Modeling maize growth and nitrogen dynamics using CERES-Maize (DSSAT) under diverse nitrogen management options in a conservation agriculture-based maize-wheat system.

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.

Scalable diversification options delivers sustainable and nutritious food in Indo-Gangetic plains.

Indo-Gangetic plains (IGP) of South Asia have supported bulk of human and bovine population in the region since ages, and a spectacular progress has been made in food production. However, malnutrition, diminishing total factor productivity, and natural resource degradation continue to plague this cereal-dominated region, which is also vulnerable to climate change. Addressing these challenges would require a transition towards diversifying cereal rotations with agroecological cropping systems. A study was, therefore, conducted at the experimental farm of ICAR-CSSRI, Karnal on crop diversification and sustainable intensification options using agro-ecological approaches such as Conservation Agriculture (CA) and diversified cropping systems to ensure food and nutritional security while sustaining the natural resources. On 2 years mean basis, CA-based cropping system management scenarios (mean of Sc2-Sc7) using diversified crop rotations; increased the system yield by 15.4%, net return by 28.7%, protein yield by 29.7%, while using 53.0% less irrigation water compared to conventional tillage (CT)-based rice-wheat system (Sc1). Maize-mustard-mungbean on permanent beds (PBs) (Sc4) recorded the highest productivity (+ 40.7%), profitability (+ 60.1%), and saved 81.8% irrigation water compared to Sc1 (11.8 Mg ha-1; 2190 USD ha-1; 2514 mm ha-1). Similarly, Sc5 (maize-wheat-mungbean on PBs) improved productivity (+ 32.2%), profitability (+ 57.4%) and saved irrigation water (75.5%) compared to Sc1. In terms of nutritional value, Sc5 was more balanced than other scenarios, and produced 43.8, 27.5 and 259.8% higher protein, carbohydrate and fat yields, respectively, compared to Sc1 (0.93, 8.55 and 0.14 Mg ha-1). Scenario 5 was able to meet the nutrient demand of 19, 23 and 32 additional persons ha-1 year-1 with respect to protein, carbohydrate and fat, respectively, compared to Sc1. The highest protein water productivity (~ 0.31 kg protein m-3 water) was recorded with CA-based soybean-wheat-mungbean (Sc6) system followed by maize-mustard-mungbean on PBs (Sc4) system (~ 0.29 kg protein m-3) and lowest under Sc1. Integration of short duration legume (mungbean) improved the system productivity by 17.2% and profitability by 32.1%, while triple gains in irrigation water productivity compared to CT-based systems. In western IGP, maize-wheat-mungbean on PBs was found most productive, profitable and nutritionally rich and efficient system compared to other systems. Therefore, diversification of water intensive cereal rotations with inclusion of legumes and CA-based management optimization can be potential option to ensure nutritious food for the dwelling communities and sustainability of natural resources in the region.

Energy and economic efficiency of climate-smart agriculture practices in a rice-wheat cropping system of India.

Intensive tillage operations, indiscriminate use of irrigation water, chemical fertilizers, and pesticides and crop biomass burning have made the conventional rice-wheat (RW) system highly energy-intensive and inefficient. In the recent past, portfolios of climate-smart agricultural practices (CSAP) have been promoted as a potential alternative to improve the energy efficiency in conventional RW system. Therefore, to evaluate the energy input-output relation, energy flow and economic efficiency in various combinations of crop management options, a 3-year (2014-2017) on-farm study was conducted at Karnal, India. Various portfolio of management practices; Sc1-Business as usual (BAU) or Conventional tillage (CT) without residue, Sc2-CT with residue, Sc3-Reduce tillage (RT) with residue + recommended dose of fertilizer (RDF), Sc4-RT/Zero tillage (ZT) with residue + RDF, Sc5-ZT with residue + RDF + GreenSeeker + Tensiometer, Sc6-Sc5 + Nutrient expert were investigated. Present study results revealed that net energy, energy use efficiency and energy productivity were 11-18, 31-51 and 29-53% higher under CSAP (mean of Sc4, Sc5 and Sc6) in RW system than Sc1, respectively. However, renewable and non-renewable energy inputs were 14 and 33% higher in Sc1 compared to CSAP (4028 and 49,547 MJ ha-1), respectively, it showed that BAU practices mostly dependents on non-renewable energy sources whereas CSAP dependents on renewable energy sources. Similarly, the adoption of CSAP improved the biomass yield, net farm income and economic efficiency by 6-9, 18-23 and 42-58%, respectively compared to Sc1. Overall, the adoption of CSAP could be a viable alternative for improving energy use efficiency, farm profitability and eco-efficiency in the RW system.

Farm typology for planning targeted farming systems interventions for smallholders in Indo-Gangetic Plains of India.

Due to complexity of smallholder farms, many times technologies with great potential fail to achieve the desired impact in leveraging productivity and profitability of the farming community. In the Indo-Gangetic Plains there is an urgent need to understand the diversity of farm households, identifying the main drivers deciding their system thus, classifying them into homogenous groups. In the present study, the diversity of smallholder farms was assessed using crop, livestock and income related characteristics and associated farm mechanization. Using principal component analysis and cluster analysis for 252 farm households, 4 farm types were identified i.e. Type 1. Small Farm households with cereal-based cropping system and subsistence livestock (39%), Type 2. Small Farm households with diversified cropping system dominated by cereal and fodder crops with only cattle herd (9%), Type 3. Marginal Farm household with diversified cropping system dominated by cash crop and herd comprising of only cattle (39%), Type 4. Marginal Farm household with diversified cropping system dominated by cereal crops and herd dominated by small ruminants (12%). Based on the constraints identified for different components of farming systems, low-cost interventions were planned for each farm type. These interventions have resulted in 84.8-103.2 per cent increase in the income of the farm HH under study suggesting usefulness of typology-based intervention planning in increasing income of small farm holders.

Water budgeting in conservation agriculture-based sub-surface drip irrigation in tropical maize using HYDRUS-2D in South Asia.

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 R2 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.

Soil enzymes activity: Effect of climate smart agriculture on rhizosphere and bulk soil under cereal based systems of north-west India.

In agriculture production system, soil enzymes are important indicators of soil quality. Measurements of soil quality parameter changes are essential for assessing the impact of soil and crop management practices. Keeping this in view, an experiment was conducted to evaluate the enzyme activities namely dehydrogenase (DHA), ß-glucosidase, acid and alkaline phosphatase (AcP & AlP), fluorescein diacetate hydrolases (FDH), cellulase, urease and aryl sulphatase in rhizosphere and bulk soil after 8 years of different management regimes. Soil organic carbon (SOC), moisture content and few enzyme indices such as enzymatic pH indicator (AcP/AlP), alteration index three (Al3) and geometric mean (GMea) were also measured. The treatments were conventional rice-wheat system (termed as scenario (Sc1), CT system), partial conservation agriculture (CA)-based rice-wheat-mungbean system (Sc2, PCA-RW), partial climate smart agriculture (CSA)-based rice-wheat-mungbean system (Sc3), partial CSA-based maize-wheat-mungbean system (Sc4), full CSA-based rice-wheat-mungbean system (Sc5), and full CSA-based maize-wheat-mungbean system (Sc6). Soil samples were collected from rhizosphere and away from roots (bulk soil) at 0-15 cm soil depth before sowing (from rhizosphere of previous crops), at maximum tillering, flowering, and after harvesting of wheat crop. Results showed that DHA activity was higher before sowing (59.8%), at maximum tillering (48.4%), flowering (8.6%) and after harvesting (19.1%) in rice based CSA systems (mean of Sc3 and Sc5) over maize based CSA systems (mean of Sc4 and Sc6) in rhizospheric soil. On average, ß-glucosidase activity was significantly higher in rhizospheric soils of rice based system over maize based CSA system. Before sowing of wheat, significantly higher (21.4%) acid phosphatase activity was observed in rhizosphere over bulk soils of maize based CSA system. Significantly higher alkaline phosphatase activity was observed before sowing of wheat in bulk soils of rice (25.3%) and maize (38.5%) based CSA systems over rhizospheric soils. Rice based CSA systems showed 27% higher FDH activity than maize based systems. Significant interaction effect was observed between the managements and enzymes. SOC played an important role in regulating the enzymes activity both in rhizosphere and bulk soil. Significant variation in AcP/AlP, Al3 and GMea was observed among the managements. Therefore, CSA managements are beneficial in improving enzyme activities not only in rhizosphere but also in bulk soil where residues are retained thereby may help in improving nutrient cycling.

Agricultural labor, COVID-19, and potential implications for food security and air quality in the breadbasket of India.

To contain the COVID-19 pandemic, India imposed a national lockdown at the end of March 2020, a decision that resulted in a massive reverse migration as many workers across economic sectors returned to their home regions. Migrants provide the foundations of the agricultural workforce in the 'breadbasket' states of Punjab and Haryana in Northwest India.There are mounting concerns that near and potentially longer-term reductions in labor availability may jeopardize agricultural production and consequently national food security. The timing of rice transplanting at the beginning of the summer monsoon season has a cascading influence on productivity of the entire rice-wheat cropping system. To assess the potential for COVID-related reductions in the agriculture workforce to disrupt production of the dominant rice-wheat cropping pattern in these states, we use a spatial ex ante modelling framework to evaluate four scenarios representing a range of plausible labor constraints on the timing of rice transplanting. Averaged over both states, results suggest that rice productivity losses under all delay scenarios would be low as compare to those for wheat, with total system productivity loss estimates ranging from 9%, to 21%, equivalent to economic losses of USD $674 m to $1.48 billion. Late rice transplanting and harvesting can also aggravate winter air pollution with concomitant health risks. Technological options such as direct seeded rice, staggered nursery transplanting, and crop diversification away from rice can help address these challenges but require new approaches to policy and incentives for change.

Indian agriculture, air pollution, and public health in the age of COVID.

Emerging evidence supports the intuitive link between chronic health conditions associated with air pollution and the vulnerability of individuals and communities to COVID-19. Poor air quality already imposes a highly significant public health burden in Northwest India, with pollution levels spiking to hazardous levels in November and early December when rice crop residues are burned. The urgency of curtailing the COVID-19 pandemic and mitigating a potential resurgence later in the year provides even more justification for accelerating efforts to dramatically reduce open agricultural burning in India.

Major Climate risks and Adaptation Strategies of Smallholder Farmers in Coastal Bangladesh.

Rural households in South Asia's coastal deltas face numerous livelihood challenges, including risks posed by climatic variability and extreme weather events. This study examines major climate risks, farmers' adaptation strategies, and the factors affecting the choice of those strategies using data collected from 630 households in southwestern coastal Bangladesh. Farmers identified cyclones, excessive rain and flooding, and salinity as direct climate risks. Increased crop diseases/pests and livestock diseases were perceived as indirect risks resulting from climatic variability. Farmers used multiple adaptation strategies against those risks such as modifications in farm management, use of savings and borrowing funds from family and neighbors, and periodically reducing household food consumption. Off-farm employment and seeking assistance from governmental as well as non-governmental organizations (NGOs) were also common adaptation strategies. The results show that male-headed households are more likely to change farming practices and reduce consumption compared with female-headed households that conversely tended to take assistance from NGOs as an adaptation strategy. Ownership of land and livestock, as well as farmers' prior exposure to climate change and educational training, also had a significant effect on the choice of adaptation strategy. Therefore, development interventions and policies that aimed at improving resource endowment and training to farmers on climatic risks and their adaptation strategies can help minimize the impact of climatic risks.

Temporal changes in soil microbial properties and nutrient dynamics under climate smart agriculture practices.

Climate smart agriculture (CSA) practices are emerging as sustainable alternative to conventional rice-wheat system to pull up natural resources degradation across south Asia. After five years of continuous CSA based experiment, a two years study was conducted to evaluate changes in microbial biomasses (microbial biomass carbon and nitrogen), enzyme activities (alkaline phosphatase, dehydrogenase and ß-glucosidase), nutrient release and uptake (N, P and K) at different wheat crop growth stages. Effect of CSA practices was also studied for carbon mineralization in an incubation experiment. Four scenarios (Sc) were included in this study- conventional tillage (CT) based rice-wheat system (Sc1), partial CSA based rice-wheat-mungbean system (Sc2), full CSA based rice-wheat-mungbean system (Sc3), and full CSA based maize-wheat-mungbean system (Sc4). Soil samples were collected from scenarios at 0-15 and 15-30 cm depth at different growth stages of wheat crop namely sowing, crown root initiation (CRI), active tillering, panicle initiation, and harvesting. Analysis of soil was done for chemical properties viz. pH, electrical conductivity, available N, P, K, NPK uptake and mineralizable carbon and biological properties viz., microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), dehydrogenase activity (DHA), alkaline phosphatase activity (APA) and ß-glucosidase. Significantly higher microbial biomass carbon (42 %) and nitrogen (79 %) were found in surface soil (0-15 cm depth) under CSA based scenarios (Sc2, Sc3 and Sc4) at harvest stage of wheat over CT based/ conventional scenario (Sc1). At surface soil, alkaline phosphatase, dehydrogenase and ß-glucosidase activity was 58, 14 and 13 % higher in CSA based scenarios, respectively than CT based scenario. CSA based scenarios showed significantly higher C mineralization after 3 days of the incubation experiment at harvest. An increase of respectively 15, 48 and 17 % of N, P and K uptake was observed with CSA based scenarios than CT based scenario. At harvest stage, 7 % higher amount of dry matter was reported with full CSA based scenarios (mean of Sc2 to Sc4) compared to Sc1. Higher wheat grain yield of ∼10 % was recorded with CSA based scenarios over CT based scenario. Therefore, CSA based scenarios with improved biological properties and nutrient availability and uptake at different wheat growth stages resulted in higher yields and hence need to be popularized among the farmers.

Conservation Agriculture-based Sustainable Intensification of Cereal Systems Leads to Energy Conservation, Higher Productivity and Farm Profitability.

In the Indo-Gangetic Plains of South Asia, the quadruple challenges of deteriorating soil quality, declining groundwater, energy shortages, and diminishing farm profitability threaten sustainability of conventional till (CT)-based cereal production systems. A 5-year study was conducted to evaluate the effect of conservation agriculture (CA)-based management (tillage, crop establishment, residue management, and system intensification through mungbean integration) on energy budget, water productivity, and economic profitability in cereal (rice-wheat, RW/maize-wheat, MW)-based systems compared with CT-based management. In CA systems, crop residues contributed the maximum (~76%) in total energy input (167,995 MJ ha-1); however, fertilizer application (nonrenewable energy source) contributed the maximum (43%) in total energy input (47,760 MJ ha-1) in CT-based systems. CA-based cereal (rice/maize) systems recorded higher net energy and energy-intensiveness (EI) levels of 251% and 300%, respectively, compared with those of the CT-based rice-wheat system (RW/CT) (295,217 MJ ha-1 and 46.05 MJ USD-1), irrespective of mungbean integration. MWMb/ZT+R utilized 204% more input energy, which resulted in 14% higher net energy and 229% higher EI compared with RW/CT. CA-based RW and MW systems enhanced the crop productivity by 10 and 16%, water productivity by 56 and 33%, and profitability by 34 and 36%, while saving in irrigation water by 38 and 32%, compared with their respective CT-based systems, respectively. CA-based system improved net energy, crop productivity, and profitability; therefore, it should be outscaled to improve the soil and environmental quality in north-west India.

Maize yield in smallholder agriculture system-An approach integrating socio-economic and crop management factors.

Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.

Re-designing irrigated intensive cereal systems through bundling precision agronomic innovations for transitioning towards agricultural sustainability in North-West India.

A study was conducted to design productive, profitable, irrigation water¸ nitrogen and energy use efficient intensive cereal systems (rice-wheat; RW and maize-wheat; MW) in North-West India. Bundling of conservation agriculture (CA) with sub-surface drip irrigation termed as CA+ were compared with CA alone and conventional tillage based and flood irrigated RW rotation (farmer's practice; ScI). In contrast to conventional till RW rotation which consumed 1889 mm ha-1 irrigation water (2-yr mean), CA+ system saved 58.4 and 95.5% irrigation water in RW and MW rotations, respectively. CA+ practices saved 45.8 and 22.7% of irrigation water in rice and maize, respectively compared to CA with flood irrigation. On a system basis, CA+ practices saved 46.7 and 44.7% irrigation water under RW (ScV) and MW (ScVI) systems compared to their respective CA-based systems with flood irrigation (ScIII and ScIV). CA+ in RW system recorded 11.2% higher crop productivity and improved irrigation water productivity by 145% and profitability by 29.2% compared to farmers' practice. Substitution of rice with maize (MW system; ScVI) recorded 19.7% higher productivity, saved 84.5% of irrigation water and increased net returns by 48.9% compared to farmer's practice. CA+ RW and MW system improved energy productivity by 75 and 169% and partial factor productivity of N by 44.6 and 49.6%, respectively compared to ScI. The sub-surface drip irrigation system saved the fertilizer N by 20% under CA systems. CA+ in RW and MW systems recorded ~13 and 5% (2-yr mean) higher profitability with 80% subsidy on installing sub-surface drip irrigation system and similar profitability without subsidy scenario compared with their respective flood irrigated CA-based systems.

Cost-effective opportunities for climate change mitigation in Indian agriculture.

Long-term changes in average temperatures, precipitation, and climate variability threaten agricultural production, food security, and the livelihoods of farming communities globally. Whilst adaptation to climate change is necessary to ensure food security and protect livelihoods of poor farmers, mitigation of greenhouse gas (GHG) emissions can lessen the extent of climate change and future needs for adaptation. Many agricultural practices can potentially mitigate GHG emissions without compromising food production. India is the third largest GHG emitter in the world where agriculture is responsible for 18% of total national emissions. India has identified agriculture as one of the priority sectors for GHG emission reduction in its Nationally Determined Contributions (NDCs). Identification of emission hotspots and cost-effective mitigation options in agriculture can inform the prioritisation of efforts to reduce emissions without compromising food and nutrition security. We adopted a bottom-up approach to analyse GHG emissions using large datasets of India's 'cost of cultivation survey' and the '19th livestock census' together with soil, climate and management data for each location. Mitigation measures and associated costs and benefits of adoption, derived from a variety of sources including the literature, stakeholder meetings and expert opinion, were presented in the form of Marginal Abatement Cost Curves (MACC). We estimated that by 2030, business-as-usual GHG emissions from the agricultural sector in India would be 515 Megatonne CO2 equivalent (MtCO2e) per year with a technical mitigation potential of 85.5 MtCO2e per year through adoption of various mitigation practices. About 80% of the technical mitigation potential could be achieved by adopting only cost-saving measures. Three mitigation options, i.e. efficient use of fertilizer, zero-tillage and rice-water management, could deliver more than 50% of the total technical abatement potential.

Effects of tillage, crop establishment and diversification on soil organic carbon, aggregation, aggregate associated carbon and productivity in cereal systems of semi-arid Northwest India.

Intensive tillage based management practices are threatening soil quality and systems sustainability in the rice-wheat belt of Northwest India. Furthermore, it is accentuated with puddling of soil, which disrupts soil aggregates. Conservation agriculture (CA) practices involving zero tillage, crop residue management and suitable crop rotation can serve as better alternative to conventional agriculture for maintaining soil quality. Soil organic carbon is an important determinant of soil quality, playing critical role in food production, mitigation and adaptation to climate change as well as performs many ecosystem functions. To understand the turnover of soil carbon in different forms (Total organic carbon-TOC; aggregate associated carbon-AAC; particulate organic carbon- POC), soil aggregation and crop productivity with different management practices, one conventional agriculture based scenario and three CA based crop management scenarios namely conventional rice-wheat system (Sc1), partial CA based rice-wheat-mungbean system (Sc2), full CA-based rice-wheat-mungbean system (Sc3) and maize-wheat-mungbean system (Sc4) were evaluated. TOC was increased by 71%, 68% and 25% after 4 years of the experiment and 75%, 80% and 38% after 6 years of the experiment in Sc4, Sc3 and Sc2, respectively, over Sc1 at 0-15 cm soil depth. After 4 years of the experiment, 38.5% and 5.0% and after 6 years 50.8% and 24.4% improvement in total water stable aggregates at 0-15 and 15-30 cm soil depth, respectively was observed in CA-based scenarios over Sc1. Higher aggregate indices were associated with Sc3 at 0-15 cm soil depth than others. Among the size classes of aggregates, highest aggregate associated C (8.94 g kg-1) was retained in the 1-0.5 mm size class under CA-based scenarios. After 6 years, higher POC was associated with Sc4 (116%). CA-based rice/maize system (Sc3 and Sc4) showed higher productivity than Sc1. Therefore, CA could be a potential management practice in rice-wheat cropping system of Northwest India to improve the soil carbon pools through maintaining soil aggregation and productivity.

Carbon mineralization in soil as influenced by crop residue type and placement in an Alfisols of Northwest India.

Carbon (C) mineralization of crop residues is an important process occurring in soil which is helpful in predicting CO2 emission to the atmosphere and nutrient availability to plants. A laboratory experiment was conducted in which C mineralization of residues of rice (Oryza sativa), wheat (Triticum aestivum), maize (Zea mays), mungbean (Vigna radiata) and their mixtures was applied to the soil surface or incorporated into an Alfisols from Northwest India. C mineralization was significantly affected by residue placement and type and their interactions. Rice residue had a higher decomposition rate (k = 0.121 and 0.076 day-1) than wheat (0.073 and 0.042 day-1) and maize residues (0.041 day-1) irrespective of placements. Higher decomposition rates of rice and wheat were observed when placed on soil surface than incorporated in the soils. Additive effects of the contribution of each residue type to C mineralization of the residue mixture were observed. When mungbean residue was added to the rice/wheat or maize/wheat mixture, decomposition of the residue mixture was enhanced. Crop residues with low N and high C/N ratio such as maize, wheat, rice and their mixtures can be applied on the soil surface for faster C and N mineralization, thereby helping to manage high volumes of residues under conservation agriculture-based practices in northwest India.

Assessing soil properties and nutrient availability under conservation agriculture practices in a reclaimed sodic soil in cereal-based systems of North-West India.

Soil quality degradation associated with resources scarcity is the major concern for the sustainability of conventional rice-wheat system in South Asia. Replacement of conventional management practices with conservation agriculture (CA) is required to improve soil quality. A field experiment was conducted to assess the effect of CA on soil physical (bulk density, penetration resistance, infiltration) and chemical (N, P, K, S, micronutrients) properties after 4 years in North-West India. There were four scenarios (Sc) namely conventional rice-wheat cropping system (Sc1); partial CA-based rice-wheat-mungbean system (RWMS) (Sc2); CA-based RWMS (Sc3); and CA-based maize-wheat-mungbean (Sc4) system. Sc2 (1.52 Mg m-3) showed significantly lower soil bulk density (BD). In Sc3 and Sc4, soil penetration resistance (SPR) was reduced and infiltration was improved compared to Sc1. Soil organic C was significantly higher in Sc4 than Sc1. Available N was 33% and 68% higher at 0-15 cm depth in Sc3 and Sc4, respectively, than Sc1. DTPA extractable Zn and Mn were significantly higher under Sc3 and Sc4 compared to Sc1. Omission study showed 30% saving in N and 50% in K in wheat after four years. Therefore, CA improved soil properties and nutrient availability and have potential to reduce external fertilizer inputs in long run.

Long-term impact of conservation agriculture and diversified maize rotations on carbon pools and stocks, mineral nitrogen fractions and nitrous oxide fluxes in inceptisol of India.

Given the increasing scarcity of production resources such as water, energy and labour coupled with growing climatic risks, maize-based production systems could be potential alternatives to intensive rice-wheat (RW) rotation in western Indo-Gangetic Plains (IGP). Conservation agriculture (CA) in maize systems has been widely promoted for minimizing soil degradation and ensuring sustainability under emerging climate change scenario. Such practices are also believed to provide mitigation co-benefits through reduced GHG emission and increased soil carbon sequestration. However, the combined effects of diversified crop rotations and CA-based management on GHG mitigation potential and other co-benefits are generally over looked and hence warrant greater attention. A field trial was conducted for 5-years to assess the changes in soil organic carbon fractions, mineral-N, N2O emission and global warming potential (GWP) of maize-based production systems under different tillage & crop establishment methods. Four diversified cropping systems i.e. maize-wheat-mungbean (MWMb), maize-chickpea-Sesbania (MCS), maize-mustard-mungbean (MMuMb) and maize-maize-Sesbania (MMS) were factorially combined with three tillage & crop establishment methods i.e. zero tilled permanent beds (PB), zero-tillage flat (ZT) and conventional tillage (CT) in a split-plot design. After 5-years of continued experimentation, we recorded that across the soil depths, SOC content, its pools and mineral-N fractions were greatly affected by tillage & crop establishment methods and cropping systems. ZT and PB increased SOC stock (0-30 cm depth) by 7.22-7.23 Mg C ha-1 whereas CT system increased it only by 0.88 Mg C ha-1as compared to initial value. Several researchers reported that SOC & mineral-N fraction contents in the top 30 cm soil depth are correlated with N2O-N emission. In our study, global warming potential (GWP) under CT system was higher by 18.1 and 17.4%, compared to CA-based ZT and PB, respectively. Among various maize systems, GWP of MMS were higher by 11.2, 6.7 and 6.6%, compared that of MWMb (1212 kg CO2-eq. ha-1), MCS (1274 kg CO2-eq. ha-1) and MMuMb (1275 kg CO2-eq. ha-1), respectively. The results of our study suggest that CA and diversified crop rotations should be promoted in north-western IGP and other similar agro-ecologies across the globe for ensuring food security, restoration of soil health and climate change mitigation, the key sustainable development goals (SDGs).