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.

Efficient use of available resources in agricultural production is important to minimize carbon footprint considering the state of climate change. In this context, the current research was conducted to identify carbon and energy-efficient fodder cropping systems for sustainable livestock production. Annual monocropping, perennial monocropping, annual cereal + legume intercropping and perennial cereal + legume intercropping systems were evaluated by employing a randomized complete block design with three replications under field conditions. The lucerne (Medicago sativa L.) monocropping system recorded significantly lower carbon input (274 kg-CE ha⁻¹ year⁻¹) and showed higher carbon indices viz., carbon sustainability index (165.8), the carbon efficiency ratio (166.8) and carbon efficiency (347.5 kg kg-CE⁻¹) over other systems. However, higher green fodder biomass led to statistically higher carbon output (78,542 kg-CE ha⁻¹ year⁻¹) in the Bajra–Napier hybrid (Pennisetum glaucum × Pennisetum purpureum) + lucerne perennial system. Similar to carbon input, lower input energy requirement (16,106 MJ ha⁻¹ year⁻¹) and nutrient energy ratio (25.7) were estimated with the lucerne perennial system. However, significantly higher energy output (376,345 and 357,011 MJ ha⁻¹ year⁻¹) and energy indices viz., energy use efficiency (13.3 and 12.2), energy productivity (5.8 and 5.3 kg MJ⁻¹), net energy (327,811 and 347,961 MJ ha⁻¹ year⁻¹) and energy use efficiency (12.3 and 11.2) were recorded with Bajra–Napier hybrid + legume [lucerne and cowpea (Vigna unguiculata (L.) Walp.)] cropping systems, respectively. However, these systems were on par with the lucerne monocropping system. Additionally, Bajra–Napier hybrid + legume [cowpea, sesbania (Sesbania grandiflora (L.) Pers.) and lucerne] cropping systems also showed higher human energy profitability. Concerning various inputs’ contribution to total carbon and energy input, chemical fertilizers were identified as the major contributors (73 and 47%), followed by farmyard manure (20 and 22%) used to cultivate crops, respectively, across the cropping systems. Extensive use of indirect (82%) and non-renewable energy sources (69%) was noticed compared to direct (18%) and renewable energy sources (31%). Overall, perennial monocropping and cereal + legume cropping systems performed well in terms of carbon and energy efficiency. However, in green biomass production and carbon and energy efficiency, Bajra–Napier hybrid + legume (lucerne and cowpea) cropping systems were identified as the best systems for climate-smart livestock feed production.

Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researchers to develop sustainable cropping strategies. In the present study, six multivariate weather-based models viz., least absolute shrinkage and selection operator (LASSO), elastic net (ENET), principal component analysis (PCA) in combination with stepwise multiple linear regression (SMLR), artificial neural network (ANN) alone and in combination with PCA and ridge regression model are examined by fixing 90% of the data for calibration and remaining dataset for validation to forecast rabi sorghum yield for different districts of Karnataka. The R² and root mean square error (RMSE) during calibration ranged between 0.42 to 0.98 and 30.48 to 304.17 kg ha⁻¹, respectively, without actual evapotranspiration (AET) whereas, these evaluation parameters varied from 0.38 to 0.99 and 19.84 to 308.79 kg ha⁻¹, respectively with AET inclusion. During validation, the RMSE and nRMSE (normalized root mean square error) varied between 88.99 to 1265.03 kg ha⁻¹ and 4.49 to 96.84%, respectively without AET and including AET as one of the weather variable RMSE and nRMSE were 63.48 to 1172.01 kg ha⁻¹ and 4.16 to 92.56%, respectively. The performance of six multivariate models revealed that LASSO was the best model followed by ENET compared to PCA_SMLR, ANN, PCA_ANN and ridge regression models because of reduced overfitting through penalisation of regression coefficient. Thus, it can be concluded that LASSO and ENET weather-based models can be effectively utilized for the district level forecast of sorghum yield.

To cope with worsening climate change and widening intergenerational equity issues, more impetus should be given to sustainable development. India, predominantly an agrarian economy, faces most pressing issues of sustainable development with a complex territorial hegemony of the population and their dynamic food demands. Regional production systems play a vital role in strengthening national sustainable development priorities in India. Hence, to realize the dimensions of sustainable development in a more meaningful way, sustainability needs to be prioritized in an agrarian economy. Sustainability is a complex phenomenon encompassing economic, ecological and equity dimensions. A modest attempt in this regard has been made to estimate normative sustainable indicators for Karnataka state considering 20 crucial indicators or variables governing different dimensions. Using principal component analysis and linear scoring techniques, a minimum dataset including forest cover, livestock and human population density, and cropping intensity governing ecological issues, groundwater availability and milk availability governing social equity issues, and net cropped area, land productivity, labor productivity, food grain productivity and fertilizer use governing economic efficiency was identified, constituting crucial indicators for the development of the sustainable livelihood security index. The computed index was used to classify districts in Karnataka into various sustainable categories. Among 27 districts, 13 districts were grouped as less sustainable, 4 as highly sustainable and 10 as moderately sustainable categories. This classification and knowledge provide clues for policy makers to transform less sustainable districts into moderately/highly sustainable ones by formulating suitable policies related to crucial factors. Formulated policies on crucial factors have a domino effect/causation effect and bring about desirable changes in all other indicator variables, leading to the sustainable development of the target districts in Karnataka. This approach can be used at different scales in other states in India and in other developing countries.

Elevated carbon dioxide (EC) can increase the growth and development of different C₃ fruit crops, which may further increase the nutrient demand by the accumulated biomass. In this context, the current investigation was conceptualized to evaluate the growth performance and nutrient uptake by tomato plants under elevated CO₂ (EC₇₀₀ and EC₅₅₀ ppm) and temperature (+2 °C) in comparison to ambient conditions. Significant improvement in the growth indicating parameters like leaf area, leaf area index, leaf area duration and crop growth rate were measured at EC₇₀₀ and EC₅₅₀ at different stages of crop growth. Further, broader and thicker leaves of plants under EC₇₀₀ and EC₅₅₀ have intercepted higher radiation by almost 11% more than open field plants. Conversely, elevated temperature (+2 °C) had negative influence on crop growth and intercepted almost 7% lower radiation over plants under ambient conditions. Interestingly, earliness of phenophases viz., branch initiation (3.0 days), flower initiation (4.14 days), fruit initiation (4.07 days) and fruit maturation (7.60 days) were observed at EC₇₀₀ + 2 °C, but it was statistically on par with EC₇₀₀ and EC₅₅₀ + 2 °C. Irrespective of the plant parts and growth stages, plants under EC₇₀₀ and EC₅₅₀ have showed significantly higher nutrient uptake due to higher root biomass. At EC₇₀₀, the tune of increase in total nitrogen, phosphorus and potassium uptake was almost 134%, 126% and 135%, respectively compared to open field crop. This indicates higher nutrient demand by the crop under elevated CO₂ levels because of higher dry matter accumulation and radiation interception. Thus, nutrient application is needed to be monitored at different growth stages as per the crop needs.

Monsoon fluctuation due to El Niño Southern Oscillation (ENSO) has a reflective influence on rice production, which is the major food grain crop in India. The impact of ENSO on the spatial variability of summer monsoon rainfall was analyzed from 1950 to 2018 and that on Kharif rice production for the period of 1998–2016. It was clear from the analysis that ENSO had varied influences on rainfall and rice production over different rice-growing districts of Karnataka. During El Niño (strong, moderate, and weak) years, southwest (S-W) monsoon rainfall was below normal in all the districts of Karnataka, wherein the highest negative deviation from normal was recorded in the Mysore district (−21.43%). In contrast, the rice production was higher in 15 districts out of 25, and the deviation from normal ranged from −39.73% in Bidar to 42.11% in Gulbarga district. During the La Niña (strong, moderate, and weak) years, S-W monsoon rainfall was above normal in 12 districts in which Bidar and Bengaluru urban districts have shown the highest positive deviation (19.93 and 19.82%, respectively). However, except for Udupi, Dakshina Kannada, Bidar, Davanagere, and Hassan districts, all the other major rice-growing districts have shown a positive deviation in rice production with the highest deviation of 62.39% in Tumkur district. Additionally, correlation coefficient values indicated the influence of southwest monsoon rainfall on Kharif rice production during El Niño years with a major contribution from September month rainfall. This kind of ENSO impact analysis on spatial rice production could be useful for formulating the farm-level site-specific management, planning, and policy decisions during ENSO periods in advance.