Main Article Content


This study aimed to analyze the farmers' willingness in adopting local feed innovation and to analyze its background factors. This study involved 106 cattle farmers who lived in Arjowilangun and Kucur villages of Malang Regency, East Java. Data were collected from respondents through personal interviews with structured questionnaires. This study also used descriptive statistical analysis and Probit regression as the methods. The research results showed that most of the farmers were willing to partially adopt local feed innovation. Social and economic factors that statistically gave significant influence on the farmers' willingness in adopting the local feed innovation are age, the number of cattle, cattle agribusiness type, membership in a farmer's group, and the perception towards the cattle farming conditions. Age and the number of cattle negatively affect the farmers' willingness while membership in a farmer's group and perception towards the cattle farming conditions has a positive effect on the farmers' willingness in adopting local feed innovation. Farmers who are running the cattle fattening business have larger probabilities to reject the local feed innovation. Furthermore, optimizing coaching and assisting activities through the farmer's group can be an effective way to increase the farmers' willingness to entirely adopt the local feed innovations.


feed innovation technology adoption local resources

Article Details

How to Cite
Putra, A. R. S., Pratama, I. W., Agustine, R., Astuti, A., Kasmiyati, K., Noviandi, C. T., Poppi, D., Harper, K., & Agus, A. (2024). The Willingness to Adopt Local Feed Innovation Among Cattle Farmers. ANIMAL PRODUCTION, 26(1), 1-8.


  1. Agus, A., & Widi, T. S. M. (2018). Current situation and future prospects for beef cattle production in Indonesia — A review. Asian-Australasian Journal of Animal Sciences, 31(7), 976–983.
  2. Aldrich, J. H., & Nelson, F. D. (1984). Linear Probability, Logit, and Probit Models. Sage Publications, Inc.
  3. Asravor, R. K. (2019). Farmers’ risk preference and the adoption of risk management strategies in Northern Ghana. Journal of Environmental Planning and Management, 62(5), 881–900.
  4. Baba, S., Dagong, M. I. A., & Sohrah, S. (2019). Factors Affecting the Adoption of Agricultural By-Products as Feed by Beef Cattle Farmers in Maros Regency of South Sulawesi, Indonesia. Tropical Animal Science Journal, 42(1), 76–80.
  5. Cahyadi, E. R., Andrianto, M. S., & Surahman, S. (2019). Risk Management in Smallholder Cattle Production in Sekaran Village, Bojonegoro. Buletin Peternakan, 43(1), 62–70.
  6. Delima, M., Karim, A., & Yunus, M. (2015). The study of prospective forage production on existing and potential land use to support increasing livestock population in Aceh Besar. Agripet, 15, 33–40.
  7. Dessart, F. J., Barreiro-Hurlé, J., & Van Bavel, R. (2019). Behavioural factors affecting the adoption of sustainable farming practices: A policy-oriented review. European Review of Agricultural Economics, 46(3), 417–471.
  8. Dung, D. V, Roubík, H., Ngoan, L. D., Phung, L. D., & Ba, N. X. (2019). Characterization of Smallholder Beef Cattle Production System in Central Vietnam–Revealing Performance, Trends, Constraints, and Future Development. Tropical Animal Science Journal, 42(3), 253–260.
  9. Fatchiya, A., Muflikhati, I., & Soedewo, T. (2018). Factors correlating with adoption of the integration system of paddy-livestock in Central Sulawesi Province, Indonesia. Jurnal Penyuluhan, 14(2), 362–370.
  10. Guntoro, B., & Priyadi, R. (2012). Motivation and performance of beef cattle smalholder farmer in Central Java Indonesia. Research Journal of Animal Sciences, 6(4–6), 85–59.
  11. Guntoro, B., Rakhman, A. N., & Suranindyah, Y. Y. (2016). Innovation Adoption of Dairy Goat Farmers in Yogyakarta , Indonesia. 2, 98–109.
  12. Gupta, V., Rai, P. K., & Risam, K. S. (2012). Integrated crop-livestock farming systems: A strategy for resource conservation and environmental sustainability. Indian Research Journal of Extension Education, Special Issue, 2, 49–54.
  13. Hayden, M. T., Mattimoe, R., & Jack, L. (2021). Sensemaking and the influencing factors on farmer decision-making. Journal of Rural Studies, 84, 31–44.
  14. Hayran, S., & Gül, A. (2015). Risk perception and management strategies in dairy farming: a case of Adana Province of Turkey. Turkish Journal of Agriculture-Food Science and Technology, 3(12), 952–961.
  15. Hifizah, A. (2016). Characteristics Of Some Potential Forages In Indonesia In Reducing Methane (Ch4) Emission From Ruminants: Benefits And Limitations. The International Journal of Tropical Veterinary and Biomedical Research, 1(1), 27–37.
  16. Keba, A. (2019). Review on Adoption of Improved Agricultural Technologies in Ethiopia. International Journal of Health Economics and Policy, 4(1), 11.
  17. Liao, T. F. F., & Liao, T. F. (1994). Interpreting probability models: Logit, probit, and other generalized linear models (Issue 101). Sage.
  18. Mulatmi, S. N. W., Guntoro, B., Widyobroto, B. P., Nurtini, S., & Pertiwiningrum, A. (2016). Strategies for increasing adoption innovation of smallholder dairy farms ini Yogyakarta Special Region, Central and East Java Provinces. Buletin Peternakan, 40(3), 219–227.
  19. Mustapha, S. (2017). Application of Multinomial Logistic to Smallholder Farmers’ Market Participation in Northern Ghana. International Journal of Agricultural Economics, 2(3), 55.
  20. Ojo, M. A., Nmadu, J. N., Tanko, L., & Olaleye, R. S. (2013). Multinomial Logit Analysis of Factors Affecting the Choice of Enterprise Among Small-holder Yam and Cassava Farmers in Niger State, Nigeria. Journal of Agricultural Sciences, 4(1), 7–12.
  21. Putra, R. A. R. S., Liu, Z., & Lund, M. (2017). The impact of biogas technology adoption for farm households – Empirical evidence from mixed crop and livestock farming systems in Indonesia. Renewable and Sustainable Energy Reviews, 74, 1371–1378.
  22. Rathod, P., Chander, M., & Chethan Sharma, G. (2017). Adoption status of artificial insemination in Indian dairy sector: Application of multinomial logit model. Journal of Applied Animal Research, 45(1), 442–446.
  23. Salendua, A. H. S., Elly, F. H., Osak, R. E. M. F., & Lumenta, I. D. R. (2018). Cattle Farm Development by Forages Cultivation on Coconut Land Based on Carrying Capacity in West Bolangitang, Indonesia. International Journal of Environment, Agriculture and Biotechnology, 3(3), 1139–1144.
  24. Setiana, L., Saleh, D. M., Nugroho, A. P., & Lana, D. L. (2020). ( AI ) TECHNOLOGY IN BREBES REGENCY Faktor - Faktor Adopsi Teknologi Inseminasi Buatan ( IB ) Sapi Potong di Kabupaten Brebes The Research method The Data Analysis collected from the Department of Livestock and Animal Health Brebes , Indonesian Statistics. Jurnal Penyuluhan, 16(01), 16–23.
  25. Sirajuddin, S. N., Sudirman, I., & Bahar, L. D. (2018). Relationship between Breeder Characteristics and Adoption of Artificial Insemination in Bali Cattle. European Journal of Sustainable Development, 7(3), 143–150.
  26. Sodiq, A., Yuwono, P., Sumarmono, J., Wakhidati, Y. N., Rayhan, M., Sidhi, A. H., & Maulianto, A. (2019). Improving production system of beef cattle agribusiness. IOP Conference Series: Earth and Environmental Science, 250(1), 12050.
  27. Sohrah, S., & Baba, S. (2019). Factors that Influence the Farmers Perception on the Utilization of Rice Straw as Feed in Bantimurung Sub-District. JITP, 7(2).
  28. Teklay, Y., & Teklay, Z. (2015). Assessment on Farmers ’ Willingness to Adopt Improved Forage Production in South Tigray , Ethiopia. Journal of Economics and Sustainable Development, 6(15), 47–58.
  29. Widarni, N. A. A., Kusumastuti, T. A., & Putra, A. R. S. (2020). A study on farmers’ choice in integrating paddy and cattle farming as farm management practices. Journal of the Indonesian Tropical Animal Agriculture, 45(4), 356–364.