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The sustainability of global agriculture at higher productivity level is a concern owing to climate change, serious environmental footprints, dipping factor productivity and shrinking availability of natural resources, especially. The situation is worsening in the 'Food Bowl of India'—Indo‐Gangetic plains (IGP) by several amalgamated factors, such as declining groundwater, unpredictable precipitation owing to climate change and cultivation of heavy water duty crops. To neutralise these issues, a field experiment was executed for the period 2019–2021 to assess the efficacy of indigenous hydrogels (P‐hydrogel and Superabsorbent polymer hydrogel‐1118) and their application methods viz., seed treatment, slurry application and soil application on crop yield and water productivity, soil moisture dynamics and profitability in a soybean–wheat cropping system under irrigation and rainfed conditions. In both study years (2019–2020 and 2020–2021), due to higher seed germination percentage, irrigation application together with seed treatment and slurry application of superabsorbent polymer hydrogel‐1118 improved system productivity by 8.1%–26.7% and system water productivity by 17.6%–33.8% over control. Wheat grain yield was enhanced by 8.0% (2019–2020) to 32.2% (2020–2021) due to superabsorbent polymer hydrogel‐1118 hydrogel with 10 cm lesser use of irrigation water compared with control (no‐hydrogel). Soil moisture content in 0–15 cm soil layer was also found higher by 1.8%–2.4% in superabsorbent polymer hydrogel‐1118 and P‐hydrogel slurry‐applied plots. Therefore, higher gross profitability (31.8%), net profitability (89.8%) and B:C (26.9%) in wheat could be attributed to increased crop yields when seeds were treated with superabsorbent polymer hydrogel‐1118. Therefore, the utilisation of modified hydrogel application, in the form of seed treatment (seed coating) and slurry application has demonstrated improvement in seed germination, crop yield and water productivity and made soybean–wheat cultivation more economical. This approach presents a feasible solution to achieving a viable production system of soybean and wheat crops by reducing irrigation amounts in the IGP of India, as well as other comparable ecological places worldwide. [ABSTRACT FROM AUTHOR]

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3- [RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03 m mol H2Om-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7 mol H2O m2 s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6 kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha-1) and biological yield (8.37 t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agroecological regions. [ABSTRACT FROM AUTHOR]

This paper deals with the significance of precision farming in addressing challenges faced by Indianagriculture. This study aims to advance our understanding of plant sensors and their effectiveness inpredicting plant nitrogen (N) status and crop yields. It seeks to establish a reliable relationship between sensor measurements and actual leaf N content using machine learning algorithms, GreenSeeker, chlorophyll meter, and spectro-radiometer to provide a more accurate and efficient means of N management. The study focuses on variable N-fertilized wheat crops. Increments of 30kg/ha in N application rate increased SPAD values and NDVI both indices showing peak values at 150 kg N/ha. There existed a nearly linear relationship between sensor indices with leaf N content within the boundaries of selected N rates (0 -240 kg N/ha). Further, a correlation analysis of differentsensor (Chlorophyll meter, GreenSeeker) indices with leaf N content was positive and significant (R²=0.86-0.95). Spectro-radiometer-based spectral-derived indices gave a good prediction of plant N status as indicated by an R² value of 0.71. Apart from these sensors, machine learning tools also revealed a very strong positive correlation(0.974) among studied parameters; the heat map generated depicted multicollinearity, which could be considered in further analysis for the predictive model. Overall, the N stress in the wheat crop can be monitored on a real-time basis for determining the N fertilization in this crop. [ABSTRACT FROM AUTHOR]

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3- [RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03 m mol H2Om-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7 mol H2O m² s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6 kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha-1) and biological yield (8.37 t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agroecological regions. [ABSTRACT FROM AUTHOR]