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With increasing adoption of residue retention over soil surface, there is an urgent need to investigate the effect of residue on soil water moderation and soil temperature distribution during crop growth period. Therefore, an investigation was carried out on wheat crop, grown under long term experiment integrating a dual strategy of field experiment and crop simulation modelling. The major aim of the present study was to simulate the conservation agriculture effects on soil water profile and soil thermal regime in wheat crop under maize based cropping system using APSIM—Agriculture Production System Simulator) model. The experiment followed a split plot design with three replications, evaluating two tillage practices: zero tillage with residue retention (ZT + R) and conventional tillage with residue incorporation (CT + R). . The APSIM model was calibrated using measured data from the 2018–19 cropping season and validated with independent datasets from 2019–20. Model performance was rigorously evaluated using statistical metrics such as the coefficient of determination (R 2 ), root mean square error (RMSE), normalized RMSE (nRMSE), Willmott’s index of agreement (D-index), and mean bias error (MBE). The results indicated that the model accurately simulated crop phenology, leaf area index, aboveground biomass, and grain yield under both tillage treatments. Results of validation of APSIM model showed good agreement for simulated soil temperature (RMSE = 1.12–1.87 °C, nRMSE = 0.08–0.12 and R 2  = 0.67–0.71) and soil water (RMSE = 0.017–0.031 cm 3 cm -3 , nRMSE = 0.07–0.13 and R 2  = 0.66—0.80) in both CT + R and ZT + R treatments. Simulated soil water content (SWC) was lower in the CT + R treatment compared to ZT + R. The model simulated transpiration and drainage were higher under ZT + R, whereas evaporation was greater in CT + R, reflecting the influence of residue management and tillage on soil moisture dynamics. APSIM showed that the soil temperature was more in CT + R than ZT + R for 0–60 cm soil depth. Additionally, diurnal fluctuations in soil temperature were more pronounced in the surface layer (0–15 cm) than in the deeper layer (45–60 cm) under both treatments. The analysis demonstrated the capabilities of APSIM to capture the effect of tillage practices and cropping system on soil water profile, temperature changes and crop growth.

In water scarce regions of South Asia, diversification of rice with maize is being advocated towards sustainability of cereal-based cropping systems. Adoption of innovative agronomic management practices, i.e., conservation agriculture (CA) and sub-surface drip irrigation (SSDI) are considered as key strategies for much needed interventions to address the challenges of water scarcity under projected climate change. Benefits from CA and SSDI concerning water economy are well-established, however, information about their complementarity and water budgeting in cereal-based systems are lacking. A field study was conducted with process-based model (HYDRUS-2D) to understand water transport, root water uptake and components of soil water balance in maize grown in rotation with wheat after five years of continuous adoption of conservation agriculture. In this study, altogether eight treatments comprising of 6 CA+ treatments (CA coupled with SSDI); permanent beds using sub-surface drip (PB-SSD) with (WR) and without (WOR) crop residue at different N rates, 0, 120 and 150 kg N ha −1 were compared with CA (PB using furrow irrigation-FI with crop residue-120 kg N ha −1 ) and conventional tillage practices (CT) (CT using FI without crop residue-120 kg N ha −1 ). Results showed that the model could simulate the daily changes in profile soil water content with reasonable accuracy in all the treatments. Simulated soil water balance indicated higher cumulative root water uptake (CRWU), lower cumulative evaporation (CE) and higher soil water retention in CA+ (PB-SSD+ crop residue at 150 and 120 kg N ha −1 ) than CA and CT plots. Hydrus-2D model efficiency > 0, RMSE between 0.009–0.026 and R 2 value between 0.80–0.92 at P  < 0.01 indicates that the model is performing efficiently. The mean evaporation from CA+ treatments was 10 and 36% less than CA and CT treatments, respectively. On average, CRWU under CA+ treatments were 14–48% higher than FI treatments. The mean cumulative deep drainage in CA+ plots was 80–100 mm less than CA and CT plots. In CA+ based plots significantly higher biomass production and radiation use efficiency were observed with reduced water use than CA and CT. Therefore, the study justifies the water-saving nature of CA+, while maintaining higher productivity and meeting the transpiration demand of crops and halting unnecessary evaporation and deep drainage losses.

Agricultural field experiments are costly and time-consuming, and often struggling to capture spatial and temporal variability. Mechanistic crop growth models offer a solution to understand intricate crop-soil-weather system, aiding farm-level management decisions throughout the growing season. The objective of this study was to calibrate and the Crop Environment Resource Synthesis CERES-Maize (DSSAT v 4.8) model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based maize system. The model was also used to investigate the relationship between, temperature, nitrate and ammoniacal concentration in soil, and nitrogen uptake by the crop. Additionally, the study explored the impact of contrasting tillage practices and fertilizer nitrogen management options on maize yields. Using field data from 2019 and 2020, the DSSAT-CERES-Maize model was calibrated for plant growth stages, leaf area index-LAI, biomass, and yield. Data from 2021 were used to evaluate the model's performance. The treatments consisted of four nitrogen management options, viz., N0 (without nitrogen), N150 (150 kg N/ha through urea), GS (Green seeker-based urea application) and USG (urea super granules @150kg N/ha) in two contrasting tillage systems, i.e., CA-based zero tillage-ZT and conventional tillage-CT. The model accurately simulated maize cultivar’s anthesis and physiological maturity, with observed value falling within 5% of the model’s predictions range. LAI predictions by the model aligned well with measured values (RMSE 0.57 and nRMSE 10.33%), with a 14.6% prediction error at 60 days. The simulated grain yields generally matched with measured values (with prediction error ranging from 0 to 3%), except for plots without nitrogen application, where the model overestimated yields by 9–16%. The study also demonstrated the model's ability to accurately capture soil nitrate–N levels (RMSE 12.63 kg/ha and nRMSE 12.84%). The study concludes that the DSSAT-CERES-Maize model accurately assessed the impacts of tillage and nitrogen management practices on maize crop’s growth, yield, and soil nitrogen dynamics. By providing reliable simulations during the growing season, this modelling approach can facilitate better planning and more efficient resource management. Future research should focus on expanding the model's capabilities and improving its predictions further.

Conservation agriculture (CA)-based practices have been promoted and recouped, as they hold the potential to enhance farm profits besides a consistent improvement in soil properties. A 7 years' field experiment consisting of three crop establishment practices viz., zero-till flatbed (ZTFB), permanent beds (PNB), conventional system (CT) along with the three-nutrient management; nutrient expert-based application (NE), recommended fertilization (RDF), and farmers’ fertilizer practice (FFP), was carried out from 2013 to 2020. The CA-based practices (ZTFB/PNB) produced 13.9–17.6% greater maize grain-equivalent yield (MGEY) compared to the CT, while NE and RDF had 10.7–20% greater MGEY than the FFP. PNB and ZTFB gave 28.8% and 24% additional net returns than CT, while NE and RDF had 22.8% and 17.4% greater returns, respectively over FFP. PNB and ZTFB had 2.3–4.1% (0.0–0.20 m soil layers) lower bulk density than the CT. Furthermore, microbial biomass carbon (MBC) increased by 8–19% (0.0–0.50 m soil layers) in ZTFB/PNB over the CT, and by 7.6–11.0% in NE/RDF over FFP. Hence, CA-based crop establishment coupled with the NE or RDF could enhance the yields, farm profits, soil properties of the maize–chickpea rotation, thereby, could sustain production in the long run.

The conventional tillage based rice-wheat system (RWS) in Indo-genetic plains (IGP) of South Asia is facing diverse challenges like increase in production cost and erratic climatic events. This results in stagnated crop productivity and declined farm profitability with increased emission of greenhouse gases. Therefore, 3-year multi-location farmer’s participatory research trial was conducted to assess the impact of crop establishment and residue management techniques on crop productivity, economic profitability and environmental footprints in RWS. The aim of this study was to analyze the effect of combinations of improved agronomic technologies compared to farmer’s practices (FP) on crop productivity, profitability, resource use efficiency and environmental footprints. The experiment had six scenarios that is, S1-Farmer’s practice; Conventional tillage (CT) without residue; S2-CT with residue, S3- Reduced tillage (RT) with residue + Recommended dose of fertilizer (RDF); S4-RT/zero tillage (ZT) with residue + RDF, S5-ZT with residue + RDF + green seeker + tensiometer + information & communication technology + crop insurance and S6- S5 + site specific nutrient management. Climate smart agriculture practices (CSAPs; mean of S4, S5 and S6) increase system productivity and farm profitability by 10.5% and 29.4% (on 3 yrs’ mean basis), whereas, improved farmers practices (mean of S2 and S3) resulted in only 3.2% and 5.3% increments compared to farmer’s practice (S1), respectively. On an average, CSAPs saved 39.3% of irrigation water and enhanced the irrigation and total water productivity by 53.9% and 18.4% than FP, respectively. In all the 3-years, CSAPs with high adaptive measures enhanced the energy-use-efficiency (EUE) and energy productivity (EP) by 43%–54% and 44%–61%, respectively than FP. In our study, global warming potential (GWP), GHG emission due to consumption energy and greenhouse gas intensity were recorded lower by 43%, 56% and 59% in Climate Smart Agriculture (CSA) with high adaptive measures than farmers practices (3652.7 kg CO2 eq. ha−1 yr−1, 722.2 kg CO2 eq. ha−1 yr−1 and 718.7 Mg kg−1 CO2 eq. ha−1 yr−1). The findings of the present study revealed that CSA with adaption of innovative measures (S6) improved 3-year mean system productivity by 10.5%, profitability by 29.4%, water productivity and energy productivity by 18.3% and 48.9%, respectively than FP. Thus, the results of our 3-year farmer’s participatory study suggest that in a RW system, climate smart agriculture practices have better adaptive capacity and could be a feasible option for attaining higher yields, farm profitability, energy-use efficiency and water productivity with sustained/improved environmental quality in smallholder production systems of Eastern IGP of India and other similar agro-ecologies of South Asia. Finally, the adoption of these CSAPs should be promoted in the RW rotation of IGP to ensure food security, restoration of soil health and to mitigate climate change, the key sustainable development goals (SDGs).

Increasing crop productivity, along with increasing water, nutrient, and energy use efficiency, is vital for sustainable food production. Globally, the maize–wheat system contributes to this goal by improving resource efficiency and ensuring food security. A field experiment was conducted in Northwest India to optimize water, nutrient, and energy use in a maize–wheat rotation system. This study evaluated four crop management systems (conventional chemical, organic, integrated, and natural farming), two irrigation methods (surface drip and subsurface drip) and two irrigation schedules (irrigation at 80% and 100% crop evapotranspiration, ETc) via a randomized complete block design over 2 years. A control with conventional flood irrigation and recommended fertilizer doses was also included for comparison. The integrated crop management system resulted in the highest productivity in terms of the maize equivalent yield (10.7 t ha−1), outperforming organic and natural farming systems by 16.8% and 32.4%, respectively, while remaining statistically equal to the conventional chemical system. System productivity was not affected by the type of drip irrigation; however, irrigation scheduling significantly influenced the grain yield of wheat alone. Combining the integrated production system with subsurface drip irrigation at 80% ETc increased productivity by 8.0%, net returns by 15.3%, reduced irrigation water use by 51.2%, and improved irrigation water productivity by 113.8% compared with conventional flood irrigation and soil application of recommended fertilizers. Additionally, the input energy was reduced by 27.9%, the output energy increased by 3.7%, and consequently, the energy use efficiency and energy productivity improved by 44.3% and 44.3%, respectively, compared with those of conventional flood irrigation and soil application with the recommended fertilizer doses. In conclusion, subsurface drip irrigation at 80% ETc, coupled with integrated crop management, significantly increased water, nutrient, and energy use efficiency, which is essential for sustainable food production in the maize–wheat cropping system.

Gaining insights into the patterns of hydroclimatic elements such as inflows to dams is essential to adeptly strategize and oversee water resource planning. For this study, we focused on Karuppanadhi and Gundar dams within the Chittar River Basin in Tamil Nadu. We employed various time series trend assessment methods – Mann–Kendall (MK), modified Mann–Kendall (MMK), Sen slope estimator, and innovative trend analysis (ITA). Furthermore, we conducted change point detection analysis using homogeneity tests, namely Pettitt's test, standard normal homogeneity test (SNHT), and Buishand test. The analysis was carried out across three-time scales: monthly, seasonal, and annual for 30 years (1991–2020) span. Results revealed declining trends significantly across all three timescales for the Karuppanadhi dam. Whereas for the Gundar dam, notable trends included increased patterns in January, March, December, and the winter season, while other months/seasons showed statistically decreasing trends. ITA exhibited greater sensitivity in identifying trends at monthly and seasonal scales, indicating its superior trend detection over MK and MMK methods. Change point analysis of trends identified a rising trend in August post-2017 for both dams. Other change points indicated decreasing inflow trends thereafter. Analysing trends and change points in dam inflows aid decisions on water resources management.

Microbial diversity formed by ages of evolution in soils plays an important role in sustainability of crop production by enriching soil and alleviating biotic and abiotic stresses. This diversity is as an essential part of the agro-ecosystems, which is being pushed to edges by pumping agrochemicals and constant soil disturbances. Consequently, efficiency of cropping system has been decreasing, aggravated further by the increased incidence of abiotic stresses due to changes in climatic patterns. Thus, the sustainability of agriculture is at stake. Understanding the microbiota inhabiting phyllosphere, endosphere, spermosphere, rhizosphere, and non-rhizosphere, and its utilization could be a sustainable crop production strategy. This review explores the available information on diversity of beneficial microbes in agricultural ecosystem and synthesizes their commercial uses in agriculture. Microbiota in agro-ecosystem works by nutrient acquisition, enhancing nutrient availability, water uptake, and amelioration of abiotic and abiotic stresses. External application of such beneficial microbiota or microbial consortia helps in boosting plant growth and provides resistance to drought, salinity, heavy metal, high-temperature and radiation stress in various crop plants. These have been instrumental in enhancing tolerance to diseases, insect pest and nematodes in various cropping system. However, studies on the microbiome in revolutionary production systems like conservation agriculture and protected cultivation, which use lesser agrochemicals, are limited and if exploited can provide valuable input in sustainable agriculture production.

Enhancing soil organic carbon (SOC) is an important strategy to sustain and improve the soil quality, mitigate climate change and increase crop productivity under intensive tillage-based rice–wheat (RW) system in the Indo-Gangetic Plains (IGP) of South Asia. Therefore, the effects of tillage, crop establishment, and residue management practices on total as well as different pools of SOC in a sandy loam after 6 years of RW system were studied. The imposed three main plot treatments to the rice plots were: (1) ZTDSR, zero till dry seeded rice; (2) CTDSR, conventional till dry seeded rice; and (3) PTR, conventional puddled transplanted rice, and the three sub-plot treatments in succeeding wheat were (i) CTW − R, conventional tillage (CT) wheat with both rice and wheat residues removed; (ii) ZTW − R, zero tillage (ZT) wheat with both the residues removed and (iii) ZTW + R, ZT wheat with rice residue. Total soil organic content increased by 6.5–12.5% and 3.1–12.9% in different soil layers up to 0–60 cm depth in ZTDSR followed by ZTW + R over PTR followed by CTW − R practices, respectively. The corresponding increase of the oxidizable C was 4.2–28.2% and 8.2–8.5%, respectively. Significant enhancement in all the carbon pools (non-labile, less labile, labile, very labile pools, water soluble and microbial biomass carbon) and glomalin content were also recorded in ZTW + R treatment. The carbon management index was significantly higher in ZTW + R than ZTW − R and CTW − R treatments. In conservation-based agriculture systems, the principal component analysis revealed that passive pools of SOC and microbial biomass carbon were the most promising and reliable indicators for assessing soil quality. This study showed that adoption of ZTDSR followed by ZTW + R was the better crop production strategy for increasing C-sequestration, improving and sustaining the soil quality and crop productivity in the RW system. This practice also provides an opportunity to retain crop residues as an alternative to burning, which causes severe air pollution in the RW system in the IGP of South Asia.

Field experiments were conducted to study the effect of irrigation and nitrogen levels on radiation use efficiency (RUE), radiation extinction coefficient (κ) and temporal variation of leaf area index (LAI) and fraction intercepted photosynthetically active radiation (fIPAR). The LAI of wheat increased with increase in irrigation and nitrogen levels. The fIPAR also followed trend similar to LAI. The LAI and fIPAR showed logarithmic relationship with R2 value of 0.92 and 0.93 for the years 2013–2014 and 2014–2015, respectively. The κ value varied between 0.41 and 0.78 and was significantly affected by nitrogen levels but was not influenced by irrigation levels. The grain and above ground biomass (AGB) yields of wheat were not affected significantly by irrigation levels. However, application of 160 kg N ha−1 (N160) registered higher grain (12–33%) and AGB (22–25%) yeilds as compared to that with application of 40 kg N ha−1 (N40). Similar to AGB, the total intercepted photosynthetically active radiation (TIPAR) was not affected by irrigation levels but N160 treatment registered 9–20% higher TIPAR compared to N40 treatment. The linear relationship between TIPAR and AGB revealed that 83–86% variation in AGB yield of wheat can be explained by TIfIPAR. The RUE of wheat under three irrigations (I3) was 6 and 18% higher (P < 0.05) than the five (I5) and two (I2) irrigation treatments, respectively for the year 2013–2014. However, there was no significant effect of irrigation on RUE of wheat in the year 2014–2015. N160 treatment registered 5–13% higher RUE than the N40 treatment. Thus wheat may be grown with three irrigations (CRI, flowering and grain filling) and 160 kg N ha−1 for higher RUE without significant reduction in AGB of wheat compared to five irrigation levels in semi-arid location of Delhi region.