N U Singh

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.

Ginger contributes substantially to the agricultural sector in Meghalaya, yet comprehensive forecasting analyses that integrate both traditional and volatility-sensitive time series approaches to study its price movements are still scarce. In this study, we explore common time series yet very powerful forecast models, namely the autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and ARIMA with exogenous inputs (ARIMAX), along with autoregressive conditional heteroscedasticity (ARCH) and generalized autoregressive conditional heteroscedasticity (GARCH) models, to forecast the monthly price of ginger in Meghalaya. During the estimation process, attention was given to the intrinsic forecasting strengths and limitations of these models, as well as to essential time series diagnostics, including stationarity, parsimony and overfitting. The discussion in this study is based on the forecast results obtained from a real-time monthly price dataset spanning 10 years. While fitting the models to the dataset, special care was taken to select the most parsimonious model. To evaluate forecast accuracy and compare the performance of the different models applied to the time series of monthly ginger prices, we used seven forecast performance measures: ME (mean error), RMSE (root mean square error), MAE (mean absolute error), MAPE (mean absolute percentage error), MASE (mean absolute scaled error), AIC (Akaike information criterion) and BIC (Bayesian information criterion). The GARCH (1,1) model outperformed the others, yielding the lowest MAE (1,212.28), MASE (0.2817) and a high persistence in volatility (β₁ = 0.99772). The average price during the study period was ₹4400.47. The forecasts indicated a decline in prices from ₹11910 in March 2024 to ₹10938 in July 2024.

The marketing effectiveness of tomato and cabbage in the Ukhrul District of Manipur was evaluated using Acharya’s modified marketing efficiency approach, with a focus on identifying the key factors influencing marketing efficiency. The economic viability of tomato and cabbage production in the state was also analyzed. The per quintal production costs of tomatoes and cabbage were found to be Rs. 219.36 and Rs. 249.31 respectively, with benefit-cost ratios of 5.76 and 2.30 respectively. Due to the perishable nature of tomatoes and cabbage, combined with limited processing and storage infrastructure, insufficient knowledge among stakeholders and the presence of numerous intermediaries, significant price fluctuations were observed, which negatively impacted both the farmers and consumers. Most tomatoes were sold through Channel 1 (Producer-Retailer-Consumer), while cabbage was mainly marketed via Channel 3 (Producer-Wholesaler-Retailer-Consumer). Marketing costs and margins varied with the length of the distribution channel; more extended channels led to higher costs and wider price spreads. As the number of intermediaries increased, both the consumer price and marketing margin rose, reducing overall marketing efficiency. Factors such as transportation, market price, marketing margin and volume significantly influenced efficiency. The highest efficiency was found in the direct channel from farmers to retailers to consumers. Developing a dedicated farmers' market model with essential infrastructure, such as storage, weighing systems, water, electricity and shelter, could streamline the supply chain, reduce costs and improve overall market performance by minimizing intermediary roles.