A scientometric review of cyber extension as a communication medium in improving farmer capacity and performance

Arief Sirajuddin; Tuti Bahfiarti; Andi Alimuddin Unde; Sudirman  Karnay

doi:10.31893/multirev.2025086

Keywords:

scientometric analysis

Abstract

This study seeks to explore through scientometrics analysis the relevance of cyber extension in agriculture as a communication tool to improve the skills and effectiveness of farmers. The approach utilized the database provided by Scopus to collect and examine related articles published between 1994 and 2023. Scientometric analysis was conducted using RStudio, VOSviewer, and CiteSpace software to uncover trends, patterns, and relationships among articles and authors in the domain of cyber extension and capacity building of farmers. The findings show that new technologies in agriculture, including agricultural robots, precision farming, and the Internet of Things, are increasingly recognized for their sustainability and influence on climate change. Innovative technologies such as deep learning and artificial intelligence are believed to improve decision-making processes especially in agriculture. The integration of cyber-enhancement in agricultural communications aims to improve farmers' knowledge and understanding, foster innovation, and advance sustainable agricultural practices. The results show that advancing cyber technology enhancement is essential to improve communication between farmers and stakeholders especially the government, which in turn can improve the overall capacity and performance of farmers. This study provides significant insights for academics, researchers, practitioners, policymakers, and observers in agriculture seeking to design successful cyber-enhancement measures to assist agriculture and raise farmers' welfare. The future of research on the application of cyber technology in agriculture presents intriguing and significant opportunities, particularly for sustainable and ecologically friendly practices. This method can enhance agricultural output while reducing adverse effects on the environment and human health. A significant problem is educating and training farmers in the utilisation of cyber technology. Future research will concentrate on efficient training methods and digital extension, facilitating the adoption of new technology by farmers, particularly in underdeveloped rural regions.
References
1. Aksnes, D. W., Liv, L., & Wouters, P. (2019). Citations, Citation Indicators, and Research Quality: An Overview of Basic Concepts and Theories. SAGE Open, 9(1), 1-17. https://doi: 10.1177/2158244019829575.
2. Antwi-Agyei, Philip, & Stringer, L. C. (2021). Improving the Effectiveness of Agricultural Extension Services in Supporting Farmers to Adapt to Climate Change: Insights from Northeastern Ghana. Climate Risk Management, 32(2021), 1-13). https://doi: 10.1016/j.crm.2021.100304.
3. Arslan, Aslihan, McCarthy, N., Lipper, L., Asfaw, S., & Cattaneo, A. (2014). Adoption and Intensity of Adoption of Conservation Farming Practices in Zambia. Agriculture, Ecosystems & Environment, 187(2014), 72–86. https://doi: 10.1016/j.agee.2013.08.017.
4. Aubert, Benoit 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 Systems, 54(1), 510–20. https://doi: 10.1016/j.dss.2012.07.002.
5. Barakabitze, Alcardo, A., Kitindi, E. J., Sanga, C., Shabani, A., Philipo, J., & Kibirige, G. (2015). New Technologies for Disseminating and Communicating Agriculture Knowledge and Information: Challenges for Agricultural Research Institutes in Tanzania. Electronic Journal of Information Systems in Developing Countries, 70(1), 1–22. https://doi: 10.1002/j.1681-4835.2015.tb00502.x.
6. Baziari, Fahimeh, Henquinet, K. B., & Cavaleri, M.A. (2019). Understanding Farmers’ Perceptions and the Effects of Shea (Vitellaria Paradoxa) Tree Distribution in Agroforestry Parklands of Upper West Region, Ghana. Agroforestry Systems, 93(2), 557–70. https://doi: 10.1007/s10457-017-0150-1.
7. Birke, Mekonnen, F., Lemma, M., & Knierim, A. (2019). Perceptions towards Information Communication Technologies and Their Use in Agricultural Extension: Case Study from South Wollo, Ethiopia. The Journal of Agricultural Education and Extension, 25(1), 47–62. https://doi: 10.1080/1389224X.2018.1524773.
8. Boursianis, Achilles, D., Papadopoulou, M. S., Diamantoulakis, P., Tsakalidi, A. L., Barouchas, P., Salahas, G., Karagiannidis, G., Wan, S., & Goudos, S. K. (2022). Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in Smart Farming: A Comprehensive Review. Internet of Things, 18(2022).100187. https://doi: 10.1016/j.iot.2020.100187.
9. Chedea, Sanda, V., Drăgulinescu, A. M., Tomoiagă, L. L., Bălăceanu, C., & Iliescu, M. L. (2021). Climate Change and Internet of Things Technologies—Sustainable Premises of Extending the Culture of the Amurg Cultivar in Transylvania—A Use Case for Târnave Vineyard. Sustainability, 13(15), 8170. https://doi: 10.3390/su13158170.
10. Chaomei, C., & Song, M. (2019). Visualizing a Field of Research: A Methodology of Systematic Scientometric Reviews. PLoS ONE, 14(10). 1-25. https://doi: 10.1371/journal.pone.0223994.
11. Chhetri, K., Arun, Pant, A., Aggarwal, P. K., Vasireddy, V. V., & Yadav, A. (2019). Stakeholders Prioritization of Climate-Smart Agriculture Interventions: Evaluation of a Framework. Agricultural Systems, 174(2019), 23–31. https://doi: 10.1016/j.agsy.2019.03.002.
12. Ding, X., & Yang, Z. (2022). Knowledge Mapping of Platform Research: A Visual Analysis Using VOSviewer and CiteSpace. Electronic Commerce Research, 22(3), 787–809. https://doi: 10.1007/s10660-020-09410-7.
13. Eitzinger, Anton, Cock, J., Atzmanstorfer, K., Binder, C. R., Läderach, P., Findji, O. B., Bartling, M., Mwongera, C., Zurita, L., & Jarvis, A. (2019). GeoFarmer: A Monitoring and Feedback System for Agricultural Development Projects. Computers and Electronics in Agriculture, 158(2019), 109–21. https://doi: 10.1016/j.compag.2019.01.049.
14. Ejem, Agwu, Aremu, C., Ajakaiye, O. O. P., Enukora, C. B., Popoola, O. E. A., Ibiwoye, T. I., & Olaniran, A. F. (2023). Perspectives on Communicating 21st-Century Agricultural Innovations to Nigerian Rural Farmers. Journal of Agriculture and Food Research, 11(2023), 100511. https://doi: 10.1016/j.jafr.2023.100511.
15. Feng, Y., Duives, D., Daamen, W., & Hoogendoorn, S. (2021). Data Collection Methods for Studying Pedestrian Behaviour: A Systematic Review. Building and Environment, 187(2021), 107329. https://doi: 10.1016/j.buildenv.2020.107329.
16. Höckert, J., & Ljung, M. (2013). Advisory Encounters towards a Sustainable Farm Development—Interaction between Systems and Shared Lifeworlds. The Journal of Agricultural Education and Extension, 19(3), 291–309. https://doi: 10.1080/1389224X.2013.782178.
17. Jarial, S., & Sachan, S. (2021). Digital Agriculture through Extension Advisory Services- Is It Gender-Responsive? A Review. International Journal of Agricultural Extension, 9(3), 559–66. https://doi: 10.33687/ijae.009.03.3687.
18. Kemeç, A., & Altınay, A. T. (2023). Sustainable Energy Research Trend: A Bibliometric Analysis Using VOSviewer, RStudio Bibliometrix, and CiteSpace Software Tools. Sustainability, 15(4), 3618. https://doi: 10.3390/su15043618.
19. Khan, Abbas, N., Ma, W., Owusu, V., & Shah, A. A. (2023). Does ICT-Based Farm Advisory Improve Farmers’ Adaptation to Climate Change? Evidence from Pakistan. Climate and Development, 15(8), 639–54. https://doi: 10.1080/17565529.2022.2143232.
20. Khanal, Sami, Kushal, K. C., Fulton, J. P., Shearer, S., & Ozkan, E. (2020). Remote Sensing in Agriculture—Accomplishments, Limitations, and Opportunities. Remote Sensing, 12(22), 3783. https://doi: 10.3390/rs12223783.
21. Krell, N. T., Giroux, S. A., Guido, Z., Hannah, C., Lopus, S. E., Caylor, K. K., & Evans, T. P. (2021). Smallholder Farmers’ Use of Mobile Phone Services in Central Kenya. Climate and Development, 13(3), 215–27. https://doi: 10.1080/17565529.2020.1748847.
22. Margot, E. (1999). ‘Who’s out There?’ — Strengthening Internet Communication for Agriculture Through Consideration of Audience Dimensions and User Needs. Journal of Applied Communications, 83(1), 2. https://doi: 10.4148/1051-0834.2133.
23. Labeyrie, Vanesse, Rono, B., & Leclerc, C. (2014). How Social Organization Shapes Crop Diversity: An Ecological Anthropology Approach among Tharaka Farmers of Mount Kenya. Agriculture and Human Values, 31(1), 97–107. https://doi: 10.1007/s10460-013-9451-9.
24. Lawelai, H., Iswanto, & Raharja, N. M. (2023). Use of Artificial Intelligence in Public Services: A Bibliometric Analysis and Visualization. TEM Journal, 12(2), 798–807. https://doi: 10.18421/TEM122-24.
25. Marcia, L. (2003). Technology and Science Education: Starting Points, Research Programs, and Trends. International Journal of Science Education, 25(6), 727–58. https://doi: 10.1080/09500690305017.
26. Mohidem, Adibah, N., Che’Ya, N .N., Juraimi, A. S., Ilahi, W. F. F., Roslim, M. H. M., Sulaiman, N., Saberioon, M., & Noor, N. M. (2021). How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields?. Agriculture, 11(10), 1004. https://doi: 10.3390/agriculture11101004.
27. Mooventhan, P., Kadian, K. S., Senthilkumar, A., Kumaresan, Manimaran, & Karpagam. (2017). Dissemination of Good Dairy Farming Practices through Interactive Educational Multimedia Module- An Innovative Approach in Farm Technology Transfer. Indian Journal of Animal Sciences, 87(3), 396–400. https://doi: 10.56093/ijans.v87i3.68888.
28. Meine, V. N. (2019). Integrated Natural Resource Management as Pathway to Poverty Reduction: Innovating Practices, Institutions and Policies. Agricultural Systems, 172(2019), 60–71. https://doi: 10.1016/j.agsy.2017.10.008.
29. Ouafiq, El Mehdi, Saadane, R., Chehri, A., & Jeon, S. (2022). AI-Based Modeling and Data-Driven Evaluation for Smart Farming-Oriented Big Data Architecture Using IoT with Energy Harvesting Capabilities. Sustainable Energy Technologies and Assessments, 52(102093). https://doi: 10.1016/j.seta.2022.102093.
30. Polman, N. B. P., & Slangen, L. H. G. (2008). Institutional Design of Agri-Environmental Contracts in the European Union: The Role of Trust and Social Capital. NJAS: Wageningen Journal of Life Sciences, 55(4), 413–30. https://doi: 10.1016/S1573-5214(08)80029-2.
31. Prakoso, V., Lawelai, H., Nurmandi, A., Purnomo, E. P., & Jovita, H. (2023). Research Trends, Topics, and Insights on Network Security and the Internet of Things in Smart Cities. Jurnal Studi Ilmu Pemerintahan, 4(2), 191–206. https://doi: 10.35326/jsip.v4i2.4707.
32. Reid, Susanna, Smit, B., Caldwell, W., & Belliveau, S. (2007). Vulnerability and Adaptation to Climate Risks in Ontario Agriculture. Mitigation and Adaptation Strategies for Global Change, 12(4), 609–37. https://doi: 10.1007/s11027-006-9051-8.
33. Shaikh, A., Tawseef, Rasool, T., & Lone, F. R. (2022). Towards Leveraging the Role of Machine Learning and Artificial Intelligence in Precision Agriculture and Smart Farming. Computers and Electronics in Agriculture, 198(2022). 107-119. https://doi: 10.1016/j.compag.2022.107119.
34. Sparrow, R., & Howard, M. (2021). Robots in Agriculture: Prospects, Impacts, Ethics, and Policy. Precision Agriculture, 22(3), 818–33. https://doi: 10.1007/s11119-020-09757-9.
35. Stovold, Elizabeth, Beecher, D., Foxlee, R., & Noel-Storr, A. (2014). Study Flow Diagrams in Cochrane Systematic Review Updates: An Adapted PRISMA Flow Diagram. Systematic Reviews, 3(1), 54. https://doi: 10.1186/2046-4053-3-54.
36. Subejo, Untari, D. W., Wati, R. I., & Mewasdinta, G. (2019). Modernization of Agriculture and Use of Information and Communication Technologies by Farmers in Coastal Yogyakarta. Indonesian Journal of Geography, 51(3), 332. https://doi: 10.22146/ijg.41706.
37. Suswadi, & Irawan, N. C. (2023). Digital Transformation of Agricultural Extension in Indonesia: A Comprehensive Analysis. Agris On-Line Papers in Economics and Informatics, 15(4), 135–46. https://doi: 10.7160/aol.2023.150410.
38. Vecchio, Yari, De Rosa, M., Adinolfi, F., Bartoli, L., & Mais, M. (2020). Adoption of Precision Farming Tools: A Context-Related Analysis. Land Use Policy, 94, 104481. https://doi: 10.1016/j.landusepol.2020.104481.
39. Wang, Chen, Miller, D., Brown, I., Jiang, Y., & Castellazzi, M. (2016). Visualisation Techniques to Support Public Interpretation of Future Climate Change and Land-Use Choices: A Case Study from N-E Scotland. International Journal of Digital Earth, 9(6), 586–605. https://doi: 10.1080/17538947.2015.1111949.
40. Zahra, Az, A., Nurmandi, A., Tenorio, C. B., Rahayu, R., Benectitos, S. H., Mina, F. L. P., & Haictin, K. M. (2021). Bibliometric Analysis of Trends in Theory-Related Policy Publications. Emerging Science Journal 5(1), 96–110. https://doi: 10.28991/ESJ-2021-01261.
41. Zhu, M., & Shang, J. (2022). Remote Monitoring and Management System of Intelligent Agriculture under the Internet of Things and Deep Learning. Wireless Communications and Mobile Computing, 1(2022), 1206677. https://doi: 10.1155/2022/1206677.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Sirajuddin, A., Bahfiarti, T., Unde, A. A., & Karnay, S. (2024). A scientometric review of cyber extension as a communication medium in improving farmer capacity and performance. Multidisciplinary Reviews, 8(3), 2025086. https://doi.org/10.31893/multirev.2025086

[1] Aksnes, D. W., Liv, L., & Wouters, P. (2019). Citations, Citation Indicators, and Research Quality: An Overview of Basic Concepts and Theories. SAGE Open, 9(1), 1-17. https://doi: 10.1177/2158244019829575.

[2] Antwi-Agyei, Philip, & Stringer, L. C. (2021). Improving the Effectiveness of Agricultural Extension Services in Supporting Farmers to Adapt to Climate Change: Insights from Northeastern Ghana. Climate Risk Management, 32(2021), 1-13). https://doi: 10.1016/j.crm.2021.100304.

[3] Arslan, Aslihan, McCarthy, N., Lipper, L., Asfaw, S., & Cattaneo, A. (2014). Adoption and Intensity of Adoption of Conservation Farming Practices in Zambia. Agriculture, Ecosystems & Environment, 187(2014), 72–86. https://doi: 10.1016/j.agee.2013.08.017.

[4] Aubert, Benoit 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 Systems, 54(1), 510–20. https://doi: 10.1016/j.dss.2012.07.002.

[5] Barakabitze, Alcardo, A., Kitindi, E. J., Sanga, C., Shabani, A., Philipo, J., & Kibirige, G. (2015). New Technologies for Disseminating and Communicating Agriculture Knowledge and Information: Challenges for Agricultural Research Institutes in Tanzania. Electronic Journal of Information Systems in Developing Countries, 70(1), 1–22. https://doi: 10.1002/j.1681-4835.2015.tb00502.x.

[6] Baziari, Fahimeh, Henquinet, K. B., & Cavaleri, M.A. (2019). Understanding Farmers’ Perceptions and the Effects of Shea (Vitellaria Paradoxa) Tree Distribution in Agroforestry Parklands of Upper West Region, Ghana. Agroforestry Systems, 93(2), 557–70. https://doi: 10.1007/s10457-017-0150-1.

[7] Birke, Mekonnen, F., Lemma, M., & Knierim, A. (2019). Perceptions towards Information Communication Technologies and Their Use in Agricultural Extension: Case Study from South Wollo, Ethiopia. The Journal of Agricultural Education and Extension, 25(1), 47–62. https://doi: 10.1080/1389224X.2018.1524773.

[8] Boursianis, Achilles, D., Papadopoulou, M. S., Diamantoulakis, P., Tsakalidi, A. L., Barouchas, P., Salahas, G., Karagiannidis, G., Wan, S., & Goudos, S. K. (2022). Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in Smart Farming: A Comprehensive Review. Internet of Things, 18(2022).100187. https://doi: 10.1016/j.iot.2020.100187.

[9] Chedea, Sanda, V., Drăgulinescu, A. M., Tomoiagă, L. L., Bălăceanu, C., & Iliescu, M. L. (2021). Climate Change and Internet of Things Technologies—Sustainable Premises of Extending the Culture of the Amurg Cultivar in Transylvania—A Use Case for Târnave Vineyard. Sustainability, 13(15), 8170. https://doi: 10.3390/su13158170.

[10] Chaomei, C., & Song, M. (2019). Visualizing a Field of Research: A Methodology of Systematic Scientometric Reviews. PLoS ONE, 14(10). 1-25. https://doi: 10.1371/journal.pone.0223994.

[11] Chhetri, K., Arun, Pant, A., Aggarwal, P. K., Vasireddy, V. V., & Yadav, A. (2019). Stakeholders Prioritization of Climate-Smart Agriculture Interventions: Evaluation of a Framework. Agricultural Systems, 174(2019), 23–31. https://doi: 10.1016/j.agsy.2019.03.002.

[12] Ding, X., & Yang, Z. (2022). Knowledge Mapping of Platform Research: A Visual Analysis Using VOSviewer and CiteSpace. Electronic Commerce Research, 22(3), 787–809. https://doi: 10.1007/s10660-020-09410-7.

[13] Eitzinger, Anton, Cock, J., Atzmanstorfer, K., Binder, C. R., Läderach, P., Findji, O. B., Bartling, M., Mwongera, C., Zurita, L., & Jarvis, A. (2019). GeoFarmer: A Monitoring and Feedback System for Agricultural Development Projects. Computers and Electronics in Agriculture, 158(2019), 109–21. https://doi: 10.1016/j.compag.2019.01.049.

[14] Ejem, Agwu, Aremu, C., Ajakaiye, O. O. P., Enukora, C. B., Popoola, O. E. A., Ibiwoye, T. I., & Olaniran, A. F. (2023). Perspectives on Communicating 21st-Century Agricultural Innovations to Nigerian Rural Farmers. Journal of Agriculture and Food Research, 11(2023), 100511. https://doi: 10.1016/j.jafr.2023.100511.

[15] Feng, Y., Duives, D., Daamen, W., & Hoogendoorn, S. (2021). Data Collection Methods for Studying Pedestrian Behaviour: A Systematic Review. Building and Environment, 187(2021), 107329. https://doi: 10.1016/j.buildenv.2020.107329.

[16] Höckert, J., & Ljung, M. (2013). Advisory Encounters towards a Sustainable Farm Development—Interaction between Systems and Shared Lifeworlds. The Journal of Agricultural Education and Extension, 19(3), 291–309. https://doi: 10.1080/1389224X.2013.782178.

[17] Jarial, S., & Sachan, S. (2021). Digital Agriculture through Extension Advisory Services- Is It Gender-Responsive? A Review. International Journal of Agricultural Extension, 9(3), 559–66. https://doi: 10.33687/ijae.009.03.3687.

[18] Kemeç, A., & Altınay, A. T. (2023). Sustainable Energy Research Trend: A Bibliometric Analysis Using VOSviewer, RStudio Bibliometrix, and CiteSpace Software Tools. Sustainability, 15(4), 3618. https://doi: 10.3390/su15043618.

[19] Khan, Abbas, N., Ma, W., Owusu, V., & Shah, A. A. (2023). Does ICT-Based Farm Advisory Improve Farmers’ Adaptation to Climate Change? Evidence from Pakistan. Climate and Development, 15(8), 639–54. https://doi: 10.1080/17565529.2022.2143232.

[20] Khanal, Sami, Kushal, K. C., Fulton, J. P., Shearer, S., & Ozkan, E. (2020). Remote Sensing in Agriculture—Accomplishments, Limitations, and Opportunities. Remote Sensing, 12(22), 3783. https://doi: 10.3390/rs12223783.

[21] Krell, N. T., Giroux, S. A., Guido, Z., Hannah, C., Lopus, S. E., Caylor, K. K., & Evans, T. P. (2021). Smallholder Farmers’ Use of Mobile Phone Services in Central Kenya. Climate and Development, 13(3), 215–27. https://doi: 10.1080/17565529.2020.1748847.

[22] Margot, E. (1999). ‘Who’s out There?’ — Strengthening Internet Communication for Agriculture Through Consideration of Audience Dimensions and User Needs. Journal of Applied Communications, 83(1), 2. https://doi: 10.4148/1051-0834.2133.

[23] Labeyrie, Vanesse, Rono, B., & Leclerc, C. (2014). How Social Organization Shapes Crop Diversity: An Ecological Anthropology Approach among Tharaka Farmers of Mount Kenya. Agriculture and Human Values, 31(1), 97–107. https://doi: 10.1007/s10460-013-9451-9.

[24] Lawelai, H., Iswanto, & Raharja, N. M. (2023). Use of Artificial Intelligence in Public Services: A Bibliometric Analysis and Visualization. TEM Journal, 12(2), 798–807. https://doi: 10.18421/TEM122-24.

[25] Marcia, L. (2003). Technology and Science Education: Starting Points, Research Programs, and Trends. International Journal of Science Education, 25(6), 727–58. https://doi: 10.1080/09500690305017.

[26] Mohidem, Adibah, N., Che’Ya, N .N., Juraimi, A. S., Ilahi, W. F. F., Roslim, M. H. M., Sulaiman, N., Saberioon, M., & Noor, N. M. (2021). How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields?. Agriculture, 11(10), 1004. https://doi: 10.3390/agriculture11101004.

[27] Mooventhan, P., Kadian, K. S., Senthilkumar, A., Kumaresan, Manimaran, & Karpagam. (2017). Dissemination of Good Dairy Farming Practices through Interactive Educational Multimedia Module- An Innovative Approach in Farm Technology Transfer. Indian Journal of Animal Sciences, 87(3), 396–400. https://doi: 10.56093/ijans.v87i3.68888.

[28] Meine, V. N. (2019). Integrated Natural Resource Management as Pathway to Poverty Reduction: Innovating Practices, Institutions and Policies. Agricultural Systems, 172(2019), 60–71. https://doi: 10.1016/j.agsy.2017.10.008.

[29] Ouafiq, El Mehdi, Saadane, R., Chehri, A., & Jeon, S. (2022). AI-Based Modeling and Data-Driven Evaluation for Smart Farming-Oriented Big Data Architecture Using IoT with Energy Harvesting Capabilities. Sustainable Energy Technologies and Assessments, 52(102093). https://doi: 10.1016/j.seta.2022.102093.

[30] Polman, N. B. P., & Slangen, L. H. G. (2008). Institutional Design of Agri-Environmental Contracts in the European Union: The Role of Trust and Social Capital. NJAS: Wageningen Journal of Life Sciences, 55(4), 413–30. https://doi: 10.1016/S1573-5214(08)80029-2.

[31] Prakoso, V., Lawelai, H., Nurmandi, A., Purnomo, E. P., & Jovita, H. (2023). Research Trends, Topics, and Insights on Network Security and the Internet of Things in Smart Cities. Jurnal Studi Ilmu Pemerintahan, 4(2), 191–206. https://doi: 10.35326/jsip.v4i2.4707.

[32] Reid, Susanna, Smit, B., Caldwell, W., & Belliveau, S. (2007). Vulnerability and Adaptation to Climate Risks in Ontario Agriculture. Mitigation and Adaptation Strategies for Global Change, 12(4), 609–37. https://doi: 10.1007/s11027-006-9051-8.

[33] Shaikh, A., Tawseef, Rasool, T., & Lone, F. R. (2022). Towards Leveraging the Role of Machine Learning and Artificial Intelligence in Precision Agriculture and Smart Farming. Computers and Electronics in Agriculture, 198(2022). 107-119. https://doi: 10.1016/j.compag.2022.107119.

[34] Sparrow, R., & Howard, M. (2021). Robots in Agriculture: Prospects, Impacts, Ethics, and Policy. Precision Agriculture, 22(3), 818–33. https://doi: 10.1007/s11119-020-09757-9.

[35] Stovold, Elizabeth, Beecher, D., Foxlee, R., & Noel-Storr, A. (2014). Study Flow Diagrams in Cochrane Systematic Review Updates: An Adapted PRISMA Flow Diagram. Systematic Reviews, 3(1), 54. https://doi: 10.1186/2046-4053-3-54.

[36] Subejo, Untari, D. W., Wati, R. I., & Mewasdinta, G. (2019). Modernization of Agriculture and Use of Information and Communication Technologies by Farmers in Coastal Yogyakarta. Indonesian Journal of Geography, 51(3), 332. https://doi: 10.22146/ijg.41706.

[37] Suswadi, & Irawan, N. C. (2023). Digital Transformation of Agricultural Extension in Indonesia: A Comprehensive Analysis. Agris On-Line Papers in Economics and Informatics, 15(4), 135–46. https://doi: 10.7160/aol.2023.150410.

[38] Vecchio, Yari, De Rosa, M., Adinolfi, F., Bartoli, L., & Mais, M. (2020). Adoption of Precision Farming Tools: A Context-Related Analysis. Land Use Policy, 94, 104481. https://doi: 10.1016/j.landusepol.2020.104481.

[39] Wang, Chen, Miller, D., Brown, I., Jiang, Y., & Castellazzi, M. (2016). Visualisation Techniques to Support Public Interpretation of Future Climate Change and Land-Use Choices: A Case Study from N-E Scotland. International Journal of Digital Earth, 9(6), 586–605. https://doi: 10.1080/17538947.2015.1111949.

[40] Zahra, Az, A., Nurmandi, A., Tenorio, C. B., Rahayu, R., Benectitos, S. H., Mina, F. L. P., & Haictin, K. M. (2021). Bibliometric Analysis of Trends in Theory-Related Policy Publications. Emerging Science Journal 5(1), 96–110. https://doi: 10.28991/ESJ-2021-01261.

[41] Zhu, M., & Shang, J. (2022). Remote Monitoring and Management System of Intelligent Agriculture under the Internet of Things and Deep Learning. Wireless Communications and Mobile Computing, 1(2022), 1206677. https://doi: 10.1155/2022/1206677.

Abstract

References

How to cite