To understand the impact of climate change on water resources, this research investigates long-term rainfall trends and anomalies across Northeastern India (NEI), covering Assam and Meghalaya (A&M); Nagaland, Manipur, Mizoram, and Tripura (NMMT); and Sub-Himalayan West Bengal and Sikkim (SHWB&S) using different statistical tests including innovative trend analysis (ITA). The study scrutinizes 146 years of rainfall statistics, trend analyses, variability, and probability distribution changes to comprehend its implications. Furthermore, the change in the assured rainfall probabilities was also worked out to understand the impact on rainfed agriculture of Northeastern India. Comparative analysis between all India (AI) and NEI reveals that NEI receives nearly double the annual rainfall compared to AI (2051 mm and 1086 mm, respectively). Despite resembling broad rainfall patterns, NEI displays intra-regional variations, underscoring the necessity for region-specific adaptation strategies. Statistical characteristics like the coefficient of skewness (CS) and coefficient of kurtosis indicate skewed rainfall distributions, notably during the winter seasons in NMMT (CS~1.6) and SHWB&S (CS~1.5). Trend analyses reveal declining rainfall trends, especially conspicuous in NEI’s winter (−1.88) and monsoon (−2.9) seasons, where the rate of decrease was higher in the last three decades. The return periods of assured rainfall at 50% and 75% probability levels also increased sharply during the winter and monsoon seasons by over 30% during the recent half, posing challenges for rainfed upland hill farming. Furthermore, this study highlights increasing variability and negative anomalies in monsoon rainfall over NEI, exacerbating decreasing rainfall trends and significantly impacting agricultural productivity. These findings underscore the urgency for adaptive measures tailored to evolving rainfall patterns, ensuring sustainable agricultural practices and efficient water resource management.

A pilot study was carried out to find out the seroprevalence of Porcine circovirus 2 (PCV2), classical swine fever virus (CSFV), and Porcine respiratory and reproductive syndrome virus (PRRS) in pig population of Meghalaya

This study analyzed the impact of weather variables on insect pest dynamics and their diversity in the radish ecosystem through field experiments conducted for two years at a locality in the eastern Himalayas. The relationship with weather variables was studied with six different dates of sowing, and diversity was assessed using standard indices. Various organic management options were also evaluated. Results revealed that temperature had a positive impact, whereas relative humidity and rainfall negatively affected the population of insect pests. The radish ecosystem harbors diverse insect species, including natural enemies, with higher species richness (4.8–5.2) and lower year-to-year variability. Organic management strategies such as neem oil, Beauveria bassiana, and Metarhizium robertsii demonstrated good efficacy against flea beetles without compromising yield, resulting in 39.76%, 39.39%, and 38.71% pest reduction over control, respectively. These biopesticides also recorded less than half to one-fourth reduction in natural predators like coccinellids compared to cypermethrin, a chemical pesticide (74%). The study suggests that, under projected climate change with higher temperatures, pest populations are assumed to increase. Considering the insect diversity of the eastern Himalayas, organic management strategies will be an adaptation strategy to conserve biodiversity while ensuring environment-friendly pest management.

The present study was conducted to assess the genetic diversity, association ship and identify stable lines of king chilli (Capsicum chinense Jacq.) at Horticulture Research Farm, ICAR Research Complex for NEH Region for three consecutive years (2021, 2022 and 2023) keeping in view the vast genetic diversity of king chilli present in the North Eastern Hill Region of India which are yet to explore to its fullest potential. The results of the study reveal that for the economic trait fruit yield per plant, the highest value was recorded in RCML5 (1003.40g) followed by RCML1 (949.85g) and RCNL4 (898.46g). Similarly, for quality parameters the highest dry matter (%), ascorbic acid content (mg/100g), total flavonoid (mg QE/g) and capsaicin (%) was recorded in RCML6 (19.78 %), RCMP6 (693.41 mg/100g), RCNL-1 (5.12 mg QE/g) and RCML16 (5.90 %), respectively. High heritability (˃60 %) coupled with high GA (˃20 %) was observed for desirable traits such as fruit yield per plant, no. of fruits per plant, no. of fruits per cluster and average fruit weight. Among the quality traits, ascorbic acid content exhibits high heritability (˃60 %) and high GA (˃20 %). This indicates the presence of additive gene action and the potential response of these traits towards selection. Cluster analysis revealed that cluster 6th, comprising of 9 accessions, was the largest, while the largest inter-cluster distance based on the Mahalnobis Euclidean Distance was recorded between cluster 8th and 6th (77.28). The Principal Component Analysis revealed that 7 PCs with eigenvalues more than 1 contribute 84.53 % of the total variability. Plant spread (E to W), no. of fruits per plant, ascorbic acid content and capsaicin content were depicted as the major predictors of total variability. The present study identifies accessions RCML5, RCML1 and RCNL4 as the best performers for fruit yield and most of its related traits. It exhibits the potential of giving higher yield in future improvement programmes, while accessions viz., RCML16, RCML5 and RCML10 are promising for capsaicin content. Based on stability analysis accession RCNL1, a moderate yielder and mid-maturity with average capsaicin content, was stable across environments. These identified accessions can served as a gene bank for future crop improvement programme in king chilli.

Maize is a staple food grain in the eastern Himalayas of India, traditionally grown only during the Kharif seasons using local cultivars. The cultivation of Rabi maize is a relatively new concept in the hills; however, favourable agro-climatic conditions offer potential for higher economic returns and proper utilisation of paddy fallow. A study was conducted in the adopted cluster villages (05 villages), Ri-Bhoi district, Meghalaya, covering a 15-hectare area, using a participatory approach to investigate the adoption of improved maize cultivars during the Rabi season. The results showed that DA 61 A and RCM 75 had promising growth and yield performances (5.2-5.8 green cob MT/ha). Prior to intervention, all the respondents grew only local varieties, and the growing seasons were mainly Kharif (76.67 %) and Zaid (23.33 %), with none cultivating during the Rabi season. In the post-intervention period, most respondents partially adopted Rabi maize cultivation technology, with a 60.0 % overall adoption level. Partial adoption was mainly due to a preference for high-value vegetables (ranked first at 100 %) and non-availability of varieties (96.67 %). The highest gross return, net return and benefit-cost ratio were recorded in improved cultivars (DA 61A and RCM 76). A negative correlation (r = -0.547*) was observed between disease incidence and Rabi maize yield. Adoption of Rabi maize cultivars shows promise for enhancing the socio-economic status and livelihoods of participating farmers.

This study examines the temporal variations in rainfall and temperature over the Lepa Rada district of Arunachal Pradesh from 1983 to 2021. Using both parametric (Linear Regression) and non-parametric (Mann-Kendall and Sen's slope) methods, significant climatic trends were identified. The analysis revealed a statistically significant declining trend in winter rainfall, with linear regression indicating a decrease of 2.809 mm/year, corroborated by significant Mann-Kendall’s Z statistic and Sen’s slope estimates. Temperature trends showed a significant increase in maximum temperatures across all seasons(spring@ 0.109 °C/year; summer @0.103 °C/year; autumn @0.113 °C/year and winter @0.139 °C/year), with annual rates of increase observed at 0.115°C/year (p<0.01) through linear regression. Similarly, the Mann-Kendall test confirmed these findings, with significant Z values across all seasons. In contrast, minimum temperatures showed a significant declining trend during spring and winter, suggesting increased coldness over time. These trends hold significant implications for agriculture and environmental planning in the region. The decline in winter rainfall and the rise in maximum temperatures could adversely affect crop yields and water resources, emphasizing the need for adaptive agricultural practices and efficient water management strategies. Additionally, the increase in coldness during winter and spring suggests the importance of developing climate-resilient crops and improving forecasting systems to help farmers better prepare for changing weather conditions.