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.

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.

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.

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Brassinosteroids (BRs) have emerged as pleiotropic phytohormone owing to their wide function in crop growth and metabolism. Homobrassinolide (HBR) being an analogue of BRs is known to improve the growth, yield and quality parameters in many crop plants. Thus, an evaluation study was conducted for two years (2018 and 2019) to elucidate the performance of tomato plants ( Solanum lycopersicum L.) to a novel group of phytohormone,HBR. The field experiment comprised of seven treatments with homobrassinolide 0.04% (Emulsifiable Concentrate) EC at four different concentrations (0.06, 0.08, 0.10 and 0.12 g active ingredient (a.i.) ha −1 ) and two well-known growth promoters viz., Gibberellic acid (GA), Naphthalene Acetic Acid (NAA) along with the untreated control. Plant height and chlorophyll concentration were found significantly different in both years of experiment as well as among the different treatments. HBR at 0.12 g a.i. ha −1 was found better with maximum number of fruits (77.36 plant −1 ), fruit length (6.72 cm), fruit breadth (6.45 cm) and fruit weight (80.52 g) over other concentrations and treatments. Fruit yield was more pronounced in the plots treated with plant growth regulators compared to untreated control. However, significantly higher fruit yield of 91.07 t ha −1 (62.58 t ha −1 with untreated control) along with improved quality traits viz., fruit firmness (4.11 kg cm −2 ), ascorbic acid content (24.09 mg 100 g −1 ), total soluble solids (4.43°Brix) and keeping quality (12.50 days) was recorded in 0.12 g a.i. ha −1 HBR treated plots. Thus, it can be inferred that HBRapplication would be a better option to enhance growth, yield as well as quality traits in tomato.