Assessing the effect of soil cultivation methods and genotypes on crop yield components, yield and soil properties in wheat (Triticum aestivum L.) and Rice (Oryza sativa L.) cropping system.

BACKGROUND: The rice-wheat cropping system is the prevailing agricultural method in the North-Western states of India, namely in the Indo-Gangetic plains. The practice of open burning of rice residue is frequently employed for expedient land preparation, but it has significant adverse impacts on both the environment and human health. These include the emission of greenhouse gases, loss of nutrients, elevated concentrations of particulate matter (PM), and disruption of the biological cycle. This research aims to investigate the implementation of effective management strategies in the rice-wheat cropping system, namely via the use of tillage-based crop cultivation techniques, stubble retention, and integration approaches. The objective is to enhance soil health features in order to augment crop yield and improve its attributes. RESULTS: The research was carried out using a split plot experimental design, consisting of three replications. The main plot consisted of four different cultivation methods, while the subplot included three genotypes of both rice and wheat. The research demonstrates the enhanced efficacy of residue application is significantly augmenting soil nutrient concentrations compared to standard tillage practices (P < 0.05). This was accomplished by an analysis of soil nutrient levels, namely nitrogen (N), phosphorus (P), potassium (K), and organic carbon (OC), at a depth of 0-15 cm. The implementation of natural farming, zero tillage, and reduced tillage practices resulted in decreases in rice grain yields of 34.0%, 16.1%, and 10.8%, respectively, as compared to conventional tillage methods. Similarly, the implementation of natural farming, zero tillage, and reduced tillage resulted in reductions in wheat grain yields of 59.4%, 10.9%, and 4.6% respectively, in comparison to conventional tillage practices. CONCLUSION: Regarding the individual crop genotypes investigated, it was continuously observed that Him Palam Lal Dhan 1 and HPW 368 displayed considerably greater grain yields for both rice and wheat during the two-year experimental period. Furthermore, when considering different cultivation methods, conventional tillage emerged as the most effective approach for obtaining higher productivity in both rice and wheat. Additionally, Him Palam Lal Dhan 1 and HPW 368 exhibited superior performance in terms of various crucial yield components for rice (such as panicle density, grains per panicle, panicle weight, and test weight) and wheat (including effective tiller density, grains per spike, spike weight, and 1000-grain weight).

Mycorrhizal effects on crop yield and soil ecosystem functions in a long-term tillage and fertilization experiment.

It is well understood that agricultural management influences arbuscular mycorrhizal (AM) fungi, but there is controversy about whether farmers should manage for AM symbiosis. We assessed AM fungal communities colonizing wheat roots for three consecutive years in a long-term (> 14 yr) tillage and fertilization experiment. Relationships among mycorrhizas, crop performance, and soil ecosystem functions were quantified. Tillage, fertilizers and continuous monoculture all reduced AM fungal richness and shifted community composition toward dominance of a few ruderal taxa. Rhizophagus and Dominikia were depressed by tillage and/or fertilization, and their abundances as well as AM fungal richness correlated positively with soil aggregate stability and nutrient cycling functions across all or no-tilled samples. In the field, wheat yield was unrelated to AM fungal abundance and correlated negatively with AM fungal richness. In a complementary glasshouse study, wheat biomass was enhanced by soil inoculum from unfertilized, no-till plots while neutral to depressed growth was observed in wheat inoculated with soils from fertilized and conventionally tilled plots. This study demonstrates contrasting impacts of low-input and conventional agricultural practices on AM symbiosis and highlights the importance of considering both crop yield and soil ecosystem functions when managing mycorrhizas for more sustainable agroecosystems.

Drought effects on trait space of winter wheat are independent of land management.

Investigating plant responses to climate change is key to develop suitable adaptation strategies. However, whether changes in land management can alleviate increasing drought threats to crops in the future is still unclear. We conducted a management × drought experiment with winter wheat (Triticum aestivum L.) to study plant water and vegetative traits in response to drought and management (conventional vs organic farming, with intensive vs conservation tillage). Water traits (root water uptake pattern, stem metaxylem area, leaf water potential, stomatal conductance) and vegetative traits (plant height, leaf area, leaf Chl content) were considered simultaneously to characterise the variability of multiple traits in a trait space, using principal component analysis. Management could not alleviate the drought impacts on plant water traits as it mainly affected vegetative traits, with yields ultimately being affected by both management and drought. Trait spaces were clearly separated between organic and conventional management as well as between drought and control conditions. Moreover, changes in trait space triggered by management and drought were independent from each other. Neither organic management nor conservation tillage eased drought impacts on winter wheat. Thus, our study raised concerns about the effectiveness of these management options as adaptation strategies to climate change.

Land use drives the distribution of free, physically protected, and chemically protected soil organic carbon storage at a global scale.

Soil organic carbon (SOC) sequestration is increasingly emphasized as a climate mitigation solution, as scientists, policy makers, and land managers prioritize enhancing belowground C storage. To identify key underlying drivers of total SOC distributions, we compiled a global dataset of soil C stocks held in three chemical forms, reflecting different mechanisms of organic C protection: free particulate organic C (fPOC), physically protected particulate organic C (oPOC), and mineral-protected soil organic C (mSOC). In our dataset, these three SOC pools were differentially sensitive to the effects of climate, soil mineralogy, and ecosystem type, emphasizing the importance of distinguishing between physical and chemical C protection mechanisms. C stocks in all three pools varied among ecosystems: cropland soils stored the least amount in each pool, with forest and grassland soils both containing significantly more fPOC (40%-60% greater in each ecosystem) than croplands. oPOC stocks did not significantly differ from zero in croplands but were substantial in forest and grassland soils. Meanwhile, mSOC stocks were the greatest in grasslands and shrublands (90%-100% greater than croplands). In cropland soils, there were no major effects of tillage on C storage in any of the three pools, while manure addition enhanced mSOC stocks, especially when added with inorganic N. Thus, the human land use intensity in croplands appears to reduce SOC storage in all major pools, depending upon management; retaining native vegetation should be emphasized to maintain current global SOC stocks.

Landscape-scale predictions of future grassland conversion to cropland or development.

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R2 = 0.89 [range: 0.83-0.96], root mean squared error [RMSE] = 9.29 ha [range: 2.83-22.77 ha]; proportional loss model: weighted group mean R2 = 0.74 [range: 0.64-0.87], RMSE = 0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.

Predicciones a escala de paisaje de la conversión futura de los pastizales a tierras de cultivo o desarrollo Resumen La planificación de la conservación de los pastizales a menudo se centra en paisajes de alto riesgo, pero muchos modelos de conversión de pastizales no están diseñados para optimizar la planificación de la conservación porque carecen de evaluaciones de riesgo multidimensionales y están mal alineados con las escalas ecológicas y de conservación. Para ayudar a la planificación de la conservación de los pastizales, desarrollamos modelos a escala de paisaje en escalas relevantes que predicen la pérdida futura (2021­2031) total y proporcional de pastizales no protegidos a tierras de cultivo o desarrollo. Desarrollamos modelos para 20 ecorregiones a lo largo de los Estados Unidos en relación con la conversión pasada (2011­2021) con un conjunto de covariables en modelos de regresión de bosque aleatorio y aplicando los modelos a covariables contemporáneas para predecir la pérdida futura. En general, los modelos de pérdida de pastizales funcionaron bien y el poder explicativo varió espacialmente entre las ecorregiones (modelo de pérdida total: media ponderada del grupoR2 = 0.89 [rango 0.83­0.96], error cuadrático medio [RMSE] = 9,29 ha [rango 2,83­22,77 ha]; modelo de pérdidas proporcionales: R2 medio ponderado del grupo = 0,74 [rango 0,64­0,87], RMSE = 0,03 [rango 0,02­0,06]). La cantidad de cultivos en el paisaje y la distancia a ciudades, plantas de etanol y operaciones concentradas de alimentación animal tuvieron una importancia variable alta en ambos modelos. La pérdida total de pastos fue mayor cuando había cantidades moderadas de pastos, cultivos o desarrollo (∼50%) en el paisaje. La pérdida proporcional de pastos fue mayor cuando había menos pastos (∼<30%) y más cultivos o desarrollo (∼>50%). Algunas variables tuvieron un gran efecto sólo en un subconjunto de ecorregiones, por ejemplo, la pérdida de pastos fue mayor cuando ∼>70% del paisaje estaba inscrito en el Programa de Reservas de Conservación. Nuestros métodos proporcionan un enfoque sencillo y flexible para desarrollar capas de riesgo adecuadas para la conservación que pueden extenderse globalmente. Nuestros modelos de conversión pueden apoyar la planificación de la conservación al permitir la priorización en función del riesgo, que puede optimizarse aún más si se incorporan el valor biológico y el costo.

How biochar curbs the negative impacts of plastic mulching on soil enzymes and microorganisms while elevating crop yields in ridge-furrow systems.

Ridge-furrow tillage is an important tillage and yield enhancement method used in dry farming areas; however, the spatial characteristics of the soil microenvironment under ridge-furrow tillage and the response of crop yields to mulching and biochar addition are not known. In this study, we conducted a three-year field experiment in which mulch and biochar, alone or combined, were introduced into ridge-furrow tillage system to explore their interactive effects on soil enzyme activities, bacterial communities, functional genes, and crop yields. The findings reveal significant spatial differences in soil physicochemical composition, enzyme activity, microbial communities, and functional genes under ridge-furrow tillage, which are further exacerbated by the addition of mulching and biochar. Under the premise of ridge-furrow tillage, both mulching and biochar addition reduce the α diversity of bacterial communities. Mulching simplifies the bacterial network, while biochar addition has the opposite effect. Mulching and biochar addition increase the relative abundance of carbon, nitrogen, and phosphorus functional genes and accelerate nutrient cycling, especially on the ridges. Mulching significantly improves crop yield but is detrimental to alkaline phosphatase activity and the abundance of the gene function. The addition of biochar mitigates the harm of mulching and further increases alfalfa yield. These findings not only provide scientific support for optimizing ridge-furrow tillage but also deepen our comprehensive understanding of the soil biochemical environment after the addition of mulching and biochar, further revealing their positive effects on yield formation.

Cleaner tillage and irrigation options for food-water-energy-carbon synergism in wheat-maize cropping systems.

The conventional wheat-maize systems in the North China Plain are energy and water intensive with high carbon emissions. It is imperative to find cleaner production technologies for sustainable food-water-energy-carbon synergism. Here, a three-year field experiment was performed to explore the effects of two tillage modes and four irrigation regimes during wheat season on crop yield, economic profile, water use efficiency, energy utilization, and carbon footprint in typical wheat-maize cropping systems in the North China Plain. Pre-sowing irrigation resulted in the lowest crop yield and benefit profile. Pre-sowing + anthesis irrigation decreased economic benefit and water use efficiency with higher carbon footprint. Pre-sowing + jointing + anthesis irrigation led to the greatest energy consumption and greenhouse gas emissions. However, pre-sowing + jointing irrigation increased yield by 2.3-8.7%, economic benefit by 4.0-11.1%, water use efficiency by 7.4-10.9%, and net energy by 6.5-12.0% but reduced carbon footprint by 9.8-14.3% compared to pre-sowing + anthesis irrigation and pre-sowing + jointing + anthesis irrigation. The corresponding metrics in rotary tillage improved by 9.6%, 13.9%, 7.0%, and 14.2%, respectively, relative to subsoiling, whereas carbon footprint decreased by 12.4-17.2%. Besides, rotary tillage coupled with additional jointing irrigation obtained the highest value based on a Z-score method, which was recommended as a cleaner management practice to improve benefit return and water use efficiency with lower energy consumption and carbon footprint. This work provides valuable insights into food-water-energy-carbon nexus for ensuring food security and achieving environmental sustainability in the wheat-maize cropping systems.

Exploring the impact of cover crops in integrated pest management: pest and natural enemies population dynamics in no-tillage cotton production.

Conservation agriculture plays an important role in the sustainability of production systems, notably for globally significant crops such as cotton. This study explores the integration of the no-tillage system (NTS) with integrated pest management (IPM) by incorporating cover crops. The aim is to assess the impact of these living or dead covers on the management of insect populations, the indices diversity of phytophagous insects and natural enemies, and to investigate the population fluctuation of these arthropods, considering a variety of crops in the NTS before and after cotton planting. The trial, conducted over two consecutive cropping seasons in Mato Grosso do Sul State, Brazil, employed a randomised block design with four repetitions. The treatments included cover crops with the highest potential for use in the region, such as millet (Pennisetum glaucum glaucum L.), corn (Zea mays L.), brachiaria (Urochloa ruziziensis), black velvet bean (Stizolobium aterrimum), forage sorghum (Sorghum bicolor L.), and white oats (Avena sativa L.) and a mix of white oats with brachiaria. The results indicated that the black velvet bean stands out as the most effective cover crop, providing the best performance in terms of non-preference to the attack of the evaluated pest insects. Conversely, brachiaria proves to be more susceptible to infestations of Dalbulus maidis (DeLong and Wolcott) (Hemiptera: Cicadellidae), and Diabrotica speciosa (Germar, 1824) (Coleoptera: Chrysomelidae). The study underscores the relevance of the judicious choice of cover crops in IPM and in promoting agricultural biodiversity, creating a strategic tool to enhance the sustainability and efficiency of the cotton production system in the context of the NTS.

Development of a Method for Soil Tilth Quality Evaluation from Crumbling Roller Baskets Using Deep Machine Learning Models.

A combination tillage with disks, rippers, and roller baskets allows the loosening of compacted soils and the crumbling of soil clods. Statistical methods for evaluating the soil tilth quality of combination tillage are limited. Light Detection and Ranging (LiDAR) data and machine learning models (Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN)) are proposed to investigate roller basket pressure settings on soil tilth quality. Soil profiles were measured using LiDAR (stop and go and on-the-go) and RGB visual images from a Completely Randomized Design (CRD) tillage experiment on clay loam soil with treatments of roller basket down, roller basket up, and no-till in three replicates. Utilizing RF, SVM, and NN methods on the LiDAR data set identified median, mean, maximum, and standard deviation as the top features of importance variables that were statistically affected by the roller settings. Applying multivariate discriminatory analysis on the four statistical measures, three soil tilth classes were predicted with mean prediction rates of 77% (Roller-basket down), 64% (Roller-basket up), and 90% (No till). The LiDAR data analytics-inspired soil tilth classes correlated well with the RGB image discriminatory analysis. Soil tilth machine learning models were shown to be successful in classifying soil tilth with regard to onboard operator pressure control settings on the roller basket of the combination tillage implement.

Reseeding increased plant biomass production and soil fertility, but not plant species diversity in degraded grasslands in China.

Reseeding is a primary measure to restore degraded grasslands. Numerous studies have conducted experiments to investigate how the properties of grassland ecosystems respond to reseeding in China. However, there is a lack of summary of the results of these studies. Here, we conducted a hierarchical random-effects meta-analysis on the effects of reseeding on plant, soil, and microbial properties. We collected 19 variables, including plant biomass, species diversity and richness, soil organic carbon content, soil total and available nutrients, soil water content, soil microbial biomass and diversity, and enzyme activity, from a dataset of 1363 paired observations (degraded vs. reseeded) from 75 publications. The results showed that reseeding increased aboveground and belowground plant biomass by 70.2% and 68.0% on average, respectively. Reseeding increased soil organic carbon, phosphorus, and potassium contents, but did not affect soil nitrogen levels. Reseeding increased soil microbial nitrogen under conditions of tillage and fertilization. Reseeding age was found to have a positive correlation with species richness, while planting type, fertilization, and tillage did not have a significant impact on the species richness and diversity. Under the treatments of fertilization, non-tillage, and mix-planting, the response ratio of aboveground biomass to reseeding was positively correlated with the response ratio of species diversity to reseeding. Our results concluded that current reseeding practices can significantly improve plant biomass production and soil fertility but have minor effects on plant species diversity. These findings indicate that the preservation of biodiversity should receive greater attention from both researchers and practitioners in grassland remediation in China.

Enhancing soil quality and yield through microbial assisted in-situ residue management in rice-rice cropping system in Odisha, Eastern India.

Crop residue management has become more challenging with intensive agricultural operations. Zero tillage and crop residue returns, along with the enhancement of in-situ residue decomposition through microbial intervention, are essential measures for preserving and enhancing soil quality. To address this problem in view of stubble burning, field experiments were conducted in rice-rice (variety Swarna) cropping systems under lowland conditions, wherein the following different residue management practices were adopted viz., conventional cultivation (CC), residue incorporation (RI @ 6 t paddy straw ha-1), residue retention (RR @6 t paddy straw ha-1), and zero tillage (ZT). In this experiment, two microbial products i.e. solid microbial consortium (SMC) at 2.0 kg ha-1) and capsule (10 numbers ha-1), were evaluated in both Rabi (dry) and Kharif (wet) seasons under different residue management practices. The results on soil microbial properties showed that application of either SMC or capsule based formulation could significantly improve the soil organic carbon (SOC) content in ZT (9.51 g/kg), followed by RI (9.36 g/kg), and RR (9.34 g/kg) as compared to CC (7.61 g/kg). There were significant differences in the soil functional properties (AcP, AkP, FDA, and DHA) with microbial interventions across all residue management practices. SOC was significantly positive correlated with cellulase (R2 = 0.64, p < 0.001), ß-glucosidase (R2 = 0.61, p < 0.001), and laccase (R2 = 0.66, p < 0.001) activity; however, the regression coefficients varied significantly with microbial intervention. Moreover, the availability of N, P, and K in soil was significantly (p < 0.05) improved under microbial treatments with either RR or RI practices. Among the different methods of residues management practices, RI with microbial intervention registered a consistent yield improvement (8.4-17.8%) compared to conventional practices with microbial intervention. The present findings prove that the application of decomposing microbial consortia for in-situ rice residue management under field conditions significantly enhances soil quality and crop yield compared to conventional practices.

Effects of the comprehensive elimination of Spartina alterniflora along China's coast on blue carbon and scenario prediction after ecological restoration.

Salt marshes cover the largest area among the three types of traditional blue carbon ecosystems in China's coastal zone, with the introduced smooth cordgrass (Spartina alterniflora Loisel.) being dominant in these marshes. The effects of eradicating S. alterniflora nationwide and the subsequent ecological restoration on blue carbon are unclear. This paper evaluates the variation in blue carbon during the national S. alterniflora eradication campaign, which involves mechanical tillage from 2022 to 2025, and proposes three scenarios for blue carbon changes after native vegetation is reestablished by 2050. The results show that, in 2025, plant carbon stock and soil carbon stock will decrease by 1.38 Tg C and 1.21 Tg C, respectively, in the areas where S. alterniflora has been removed and managed. Although blue carbon is reduced in coastal wetlands in 2025, carbon stock is expected to increase in restored native vegetated wetlands by 2050. S. alterniflora is resilient and competitive, posing a high risk in secondary invasion. Scenario Ⅰ suggests that S. alterniflora marshes could almost recover to their original state from 2022, with 7.70 Tg C stored in plant and soil carbon stocks. Scenario Ⅱ involves native vegetated wetlands coexisting with invasive S. alterniflora marshlands, with a total carbon stock estimated at 7.15 Tg C, reflecting a decrease of 0.39 Tg C in soil carbon stock and by 0.16 Tg C in plant carbon stock. In Scenario Ⅲ, mudflats dominant and native vegetated habitats are reestablished only in suitable sites, with the total carbon stock estimated at 5.63 Tg C, a 26.9% decrease compared to 2022 levels. While eradicating invasive S. alterniflora and restoring native vegetation in China's coast enhance the ecosystem services, it reduces blue carbon stocks. Therefore, developing additional strategies to increase carbon storage in coastal wetlands is necessary.

Carbon trade-off and energy budgeting under conventional and conservation tillage in a rice-wheat double cropping system.

Amid rising energy crises and greenhouse gas (GHG) emissions, designing energy efficient, GHG mitigation and profitable conservation farming strategies are pertinent for global food security. Therefore, we tested a hypothesis that no-till with residue retaining could improve energy productivity (EP) and energy use efficiency (EUE) while mitigating the carbon footprint (CF), water footprint (WF) and GHG emissions in rice-wheat double cropping system. We studied two tillage viz., conventional and conservation, with/without residue retaining, resulting as CT0 (puddled-transplanted rice, conventional wheat -residue), CTR (puddled-transplanted rice, conventional wheat + residue), NT0 (direct seeded rice, zero-till wheat -residue), and NTR (direct seeded rice, zero-till wheat + residue). The overall results showed that the NTR/NT0 had 34% less energy consumption and 1.2-time higher EP as compared to CTR/CT0. In addition, NTR increased 19.8% EUE than that of CT0. The grain yield ranged from 8.7 to 9.3 and 7.8-8.5 Mg ha-1 under CT and NT system, respectively. In NTR, CF and WF were 56.6% and 17.9% lower than that of CT0, respectively. The net GHG emissions were the highest (7261.4 kg CO2 ha-1 yr-1) under CT0 and lowest (4580.9 kg CO2 ha-1 yr-1) under NTR. Notably, the carbon sequestration under NTR could mitigate half of the system's CO2-eq emissions. The study results suggest that NTR could be a viable option to offset carbon emissions and water footprint by promoting soil organic carbon sequestration, and enhancing energy productivity and energy use efficiency in the South Asian Indo-Gangetic Plains.

Impact of crop rotation and tillage operations on mitigating greenhouse gas emissions and evaluation of sustainability index in rice- wheat-green gram cropping system of north Bihar.

In North Bihar (NB), the conventional rice-wheat cropping system has led to soil, water, and environmental degradation, alongside low profitability, threatening sustainability. To address these concerns, a thorough field research was conducted over the course of three years to assess different methods of tillage and crop establishment in a rice, wheat, and greengram cycle. The experiment involved five scenarios with different combinations of crop rotation, tillage techniques, seeding procedures, fertilizer use, and irrigation strategies. Uncertainty analysis showed no significant change in mean and variance estimation among seven scenario replications at 5% significance level. Compared to traditional farming (SN-1), managing DSR-rice (SN-5) increased profitability by 17.56%, improved energy use efficiency (EUE) by 32.16%, and reduced irrigation by 24.76% and global warming potential (GWP) by 23.46%. Similarly, substituting zero tillage wheat (ZTW) SN-5 resulted in comparable profitability gains (18.25%) and significant improvements in irrigation (10 %), EUE (+48.65%), and GWP (-20 %) compared to SN-1. Green gram ZT also showed increased profitability (17.35%), with notable improvements in EUE (+38.31%) and GWP (-12.92%) compared to SN-1. Principal component and correlation analyses revealed relationships between total energy inputs, yields, economic returns, and sustainability indices, highlighting the benefits of crop rotation and tillage practices in optimizing resource use. The study suggests that compared to conventional systems, significant improvements in productivity, profitability, energy-use efficiency, and environmental mitigation can be achieved with Crop Rotation and Tillage Operations techniques.

Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota.

The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in mitigating climate change, there are very few studies that have assessed the overall spatial distribution of cover crops and tillage practices based on the farm's pedoclimatic and topographic characteristics. Hence, the primary objective of this study was to use multiple satellite-derived indices and environmental drivers to infer the level of tillage intensity and identify the presence of cover crops in eastern South Dakota (SD). We used a machine learning classifier trained with in situ field samples and environmental drivers acquired from different remote sensing datasets for 2022 and 2023 to map the conservation agriculture practices. Our classification accuracies (>80%) indicate that the employed satellite spectral indices and environmental variables could successfully detect the presence of cover crops and the tillage intensity in the study region. Our analysis revealed that 4% of the corn (Zea mays) and soybean (Glycine max) fields in eastern SD had a cover crop during either the fall of 2022 or the spring of 2023. We also found that environmental factors, specifically seasonal precipitation, growing degree days, and surface texture, significantly impacted the use of conservation practices. The methods developed through this research may provide a viable means for tracking and documenting farmers' agricultural management techniques. Our study contributes to developing a measurement, reporting, and verification (MRV) solution that could help used to monitor various climate-smart agricultural practices.

Impacts of conservation agriculture on crop yield and soil carbon sequestration: a meta-analysis in the Indian subcontinent.

In the quest of achieving sustainable crop productivity, improved soil health, and increased carbon (C) sequestration in the soil, conservation agriculture (CA) is increasingly being promoted and adopted in the Indian subcontinent. However, because some researchers from different regions of the world have reported reduced crop yield under CA relative to agriculture based on conventional tillage (CT), a meta-analysis has been conducted based on published research from India to evaluate the effects of CA on the yield of crops, accumulation of soil organic C as an index of soil health, and C sequestration in the soil in different regions and soil textural groups in the country. The meta-analysis is based on 544 paired observations under CA and CT from 35 publications from India was carried out using Meta Win 2.1 software. The results showed an overall significant (p < 0.05) reduction of 1.15% crop yield under CA compared to CT. Yearwise data showed a reduction of yields under CA from 2009 to 2016, but an increase from 2017 to 2020. Yield reduction was observed in the eastern, north-eastern, and southern regions of India but in western, northern, and north-western regions of the country, an increase was observed under CA rather than CT. Sandy loam and clayey soils exhibited higher crop yield under CA than under CT. Compared to CT, soil organic C content and soil C sequestration under CA increased by 8.9% and 7.3%, respectively. Also, in all the regions and soil textural groups both soil organic C accumulation and soil C sequestration were higher under CA than under CT. Factors such as rainfall, soil depth, available nitrogen (N), and total N significantly influenced the extent of yield increase/decrease and soil organic C accumulation under CA. Overall, results of the meta-analysis suggest that the promotion of CA in India will have to be location-specific taking into consideration the crops, soil attributes, and climatic conditions.

Response of nitrate leaching to no-tillage is dependent on soil, climate, and management factors: A global meta-analysis.

No tillage (NT) has been proposed as a practice to reduce the adverse effects of tillage on contaminant (e.g., sediment and nutrient) losses to waterways. Nonetheless, previous reports on impacts of NT on nitrate ( NO 3 - ) leaching are inconsistent. A global meta-analysis was conducted to test the hypothesis that the response of NO 3 - leaching under NT, relative to tillage, is associated with tillage type (inversion vs non-inversion tillage), soil properties (e.g., soil organic carbon [SOC]), climate factors (i.e., water input), and management practices (e.g., NT duration and nitrogen fertilizer inputs). Overall, compared with all forms of tillage combined, NT had 4% and 14% greater area-scaled and yield-scaled NO 3 - leaching losses, respectively. The NO 3 - leaching under NT tended to be 7% greater than that of inversion tillage but comparable to non-inversion tillage. Greater NO 3 - leaching under NT, compared with inversion tillage, was most evident under short-duration NT (<5 years), where water inputs were low (<2 mm day-1 ), in medium texture and low SOC (<1%) soils, and at both higher (>200 kg ha-1 ) and lower (0-100 kg ha-1 ) rates of nitrogen addition. Of these, SOC was the most important factor affecting the risk of NO3 - leaching under NT compared with inversion tillage. Globally, on average, the greater amount of NO3 - leached under NT, compared with inversion tillage, was mainly attributed to corresponding increases in drainage. The percentage of global cropping land with lower risk of NO3 - leaching under NT, relative to inversion tillage, increased with NT duration from 3 years (31%) to 15 years (54%). This study highlighted that the benefits of NT adoption for mitigating NO 3 - leaching are most likely in long-term NT cropping systems on high-SOC soils.

Soil organic carbon, aggregation and fungi community after 44 years of no-till and cropping systems in the Central Great Plains, USA.

Implementing sustainable agricultural land management practices such as no-till (NT) and diversified crops are important for maintaining soil health properties. This study focuses on the soil health of three long-term (44 years) tillage systems, NT, reduced tillage (RT), and conventional tillage (CT), in monoculture winter wheat-fallow (W-F) (Triticum aestivum L.) and wheat-soybean (W-S) (Glycine max (L.) Merrill) rotation. Soil organic carbon (C) was higher in NT than CT in the surface 0-5 cm, but not different in the 5-15 cm, demonstrating SOC stratification on the soil profile. The soil water content was higher in NT followed by RT and CT in the top 0-5 cm. We found an association between increased carbon, aggregation, and AMF biomass. Greater soil aggregation, carbon and AMF were observed in NT at 0-5 cm soil depth. The W-S cropping system had greater soil microbial community composition based on fungi biomass, AMF and fungal to bacteria ratio from phospholipid fatty acid analysis (PLFA). Large macroaggregates were positively correlated with total C and N, microbial biomass, Gram + , and AMF. Soil water content was positively correlated with macroaggregates, total C and N, and AC. No-till increased soil carbon content even after 44 years of cultivation. By implementing conservation tillage systems and diversified crop rotation, soil quality can be improved through greater soil organic C, water content, greater soil structure, and higher AMF biomass than CT practice in the Central Great Plains.

Contribution of Ammonium-Induced Nitrifier Denitrification to N2O in Paddy Fields.

Paddy fields are one of the most important sources of nitrous oxide (N2O), but biogeochemical N2O production mechanisms in the soil profile remain unclear. Our study used incubation, dual-isotope (15N-18O) labeling methods, and molecular techniques to elucidate N2O production characteristics and mechanisms in the soil profile (0-60 cm) during summer fallow, rice cropping, and winter fallow periods. The results pointed out that biotic processes dominated N2O production (72.2-100%) and N2O from the tillage layer accounted for 91.0-98.5% of total N2O in the soil profile. Heterotrophic denitrification (HD) was the main process generating N2O, contributing between 53.4 and 96.6%, the remainder being due to ammonia oxidation pathways, which was further confirmed by metagenomics and quantitative polymerase chain reaction (qPCR) assays. Nitrifier denitrification (ND) was an important N2O production source, contributing 0-46.6% of total N2O production, which showed similar trends with N2O emissions. Among physicochemical and biological factors, ammonium content and the ratio of total organic matter to nitrate were the main driving factors affecting the contribution ratios of the ammonia oxidation pathways and HD pathway, respectively. Moisture content and pH affect norC-carrying Spirochetes and thus the N2O production rate. These findings confirm the importance of ND to N2O production and help to elucidate the impact of anthropogenic activities, including tillage, fertilization, and irrigation, on N2O production.

Deciphering insights into rhizospheric microbial community and soil parameters under the influence of herbicides in zero-tillage tropical rice-agroecosystem.

Extensive use of chemicals like herbicides in rice and other fields to manage weeds is expected to have a lasting influence on the soil environment. Considering this rationale, we aimed to decipher the effects of herbicides, Pendimethalin and Pretilachlor, applied at 0.5 and 0.6 kg ha-1, respectively on the rhizosphere microbial community and soil characteristics in the tropical rice field, managed under zero tillage cultivation. The quantity of herbicide residues declined gradually since application up to 60 days thereafter it reached the non-detectable level. Most of the soil variables viz., microbial biomass, soil enzymes etc., exhibited slight reduction in the treated soils compared to the control. A gradual decline was observed in Mineral-N, MBC, MBN and enzyme activities. Quantitative polymerase chain reaction results showed maximal microbial abundance of bacteria, fungi and archaea at mid-flowering stage of rice crop. The 16 rRNA and ITS region targeted amplicons high throughput sequencing microbial metagenomic approach revealed total of 94, 1353, and 510 species for archaea, bacteria and fungi, respectively. The metabarcoding of core microbiota revealed that the archaea comprised of Nitrososphaera, Nitrosocosmicus, and Methanosarcina. In the bacterial core microbiome, Neobacillus, Nitrospira, Thaurea, and Microvigra were found as the predominant taxa. Fusarium, Clonostachys, Nigrospora, Mortierella, Chaetomium, etc., were found in core fungal microbiome. Overall, the study exhibited that the recommended dose of herbicides found to be detrimental to the microbial dynamics, though a negative relation between residues and soil variables was observed that might alter the microbial diversity. The outcomes offer a comprehensive understanding of how herbicides affect the microbial community in zero tillage rice soil, thus has a critical imputation for eco-friendly and sustainable rice agriculture. Further, the long-term studies will be helpful in elucidating the role of identified microbial groups in sustaining the soil fertility and crop productivity.