| 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), pp 158-63 (NAAS rating: 6.37) |
| 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, 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, 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. |
| Singh DP, Bisen MS, Prabha R, Maurya S, Yerasu SR, Shukla R, Tiwari JK, Chaturvedi KK, Farooqi MS, Srivastava S, Rai A, Sarma BK, Rai N, Singh PM, Behera TK, Farag MA. Untargeted Metabolomics of Alternaria solani-Challenged Wild Tomato Species Solanum cheesmaniae Revealed Key Metabolite Biomarkers and Insight into Altered Metabolic Pathways. Metabolites. 2023; 13(5):585. https://doi.org/10.3390/metabo13050585 |
| Prabha R, Singh DP, Sinha S, Ahmad K, Rai A. 2016. Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes. Marine Genomics (Elsevier). 32:31-39. |
| Prabha R, Singh DP, Gupta SK, Rai A. 2014. Whole genome phylogeny of Prochlorococcus marinus group of cyanobacteria: genome alignment and overlapping gene approach. Interdisciplinary Sciences: Computational Life Sciences (Springer), 6:1–9. |
| Singh DP, Singh V, Shukla R, Sahu P, Prabha R, Gupta A, Sarma BK, Gupta VK. Stage-dependent concomitant microbial fortification improves soil nutrient status, plant growth, antioxidative defense system and gene expression in rice. Microbiological Research. 2020. Volume 239, 126538 |
| Singh DP, Singh V, Gupta VK, Shukla R, Prabha R, Sarma BK, Patel JS. Microbial inoculation in rice regulates antioxidative reactions and defense related genes to mitigate drought stress. Scientific Reports 2020, 10(1):1-17. |
| Prabha R, Singh DP, Gupta S, Gupta VK, El-Enshasy HA, Verma MK. Rhizosphere metagenomics of Paspalum scrobiculatum L. (Kodo millet) reveals rhizobiome multifunctionalities. Microorganisms 2019, 7:608. |
| Prabha R, Singh DP (2019) Cyanobacterial phylogenetic analysis based on phylogenomics approaches render evolutionary diversification and adaptation: an overview of representative orders. 3 Biotech, 9(3), 87. |
| Singh DP#, Prabha R#, Gupta VK, Verma MK (#Joint First Authors). 2018. Metatranscriptome analysis deciphers multifunctional genes and enzymes linked with the degradation of aromatic compounds and pesticides in the wheat rhizosphere. Frontiers in Microbiology, 9:1331. |
| Prabha R, Singh DP, Ahmad K, Kumar SPJ, Kumar P. 2019. Subtractive genomics approach for identification of putative antimicrobial targets in Xanthomonas oryzae pv. oryzae KACC10331. Archives of Phytopathology and Plant Protection, 53 (7-8): 863-872. |
| Prabha R, Singh DP, Rai A (2015) StressMicrobesInfo: Database of Microorganisms Responsive to Stress Conditions. Interdiscip Sci. (Springer) 8(3):203-8 |