Agricultural development and farmers’ welfare occupy a central place in the development goals of India. Various pathways which have evolved over the years have been implemented in the country to propel agricultural growth by shifting its focus from achieving food sufficiency to sustainable income and inclusive growth. The Farmer FIRST Programme (FFP), an innovative frontline extension program of the Indian Council of Agricultural Research (ICAR), was launched in 2016 to enhance the reach and effectiveness of agricultural research with a multi-stakeholder approach. This paper evaluates the outcomes of the FFP implemented in ICAR institutions for the upscaling of those promising technologies, which have resulted in a significant impact on the farming community. The criteria chosen for assessing the outcomes are farm income, cropping intensity, use of chemical fertilizers, pesticides, and organic manure, and nutritional security. The data were collected from 50 FFP-implementing institutions for the period 2016–2021 and grouped into six different zones. The results revealed that there is a significant increase in income, cropping intensity, nutritional security, and saving pesticides through this program. The nutritional security, measured using cereal equivalent quantity (CEQ), showed a considerable increase in average consumption in all the zones. Overall, FFP interventions have resulted in achieving significantly higher income and the nutritional security of the farmholds compared to the control. The recorded results are favorable for scaling up and institutionalizing the FFP approach at the national level. The study recommends a participatory mode of an interdisciplinary approach for the effective scaling-up of the FFP across the agricultural research and development landscape of India.

Climate change poses enormous challenges for agriculture in developing countries, impacting farmers' livelihoods. Farmers are extremely affected by their need to adapt to changing climatic variations. Climate resilient technologies are an effective means to protect farming systems from climate variability. National Innovations on Climate Resilient Agriculture (NICRA) is a flagship initiative of the Indian Council of Agricultural Research (ICAR), New Delhi which has demonstrated, and promoted the application of climate-resilient technologies in the most vulnerable 151 districts across 28 states and 1 union territory in India. This study has been conducted to investigate the extent to which CRA technologies are being adopted by the farmers in the NICRA project executed in villages of Suryapet and Khammam districts in Telangana state, India. It further studied the factors affecting the extent of adoption of CRA technologies and whether these technologies help achieve the United Nations (UN) Sustainable Development Goals (SDGs). A structured interview was carried out to obtain data from 200 respondents. Data was analyzed using normalization of the adoption index and step-wise multiple regression analysis. Results discovered medium to high levels of adoption of CRA technologies by the farmers with interventions like deep ploughing, in situ moisture conservation technologies, improved paddy varieties, crop diversification, crop rotation, deworming in sheep and goats, improved backyard poultry breeds and Custom Hiring Centres were highly adopted by the farmers. Factors like innovative proneness, availability of water resources, economic motivation, farming system, land holding, and risk-taking ability have significantly contributed to the adoption of CRA technologies. Results revealed that NICRA interventions facilitated the achievement of various SDGs, viz., SDG-1 (no poverty), SDG-2 (zero hunger), SDG-3 (good health and well-being), SDG-8 (decent work and economic growth), SDG-12 (responsible consumption and production), SDG-13 (climate action), and SDG-15 (life on land). The study recommends increasing awareness among farmers and enhancing their capacity through various programmes by extension personnel to further improve the adoption of CRA technologies and achieve SDGs.

Introduction: Nutrition-sensitive agricultural interventions are crucial in addressing malnutrition and promoting food security. The Farmer, Farm, Innovation, Resources, Science, and Technology (FIRST) Program is a national-level agricultural intervention program that was started in 2016 by the Indian Council of Agricultural Research (ICAR). Its primary objective is to transform the lives and livelihoods of Indian farmers, with a focus on income and livelihood security. This program envisages agricultural interventions ensuring national food security goals, with improved agricultural practices, enhanced food production, and increased access to nutritious food, especially for vulnerable populations.Methods: This study aims to investigate the food security improvement resulting from implementing nutrition-sensitive interventions introduced under the Farmer FIRST Program (FFP) in 15 agroecological zones. Four key indicators were employed to assess food security in the technology-focused field intervention: food availability, purchasing power, food gap, and food diversity. Food availability was measured at the macro level (state or national) using per capita food availability. However, at the micro level, particularly for farmers who produce their food and are secure in terms of availability, yield increases from the selected interventions under FFP served as an alternative measure. Purchasing power was assessed by the additional income generated to buy food during the off-season. The food gap was assessed using the cereal equivalent quantity (CEQ), which captures an aspect of consumers’ nutritional security. Its impact in India was evaluated using the propensity score matching technique with difference-in-difference (D-i-D) measure to estimate the unbiased overall effect on food security. Food diversity was captured using Barry’s index.Results: A sample of 2,282 respondents were interviewed from 2016 to 2020 to elicit data on the prevalence of undernutrition in India, which is 16.3%. The results revealed that post-intervention of the FFP, cereal availability increased by 147.74% in the Northern Plain, while pulses recorded over 200% growth in three regions. The incremental per capita farm income exceeded INR 20,000 in several zones, with the Northern Plain showing an increase of over 21 times. Food diversity improved marginally, supported by the integrated farming system. Overall, FFP interventions transformed nutritional security, benefiting 1,915 households, particularly in regions with historically low calorie intake, thereby demonstrating substantial gains in food security and living standards.Conclusion: The Farmer FIRST Program (FFP) has significantly improved dietary intake among participating households, enhancing food security. Nutrition-sensitive agricultural interventions under the FFP have reduced undernutrition by increasing food availability, boosting purchasing power, and narrowing the food gap.

This study investigates the factors influencing the spending patterns of farmers receiving financial assistance through the Pradhan Mantri Kisan Samman Nidhi (PM KISAN) program in five southern Indian states. Using a mixed-methods approach, the research collected data from 1900 PM KISAN beneficiaries across Tamil Nadu, Kerala, Andhra Pradesh, Telangana and Karnataka. The study employed factor analysis to identify key determinants of spending behaviour. Results reveal four primary factor groups: agricultural spending, repayment, social spending and household mandatory spending. The timing of fund disbursement coinciding with agricultural operations emerged as the most influential determinant, followed by farmers' interest in agriculture. Regional variations were observed, with Kerala and Tamil Nadu showing higher agricultural spending tendencies, while Andhra Pradesh and Telangana displayed stronger influences from financial pressures and social factors. The study also highlights the significant impact of socio-economic characteristics, such as farm size, education level and credit orientation, on spending decisions. These findings suggest that aligning fund disbursement with agricultural cycles enhances program efficacy. Policy recommendations include financial literacy programs and improved fund allocation strategies. The study contributes to a more nuanced understanding of the PM KISAN program's impact on rural livelihoods and agricultural productivity in southern India.

Aim: This paper employed Social Network Analysis approach to visualize and calculate different social network metrics. It identifies key communicators who play pivotal roles in information flow. Methodology: Research was conducted at Jammulapalem and Perali villages of Bapatla district, Andhra Pradesh, India, during 2022-23 using an exploratory research design. A total of 120 farmers Eigen vector were selected using simple random technique, and data was collected using a well-developed interview schedule. Network metrics such as Degree centrality, betweenness centrality, and eigen vector centrality were computed to evaluate the network structure using R software (version 4.3.1). R packages, namely igraph, statnet and network D3, were used for network creation, analysis and visualization to identify the influential nodes. Results: The study revealed a complex web of relationships among various stakeholders within the agricultural network through a network graph, identifying key communicators with the highest Degree centrality. Interpretation: The focal points identified through Social Network Analysis represent a specific demographic and socio-economic group, typically aged between 35 and 55, primarily medium-scale farmers,with landholdings spanning 10 to 25 acres and high annual income, with educational backgrounds ranging from high school to pre-university college, and wield significant influence within their local communities. They require sensitization, training, practical demonstrations, and personalized support to effectively disseminate agricultural information. Key words: Agricultural Information System Network, Centrality measures, Information Sources, Key Communicators, Network visualization, Social Network Analysis