Rice (Oryza sativa L.) is a member of the grass family, Gramineae. India holds the largest rice acreage, covering 43.97 million hectares, with a production of 104.32 million tonnes and a yield of 2372 kg/ha (Government of India, 2012). In 2010, hybrid rice was cultivated across 1.3 million hectares, contributing an additional 1.5 to 2.5 million tonnes to the national food production. The study focused on Surajpur district in Chhattisgarh, specifically the Surajpur and Pratapur blocks, with a total sample size of 120. A comprehensive analysis of farmers’ socio-personal characteristics revealed that the majority were middle-aged, with education up to middle school, living in nuclear families, and predominantly engaged in agriculture. Most respondents had moderate farming experience, and their land holdings were mainly small. Survey results indicated that 56.67% of respondents possessed a moderate level of knowledge, while 38.33% had a high level, and 5.00% had a low level. Adoption levels showed that 55.83% had a medium level, 40.00% had a high level, and 4.17% had a low level. Factors such as education, occupation, extension contact, source of irrigation, information-seeking behavior, and mass media exposure were found to be significantly associated with both knowledge and adoption levels. The primary reasons for cultivating hybrid rice were the availability of seeds and the high productivity achieved.

Keywords: Hybrid rice, Adoption levels, Socio-personal characteristics, Knowledge

Maize (Zea mays), a global staple, faces escalating challenges from climate change, including altered precipitation patterns and extreme weather events. This review underscores the imperative of harnessing genetic diversity to breed climate-resilient maize varieties. The genetic landscape of maize, shaped by historical and evolutionary processes, provides a foundation for effective breeding strategies. Key markers like FST quantify genetic diversity within populations. Climate-related traits, including drought and heat resistance, are explored, emphasizing the genetic basis of resilience. Successful breeding programs, exemplified by case studies, demonstrate the practicality of diverse strategies.Challenges such as gene flow and ethical considerations are discussed, emphasizing responsible practices. The future envisions gene editing and collaborative global initiatives, urging public-private partnerships. In conclusion, the review stresses the pivotal role of genetic diversity in developing resilient maize varieties and calls for continued research, collaboration, and innovative breeding strategies to secure global food security amidst climate change.

Keywords: Maize, Genetic Diversity, Climate Resilience, Breeding Strategies, Climate-Related Traits, FST, Gene Editing

The study examines the intricate connection between weather parameters and grape yield in Vijayapura district, Karnataka, India, with a focus on the impact of maximum temperature, minimum temperature, relative humidity, rainfall, and windspeed on grape production. Correlation analysis revealed significant relationships between these weather parameters and grape yield. Maximum and minimum temperatures exhibited positive associations, suggesting that higher temperatures contribute to increased grape production by reducing disease incidence. In contrast, windspeed showed a significant negative influence on grape yield, indicating that increased windspeed is associated with reduced production. Stepwise regression analysis further emphasized the importance of maximum temperature, minimum temperature, and windspeed in predicting grape yield. These findings hold implications for vineyard management and grape growers, highlighting the need to consider specific weather factors to optimize grape production. Understanding the interplay of weather parameters and grape yield is crucial for adapting to climate change and ensuring the sustainability of grapevine productivity. It also underscores the broader concerns of climate change’s impact on agriculture and the need for informed policy decisions to safeguard the agricultural sector.

In the era of climate change, trees play a vital role in bolstering the resilience of agriculture by providing crucial benefits such as carbon sequestration, livelihood improvement, and enhanced food security. This review explores the multifaceted roles of agroforestry in providing essential ecosystem services and contributing significantly to carbon sequestration. In terms of ecosystem services, agroforestry promotes biodiversity conservation by creating diverse habitats and food resources. It plays a vital role in soil conservation and fertility enhancement through reduced erosion, improved soil structure, and organic matter enrichment. Furthermore, agroforestry systems contribute to effective water management, microclimate regulation, and pollination services, positively impacting overall agricultural productivity. On the carbon sequestration front, agroforestry serves as a potent carbon sink, storing carbon both above and below ground. Long-term carbon locking is facilitated through the incorporation of long-lived tree species and the sustainable utilization of harvested wood. Therefore, agroforestry systems provide ‘win-win’ opportunity to bridge-up the adaptation and mitigation strategies help to reduce the impact of climate change.

Keywords: Carbon sequestration, livelihood, adaptation, climate-smart agriculture

Keeping cocoa competitive in the export market is critical to India’s economic well-being. This study project aims to examine cocoa farming’s area, production, and productivity while also determining the industry’s competitiveness and charting the various government policies that influence it. There is a mix of descriptive, qualitative, and quantitative methods. The data is analyzed using ARIMA (autoregressive integrated moving average) and an ETS state space model with level, trend, and seasonal components (T, S), as well as an error term (E). In this case, the best model was chosen because it had the lowest RMSE values both within and outside of the sample. In terms of area and output and productivity, the best models are ETS (M, M, N) and ARIMA (M, 0, M). The study predicted that area would increase from 119.61 in 2021 to 203.90 by 2027, production would increase from 28.98 to 43.78 by 2027, and productivity would increase from 0.279 to 0.2108 by 2027.We need to develop unique policies for cocoa areas, production, and productivity so that cocoa planting generates better net transfer values for farmers. The Sustainability index is increased ,from (period 1) to (period 2) in SI 1, SI 2 and SI 3 that means meeting our own needs without compromising the ability of future.

Keywords: Modelling, Forecasting, ARIMA, Exponential Smoothing, Area, Production, Productivity, and Cocoa.