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The present study was performed at three diverse agro-climatic zones of Indian Punjab. A validated DSSAT-CANEGRO model was used to simulate the response of different climate change scenarios on cane yield of four sugarcane varieties (CoPb 91, CoJ 88, Co 118 and Co 238) for each zone. Results described that elevated and lowered minimum temperature upto 3.0°C may alter cane yield by -17.9 to 18.0 per cent. Similarly, ±3.0°C altered maximum temperature may change the cane yield by -17.6 to 17.5 per cent. The sugarcane yield may be decreased by 2.4 to 14.4 per cent, 3.3 to 17.6% and 0.3 to15.4 per cent with 2.5 to 15 per cent reduced solar radiation and increase in the same unit may enhance the yield by 1.9 to 9.0 per cent, 1.3 to 13.6 per cent and 2.0 to 12.3 per cent at Faridkot, Gurdaspur and Kapurthala, respectively. A±30 mm rainfall may change the cane yield by 9.2 to 18.0 % similarly, rise and fall in CO2 by 5 to 30 ppm was able to increase and decrease the cane yield by 2.4- 22.6 and 3.5 - 27.8 per cent, at different regions. This study confirmed that for sugarcane cultivation in Punjab CoPb 91 should be preferred. However, CoJ 88 and Co 238 may suffer cane yield loss of 7.8 and 9.9 per cent respectively.

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Sammen (2021) Daily pan-evaporation estimation in different agroclimatic zones using novel hybrid support vector regression optimized by Salp swarm algorithm in conjunction with gamma test, Engineering

In this study an attempt has been made to estimate the actual wheat crop evapotranspiration (ET c ) by Surface Energy Balance Algorithm (SEBAL) and standardized FAO-Penman-Monteith (FAO-PM). Improved knowledge of evapotranspiration (ET) helps in understanding the water balance of any region. The results obtained through measured lysimeter, SEBAL and PM method were evaluated through statistical performance measure tests. ET c estimated from SEBAL was found to correlate significantly as r 2 (0.910) with the measured ET c of lysimeter. ET c estimated by SEBAL was also compared with PM ET c with the help of crop coefficient and was found to correlate significantly as r 2 (0.850). The other statistical parameters (RMSE=0.561, nRMSE=0.090, MAE=0.265, NRMSE=0.2033, R-RMSE=0.268, NSE=1, d=0.870 (≈1)) were also showing a good agreement between SEBAL ET c and PM ET c . The findings of work have suggested that SEBAL model shows a good potential to estimate spatial ET c for the region. Additionally the validation of models results were performed with the analysis of correlation between models ET c and district level wheat production and area under crop of five years. The results of this analysis outline that water availability and good amount of rainfall gives higher wheat yield and resulted into more ET c .

Use of seasonal and sub-seasonal forecast products of experimental extended range forecast system (ERFS) in crop models is investigated for improving the rice grain yield prediction skill for the ensuing monsoon season in the experimental station at Bhubaneswar, India. A stochastic disaggregation is used to downscale seasonal and monthly forecast products in daily weather sequences. These weather series are taken as input in Crop Estimation through Resource and Environment Synthesis (CERES)-rice crop simulation model for the crop yield prediction at different stages of forecast: June-September (4 month forecast), July-September (3 month forecast), August-September (2 month forecast) and monthly forecast for September (1 month forecast). To avoid a technological trend in historical yield data, yields simulated with observed weather data have been used as the benchmark (observed rice yield) to evaluate the yields simulated using experimental ERFS forecasts. The findings recommend the efficiency of forecast products to capture year-to-year variability in observed rice yield at experimental stations. A significant enhancement in the prediction skill is noticed as the season advances due to incorporation of observed weather data, reducing uncertainty of yield prediction. The outcomes are useful for taking decisions well in advance for transplanting of rice as well as for other input management and farm activities during different stages of the crop growing season.

Plant hormones influence various physiological processes during the growth and development of plants, but their critical roles in influencing yield and antioxidant activities in dry-seeded rice (DSR) have not been adequately explored. This study aims to analyze the performance and antioxidant activity of contrasting genotypes of DSR in response to soil moisture regimes and foliar-applied hormones. The study comprised sixteen treatments that were evaluated under field conditions as per split-plot design in three replications. Treatments comprised combinations of two soil moisture tension regimes (10 kPa and 20 kPa) and two genotypes (PR-111, non-stay-green type and PR-123, stay-green type) applied to the main plots and foliar application of three hormones (gibberellic acid (GA3) 40 mg kg−1, abscisic acid (ABA) 20 mg kg−1, and cytokinin (CK) 40 mg kg−1)) and a control (unsprayed) to subplots. The non-stay-green genotype (PR-111) resulted in 34.6% more grain yield (6.48 t ha−1) than the stay-green genotype (PR-123) at the lower soil moisture tension regime (SMTR) (10 kPa) due to the increased number of filled grains per panicle and improvement in harvest index (HI). At the higher SMTR (20 kPa), the stay-green genotype (PR-123) produced 26.4% more grain yield (5.21 t ha−1) than non-stay green genotype (4.12 t ha−1) and showed enhanced superoxide dismutase (SOD) and peroxide dismutase (POD) activity that may have contributed in maintaining sink size through improved chlorophyll content. Grain yield (6.35 t ha−1) with foliar-applied GA3 (40 mg kg−1) at SMTR of 10 kPa was higher by 12.2% and 24.0% than with foliar-applied ABA (20 mg kg−1) and unsprayed treatments, respectively. Irrigation application at SMTR of 20 kPa and foliar application of ABA gave 24.1% higher grain yield (5.15 t ha−1) than the unsprayed treatment, but it was similar to foliar-applied GA3 and CK. This study implied that the stay-green genotype (PR-123) was more suitable under moisture stress conditions (20 kPa) in DSR, as it maintained sink size even under moisture stress conditions by improving dry matter translocation and enhancing SOD and POD activity. The study suggests the need to find out the endogenous level of these plant hormones in rice genotypes under a range of water regimes to develop high yielding and water use efficient genotypes of DSR.