Predicting farmer’s inclination towards adoption of anionic mineral mixture in Haryana: A case study

S  GOYAL; G  SANKHALA; C  DATT

doi:10.56093/ijans.v95i8.158620

Authors

S GOYAL Gochar Mahavidyalaya, Saharanpur, 247451, India
G SANKHALA ICAR- National Dairy Research Institute, Karnal, 132001, India
C DATT ICAR-National Dairy Research Institute, Karnal, 132001, India

https://doi.org/10.56093/ijans.v95i8.158620

Keywords:

AMM, ADOPT, Diffusion, Dairy farmer, Milk fever, Milk yield

Abstract

Milk fever is a critical metabolic disorder in high-yielding dairy animals, causing significant production and economic losses. Anionic Mineral Mixture (AMM) has been identified as a promising intervention to prevent milk fever and enhance milk yield, justifying the need to assess its adoption potential among dairy farmers. This study applied the Adoption and Diffusion Outcome Prediction Tool (ADOPT) to predict the uptake of AMM in Haryana, India. Data were collected from 300 dairy farmers and 10 subject-matter specialists on 22 variables related to adoption behavior. The model predicted a peak adoption rate of 98% in six years, with 50% adoption achieved within 2.7 years. The findings highlight the strong potential of AMM adoption, driven by awareness programs and farmer readiness, though sustainability may be influenced by cost and access once subsidies are withdrawn. Strengthening extension activities, ensuring affordable supply, and continuous capacity building are suggested as the way forward to accelerate adoption and maximize benefits.

Downloads

Download data is not yet available.

References

Alcon F, Tapsuwan S, Martínez-Paz JM, Brouwer R and de Miguel MD. 2014. Forecasting deficit irrigation adoption using a mixed stakeholder assessment methodology. Technological Forecasting and Social Change 83:183–93.

Buragohain R and Kalita G. 2016. Milk fever: Prevention strategies with special emphasis on nutritional management. CAU Farm Magazine 6 (1): 41–43.

Cariappa AGA, Chandel BS, Sankhala G, Mani V, Ramadas S, Dixit AK and Meena BS. 2022. Estimation of economic losses due to milk fever and efficiency gains if prevented: evidence from Haryana, India. SSRN Electronic Journal [online].

A G Adeeth Cariappa, B S Chandel, Gopal Sankhala, Veena Mani, Sendhil R, A K Dixit and B S Meena. 2023. Anionic mineral mixture prevents milk fever and improves farmer income: evidence from a randomized controlled trial. Agricultural Economics Research Review 35(1): 19–36.

DeGaris PJ and Lean IJ. 2008. Milk fever in dairy cows: A review of pathophysiology and control principles. Veterinary Journal 176 (1): 58–69.

Department of Animal Husbandry and Dairying. 2020. Annual report 2019–20. Ministry of Fisheries, Animal Husbandry and Dairying, Government of India.

Dhehibi B, Aw-Hassan A, Ben Salah M, Al Raisi Y, Al Bousaidi I, Al Amri S and Al Sobahi S. 2018. Predicting farmers’ willingness to adopt liquid pollination and polycarbonate drying house technologies: A case study from the date palm growers in the Sultanate of Oman. New Medit 17 (1): 25–38.

Kassie M, Jaleta M, Shiferaw B, Mmbando F and Mekuria M. 2013. Adoption of interrelated sustainable agricultural practices in smallholder systems: evidence from rural Tanzania. Technological Forecasting and Social Change 80 (3): 525–40.

Kuehne G, Llewellyn R, Pannell DJ, Wilkinson R, Dolling P, Ouzman J and Ewing M. 2017. Predicting farmer uptake of new agricultural practices: A tool for research, extension and policy. Agricultural Systems 156:115–25.

Mani V. 2018. Anionic mineral mixture for reducing post-partum problems in cattle and buffaloes. In: Sharma R and Singh AK (Eds). Technologies available at NDRI for commercialization, pp. 69-70. ICAR-NDRI, Karnal.

Melendez P and Poock S. 2017. A dairy herd case investigation with very low dietary cation–anion difference in prepartum dairy cows. Frontiers in Nutrition 4: 26.

Ministry of Fisheries, Animal Husbandry and Dairying. 2019. Basic animal husbandry statistics 2019. Government of India. Oetzel GR and Miller BE. 2012. Effect of oral calcium bolus supplementation on early-lactation health and milk yield in commercial dairy herds. Journal of Dairy Science 95 (12):7051–65.

Reinhardt TA, Lippolis JD, McCluskey BJ, Goff JP and Horst RL. 2011. Prevalence of subclinical hypocalcemia in dairy herds. Veterinary Journal 188 (1): 122–24.

Schut M, Klerkx L, Rodenburg J, Kayeke J, Hinnou LC, Raboanarielina CM, Adegbola PY, van Ast A and Bastiaans L. 2015. RAAIS: Rapid appraisal of agricultural innovation systems (Part I). A diagnostic tool for integrated analysis of complex problems and innovation capacity. Agricultural Systems 132: 1–11.

Sendhil R, Singh S, Kumar R, Kumar S, Arora K, Kumar A, Khippal A, Goyal SK, Singh M, Chand R and Singh GP. 2022. Predicting farmer uptake of innovation on ‘Biofortified Wheat Variety’ for seed production – An application of the adoption and diffusion outcome prediction tool (ADOPT). Available at SSRN: https://ssrn.com/abstract=4198456, https://dx.doi. org/10.2139/ssrn.4198456

Thornton PK, Schuetz T, Förch W, Cramer L, Abreu D, Vermeulen S and Campbell BM. 2017. Responding to global change: A theory of change approach to making agricultural research for development outcome-based. Agricultural Systems 152: 145–53.