihad Experts. Journal of Plant Cellular and Molecular Biology, 13(2): 15–25(In Persian).
Schimmelpfennig, D. & Ebel, R. (2016). Sequential adoption and cost savings from precision agriculture. Journal of Agricultural and Resource Economics, 41(1), 97–115
Sean M, Alfons W, Nicholas B, 2020, Adoption Barriers for Precision Agriculture Technologies in Canadian Crop Production. Canadian Journal of Plant Science, 101(3) https://www.researchgate.net/publication/347458420.
Shirkhani, M., Pezeshki-Rad G.R. & Sadighi, H. (2016). Evaluation of Agricultural Experts' knowledge toward Precision Agriculture in the Province of Tehran-Iran. Iranian Journal of Agricultural Economics and Development Research, 47(3), 533-769 (In Persian).
Steele, D. (2018). Analysis of precision agriculture adoption & barriers in western Canada: producer survey. Report prepared for Agriculture and Agri-Food Canada (AAFC), April 2017. [Online]. Available from https://static.agcanada.com/wp-content/uploads/sites/3/2017/05/Final-Report-Analysis-of-Precision-Agriculture-Adoption-and-Barriers-in-western-Canada-April-2017.pdf.
Sumiahadi, A., Direk, M. & Acar, R. (2019). Economic assessment of precision agriculture: a short review. International conference on Sustainable agriculture and environment, 3 – 5.
Szolnoki, A. & Nábrádi, A. (2017). Economic, practical impacts of precision farming – with especial regard to harvesting. Applied Studies in Agribusiness and Commerce – APSTRACT, 8(2–3), 41–146.
Tabachnick, B. G. & Fidell, L.S. (2007). Using multivariate statistics. (5th ed.). New York: Allyn and Bacon.
Ullah, A., Ahmad, J., Muhammad, K., Lee, M.Y., Kang, B., Soo, O.B. & Baik S.W. (2017). A Survey on precision agriculture: Technologies and challenges. The 3rd International Conference on Next Generation Computing (ICNGC2017b) Kaohsiung, Taiwan.
Villa-Henriksen, A., Edwards, G.T.C., Pesonen, L.A., Green, O. & Sørensen, C.A.G. (2020) Internet of Things in arable farming: Implementation, applications, challenges and potential, Biosystems Engineering, 191, 60–84.