A Guava-Based Hortipasture System for Mitigating Climate Change and Sustaining Fodder & Fruit Supply in Semi-Arid Regions of India

Hortipasture systems have huge potential to mitigate climate change via sequestering carbon along with sustaining fodder and fruit supply especially in semi-arid regions. Therefore to evaluate climate change mitigation, fruit and fodder production potential of 10 year old rainfed based Hortipasture system (Psidium guajava (Guava) + Cenchrus ciliaris + Stylosanthes hamata) established at Central Research Farm of ICAR-Indian Grassland and Fodder Research Institute (Bundelkhand region, Jhansi, Uttar Pradesh, India), carbon stock of tree and under storey pasture components was quantified along with fruit and forage production. The experimental site is drought prone semi arid region characterized by poor soil quality, harsh climate and erratic rainfall. Two cultivars of Guava (Lalit and Shweta) integrated with C. ciliaris + S. hamata were pruned to enhance fruit yield of 10 year old trees. The Cv. Lalit produced higher (10.40 %) fruit yield compared to Shweta and medium pruned trees produced highest fruit yield (Lalit: 15.46 t ha-1 & Shweta: 14.87 t ha-1) compared to unpruned and highly pruned trees. The under storey pasture production (C. ciliaris+ S. hamata) was 5.6 t DM ha-1. Total tree carbon stock in Guava ranged between 7.92 to 11.34 t ha-1 (Cultivar: Shweta-10.24 t ha-1and Lalit-9.20 t ha-1). Under storey pasture carbon stock ranged from 4.26 t ha-1 to 4.43 t ha-1. Total carbon stock potential of system (in biomass) ranged from 12.23 t ha-1 to 15.77 t ha-1 with 78.90−84.70 % and 15.30−21.10 % contribution of above and below ground biomass respectively to total carbon stock. Therefore in semi arid regions of India, where 90% of people depend on livestock for their livelihood security, establishment of Guava + C. ciliaris+ S. hamata based hortipasture system can enhance economic returns of the farmers and mitigate climate change via carbon sequestration in biomass leading to the offsetting of green house gases emission from livestock sector

Sensor-based precision nutrient and irrigation management enhances the physiological performance, water productivity, and yield of soybean under system of crop intensification

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 H2O m−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 agro-ecological regions

Simulated impacts of rise in temperature on kharif sorghum genotypes in Northern Transitional Zone of Karnataka, India

Thoroughly calibrated and validated DSSAT–CERES sorghum model’s seasonal analysis tool was used to evaluate the sensitivity of four kharif sorghum cultivars across three dates of sowing to changes in temperature. Five temperature scenarios (no change in temp, +0.5 °C, +1 °C, +1.5 °C and +2 °C) were created using 32 years’ observed past weather data (1985–2016). The model was run for all four cultivars across three dates of sowing under standard package of practices recommended to Northern Transition Zone of Karnataka for 32 years under rainfed conditions. Average of 32 years’ model simulated outputs revealed that kharif sorghum yield is sensitive to changes in temperature. Among the genotypes tested, CSH-16 gave the highest grain yield in all temperature scenarios across dates of sowing, and was followed by CSV-17, CSV-23 and CSH-23. Among the dates of sowing, across all temperature scenarios, early sowing (15th June) gave the highest grain yield as compared to later sowings (i.e., 30th June and 15th July of 2011 and 2012). Among the cultivars tested, irrespective of dates of sowing, for every 0.5 °C increase in temperature, the average yield reduction was found to be the highest in CSV-23 (9.39%), followed by CSV-16 (7.51%), CSH-23 (7.26%) and CSV-17 (7.25%), which shows the diferential response among cultivars to rise in temperature. This study indicates that as part of adaptation to future climates manipulation in sowing date as well as choice of heat tolerant cultivars would be required

Differentiating biological and chemical factors of top and deep soil carbon sequestration in semi-arid tropical Inceptisol: an outcome of structural equation modeling

Though soils sequester large amounts of carbon (C), variations in physical and chemical characteristics of top and deep layers necessitate the study of factors governing topsoil and deep soil C sequestration to predict land-use changes to alleviate climate change. Land-use systems involving pasture, trees, trees  pasture and fallow were considered. The upper soil (0–15 cm) had ∼12, 34 and 59% higher microbial biomass C than the 15–30, 30–45 and 45–60 cm layers, respectively. Fluorescein diacetate (FDA) and dehydrogenase activities had similar trends. Across the land uses, topsoil layers had ∼17% lower silt + clay (s + c) content than deep layers. Amorphous iron content significantly increased with soil depth. In the top two soil layers, s + c accounted for ∼19–30% of total soil organic carbon (SOC); in the next two layers s + c could store >30% of total SOC. Stepwise regression analysis revealed FDA to be the most significant biological driver for SOC sequestration. Structural equation modeling showed that biological factors controlled C sequestration in topsoil layers, while s + c and amorphous iron were the major factors of C sequestration in deep layers. Current land uses are largely deficient of SOC and have the potential to store an additional22 Mg CO2e per ha