Digital agriculture involving different tools and management practices has advanced considerably in recent years, intending to overcome climate risk and reduce food insecurity. Climate change and its impacts on agricultural production and food security are significant sources of public concern worldwide. The objective of this study was to provide an overview of the potential impact of digital agriculture technologies and practices that can reduce greenhouse gas emissions and enhance productivity while ensuring food security. Based on a comprehensive survey of the previously published works, it was found that due to global warming, altered precipitation patterns, and an increase in the frequency of extreme events, climate change has negatively impacted food security by reducing agricultural yields, slowing animal growth rates, and decreasing livestock productivity. The reviewed works also suggest that using digital technology in agriculture is necessary to mitigate the effect of climate change and food insecurity. In addition, issues regarding creating sustainable agricultural food systems, minimizing environmental pollution, increasing yields, providing fair and equitable food distribution, and reducing malnutrition leading to food security were discussed in detail. It was shown that while digital agriculture has a crucial role in mitigating climate change and ensuring food security, it requires a concerted effort from policymakers, researchers, and farmers to ensure that the benefits of digitalization are realized in a sustainable and equitable manner.

Guar, the most popular vegetable, is tolerant of drought and is a valuable industrial crop enormously grown across India, Pakistan, USA, and South Africa for pharmaceutically and cosmetically usable galactomannan (gum) content present in seed endosperm. Guar genotypes with productive traits which could perform better in differential environmental conditions are of utmost priority for genotype selection. This could be achieved by employing multivariate trait analysis. In this context, Multi-Trait Stability Index (MTSI) and Multi-Trait Genotype-Ideotype Distance Index (MGIDI) were employed for identifying high-performing genotypes exhibiting multiple traits. In the current investigation, 85 guar accessions growing in different seasons were assessed for 15 morphological traits. The results obtained by MTSI and MGIDI indexes revealed that, out of 85, only 13 genotypes performed better across and within the seasons, and, based on the coincidence index, only three genotypes (IC-415106, IC-420320, and IC-402301) were found stable with high seed production in multi-environmental conditions. View on strengths and weakness as described by the MGIDI reveals that breeders concentrated on developing genotype with desired traits, such as quality of the gum and seed yield. The strength of the ideal genotypes in the present work is mainly focused on high gum content, short crop cycle, and high seed yield possessing good biochemical traits. Thus, MTSI and MGIDI serve as a novel tool for desired genotype selection process simultaneously in plant breeding programs across multi-environments due to uniqueness and ease in interpreting data with minimal multicollinearity issues.

Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers’ perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers’ perceptions about climate change, and farmers’ adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers’ perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change.

Climate change has increasing effects on horticultural crops. To investigate the impact of CO2 and temperature at elevated levels on tomato production and quality of fruits an experiment was conducted by growing plants in open top chambers. The tomato plants were raised at EC₅₅₀ (elevated CO₂ at 550 ppm) and EC₇₀₀ (elevated CO₂ at 700 ppm) alone and in combination with elevated temperature (ET) + 2 °C in the open top chambers. These elevate CO₂ and temperature treatment effects were compared with plants grown under ambient conditions. Outcome of the experiment indicated that growth parameters namely plant stature in terms of height (152.20 cm), leaf number (158.67), canopy spread (6127.70 cm²), leaf area (9110.68 cm²) and total dry matter (223.0 g/plant) were found to be high at EC₇₀₀ compared to plants grown at ambient conditions in open field. The plants grown at EC₇₀₀ also exhibited significantly higher number of flowers (273.80) and fruits (261.13), more fruit weight (90.46 g) and yield (5.09 kg plant⁻¹) compared to plants grown at ambient conditions in open field. The percent increase in fruit yield due to EC varied from 18.37 (EC₅₅₀) to 21.41 (EC₇₀₀) percent respectively compared to open field and the ET by 2 °C has reduced the fruit yield by 20.01 percent. Quality traits like Total Soluble Solids (3.67 °Brix), reducing sugars (2.48%), total sugars (4.41%) and ascorbic acid (18.18 mg/100 g) were found maximum in EC₇₀₀ treated tomato than other elevated conditions. Keeping quality was also improved in tomato cultivated under EC₇₀₀ (25.60 days) than the open field (17.80 days). These findings reveal that CO₂ at 700 ppm would be a better option to improve both quantitative as well as qualitative traits in tomato. Among the combinations, EC₅₅₀ + 2 °C proved better than EC₇₀₀ + 2 °C with respect to yield as well as for the quality traits. The tomato grown under ET (+2 °C) alone recorded lowest growth and yield attributes compared to open field conditions and rest of the treatments. The positive influence of EC₇₀₀ is negated to an extent of 14.35 % when the EC₇₀₀ combined with elevated temperature of + 2 °C. The present study clearly demonstrates that the climate change in terms of increased temperature and CO₂ will have a positive effect on tomato by way of increase in production and quality of fruits. Meanwhile the increase in EC beyond 700 ppm along with ET may reduce the positive effects on yield and quality of tomato.

Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (>20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka.