Dr Md Yeasin


Dr Md Yeasin






1.      Gurung, B., Singh, K. N., Shekhawat, R. S., and Yeasin, M. (2018). An insight into technology diffusion of tractor through Weibull growth model. Journal of Applied Statistics45(4): 682-696.


2.      Lama, A., Singh, K.N., Sinha, K., Shekhawat, R.S., Yeasin, M. and Gurung, B. (2018). Modelling transmission of potato price volatility in West Bengal markets: MGARCH approach. RASHI, 3(1): 33-38.


3.      Yeasin, M., Singh, K.N., Lama, A. and Paul, R. K.  (2020). Modelling Volatility Influenced by Exogenous Factors using an Improved GARCH-X Model. Journal of the Indian Society of Agricultural Statistics, 74(3): 209–216.


4.      Yeasin, M., Singh, K. N., Lama, A., and Gurung, B. (2021). Improved weather indices-based Bayesian regression model for forecasting crop yield. Mausam, 72(4): 879-886.


5.      Ghosh, S., Das, T. K., Shivay, Y. S., Bhatia, A., Biswas, D. R., Bandyopadhyay, K. K., Sudhishri, S., Yeasin, M., Raj, R., Sen, S. and Rathi, N. (2021). Conservation agriculture effects on weed dynamics and maize productivity in maize- wheat- greengram system in north-western Indo-Gangetic Plains of India. Indian Journal of Weed Science, 53(3):244–251.


6.      Yadav, D.K., Kaushik, P., Tripathi, K.P., Rana, V.S., Yeasin, M., Kamil, D., Pankaj, Khatri, D. and Shakil, N. A., (2022). Bioefficacy evaluation of ferrocenyl chalcones against Meloidogyne incognita and Sclerotium rolfsii infestation in tomato. Journal of Environmental Science and Health, Part B, 57(3): 192-200. DOI: 10.1080/03601234.2022.2042154


7.      Yeasin, M., Haldar, D., Kumar, S., Paul, R. K. and Ghosh, S. (2022). Machine Learning Techniques for Phenology Assessment of Sugarcane Using Conjunctive SAR and Optical Data. Remote Sensing, 4(14): 32-49. doi:10.3390/rs14143249


8.      Paul, R. K., Yeasin, M., Kumar, P., Kumar, P., Balasubramanian, M., Roy, H. S., Paul, A. K. and Gupta, A. (2022). Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India. PLOS ONE, 17(7). doi:10.1371/journal.pone.0270553


9.      Paul, R. K., Vennila, S., Yeasin, M., Yadav, S. K., Nisar, S., Paul, A. K., Gupta, A., Malathi, S., Jyosthna, M. K., Kavitha, Z. and Mathukumalli, S. R. (2022). Wavelet Decomposition and Machine Learning Technique for Predicting Occurrence of Spiders in Pigeon Pea. Agronomy,2(6): 14-29.  doi:10.3390/agronomy12061429


10.  Ghosh, Sonaka, Das, T. K., Shivay, Y. S., Bhatia, A., Sudhishri, S., and Yeasin, M. (2022). Impact of Conservation Agriculture on Wheat Growth, Productivity and Nutrient Uptake in Maize-Wheat-Mungbean System. International Journal of Bio-resource and Stress Management, 13(4): 422–429. doi:10.23910/1.2022.2806


11.  Ghosh, S., Das, T. K., Shivay, Y. S., Bandyopadhyay, K. K., Bhatia, A., and Yeasin, M. (2022). Weed interference and wheat productivity in a conservation agriculture-based maize-wheat-mungbean system. Journal of Crop and Weed, 18(1): 111–119.


12.  Roy, H. S., Paul, A. K., Paul, R. K., Singh, R. K., Yeasin, M. and Kumar, P. (2022). Estimation of Heritability of Karan Fries Cattle using Bayesian Procedure. The Indian Journal of Animal Sciences92(5): 645–648


13.  Paul, R. K., Mitra, D., Roy, H.S., Paul, A. K. and Yeasin, M. (2022). Forecasting price of Indian mustard (Brassica juncea) using long memory time series model incorporating exogenous variable. Indian Journal of Agricultural Sciences, 92 (7): 825–30.


14.  Kumar, S. S., Mir, S. A., Wani, O. A., Babu, S., Yeasin, M., Bhat, M. A., Hussain, N., Ali Wani A. I., Kumar, R., Yadav, D., and Dar, S. R. (2022). Land-use systems regulate carbon geochemistry in the temperate Himalayas, India. Journal of Environmental Management, 320, 115811.


15.  Paul, R. K., Yeasin, M.* and Paul, A. K. (2022). The volatility spillover of potato prices in different markets of India. Current Science, 123(3): 482-487.


16.  Ghosh, S., Das, T. K., Shivay, Y. S., Bandyopadhyay, K. K., Sudhishri, S., Bhatia, A., Biswas, D. R., Yeasin M., Ghosh, S. (2022). Weeds response and control efficiency, greengram productivity and resource-use efficiency under a conservation agriculture-based maize-wheat-greengram system. Indian Journal of Weed Science,54(2): 157–164.



Yeasin M., Dhandapani A., and Ravichandran S. (2021). Artificial Intelligence in Agriculture. In: Ch. Srinivasarao et al., (Eds). Agricultural Research, Technology and Policy: Innovations and Advances, ICAR-National Academy of Agricultural Research Management (NAARM), Hyderabad, Telangana, India, 291-306.


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