Adoption and Impact of Wheat variety HD 3086: An analysis using structural equation modeling

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  • NEERU BHOOSHAN ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • AMARJEET SINGH ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • AKRITI SHARMA ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India


Adoption, Research Centre, SEM model, Wheat variety HD 3086, Yield


Varietal development plays a crucial role in improving the overall yield of a crop and the impact assessment of a particular variety is essential to support this statement. Present study was carried out in North-Western Indo-Gangetic Plains (Punjab, Haryana and Western Uttar Pradesh) in India during 2017–18 to observe the response on the yield with the adoption of newly developed yellow rust resistant wheat variety HD 3086. The Structural Equation Model (SEM) was used to establish a relationship between the rate of adoption and factors affecting the same. Households (1000) were surveyed through random sampling for the study. Punjab was found to have the highest adoption rate amongst the 3 states followed by Haryana. This study has observed an increasing trend in coverage of farm area under HD 3086 in Punjab and Haryana. However, in Uttar Pradesh creating awareness among the seed companies and Krishi Vigyan Kendra (KVK) centres was found imperative for the multiplication of HD 3086.


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Agricultural Statistics at Glance. 2016. Govt. of India, Ministry of Agricultural & Farmer Welfare, Department of Agricultural, cooperation and Farmers Welfare, Directorate of Economics and Statistics.

AHDB. 2016. Cereal and oilseeds. Wheat disease management guide. February, P.14.

Dadi L, Burton M and Ozanne A. 2004. Duration Analysis of Technological Adoption in Ethiopian Agriculture. Journal of Agricultural Economics 55(3): 613–31.

Efisue A, Tongoona P, Derera J, Langyintuo A, Laing M and Ubi B. Ubi. 2008. Farmers’ perceptions on rice varieties in Sikasso region of Mali and their implications for rice breeding. Journal of Agronomy and Crop Science 194(5): 393–400.

Franklin Simtowe, Menale Kassie and Aliou Diagne.2011. Determinants of Agricultural Technology Adoption: The Case of Improved Pigeonpea Varieties in Tanzania. Quarterly. Journal of International Agriculture 4: 325–45.

Hanan Suliman Mohamed and Samar Abdalla. 2014. Impact Assessment of Improved Wheat Production Package in Sudan, Agricultural Research Corporation, Agricultural Economics and Policy Research Centre (AEPRC) Shambat. Sudan.

Maertens A and Barrett C B. 2013. Measuring Social Networks' Effect on Agricultural Technology Adoption. American Journal of Agricultural Economics 95(2): 353–59.

Mazid A, Amegbeto K N, Keser M, Morgounov A, Peker K, Bagc A, Akin M, Kucukcongar M, Kan M, Karabak S, Semerci A, Altikat A and Yaktubay S. 2009. Adoption and impacts of improved winter and spring wheat varieties in Turkey. Aleppo, Syria, International Center for Agricultural Research in the Dry Areas (ICARDA).

Smale M, Singh J, Di Falco S and Zambrano P. 2008. Wheat breeding, productivity and slow variety change: evidence from the Punjab of India after the Green Revolution. Australian Journal of Agricultural and Resource Economics 52(4): 419–32.

Thapa G, Otsuka K and Barker R. 1992. Effect of modern rice varieties and irrigation on household income distribution in Nepalese villages. Agricultural Economics 7(3–4). 245–65.









How to Cite

BHOOSHAN, N., SINGH, A., & SHARMA, A. (2022). Adoption and Impact of Wheat variety HD 3086: An analysis using structural equation modeling. The Indian Journal of Agricultural Sciences, 92(3), 377-381.