The global increases in the surface and groundwater nitrate (NO₃⁻) concentrations due to synthetic fertilizer input have emerged as major sustainability threats to terrestrial and aquatic ecosystems. Cover crops can reportedly reduce nitrate leaching from croplands. However, the underlying mechanisms and the effectiveness of cover crops in reducing nitrate leaching across species, soil types, agronomic management, and climates remain elusive. We conducted a global meta‐analysis to evaluate the effects of cover crops on nitrate leaching and water drainage. A random‐effects analysis was established to investigate seven moderating variables in 41 articles. Results showed that globally, cover crops reduced nitrate leaching by 69% compared with fallow while demonstrating no effect on water drainage. Overall, cover crops from Brassicaceae and Poaceae families showed the greatest effect with 75% and 52% reduction in nitrate leaching, respectively. Cover cropping on Ultisols, Histosols, and Inceptisols resulted in the greatest reduction in nitrate leaching (77%, 78%, and 77%, respectively). Greater efficacy of cover crops at reducing nitrate leaching was evident with increasing soil sand content. In general, cover crops appeared to perform better to reduce nitrate leaching in vegetable systems compared to field crops. Cover cropping on conventional tillage resulted in a 63% reduction in nitrate leaching compared with no‐tillage (50%) and reduced tillage (38%) systems. The impact of cover crops on water drainage was nonsignificant which implies that nitrate leaching control by cover crops is unlikely exerted through reducing water drainage. This study brings further insight into the intrinsic factors affecting cover crop efficacy and management practices that enhance cover crop potential in reducing nitrate leaching from agricultural systems.

Crop yield forecasting before harvesting is critical for the creation, implementation, and optimization of policies related to food safety as well as for agro-product storage and marketing. Crop growth and development are influenced by the weather. Therefore, models using weather variables can provide reliable predictions of crop yields. It can be tough to select the best crop production forecasting model. Therefore, in this study, five alternative models, viz., stepwise multiple linear regression (SMLR), an artificial neural network (ANN), the least absolute shrinkage and selection operator (LASSO), an elastic net (ELNET), and ridge regression, were compared in order to discover the best model for rice yield prediction. The outputs from individual models were used to build ensemble models using the generalized linear model (GLM), random forest (RF), cubist and ELNET methods. For the previous 21 years, historical rice yield statistics and meteorological data were collected for three districts under three separate agro-climatic zones of Chhattisgarh, viz., Raipur in the Chhattisgarh plains, Surguja in the northern hills, and Bastar in the southern plateau. The models were calibrated using 80% of these datasets, and the remaining 20% was used for the validation of models. The present study concluded that for rice crop yield forecasting, the performance of the ANN was good for the Raipur ($R_{cal}^2$ = 1, $R_{val}^2$= 1 and $RMS{E}_{cal}$ = 0.002, $RMS{E}_{val}$ = 0.003) and Surguja ($R_{cal}^2$ = 1, $R_{val}^2$= 0.99 and $RMS{E}_{cal}$ = 0.004, $RMS{E}_{val}$ = 0.214) districts as compared to the other models, whereas for Bastar, ELNET ($R_{cal}^2$ = 90, $R_{val}^2$= 0.48) and LASSO ($R_{cal}^2$ = 93, $R_{val}^2$= 0.568) performed better. The performance of the ensemble model was better compared to the individual models. For Raipur and Surguja, the performance of all the ensemble methods was comparable, whereas for Bastar, random forest (RF) performed better, with R² = 0.85 and 0.81 for calibration and validation, respectively, as compared to the GLM, cubist, and ELNET approach.

Residue management has become a new challenge for Indian agriculture and agricultural growth, as well as environmental preservation. The rice-wheat cropping system (RWCS) is predominantly followed cropping system in the Indo-Gangetic plain (IGP), resulting in generating a large volume of agricultural residue. Annually, India produces 620 MT of crop residue, with rice and wheat accounting for 234 MT of the surplus and 30% of the total. Farmers are resorting to burning crop residue due to the short window between paddy harvest and seeding of rabi season crops, namely wheat, potato, and vegetables, for speedy field preparation. Burning of residues pollutes the environment, thus having adverse effects on human and animal health, as well as resulted in a loss of plant important elements. This problem is particularly prevalent in rice-wheat-dominant states such as Punjab, Haryana, Uttarakhand, and Uttar Pradesh. If we may use in situ management as residue retention after chopper and spreader, sowing wheat with Happy seeder/zero drill/special drill with full residue load, full residue, or full residue load incorporation with conventional tillage, burning is not the sole approach for residue management. In addition, off-farm residues generated are being utilized for animal feed and raw materials for industries. While there are regional variations in many mechanization drivers and needs, a wide range of mechanization components can be transported to new places to fit local conditions. This article focuses on innovations, methods, and tactics that are relevant to various mechanization systems in particular geographical areas. This article also stresses the need for a thorough analysis of the amount of residue generated, residue utilization using modern mechanical equipment, and their positive and negative effects on crop yield and yield attributes, weed diversity, soil physic-chemical, biological properties, beneficial, and harmful nematode populations in the IGP, which will aid researchers and policymakers in farming research priorities and policy for ensuring sustainability in RWCS.

Clay–organic complexes (COC) impart chemical and physical protection to soil carbon (C). In the present study, the aim was to assess the long-term effects of different organic amendments on C stability in COC, distribution of the aggregates, C concentration in the aggregates and labile organic C fractions in the inceptisols located at the research farm situated in the semi-arid sub-tropical climate of India. The results showed that the COC, the percentage of large macroaggregates (LMA) (>2 mm) and the C associated with the aggregates decreased through the soil depths, whereas the other size fractions of soil aggregates (<2 mm) showed an increasing trend. The COC was significantly higher (4.4 times) in soil treatments where farmyard manures (FYM), green manure (GM) and biofertilizers (BF) were applied together (FYM + GM + BF). The organic amendments increased the proportion of LMA over control (no application of organic amendments) to a magnitude of 83 to 101% and the C associated with LMA to a magnitude of 0.48 to 9.8% over control in surface soil. On average, the combined application of FYM, GM and BF exhibited higher C accumulation in almost all soil aggregate fractions, except microaggregates (mA), i.e., (0.25–0.053 mm) size fractions, where application of FYM alone recorded the highest value. Averaged over soil depths, the particulate organic C (POC), dissolved organic C (DOC) and potassium permanganate oxidizable C (POXC) were significantly higher under integrated organic treatments than individual amendments. The significantly higher correlation between COC and the percentage of LMA and aggregate-associated C implied their direct role in soil aggregate formation and their stability. The carbon stability, i.e., retention time of humus in soil, was significantly correlated with soil organic carbon, dissolved organic carbon, particulate organic carbon, potassium permanganate oxidizable C, C mineralization (C_min), glomalin-related soil protein (GRSP), macroaggregate (MA)-associated C and rice equivalent yield (REY). Overall, the data suggest that the combined application of FYM + GM + BF promotes soil quality under rice–wheat rotation in inceptisols in semi-arid sub-tropical India.

Cover cropping in the fallow phase of winter wheat (Triticum aestivum L.)–fallow systems of the semiarid Pacific Northwest has been identified as an opportunity to build resilience and enhance farm profitability. Nine fall‐ and spring‐sown cover crops (CCs) grown during the traditional fallow period were evaluated at sites in the low and intermediate precipitation zones of the region in a 2‐year study (2021 and 2022). The fall‐sown CCs included winter pea (Pisum sativum L.), winter lentil (Lens culinaris Medik.), and fall species mix; and the spring‐sown CCs included common vetch, yellow mustard, lacy phacelia, tillage radish (Raphanus sativus L.), spring barley (Hordeum vulgare L.), and a spring species mix. CCs were evaluated for biomass production and impacts on soil water and weeds. CC growth was dependent on location, year, planting timing, and CC species. Fall‐sown CCs generally produced more biomass than spring‐sown CCs across site‐years, with winter peas and the fall species mix being most productive. Following a year of greater than average precipitation, no negative effects of CCs on fall soil moisture were observed at the intermediate precipitation site, while fall‐sown CCs reduced soil moisture at the low precipitation site. The suppressive effect of CCs on weeds ranged from null to moderate, depending on site, year, and CC seeding time. Fall‐sown CCs more consistently suppressed weeds than spring‐sown CCs. Additionally, fall‐sown CCs were terminated in the spring before weeds set viable seeds, saving a herbicide application and reducing herbicide pressure without exacerbating future weed issues. Overall, select fall‐sown CCs showed promise to enhance ecosystem services during the traditional fallow period.