National Academy of Agricultural Research Management

Agricultural marketing in India has undergone several reforms to improve efficiency, transparency and price realization for farmers. Despite the establishment of regulated markets under the Agricultural Produce Market Committee (APMC) system, farmers continued to face problems such as limited competition, lack of transparency and dependence on intermediaries. To address these issues, the Government of India launched the electronic National Agriculture Market (e-NAM) in 2016 to integrate Agricultural Produce Market Committees (APMCs) across the country through a unified online trading platform. The present study examines the progress of e-trading in Telangana and identifies the constraints faced by farmers in participating through the e-NAM platform. Both primary and secondary data were used for the study. Secondary data relating to stakeholder participation and commodity-wise trade were collected for the period 2016-17 to 2023-24 from the e-NAM portal and the Department of Agricultural Marketing, Telangana. Primary data were collected from 100 farmers across five selected e-NAM markets using a structured interview schedule. The data were analysed using descriptive statistics, Compound Annual Growth Rate (CAGR) and the Garrett ranking technique. The results revealed that out of 197 regulated markets in Telangana, only 57 markets (28.93%) have been integrated under e-NAM. The platform has registered 18.23 lakh farmers, 6,371 traders, 5,161 commission agents and 137 Farmer Producer Organizations (FPOs). From 2016-17 to 2023-24, a total of 64.68 lakh tonnes of commodities valued in Rs 23,637.6 crore were traded through e-NAM. Commodity-wise analysis shows that paddy was found to be high in traded volume, whereas turmeric, chilli and cotton account for a higher share in trade value. The compound annual growth rate of the value of trade was positive and significant (8.69%). Inter-mandi trade was more active compared to interstate trade, which remained limited. The study also identified lack of digital literacy, inadequate understanding of e-NAM procedures and dependence on commission agents as the major constraints faced by farmers. The findings suggest that strengthening digital awareness, improving infrastructure and expanding market integration are essential for enhancing the effectiveness of the e-NAM platform in Telangana.

Agriculture plays a vital role in the economy of Andhra Pradesh, contributing significantly to food security, employment generation, and rural livelihoods, with diverse agro-climatic conditions supporting a wide range of crops. However, increasing climatic variability, market fluctuations, and structural changes in cropping patterns necessitate systematic time series analysis to understand production dynamics and generate reliable forecasts for informed agricultural planning. This study conducts a comprehensive time series (TS) analysis and forecasting of major crops in Andhra Pradesh, a key agricultural state in India. Focusing on the core crop groups of cereals, millets, pulses, and oilseeds, the research analyzes long-term historical data on area, production, and yield (1975-2023). The analysis covers cereals, millets, pulses, and oilseeds, which together account for most of the state’s cultivated area and food output. Polynomial regression models are employed to identify structural growth patterns, followed by ARIMA models to generate five-year production forecasts. Stationarity testing and model diagnostics were conducted to ensure robust model specification, and forecast accuracy was evaluated using standard error measures. The results reveal significant heterogeneity in the growth patterns and predictability across crop groups. The results reveal significant heterogeneity in growth dynamics and predictability across crop groups. Rice exhibits a strong non-linear upward trend in production (R² = 0.963), driven largely by sustained yield improvements (R² = 0.972), and demonstrates high forecasting accuracy (MAPE = 6.28%), indicating a stable and predictable production system. Millets display pronounced non-linear fluctuations in cultivated area (R² ≈ 0.97), yet ragi production shows relatively strong forecast reliability (MAPE = 11.16%), despite their predominantly rainfed nature. In contrast, pulses and oilseeds exhibit persistent non-stationarity and higher forecast errors (MAPE ranging from 14–20%), reflecting greater sensitivity to climatic variability and market shocks. The study concludes that agricultural planning in Andhra Pradesh requires crop-specific, evidence-based strategies. The findings advocate for continued investment in productivity-enhancing technologies for stable cereals, targeted support for climate-resilient practices in millets, and robust policy interventions, including improved irrigation, varietal adoption, and market support to mitigate volatility in pulses and oilseeds. The forecasts (2024–2028) provide practical guidance for production planning, procurement decisions, price stabilization, and climate-resilient agricultural policy in the state. The findings emphasize the need for crop-specific, evidence-based interventions, including productivity-enhancing technologies for cereals, climate adaptation support for millets, and improved irrigation, varietal innovation, and market mechanisms for pulses and oilseeds. By combining structural trend analysis with ARIMA forecasting, the study offers an empirically grounded framework for regional crop predictability and strengthens the agricultural forecasting literature.

Extension personnel serve as vital intermediaries between research institutions and farming communities, and understanding the scientific production surrounding their training, capacity-building, and performance is essential for improving agricultural outcomes. The study applied the PRISMA methodology for a systematic literature review and employed R-studio for bibliometric analysis to examine global research trends on the capacity management of extension personnel, with particular attention to their role in agricultural development and knowledge dissemination. The study examined the literature published between 2020 and 2025. Well-screened data were obtained from the Scopus database with inclusion as well as exclusion criteria results of 65 relevant studies being reviewed. The annual scientific production analysis indicates fluctuating research activity, with a notable peak in 2021 followed by a gradual decline. This suggests that while scholarly interest in extension capacity remains significant, research may be shifting toward more specialized or applied approaches. Citation analysis reveals Ghana and Belgium as the most influential contributors, followed by the United States, South Africa, India, and Nigeria. This distribution highlights both developed and developing countries as key drivers of discourse, reflecting the global recognition of extension services in addressing agricultural and climate challenges. Keyword and thematic analyses further highlight “capacity building,” “adaptation,” and “sustainability” as central concepts, reinforcing the relevance of professional training and institutional support. Overall, the findings demonstrate that strengthening extension personnel capacity is critical to bridging knowledge gaps, enhancing farmer decision-making, and fostering sustainable agricultural development. Future research should emphasize cross-country collaboration, context-specific training, and innovative extension strategies to meet evolving global challenges.

Present study was conducted using 250 individuals of F2 population derived from a cross between pre harvest sprouting tolerance genotype PUSA M 19111 and a susceptible genotype LGG 668 to analyze inheritance pattern and gene action of PHS traits in greengram. Sixteen traits pertaining to pre-harvest sprouting (PHS) were studied to determine their distribution patterns. The inheritance studies through chi square analysis revealed that PHS tolerance was found to be predominantly governed by complementary gene action. Further the associated traits namely, water imbibition by seeds and pods (%), hard seeds (%), hard seed (%) in pods, epicuticular wax content, alpha amylase activity (at harvest, 24 hours, 48 hours and 72 hours after germination), pod length, pod beak length, pod wall thickness, surface area, and pre-harvest sprouting (%), exhibited positive skewness with platykurtic distribution. This suggests the presence of complementary gene action, with necessary stringent selection for rapid genetic gain due to the involvement of numerous genes. Conversely, fresh seed germination (%) and pod diameter (mm) displayed negative skewness and platykurtic distribution, indicating the influence of multiple genes with duplicate epistasis interaction. In these cases, mild selection pressure may be sufficient to achieve relatively quick genetic improvement.

India’s changing climatic pattern has negatively impacted its agriculture-dependent rural economy, particularly in climatically vulnerable regions. State and national assessments have identified Jharkhand’s high climate variability and district-level vulnerability, which impacts agriculture, livestock, and livelihoods. New models can improve micro-level risk mapping to inform targeted adaptation and policy. A vulnerability index comprising Exposure, Sensitivity, and Adaptive Capacity indicators relevant to agriculture and dairy sectors was developed by normalization, followed by PCA for assigning weights to each indicator. Later, the districts of Jharkhand were categorized into high, moderate, and low vulnerability based on their Index scores. The highest exposure in the Vulnerability index was in Garhwa (0.617) and the lowest in East Singhbhum (0.176). The highest sensitivity was found in Latehar (0.695) and the lowest in Ranchi (0.281). Giridih (0.615) had the highest adaptive capacity and Lowest in Koderma (0.122). Latehar (0.967), followed by Chatra (0.907) , had highest vulnerability scores due to highest exposure and sensitivity with low to moderate adaptive capacity. District-level vulnerability mapping indicated that eight districts fell into the highly vulnerable category and ten into the moderate category . Policymakers may consider expanding micro-irrigation networks, raising awareness of climate change and incorporating livelihood diversification while formulating developmental projects.

Efficient nitrogen management is critical to improving maize (Zea mays L.) productivity and sustainability under rainfed conditions, where excessive or untimely N use can result in environmental degradation and low nitrogen use efficiency (NUE). Two years of field studies were conducted during consecutive Rabi seasons (2017-18 and 2018-19) at the wetland Farm of S.V. Agricultural College, Tirupati, to calibrate the lead colour chart (LCC) for increasing grain yield, NUE and nutrient uptake under varied planting densities. The study intended to establish threshold leaf greenness values as practical guides for in-season, need based nitrogen top dressing in maize. A split-split plot design was used with three planting densities (66666, 83333 and 111111 plants ha-1), three nitrogen levels (30, 35 and 40 kg N ha-1) and three LCC thresholds (4, 4.5 and 5). Results showed that highest planting density (111111 plants ha-1) combined with 40 kg N ha-1 applied in splits based on LCC 5 significantly improved plant growth parameters, chlorophyll content, dry matter accumulation and kernel yield (5.36 t ha-1), along with enhanced nitrogen uptake (114.1 kg ha-1) and NUE (31.4 kg grain per kg N). Regression analysis revealed that dry weight (R² = 0.96), LAI (R² = 0.84) and NUE (R² = 0.70) were the strongest predictors of yield. LCC based nitrogen scheduling synchronized N supply with crop demand, minimized losses and improved soil N balance. These findings validate that LCC is an effective, ow cost tool for enhancing maize productivity and nutrient efficient under rainfed conditions.

ABSTRACT The Shoe Dhoni fisherfolk community exemplifies a distinctive and resilient livelihood system centered around indigenous, shoe-shaped fishing crafts known as “Shoe Dhoni,” which serve as both mobile homes and tools for traditional fishing practices, such as shell collection. This research employs a case study approach with an ex post facto design, followed by a enumeration method, using mixed methods to investigate the socio-economic dynamics, historical evolution, and current challenges of the Shoe Dhoni fisherfolk in the Godavari Estuary, Andhra Pradesh, India. The study revealed that currently, 63 families maintain this heritage, living on 63 boats and facing mounting challenges from environmental changes, modernisation, and diminishing fishery resources that threaten their economic stability and way of life. Their unique adaptation to aquatic life, primarily reliant on bivalve and gastropod fishing, offers insights into the community’s resilience, socio-economic struggles, and strategies for sustaining their traditional livelihoods amidst changing conditions. The study results indicate that policy directions must focus on ensuring the cultural preservation and socio-economic resilience of heritage communities, such as the Shoe Dhoni fisherfolk in the Godavari Estuary, through integrated interventions that prioritise ecological conservation, livelihood diversification, gender inclusion, and the documentation and promotion of traditional knowledge. Key Policy Highlights Socio-economic empowerment and livelihood diversification to enhance economic resilience and reduce dependency on a single livelihood source. Inclusive governance and ecological co-management to ensure sustainable management of natural resources while empowering the “Shoe Dhoni” community.