The interplay between external residue addition, and soil organic carbon dynamics and mineralization kinetics: Experiences from a 12-year old conservation agriculture.

Maintaining soil carbon is vital under changing climate. Conservation agriculture (CA) is reported to have potential to store soil organic carbon (SOC). The impact of carbon inputs on SOC dynamics and mineralization kinetics, and the priming effect of residue addition under long-term CA in subtropical regions, however, are not clear or adequately evaluated. Therefore, we studied these under a 12-year-old CA-based pigeon pea-wheat cropping system with permanent broad bed with residue (CA-PBB), permanent flatbed with residue (CA-PFB), permanent narrow bed with residue (CA-PNB), and conventional till (CT) treatments. Also, an incubation study was undertaken to understand better the processes involved. Results showed that CA treatments significantly enhanced the total SOC compared to CT practice, and, among them, the CA-PFB exhibited highest total SOC with 36.6% and 35.8% higher values at 0-5 and 5-15 cm depths, respectively. The CA-PFB followed by CA-PBB and CA-PNB had significantly higher carbon management index and carbon retention efficiency than CT. The CA-PFB also showed higher carbon sequestration rates of 68.4 and 188.8 kg ha-1 year-1, surpassing values of 8.4 and 52.9 kg ha-1 year-1 under CT at 0-5 and 5-15 cm depth, respectively. Furthermore, soil incubation study revealed that the CA systems had higher cumulative mineralization values at 0-5 cm soil layer but lower at 5-15 cm soil compared to CT, indicating a considerable improvement in SOC at 5-15 cm soil depth. On the contrary, the SOC decay rate was higher under CA than CT, and at 35 °C than at 15 °C. A positive priming effect was also observed, depending on the substrate type, pigeon pea residue exhibiting higher priming effect than wheat residue. Thus, these studies show that residue input increases cumulative mineralization and SOC decay rate vis-à-vis helps to sequester carbon in the recalcitrant fraction, leading to higher stable carbon in soil.

Reducing the environmental impact of rice production in subtropical India by minimising reactive nitrogen loss.

The future of reactive nitrogen (N) for subtropical lowland rice to be characterised under diverse N-management to develop adequate sustainable practices. It is a challenge to increase the efficiency of N use in lowland rice, as N can be lost in various ways, e.g., through nitrous oxide (N2O) or dinitrogen (N2) emissions, ammonia (NH3) volatilization and nitrate (NO3-) leaching. A field study was carried out in the subsequent wet (2021) and dry (2022) seasons to assess the impacts of different N management strategies on yield, N use efficiency and different N losses in a double-cropped rice system. Seven different N-management practices including application of chemical fertilisers, liquid organic fertiliser, nitrification inhibitors, organic nutrient management and integrated nutrient management (INM) were studied. The application of soil test-based neem-coated urea (NCU) during the wet season resulted in the highest economic yield, while integrated nutrient management showed the highest economic yield during the dry season. Total N losses by volatilization of NH3, N2O loss and leaching were 0.06-4.73, 0.32-2.14 and 0.25-1.93 kg ha-1, corresponding to 0.06-5.84%, 0.11-2.20% and 0.09-1.81% of total applied N, respectively. The total N-uptake in grain and straw was highest in INM (87-89% over control) followed by the soil test-based NCU (77-82% over control). In comparison, recovery efficiency of N was maximum from application of NCU + dicyandiamide during both the seasons. The N footprint of paddy rice ranged 0.46-2.01 kg N-eq. t-1 during both seasons under various N management. Ammonia volatilization was the process responsible for the largest N loss, followed by N2O emissions, and NO3- leaching in these subtropical lowland rice fields. After ranking the different N management practices on a scale of 1-7, soil test-based NCU was considered the best N management approach in the wet year 2021, while INM scored the best in the dry year 2022.

How Modelers Model: the Overlooked Social and Human Dimensions in Model Intercomparison Studies.

There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler's experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in "trial-and-error" calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler's assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details.

Influence of cyanobacterial inoculants, elevated carbon dioxide, and temperature on plant and soil nitrogen in soybean.

Climate change affects nitrogen dynamics in crops and diazotrophic microorganisms with carbon dioxide (CO2 ) sequestering potential such as cyanobacteria can be promising options. The interactions of three cyanobacterial formulations (Anabaena laxa, Calothrix elenkinii and Anabaena torulosa-Bradyrhizobium japonicum biofilm) on plant and soil nitrogen in soybean, were investigated under elevated CO2 and temperature conditions. Soybean plants were grown inside Open Top Chambers under ambient and elevated (550 ± 25 ppm) CO2 concentrations and elevated temperature (+2.5-2.8°C). Interactive effect of elevated CO2 and cyanobacterial inoculation through A. laxa and Anabaena torulosa-B. japonicum biofilm led to improved growth, yield, nodulation, nitrogen fixation, and seed N in soybean crop. Nitrogenase activity in nodules increased in A. laxa and biofilm treatments, with an increase of 55% and 72%, respectively, over no cyanobacterial inoculation treatment. Although high temperature alone reduced soil microbial biomass carbon, dehydrogenase activity, and soil available N, the combined effect of CO2 and temperature were stimulatory; cyanobacterial inoculation further led to an increase under all the conditions. The highest seed N uptake (758 mg plant-1 ) was recorded with cyanobacterial biofilm inoculation under elevated CO2 with control temperature conditions. The positive interactions of elevated CO2 and cyanobacterial inoculation, particularly through A. laxa and A. torulosa-B. japonicum biofilm inoculation highlights their potential in counteracting the negative impact of changing climate along with enhancing plant and soil N in soybean.

Interactive effect of elevated tropospheric ozone and carbon dioxide on radiation utilisation, growth and yield of chickpea (Cicer arietinum L.).

An experiment was conducted in the Free Air Ozone and Carbon dioxide Enrichment (FAOCE) facility to study the impact of elevated O3, CO2 and their interaction on chickpea crop (cv. Pusa-5023) in terms of phenology, biophysical parameters, yield components, radiation interception and use efficiency. The crop was exposed to elevated O3 (EO:60ppb), CO2 (EC:550 ppm) and their combined interactive treatment (ECO: EC+EO) during the entire growing season. Results revealed that the crop's total growth period was shortened by 10, 14 and 17 days under elevated CO2, elevated O3 and the combined treatment, respectively. Compared to ambient condition, the leaf area index (LAI) under elevated CO2 was higher by 4 to 28%, whilst it is reduced by 7.3 to 23.8% under elevated O3. The yield based radiation use efficiency (RUEy) was highest under elevated CO2 (0.48 g MJ-1), followed by combined (0.41 g MJ-1), ambient (0.38 g MJ-1) and elevated O3 (0.32 g MJ-1) treatments. Elevated O3 decreased RUEy by 15.78% over ambient, and the interaction results in a 7.8% higher RUEy. The yield was 31.7% more under elevated CO2 and 21.9% lower in elevated O3 treatment as compared to the ambient. The combined interactive treatment recorded a higher yield as compared to ambient by 9.7%. Harvest index (HI) was lowest under elevated O3 (36.10%), followed by ambient (39.18%), combined (40.81%), and highest was under elevated CO2 (44.18%). Chickpea showed a positive response to elevated CO2 resulting a 5% increase in HI as compared to ambient condition. Our findings quantified the positive and negative impacts of elevated O3, CO2 and their interaction on chickpea and revealed that the negative impacts of elevated O3 can be compensated by elevated CO2 in chickpea. This work promotes the understanding of crop behaviour under elevated O3, CO2 and their interaction, which can be used as valuable inputs for radiation-based crop simulation models to simulate climate change impact on chickpea crop.

Methane utilizing plant growth-promoting microbial diversity analysis of flooded paddy ecosystem of India.

Methane utilizing bacteria (MUB) are known to inhabit the flooded paddy ecosystem where they play an important role in regulating net methane (CH4) emission. We hypothesize that efficient MUB having plant growth-promoting (PGP) attributes can be used for developing novel bio-inoculant for flooded paddy ecosystem which might not only reduce methane emission but also assist in improving the plant growth parameters. Hence, soil and plant samples were collected from the phyllosphere, rhizosphere, and non-rhizosphere of five rice-growing regions of India at the tillering stage and investigated for efficient methane-oxidizing and PGP bacteria. Based on the monooxygenase activity and percent methane utilization on NMS medium with methane as the sole C source, 123 isolates were identified and grouped phylogenetically into 13 bacteria and 2 yeast genera. Among different regions, a significantly higher number of isolates were obtained from lowland flooded paddy ecosystems of Aduthurai (33.33%) followed by Ernakulum (20.33%) and Brahmaputra valley (19.51%) as compared to upland irrigated regions of Gaya (17.07%) and Varanasi (8.94%). Among sub-samples, a significantly higher number of isolates were found inhabiting the phyllosphere (58.54%) followed by non-rhizosphere (25.20%) and rhizosphere (15.45%). Significantly higher utilization of methane and PGP attributes were observed in 30 isolates belonging to genera Hyphomicrobium, Burkholderia, Methylobacterium, Paenibacillus, Pseudomonas, Rahnella, and Meyerozyma. M. oryzae MNL7 showed significantly better growth with 74.33% of CH4 utilization at the rate of 302.9 ± 5.58 and exhibited half-maximal growth rate, Ks of 1.92 ± 0.092 mg CH4 L-1. Besides the ability to utilize CH4, P. polymyxa MaAL70 possessed PGP attributes such as solubilization of P, K, and Zn, fixation of atmospheric N and production of indole acetic acid (IAA). Both these promising isolates can be explored in the future for developing novel biofertilizers for flooded paddies.

Wheat Cultivar Growth, Biochemical, Physiological and Yield Attributes Response to Combined Exposure to Tropospheric Ozone, Particulate Matter Deposition and Ascorbic Acid Application.

In the present study wheat (Triticum aestivum) cultivar HD 2967 was exposed to ambient and elevated levels of O3 and PM deposition, with and without exogenous application of ascorbic acid (AA). Cultivar HD 2967 exposed to eight treatments in free air O3 enrichment facility and the assessed results showed that wheat cultivar, growth, biochemical, physiological and yield attributes were variably but adversely affected by combined exposure to O3 and PM deposition. PM deposition clogged stomata and enhanced leaf temperature. However, plants exposed to O3 and PM deposition and treated with AA exhibited less reduction in yield as compared to plants exposed to O3 and PM deposition without AA treatment. The decline in grain yield of HD 2967 due to combined exposure of O3 and PM deposition were in the range of 4%-17%. AA spray partially mitigated ozone and PM deposition adverse impact and enhanced wheat yield by 16%.

Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2 O emissions.

Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2 O) emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2-4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2 O emissions. Results showed that across sites and crop/grassland types, 23%-40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2 O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2 O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2-4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2 O emissions. Yield-scaled N2 O emissions (N2 O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N2 O emissions at field scale is discussed.

Effect of elevated carbon dioxide on soil hydrothermal regimes and growth of maize crop (Zea mays L.) in semi-arid tropics of Indo-Gangetic Plains.

To see the effect of climate change on the variation of soil hydrothermal regimes and growth of maize crop, an experiment was conducted in free-air carbon dioxide enrichment (FACE) facility during the kharif season of 2015 at Climate Change Facility of Indian Agricultural Research Institute, New Delhi, India. Under elevated CO2 and ambient condition, surface bulk density (BD) were 1.38 Mgm-3 and 1.44 Mgm-3, respectively but BD were not significantly different. During different days after sowing (DAS), in 0 to 10-cm soil depth, soil water content (SWC) in FACE varied between 14.58-20.70%, whereas in ambient condition, SWC variations were in between 19.33-22.94%. In 10 to 20-cm soil depth, SWC ranged in between 20.47-27.14% in FACE and 23.57-25.42% in ambient condition for different DAS. It is also observed that the arrival of peak surface ST was 1 h early in elevated CO2 condition. Photosynthetic rate increased by 5.7% on 44 DAS and 18.1% on 70 DAS under elevated carbon dioxide condition. Elevated carbon dioxide had reduced the stomatal conductance but the reduction was not significant. Like variation in air temperature for climate change, more intensive study is required to see the effect of climate change on soil temperature and its effect on crop growth.

Effect of elevated temperature on soil hydrothermal regimes and growth of wheat crop.

An attempt has been made to study the effect of elevated temperature on soil hydrothermal regimes and winter wheat growth under simulated warming in temperature gradient tunnel (TGT). Results showed that bulk density (BDs) of 0, 0.9, and 2.5 °C were significantly different whereas BDs of 2.8 and 3.5 °C were not significantly different. Water filled pore space (WFPS) was maximum at 3.5 °C temperature rise and varied between 43.80 and 98.55%. Soil surface temperature (ST) at different dates of sowing increased with rise in sensor temperature and highest ST was observed at S5 sensors (3.5 °C temperature rise). Temperature and its difference were high for the top soil, and were stable for the deep soil. Photosynthesis rate (µmol CO2 m-2 s-1) of wheat was lower at higher temperature in different growth stages of wheat. In wheat, stomatal conductance declined from 0.67 to 0.44 mol m-2 s-1 with temperature rise. Stomatal conductance decreased with increase in soil temperature and gravimetric soil moisture content (SWC). In TGT, 0 °C temperature rise showed highest root weight density (RWD) (5.95 mg cm-3); whereas, 2.8 and 3.5 °C showed lowest RWD (4.90 mg cm-3). Harvest index was maximum (0.37) with 0 °C temperature rise, and it decreased with increase in temperature, which indicated that both grain and shoot biomass decreased with increase in temperature. Intensive studies are needed to quantify the soil hydrothermal regimes inside TGT along with the crop growth parameters.

Adaptive nitrogen and integrated weed management in conservation agriculture: impacts on agronomic productivity, greenhouse gas emissions, and herbicide residues.

Increasing nitrogen (N) immobilization and weed interference in the early phase of implementation of conservation agriculture (CA) affects crop yields. Yet, higher fertilizer and herbicide use to improve productivity influences greenhouse gase emissions and herbicide residues. These tradeoffs precipitated a need for adaptive N and integrated weed management in CA-based maize (Zea mays L.)-wheat [Triticum aestivum (L.) emend Fiori & Paol] cropping system in the Indo-Gangetic Plains (IGP) to optimize N availability and reduce weed proliferation. Adaptive N fertilization was based on soil test value and normalized difference vegetation index measurement (NDVM) by GreenSeeker™ technology, while integrated weed management included brown manuring (Sesbania aculeata L. co-culture, killed at 25 days after sowing), herbicide mixture, and weedy check (control, i.e., without weed management). Results indicated that the 'best-adaptive N rate' (i.e., 50% basal + 25% broadcast at 25 days after sowing + supplementary N guided by NDVM) increased maize and wheat grain yields by 20 and 14% (averaged for 2 years), respectively, compared with whole recommended N applied at sowing. Weed management by brown manuring (during maize) and herbicide mixture (during wheat) resulted in 10 and 21% higher grain yields (averaged for 2 years), respectively, over the weedy check. The NDVM in-season N fertilization and brown manuring affected N2O and CO2 emissions, but resulted in improved carbon storage efficiency, while herbicide residuals in soil were significantly lower in the maize season than in wheat cropping. This study concludes that adaptive N and integrated weed management enhance synergy between agronomic productivity, fertilizer and herbicide efficiency, and greenhouse gas mitigation.

Heavy Metal Contamination of Soil, Irrigation Water and Vegetables in Peri-Urban Agricultural Areas and Markets of Delhi.

Dietary exposure to heavy metals, namely cadmium (Cd), lead (Pb), zinc (Zn), and copper (Cu), has been identified as a risk to human health through consumption of vegetable crops. The present study investigates heavy metal contamination in irrigation water, soil, and vegetables at four peri-urban and one wholesale site in Delhi, India, and estimates the health risk index. Most of the samples collected from peri-urban areas exceeded the safe limits of lead and cadmium, whereas only lead concentration was found to be higher in vegetable samples collected from the wholesale market. Average uptake of metals by vegetables from soil decreased in the order Cd>Zn>Cu>Pb. The order of metal uptake based on transfer factor was highest in okra, cauliflower, and spinach, from greatest to least. Among the vegetables from peri-urban sites, only okra crossed the safe limit for cadmium; whereas vegetables from the wholesale site exceeded the limit for lead (potato, coriander, chilies, pea, and carrot, in order from greatest to least) with respect to health risk index.

Vis-NIR spectroscopy based rapid and non-destructive method to quantitate microplastics: An emerging contaminant in farm soil.

Microplastics (MPs) is the second most important environmental issue and can potentially enter into food chain through farmland contamination and other means. There are no standardized extraction methods for quantification of MPs in soil. The embedded errors and biases generated serious problems regarding the comparability of different studies and leading to erroneous estimation. To address this gap, present study was formulated to develop an efficient method for MPs analysis suitable for a wide range of soil and organic matrices. A method based on Vis-NIR (Visible-Near Infra Red) spectroscopy is developed for four different soil belonging to Alfisol, Inceptisol, Mollisol and Vertisol and two organic matter matrices (FYM and Sludge). The developed method was found as rapid, reproducible, non-destructive and accurate method for estimation of all three-density groups of MPs (Low, Medium and High) with a prediction accuracy ranging from 1.9 g MPs/kg soil (Vertisol) to 3.7 g MPs/kg soil (Alfisol). Two different regression models [Partial Least Square Regression (PLSR) and Principal Component Regression (PCR)] were assessed and PLSR was found to provide better information in terms of prediction accuracy and minimum quantification limit (MQL). However, PCR performed better for organic matter matrices than PLSR. The method avoids any complicated sample preparation steps except drying and sieving thus saving time and acquisition of reflectance spectrum for single sample is possible within 18 s. Owing to have the minimum quantification limit ranging from 1.9-3.7 g/kg soil, the vis-NIR based method is perfectly suitable for estimation of MPs in soil samples collected from plastic pollution hotspots like landfill sites, regular based sludge amended farm soils. Additionally, the method can be adapted by small scale compost industries for assessing MPs load in product like city compost which are applied at agricultural fields and will be helpful in quantifying possible MPs at the sources itself.

Synergistic action of tropospheric ozone and carbon dioxide on yield and nutritional quality of Indian mustard (Brassica juncea (L.) Czern.).

Field experiments were conducted in open top chamber during rabi seasons of 2009-10 and 2010-11 at the research farm of the Indian Agricultural Research Institute, New Delhi to study the effect of tropospheric ozone (O3) and carbon dioxide (CO2) interaction on yield and nutritional quality of Indian mustard (Brassica juncea (L.) Czern.). Mustard plants were grown from emergence to maturity under different treatments: charcoal-filtered air (CF, 80-85 % less O3 than ambient O3 and ambient CO2), nonfiltered air (NF, 5-10 % less O3 than ambient O3 and ambient CO2 ), nonfiltered air with elevated carbon dioxide (NF + CO2, NF air and 550 ± 50 ppm CO2), elevated ozone (EO, NF air and 25-35 ppb elevated O3), elevated ozone along with elevated carbon dioxide (EO + CO2, NF air, 25-35 ppb O3 and 550 ± 50 ppm CO2), and ambient chamber less control (AC, ambient O3 and CO2). Elevated O3 exposure led to reduced photosynthesis and leaf area index resulting in decreased seed yield of mustard. Elevated ozone significantly decreased the oil and micronutrient content in mustard. Thirteen to 17 ppm hour O3 exposure (accumulated over threshold of 40 ppm, AOT 40) reduced the oil content by 18-20 %. Elevated CO2 (500 ± 50 ppm) along with EO was able to counter the decline in oil content in the seed, and it increased by 11 to 13 % over EO alone. Elevated CO2, however, decreased protein, calcium, zinc, iron, magnesium, and sulfur content in seed as compared to the nonfiltered control, whereas removal of O3 from air in the charcoal-filtered treatment resulted in a significant increase in the same.

Cultivar assortment index (CAI): a tool to evaluate the ozone tolerance of Indian Amaranth (Amaranthus hypochondriacus L.) cultivars.

The adverse impact of climate change on crop yield has accelerated the need for identification of crop cultivars resistant to abiotic stress. In the present study, a cultivar assortment index (CAI) was generated for the evaluation of forty Amaranthus hypochondriacus cultivars response to elevated ozone (EO) concentrations (AO + 30 ppb) in Free Air Ozone Enrichment (FAOE) facility using the parameters viz. foliar injury, gaseous exchange attributes, namely, net photosynthetic rate, stomatal conductance, transpiration rate, intercellular carbon dioxide, and water use efficiency along with above ground biomass and grain yield attributes. The dataset was used to identify key indicator parameters responsive to EO through principal component analysis (PCA) and further transformed to obtain linear score and weighted score. The CAI varied from 70.49 to 193.43. Cultivars having CAI value less than 151 were ozone tolerant (OT) whereas cultivars with CAI values between 150 and 170 were moderately tolerant (MOT). The cultivars exhibiting CAI values above 170 were ozone sensitive (OS). The cultivars exhibited differential sensitivity to EO with IC-5994 (CAI = 187.26) being the most affected cultivar whereas IC-5576 (CAI = 83.38) and IC-5916 (CAI = 70.49) being the least affected ones. The CAI, based on linear score and weighted score, offers easy identification of ozone sensitive (OS) and ozone tolerant (OT) cultivars. This index could help researchers to define a clear and strong basis for identification of OT cultivars which will reduce the time required for preliminary screening and further evaluation of crop cultivars for the development of climate smart crops.

Timely sown maize hybrids improve the post-anthesis dry matter accumulation, nutrient acquisition and crop productivity.

Delayed sowing of maize hybrids could exacerbate the capability of maximizing the yield potential through poor crop stand, root proliferation, nutrient uptake, and dry matter accumulation coupled with the inadequate partitioning of the assimilates. This study appraised the performance of five recent maize hybrids viz., PMH-1, PJHM-1, AH-4158, AH-4271, and AH-8181 under timely and late sown conditions of the irrigated semi-arid ecologies. Timely sowing had the grain and stover yields advantage of 16-19% and 12-25%, respectively over the late sown maize hybrids. The advanced hybrids AH-4271 and AH-4158 had higher grain yields than the others. During the post-anthesis period, a greater dry matter accumulation and contribution to the grain yield to the tune of 16% and 10.2%, respectively, was observed under timely sown conditions. Furthermore, the nutrient acquisition and use efficiencies also improved under the timely sown. The nutrient and dry matter remobilization varied among the hybrids with AH-4271 and PMH-1 registering greater values. The grain yield stability index (0.85) was highest with AH-4158 apart from the least yield reduction (15.2%) and stress susceptibility index (0.81), while the maximum geometric mean productivity was recorded with the AH-4271 (5.46 Mg ha-1). The hybrids AH-4271 and PJHM-1 exhibited improved root morphological traits, such as root length, biomass, root length density, root volume at the V5 stage (20 days after sowing, DAS) and 50% flowering (53 DAS). It is thus evident that the timely sowing and appropriate hybrids based on stress tolerance indices resulted in greater yields and better utilization of resources.

Above and below-ground growth, accumulated dry matter and nitrogen remobilization of wheat (Triticum aestivum) genotypes grown in PVC tubes under well- and deficit-watered conditions.

The continuing decline in water resources under the ever-changing climate compels us to re-orient our focus to a more sustainable practice. This study investigates the performance of Triticum aestivum wheat genotypes viz. HD-2967, HD-3086, HD-3249, DBW-187, and HD-3226 under well- and deficit-watered conditions for their root-traits, biomass and nitrogen accumulation and remobilization, and water use efficiencies, grown in PVC-tubes. The genotypes HD-2967, HD-3086, HD-3249, DBW-187, and HD-3226 under well-watered (WW) resulted in 36, 35, 38, 33, and 42% more grain yield compared to deficit-watered (DW). Among the genotypes, HD-3249 had the highest grain yield under both well- and deficit-watered conditions. Compared to DW, the WW had 28%, 30%, and 28% greater root length, biomass, and root length density at flowering {102 days (d), Z61}, while among the genotypes, HD-3249 had relatively greater root-traits. At flowering (Z61) and maturity (132 d, Z89), genotypes under WW accumulated 30-46% and 30-53%, respectively greater shoot biomass over the DW. Furthermore, the shoot biomass remobilised for HD-2967, HD-3086, HD-3249, DBW-187, and HD-3226 under the WW was 32, 37, 39, 35, and 35% greater than the DW. The nitrogen partitioning to different plant parts at flowering (Z61) and maturity (Z89) was significantly greater with the WW than with DW. The total nitrogen- remobilized and contribution to grain-N under the WW was 55, 58, 52, 53, 58% and 9, 19, 15, 17, 17% greater than the DW for the genotypes HD-2967, HD-3086, HD-3249, DBW-187, and HD-3226. The irrigation water use efficiency (WUE) at flowering (Z61) was more under the deficit-watered, but the biomass and grain total WUE was improved with the well-watered condition. Hence, it is apparent that proper scheduling of irrigation and N applications, along with the adoption of a genotype suited to a particular environment, will result in better WUE and grain yields, along with better utilization of scarce resources.

Greenhouse gas mitigation in rice-wheat system with leaf color chart-based urea application.

Conventional blanket application of nitrogen (N) fertilizer results in more loss of N from soil system and emission of nitrous oxide, a greenhouse gas (GHG). The leaf color chart (LCC) can be used for real-time N management and synchronizing N application with crop demand to reduce GHG emission. A 1-year study was carried out to evaluate the impact of conventional and LCC-based urea application on emission of nitrous oxide, methane, and carbon dioxide in a rice-wheat system of the Indo-Gangetic Plains of India. Treatments consisted of LCC scores of ≤4 and 5 for rice and wheat and were compared with conventional fixed-time N splitting schedule. The LCC-based urea application reduced nitrous oxide emission in rice and wheat. Application of 120 kg N per hectare at LCC ≤ 4 decreased nitrous oxide emission by 16% and methane by 11% over the conventional split application of urea in rice. However, application of N at LCC ≤ 5 increased nitrous oxide emission by 11% over the LCC ≤ 4 treatment in rice. Wheat reduction of nitrous oxide at LCC ≤ 4 was 18% as compared to the conventional method. Application of LCC-based N did not affect carbon dioxide emission from soil in rice and wheat. The global warming potential (GWP) were 12,395 and 13,692 kg CO(2) ha(-1) in LCC ≤ 4 and conventional urea application, respectively. Total carbon fixed in conventional urea application in rice-wheat system was 4.89 Mg C ha(-1) and it increased to 5.54 Mg C ha(-1) in LCC-based urea application (LCC ≤ 4). The study showed that LCC-based urea application can reduce GWP of a rice-wheat system by 10.5%.

Appraisal of probabilistic levels of toxic metals and health risk in cultivated and marketed vegetables in urban and peri-urban areas of Delhi, India.

A total of six vegetables (S. tuberosum, D. carota, S. lycopersicum, A. esculentus, S. oleracea and B. juncea) were analysed for five heavy metals (As, Cd, Cr, Hg, and Pb) to evaluate the contamination load in vegetables collected from five cultivated and two market sites (n = 504) at Delhi, India. The irrigation water samples and soil samples (n = 180) were only collected from cultivated sites. The results showed that the concentration of heavy metals in soil and water samples were well below the permissible level except for Cd 0.001-0.013 µg g-1. Similarly, the concentration of Cd (>0.20 µg g-1) was detected higher in all investigated vegetables except for tomato. The evaluation index value was highest for spinach and lowest for tomato. The transfer factor values and metal pollution index was maximum in spinach and okra. Principal component analysis (PCA), Tukey's HSD (Honestly Significant Difference) test, and one-way and two-way ANOVA (Analysis of Variance) were also applied to statistically analyse the results.

Inoculation of plant growth promoting-methane utilizing bacteria in different N-fertilizer regime influences methane emission and crop growth of flooded paddy.

Methane (CH4) emission in rice fields is greatly influenced by the type and quantity of nitrogenous fertilizer used. The net methane emission from paddy fields is also influenced by the activity of methane utilizing bacteria, which inhabit the flooded paddy ecosystem. Efficient methane utilizing and plant growth promoting bacteria Methylobacterium oryzae MNL7 and Paenibacillus polymyxa MaAL70, respectively were co-inoculated along with different nitrogenous fertilizer combinations in flooded paddy to assess their impact on cumulative methane emission and crop growth promotion. Co-inoculation significantly influenced the plant growth parameters of paddy, resulting in an increase in grain yield by 14.04, 11.08, and 12.38% in treatments receiving Urea, Di-ammonium Phosphate (DAP) + Urea, or farm yard manure (FYM), over their respective un-inoculated plots. Significant improvement in the rice grain nutrient quality in term of crude protein, Fe and Zn content was observed as a result of bacterial co-inoculation in FYM fertilized plots as compared to Urea and DAP+ Urea fertilized plots. Significantly higher cumulative methane emission of 63.39 kg ha-1 was observed in uninoculated plots fertilized with FYM treatment as compared to Urea (33.83 kg ha-1) and DAP+Urea (31.66 kg ha-1) treatments. Bacterial co-inoculation significantly reduced the cumulative methane emission by 12.03, 11.47 and 6.92% in Urea, DAP+Urea, and FYM fertilized plots over their respective uninoculated treatments. Among the different fertilizer treatments, bacterial co-inoculation with urea application performed significantly better in reducing cumulative methane emission. These findings suggest that methane utilizing bacteria which also possess plant growth promoting trait can be explored for developing a novel biofertilizer for flooded paddies, as they can aid in managing both the overall methane emission and enhancing crop yield.