Agricultural Knowledge Management Unit (AKMU) Research Publications

Rajeev Ranjan Kumar, S. Vishnu Shankar, Ronit Jaiswal, Jaiprakash Bisen, Kapil Choudhary, V. Lavanya, Mrinmoy Ray & K. N. Singh (2025). Modelling Price Dynamics in Indian Potato Markets: A Comprehensive Econometric Approach, Potato Research/ Springer Nature, NA (NAAS rating: 8.30)
Rahul Chandel, Deeba Kamil, Amrender Kumar, Yashpal Taak and Anil Khar (2024). Morpho-cultural and molecular variability of Stemphylium vesicarium causing Stemphylium leaf blight in tropical onions, Heliyon, 10(20) (NAAS rating: 10.00)
M. N. Rudra Gouda, Sagar D, Kishor Gaikwad, Ratna Prabha, Amrender Kumar and Sabtharishi Subramanian (2024). Elucidation of ejaculatory bulb proteins in Bemisia tabaci Asia‑1 and Asia II‑1 and confirmation of their mating transfer via RNAi, Molecular Biology Reports, 51:861 (NAAS rating: 8.80)
Tarun kumar, Prameela Krishnan, Sona Kumar, Amrender Kumar and Anju Mahendru Singh (2024). Identification of the cultivars of the wheat crop from their seed images using deep learning: convolutional neural networks, Genetic Resources and Crop Evolution, 10(20) (NAAS rating: 10.00)
Rahul Chandel, Shrawan Singh, Amrender Kumar, Yashpal Taak and Anil Khar (2024). Genetic diversity of morphological, biochemical and mineral traits in Indian onion (Allium cepa) genotypes, Indian Journal of Agricultural Sciences , 94 (6), 632-637 (NAAS rating: 6.40)
G. Avinash, V. Ramasubramanian, Mrinmoy Ray, Ranjit Kumar Paul, Samarth Godara, G.H. Harish Nayak, Rajeev Ranjan Kumar B. Manjunatha, ,Shashi Dahiya,Mir Asif Iquebal (2024). Hidden Markov guided Deep Learning models for forecasting highly volatile agricultural commodity prices, Applied Soft Computing/Elsevier, 158 & 111557 (NAAS rating: 13.2)
Pooja Belwal, Manisha Mangal, Navinder Saini, Brij Bihari Sharma, Mahesh Rao, Amrender Kumar, M. C. Singh and Anil Khar (2023). Efect of genotype, media and stress treatments on gynogenesis efficiency in short‑day tropical Indian onion (Allium cepa L.), Plant Cell, Tissue and Organ Culture (PCTOC), 156, 14 (NAAS rating: 8.73)
Hira Singh, Mauro Lombardo, Abhishek Goyal, Amrender Kumar and Anil Khar (2023). Genotypic variation in Na, K and their ratio in 45 commercial cultivars of Indian tropical onion: A pressing need to reduce hypertension among the population, Front. Nutr.,, 10 (NAAS rating: 12.59)
Amrender Kumar, Nidhi Verma, K Veeranjaneyulu and P S Pandey (2022). Krishikosh: A new dimension of digital repository in agriculture, Indian Journal of Agricultural Sciences, 92(2), 58-63 (NAAS rating: 6.40)
Amrender Kumar, P.W. Nemade, Rakhee Sharma, R. K Tanwar, C. Chattopadhyay, S.S. Wanjari and T.H. Rathod (2018). Statistical forewarning models for sucking pests of cotton in Maharashtra, Journal of Agrometeorology, 20 (1), pp 62-65 (NAAS rating: 6.36)
Amrender Kumar, C. Chattopadhyay, K. N. Singh, S. Vennila and VUM Rao (2014). Trend analysis of climatic variables in Pigeonpea growing regions in India, Mausam, 65(2), pp 161-170 (NAAS rating: 6.64)
Amrender Kumar, C. Chattopadhyay, K. N. Singh, S. Vennila and VUM Rao (2014). Trend analysis of climatic variables in Pigeonpea growing regions in India, Mausam, 65(2), 161-170 (NAAS rating: 6.60)
Amrender Kumar, Tanuj Misra, Kamal Batra, Rakhee Sharma, A. K. Mishra, S. Vennila, R. K. Tanwar, N. Singh, Priyanka Wahi, R. Rajendran, D. K. Sidde GOWDA, P. S. Sarao, V. N. Jalgaonkar, S. K. Roy and C. Chattopadhyay (2016). Web enabled and weather based forewarning of yellow stem borer and leaf folder for different rice growing locations of India, Mausam, 67(4), pp 861-868 (NAAS rating: 6.64)
Amrender Kumar, B. K. Bhattacharya, Vinod Kumar, A. K. Jain, A. K. Mishra and C. Chattopadhyay (2016). Epidemiology and forecasting of insect-pests and diseases for value-added agro-advisory. Mausam, 67(1), pp 267-276 (NAAS rating: 6.64)
Mrinmoy Ray, Anil Rai, K.N. Singh, Ramasubramanian V. and Amrender Kumar (2017). Technology forecasting using time series intervention based trend impact analysis for wheat yield scenario in India, Technological Forecasting & Social Change, 118, May 2017, pp 128-133 (NAAS rating: 9.22)
Varsha Rana, N.R. Patel, C. Chattopadhyay and Amrender Kumar (2017). Development of forewarning model for brown plant hopper in rice using satellite and meteorological data. Journal of Agrometeorology, 19, pp 192-195 (NAAS rating: 6.36)
Irani Mukherjee, T.K. Das, Amrender Kumar, Bipasa Sarkar and K.K. Sharma (2015). Behavior and bioefficacy of tribenuron-methyl in wheat (Triticum astevum L.) under irrigated agro-ecosystem in India. Environmental Monitoring and Assessment, 187(10), pp 610(1-9) (NAAS rating: 8.51)
Pankaj Sharma, P. D. Meena, Amrender Kumar, Vinod Kumar, and D. Singh (2015). Forewarning models for Sclerotinia rot (Sclerotinia sclerotiorum) in Indian mustard (Brassica juncea L.) Phytoparasitica 43, 509-516 (NAAS rating: 7.44)
Ritika and Vikas kumar , An ensemble based stacking approach for Network Intrusion Detection System, Journal of Emerging Technologies and Innovative Research,Volume 6, Issue 6, 2019
Dheeraj, A., Nigam, S., Begam, S., Naha, S., Devi, S. M., Chaurasia, H.S, Kumar, D., Ritika, Soam, S.K., Rao, N.S., Arora, A., Sreekanth, P.D. and Kumar, V.V.S. (2020). Role of Artificial Intelligence (AI) and Internet of Things (IoT) in mitigating climate change. In: Ch. Srinivasarao et al., (Eds). Climate Change and Indian Agriculture: Challenges and Adaptation Strategies, ICAR-National Academy of Agricultural Research Management, Hyderabad, Telangana, India. Pp-465-472.
Ray, M.*, Rai A., Singh, K. N., V., Ramasubramanian and Kumar, A. (2017).Technology forecasting using time series intervention based trend impact analysis for wheat yield scenario in India. Technological Forecasting and Social Change, 118,128-133. [NAAS:18.9]
Ray, M.*, V., Ramasubramanian, Kumar, A. and Rai, A. (2014). Application of time series intervention modelling for modelling and forecasting cotton yield. Statistics and Applications, 12 (1&2), 61-70. [NAAS:6.3]
Kumar, R.R., Shankar, S.V., Jaiswal, R., Ray, M.*, Budhlakoti, N., & Singh, K .N.(2025). Advances in Deep Learning for Medical Image Analysis: A Comprehensive Investigation. Journal of Statistical Theory and Practice, 19, Article 9. https://doi.org/10.1007/s42519-024-00422-2 [NAAS:6.60]
Nayak, G.H.H., Alam, M.W., Avinash, G., Kumar, R.R., Ray, M.*, Barman, S., Singh, K.N., Naik, B.S., Alam, N.M., Pal, P., Rathod, S., & Bisen, J. (2024). Transformer based deep learning architecture for time series forecasting. Software Impacts, 22, 100716. https://doi.org/10.1016/j.simpa.2024.100716 [NAAS:7.30]
Nayak, G.H.H., Alam, M.W., Singh, K.N., Avinash, G., Kumar, R.R., Ray, M.*, &Deb, C.K. (2024). Exogenous variable driven deep learning models for improved price forecasting of TOP crops in India. Scientific Reports, 14, 17203. https://doi.org/10.1038/s41598-024-68040-3 [NAAS:9.80]
Ray, M.*, Rai, A., Singh, K. N. and V., Ramasubramanian. (2017).Modeling and forecasting of hybrid rice yield using a grey model improved by the genetic algorithm. International Journal of Agricultural and Statistical Sciences. 13 (2), 563-566. [NAAS:6.30]
Ray, M.*, Singh, K. N., Ramasubramanian, V., Paul, R. K., Mukherjee, A. and Rathod, S. (2020). Integration of Wavelet Transform with ANN and WNN for Time Series Forecasting: an Application to Indian Monsoon Rainfall. National Academy Science Letter. 43, 509-513. [NAAS:7.20]
Saha, A., Singh, K. N., Ray, M.* and Rathod, S. (2022). Fuzzy rule–based weighted space–time autoregressive moving average models for temperature forecasting.Theoretical and Applied Climatology, 150, 1321-1335. [NAAS:8.80]
Ray, M.*, Ramasubramanian, V., Singh, K.N. et al. (2022). Technology Forecasting for Envisioning Bt Technology Scenario in Indian Agriculture. Agricultural Research, 11, 747–757. https://doi.org/10.1007/s40003-022-00612-z [NAAS:7.40]
Harish Nayak G. H., Alam, W., Singh, K.N. Avinash, G., Ray, M.* and Kumar, R.R. (2024) Modelling Monthly Rainfall of India through Transformer-based Deep Learning Architecture, Modeling Earth Systems and Environment, https://doi.org/10.1007/s40808-023-01944-7 [NAAS:8.70]