Agriculture is the backbone of Indian economy and farmers play significant role in sustaining the sector. However, farmers face several challenges such as poor market access and limited access to market information which adversely affect their marketing performance. Therefore, this study aimed to examine the marketing performance and factors influencing farmers choice for agricultural output marketing channels in garden pea in the Indian state of Himachal Pradesh. The study utilized primary data collected through structured questionnaires administered via the interview method to a sample size of 400 farmers selected through a multistage stratified random sampling technique. The data collected were analyzed using descriptive statistics and acharya approach to study the marketing performance. Further, a multinomial logistic regression model was used to determine the factors that influence farmers marketing choice of marketing channels. Additionally, the constraints experienced by farmers during marketing were investigated using garret ranking. The study revealed that farmers who sold their pea directly to consumer had higher marketing performance than those who sold through market intermediaries such as local traders, commission agents and wholesalers. Further, the results indicated that farm income, farm experience, distance to the market and market information were significant determinants of farmers choice for marketing channels. Whereas, lack of market consultancy, high commission chargers and poor transportation were the major constraints faced by farmers during marketing of pea. The findings of this study highlight the need for policymakers to develop and implement interventions that enhance farmers marketing skill, facilitate access to markets, improve negotiation power which can lead to higher incomes for farmers, improve their livelihoods, better quality produce for consumers and a more efficient and sustainable food system.

The interaction between selective nutrients and linked genes involving a specific organ reveals the genetic make-up of an individual in response to a particular nutrient. The interaction of genes with food opens opportunities for the addition of bioactive compounds for specific populations comprising identical genotypes. The slight difference in the genetic blueprints of humans is advantageous in determining the effect of nutrients and their metabolism in the body. The basic knowledge of emerging nutrigenomics and nutrigenetics can be applied to optimize health, prevention, and treatment of diseases. In addition, nutrient-mediated pathways detecting the cellular concentration of nutrients such as sugars, amino acids, lipids, and metabolites are integrated and coordinated at the organismal level via hormone signals. This review deals with the interaction of nutrients with various aspects of nutrigenetics and nutrigenomics along with pathways involved in nutrient sensing and regulation, which can provide a detailed understanding of this new leading edge in nutrition research and its potential application to dietetic practice.

Forecasts are valuable to countries to make informed business decisions and develop data-driven strategies. The production of pulses is an integral part of agricultural diversification initiatives because it offers promising economic opportunities to reduce rural poverty and unemployment in developing countries. Pulses are the cheapest source of protein needed for human health. India's pulses production guidelines must be based on accurate and best forecast models. Comparing classical statistical and machine learning models based on different scientific data series is the subject of high-level research today. This study focused on the forecasting behaviour of pulses production for India, Karnataka, Madhya Pradesh, Maharashtra, Rajasthan and Uttar Pradesh. The data series was split into a training dataset (1950–2014) and a testing dataset (2015–2019) for model building and validation purposes, respectively. ARIMA, NNAR and hybrid models were used and compared on training and validation datasets based on goodness of fit (RMSE, MAE and MASE). This research demonstrates that due to the diverse agricultural conditions across different provinces in India, there is no single model that can accurately predict pulse production in all regions. This study’s highest accuracy model is ARIMA. ARIMA outperforms NNAR, a machine learning model. Pulse production in India, Rajasthan, and Madhya Pradesh will expand by 26.11%, 12.62%, and 0.51% from 2020 to 2030, whereas it would decline by − 6.5%, − 6.21%, and − 6.76 per cent in Karnataka, Maharashtra, and Uttar Pradesh, respectively. The current forecast results could allow policymakers to develop more aggressive food security and sustainability plans and better Indian pulses production policies in the future.

Vegetables are important for both nutritional and economic stability and contribute significantly to the agricultural landscape of India. The demand for vegetables is rising, driven by population growth and increased awareness of their benefits. This empirical study highlights the dynamics of agricultural production supply chain networks of capsicum crops in the northwestern Himalayan region, specifically Himachal Pradesh, India. The study employs the Acharya approach to analyse the various marketing channels utilized by farmers in the capsicum supply chain. This methodology sheds light on the economic nuances at each stage and examines marketing channels, costs, margins, price spread and marketing efficiency. Simultaneously, the Garrett ranking method is applied to discern and prioritize constraints faced by farmers. This comprehensive approach ensures a nuanced understanding of the economic and logistical intricacies of capsicum marketing. The analysis of marketing channels reveals five distinct pathways employed by farmers, with Channel-C (Producer–Commission Agent–Retailer–Consumer) standing out as the most dominant, representing 47.25% of the total quantity. Moreover, Channel-A (Producer–Consumer) proves to be the most cost-effective for producers and boasts the highest producer price, while Channel-C, involving commission agents, incurs higher costs. This suggests a preference for intermediaries, emphasizing factors like market access and negotiation skills, whereas Channel-D (Producer–Local Trader–Wholesaler–Retailer–Consumer) has the highest gross marketing margin, emphasizing the trade-offs between efficiency and transaction volume. The results indicate that while Channel-A is the most efficient, it is not the preferred choice due to the lower transaction quantity. Further, the absence of market consultation services, inadequate road infrastructure, high commission charges, nonremunerative prices and untimely availability of vehicles are the major constraints in marketing. The findings of the study call for targeted interventions to create a more robust and farmer-friendly marketing environment for capsicum crops in the region. The study proposes targeted recommendations, emphasizing collaborative efforts between stakeholders, government bodies and farmers. This research contributes to the academic discourse and also offers actionable insights for researchers and policymakers, fostering sustainability, profitability and equity within the capsicum supply chain.