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Climate change poses significant challenges to livestock production worldwide. Wherein, it affects communities in developing nations primarily dependent on agriculture and animal husbandry. Its direct and indirect deleterious effects on agriculture and animal husbandry includes aberrant changes in weather patterns resulting in disturbed homeorhetic mechanism of livestock vis a vis indirectly affecting nutrient composition of feed and fodder. The nutritional stress (i.e. non-availability of nutrients in the required quantity and quality for particular livestock) is the critical factor affecting livestock performance, productivity, and reproductive efficiency. Nutritional stress may arise from both macro- and micro- nutrient imbalances; however, micronutrients are of paramount importance in climate change context due to their role in various vital functions of body namely, body metabolism, production, reproduction, and health. The micronutrients, minerals and vitamins, when supplied in adequate quantity and proportion aid in mitigating the stress induced by climate change on animals. Here, we tried to discuss the impact of climate change induced stresses on milk production, reproduction, and metabolic acclimation of heat-stressed animals. Furthermore, emphasis is given on the importance of dietary micronutrients management strategies to support livestock health and resilience during changing climatic conditions. By addressing the nutritional needs of livestock, farmers can achieve sustainability and well-being in livestock production under changing climatic condition.

This study quantified the environmental impacts of residue burning of major produced and burned crops in Madhya Pradesh, central India. The environmental impacts were quantified using Life Cycle Assessment (LCA) coupled with Monte Carlo simulation of 1000 iterations. Crop wise marginal impacts of the crops have been quantified using Multivariate regression model. The results showed that sugarcane and rice have the highest emissions in key impact categories, such as particulate matter formation (PMF) and global warming potential (GWP), whereas wheat and maize exhibit comparatively lower impacts. The combustion of residues significantly increases marine eutrophication (MEUT), agricultural land use (ALU), terrestrial acidification (TEAF) and GWP. Each kilogram of burned residue results in an increase of 21% in MEUT, 0.05% in ALU, 0.046% in TEAF and 0.028% in GWP, intensifying climate change. The results underscore the immediate necessity for specialized residue management strategies for sugarcane and rice crops. It is advisable to utilize sustainable alternatives such as composting or biochar production to mitigate emissions and enhance soil health, thereby addressing environmental and human health issues.

Rice crop disease is critical in precision agriculture due to various influencing components and unstable environments. The current study uses machine learning (ML) models to predict rice crop disease in Eastern India based on biophysical factors for current and future scenarios. The nine biophysical parameters are precipitation (Pr), maximum temperature (Tmax), minimum temperature (Tmin), soil texture (ST), available water capacity (AWC), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference chlorophyll index (NDCI), and normalized difference moisture index (NDMI) by Random forest (RF), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), Artificial Neural Net (ANN), and Support vector Machine (SVM). The multicollinearity test Boruta feature selection techniques that assessed interdependency and prioritized the factors impacting crop disease. However, climatic change scenarios were created using the most recent Climate Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways (SSP) 2-4.5 and SSP5-8.5 datasets. The rice crop disease validation was accomplished using 1105 field-based farmer observation recordings. According to the current findings, Purba Bardhaman district experienced a 96.72% spread of rice brown spot disease due to weather conditions. In contrast, rice blast diseases are prevalent in the north-western region of Birbhum district, affecting 72.38% of rice plants due to high temperatures, water deficits, and low soil moisture. Rice tungro disease affects 63.45% of the rice plants in Bankura district due to nitrogen and zinc deficiencies. It was discovered that the link between NDMI and NDVI is robust and positive, with values ranging from 0.8 to 1. According to SHAP analysis, Pr, Tmin, and Tmax are the top three climatic variables impacting all types of disease cases. The study's findings could have a substantial impact on precision crop protection and meeting the United Nations Sustainable Development Goals.

Climate change, resulting from anthropogenic activities, poses a substantial global challenge, inducing discernible shifts in hydro-climatic variables such as temperature, precipitation, river discharge, and extreme weather events. Its implications extend to India's natural resources and agricultural sectors. This research rigorously examines the long-term spatial and temporal changes in rainfall patterns in Bihar, India, utilising high-resolution daily rainfall gridded data from the India Meteorological Department, which includes data from a total of 133 grid points. Coefficient variation analysis reveals low monsoon and annual rainfall variability but substantial variations in the pre-monsoon, post-monsoon, and winter seasons, indicating pronounced changes in Bihar's precipitation patterns. Trend analysis offers nuanced insights, using Modified Mann-Kendall (MMK) and Innovative Trend Analysis (ITA). Pre-monsoon rainfall exhibits a statistically significant increasing trend (Z = 3.252), with an annual increment of 0.748 mm. In contrast, a persistent decline characterises monsoon (Z = - 0.598), post-monsoon (Z = - 0.112), winter (Z = - 0.297), and annual (Z = - 0.219) precipitation patterns over 72 years. Change point analysis identifies pivotal shifts in 1982 (annual), 2007 (monsoon), 2012 (pre-monsoon), 1954 (post-monsoon), and 1997 (winter). Spatial-temporal analysis indicates regional shifts post-1982, with maximum annual rainfall significantly decreasing from 2769 to 2453 mm. The findings underscore the necessity to reassess water resource management, employing diverse analytical approaches for robust climate adaptation, resource planning, and disaster preparedness. This research enhances the scientific understanding of long-term climate dynamics, offering insights into sustainable practices in Bihar's agriculture and environmental ecosystems.

Over the past billion years, the fungal kingdom has diversified to more than two million species, with over 95% still undescribed. Beyond the well-known macroscopic mushrooms and microscopic yeast, fungi are heterotrophs that feed on almost any organic carbon, recycling nutrients through the decay of dead plants and animals and sequestering carbon into Earth's ecosystems. Human-directed applications of fungi extend from leavened bread, alcoholic beverages and biofuels to pharmaceuticals, including antibiotics and psychoactive compounds. Conversely, fungal infections pose risks to ecosystems ranging from crops to wildlife to humans; these risks are driven, in part, by human and animal movement, and might be accelerating with climate change. Genomic surveys are expanding our knowledge of the true biodiversity of the fungal kingdom, and genome-editing tools make it possible to imagine harnessing these organisms to fuel the bioeconomy. Here, we examine the fungal threats facing civilization and investigate opportunities to use fungi to combat these threats.

The policymakers in emerging economies have accelerated their efforts to move toward sustainable development due to the associated challenges of environmental degradation and disparities in economic growth. The present study is an effort in that direction; it looks at trade-adjusted carbon emissions (TACE) to help policymakers develop a relevant policy response to mitigate climate change in the BRICST (comprising Brazil, Russia, India, China, South Africa, and Turkey) regions. The study investigates the impact of financial inclusion, green finance, and sustainable economic development on carbon emissions adjusted for trade. The study utilizes the panel dataset of the BRICST regions from 2000 to 2023 by employing the econometric methods of the Method of Moments Quantile Regression (MMQR) approach. It recommends green finance, financial inclusion, and sustainable economic development to curb TACE. The research findings indicate a noteworthy correlation between green finance, financial inclusion, sustainable economic development and TACE. The study recommends policy measures for the BRICST regions that align with the Sustainable Development Goals, focusing on green finance, financial inclusion, and sustainability. By promoting renewable energy, enhancing financial access, and encouraging international cooperation, these strategies aim to reduce TACE and foster sustainable development.