Heat stress impacts ruminant livestock production on varied levels in this alarming climate breakdown scenario. The drastic effects of the global climate change-associated heat stress in ruminant livestock demands constructive evaluation of animal performance bordering on effective monitoring systems. In this climate-smart digital age, adoption of advanced and developing Artificial Intelligence (AI) technologies is gaining traction for efficient heat stress management. AI has widely penetrated the climate sensitive ruminant livestock sector due to its promising and plausible scope in assessing production risks and the climate resilience of ruminant livestock. Significant improvement has been achieved alongside the adoption of novel AI algorithms to evaluate the performance of ruminant livestock. These AI-powered tools have the robustness and competence to expand the evaluation of animal performance and help in minimising the production losses associated with heat stress in ruminant livestock. Advanced heat stress management through automated monitoring of heat stress in ruminant livestock based on behaviour, physiology and animal health responses have been widely accepted due to the evolution of technologies like machine learning (ML), neural networks and deep learning (DL). The AI-enabled tools involving automated data collection, pre-processing, data wrangling, development of appropriate algorithms, and deployment of models assist the livestock producers in decision-making based on real-time monitoring and act as early-stage warning systems to forecast disease dynamics based on prediction models. Due to the convincing performance, precision, and accuracy of AI models, the climate-smart livestock production imbibes AI technologies for scaled use in the successful reducing of heat stress in ruminant livestock, thereby ensuring sustainable livestock production and safeguarding the global economy.

Studies in India from the early to late 1990s found that rural youths and women played a predominant role in livestock farming. Even though many studies differ in the extent and nature of the contribution of youths and women in livestock farming, all acknowledge their roles and contribution. Livestock farming acts as a source of supplementary income to youths and women and provides increased nutritional security. New economic policies of the1990s have brought changes to the livestock farming community. This paper attempts to understand and describe the role of women and youths in livestock farming. The research methodology employed for the present study is ex post facto design, and includes semi-structured open-ended interviews, observation and conversations with key informants. The study has found that a change in the roles of women and the participation of youths in livestock farming has occurred, which could be detrimental to the well-being of rural family farmers.

The study in India involving 384 households found that 42.7% of dairy farmers adopted new forage varieties when varieties were released. The farmer’s resources, their caste, access to markets for milk and price received for milk had positive effects on the decision to adopt. Management of farms by women had negative effects on the adoption decision. Increased forage yield and ease of propagation and establishment were important reasons for adoption of varieties, e.g. the relative advantage of pearl millet × Napier grass (Cenchrus americanus × C. purpureus) vs. hedge lucerne (Desmanthus virgatus). Thus, researchers need to address these issues when developing new germplasm, if farmers are to readily adopt new varieties, especially in the case of resource-poor farmers.

In the context of structural transformation of Indian economy, we examined the patterns of income, migration, milk marketing, dairy trends and future plans at the household level in Tamil Nadu state in south India. The study finds that majority of the dairy households in various farming systems have poor landholdings; belong to low or middle income classes; have one migrant in their families, and diversified sources of income. Given this backdrop, continuing dairy activity in the near future differed based on farming system and market opportunities. The majority were not willing to motivate the next generation to take up dairying as a profession.