Response of maize and its pest Chilo partellus to ozone and carbon dioxide exposure

In the present study, the direct effect of ozone (O3) and carbon dioxide (CO2) exposure on growth and yield of maize (var HQPM 1) and the indirect effect on development of its herbivore pest Chilo partellus were investigated. Maize crop was exposed to different concentrations of O3 and CO2 in open top chambers (OTCs). During the exposure, maize plants at the early vegetative stage were incubated with C. partellus eggs. Changes in biomass and yield of maize plants with and without Chilo infestation under O3 and CO2 exposure were monitored. Indirect effects of O3 and CO2 on maize pest were monitored with respect to release and survival of larvae, mean body weight of ἀfth instar stage larvae and emergence of adults from pupae. Higher reductions in aboveground and belowground biomass were observed in maize plants with pest with respect to plants without pest during O3 and CO2 exposure. Maximum and minimum reductions in aboveground (39.5% and 4.7%) and belowground biomass (43.0% and 5.4%) were observed in maize plants grown under O3 and CO2 treatments, respectively. Reduction in yield varied from 33.8% to 15.2% for maize plants grown under different treatments as compared to plants grown under low O3 conditions. Signiἀcant changes in development of C. partellus, fed on tissues of maize plants exposed to different treatments were observed. Moreover, the mean body weight of larvae decreased with increasing O3 concentrations. Mean body weight was 62% higher and 65% lower for larvae fed on maize plant tissue exposed to CO2 and CO2+EO3, respectively, as compared to maize plants grown under low O3 conditions. Development of male and female adults from pupae was observed only from larvae isolated from ambient and CO2 treated maize plants. The present study showed that the exposure of maize crop to O3 and CO2 and its pest C. partellus, adversely affected not only maize growth and yield but also development of C. partellus. This study suggests that predicting the outcome of O3 and CO2 on crop-insect pest interactions will require comprehensive examination of behavioural growth of both harmful and beneἀcial insects of the agro-ecosystem

Effect of elevated ozone and carbon dioxide interaction on growth and yield of maize

The effect of elevated tropospheric ozone and carbon dioxide interaction were evaluated on the growth and pro¬ductivity of high quality protein maize (HQPM-1) at the research farm of the Indian Agricultural Research Institute, New Delhi. Maize plants were exposed from emergence to maturity for two years to different ozone levels in non fil¬ter air (NF), charcoal filter air (CF), non-filter air with elevated CO2 (NF+CO2), elevated ozone (EO and EO1), elevated ozone with elevated CO2 (EO+CO2) and ambient control (AC) in open top chambers. Elevated ozone significantly decreased growth attributes of leaf and shoot biomass and leaf area index and the yield attributes. Highest values of all the growth and yield attributes were observed in CF treatment. The photosynthetic rate decreased by 24 to 37% and from 41 to 56% under EO (ambient + 25-35 ppb O3) over NF at tasseling and silking stage respectively. The yield increased by 21 to 31% in the sub ambient ozone levels in the CF treatment over non-filtered control whereas it decreased by 13 and 20 % under EO in both the years respectively. The presence of higher levels of ozone EO1 (ambient + 45-50 ppb O3) however made the plant weak and more susceptible to pest attack, result¬ing in a complete loss in yield. The presence of elevated carbon dioxide along with elevated ozone in the EO+CO2 treatment increased the yield by 9 to 10% over EO alone. Elevated CO2 was able to counter the negative effect of O3 on growth and yield parameters of maize to a certain extent

Minimal cost multifactor experiments for agricultural research involving hard-to-change factors

Multifactor experiments are very common in agricultural research. Randomizing run orders in multifactor experiments often witness in large number of factorwise level changes which will increase the cost and time of the experiments. Minimal cost multifactor experiments are such experiments where the cost of the experiment is minimum which can be achieved by choosing a factorial run order where the total number of factor level change is minimum as cost of the experiment is directly proportional to the number of level changes of factors. Here, a method of constructing minimal cost 2-level multifactor experiments with minimum number of factorwise level changes has been proposed. As for a same factorial combination, there may exist more than one minimally changed factorial run order, an exhaustive search was also performed to obtain all possible minimally changed run order for two level multifactorial experiments with three factors. Due to restricted randomization, adaption of these run orders may witness the effect of systematic time trend. Hence, the usual method of analysis may not be a feasible solution due to lack of randomization. Here, the analytical procedure of experiments using minimal cost multifactorial run order has also been highlighted based on a real experimental data. The work has been carried out at ICAR-Indian Agricultural Statistics Research Institute, New Delhi during 2019-20. The data from the real experiment used for explaining the analysis procedure has been collected from Climate Change Facility of ICAR-Indian Agricultural Research Institute farm, New Delhi, India based on experiments conducted during 2014-15

Functionalization of ash gourd: Infusion of citrus peel polyphenols through vacuum impregnation

Citrus peels have high flavonoids known for potent pharmaceutical and food applications. The present study explores the infusion of citrus peel polyphenols (CPP) into ash gourd (Benincasa hispida) through vacuum impregnation (VI). The intent was to functionalize ash gourd for diversifying its food use. Vacuum infused ash gourd (VIAG) cubes were evaluated for physicochemical parameters, total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (AOX), and sensory quality. The VI process was optimized through Box-Behnken Design (BBD) of response surface methodology (RSM), considering blanching time, vacuum pressure and vacuum time as independent variables, and TPC, TFC and AOX as dependent variables. At optimized conditions of blanching pre-treatment (2.21 min), vacuum pressure (432.31 mbar) and time (28.18 min), there was ∼300% increase in TPC and AOX. Peleg model validated the mass transfer kinetics for TPC. Sensory evaluation through descriptive analysis revealed no perceived bitterness in VIAG. Overall, it seems that VI is a promising tool for functionalization of ash gourd with bioactives

Evaluation of urea loaded nanoclay biopolymer composites with Zn and P solubilizing microbes for nitrogen uptake and use efficiency in maize (Zea mays)-wheat (Triticum aestivum) cropping system

A field experiment was conducted during rainy (kharif) 2022 (July 2022–October 2022) and winter (rabi) 2022–23 (November 2022–March 2023) seasons at ICAR-Indian Agricultural Research Institute, New Delhi to evaluate a series of Zn and P solubilizing microbial culture enriched nanoclay biopolymer composite (NCBPC) loaded with nitrogenous fertilizer (urea) and the efficiency of the products for maize (Zea mays L.) and wheat (Triticum aestivum L.). Experiment consisted of 10 treatments, viz. T1, Control; T2, 100% N though urea; T3; T5; T7; and T9, 75% N as urea loaded NCBPC-A (prepared using acrylic acid + acrylamide + mango kernel flour) alone or along with P or Zn or P + Zn solubilizers; T4; T6; T8 and T10, 75% N as urea loaded NCBPC-B (prepared using acrylic acid + acrylamide + maize flour) alone or along with P or Zn or P + Zn solubilizers in a randomized block design (RBD) and replicated thrice. In both maize and wheat crop, highest grain (5.09 and 5.32 t/ha) and straw yield (6.56 and 7.45 t/ha), apparent N recovery (51.26 and 47.26%) and agronomic efficiency (12 and 13.3 kg grain yield obtained/kg N application) were obtained in treatment T10 followed by T9. In addition, total N uptake significantly enhanced by 20.1–28.4% in maize and 22.1–30.8% in wheat (T9 and T10); apparent nitrogen recovery (ANR) improved by 12.9–18.2 and 15.2–21.1% and agronomic efficiency (AE) triggered by 19.5–21.2 and 15.4–20.8% in maize and wheat crops respectively, under T9 and T10 treatments over standard urea fertilization (T2). Thus, the study concludes that, 25% N requirement could be cut down through application of 75% N (urea) loaded NCBPCs in conjunction with Zn or P or Zn + P solubilizing microbial culture as compared to sole urea application under maize-wheat cropping system

Leveraging population admixture to characterize the heritability of complex traits.

Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2)

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.info:eu-repo/semantics/acceptedVersio

Long-term adoption of bed planted conservation agriculture based maize/cotton-wheat system enhances soil organic carbon stabilization within aggregates in the indo-gangetic plains

Sustainability of contemporary crop establishment and management practices is questioned due to soil degradation, higher carbon emission and declining soil productivity. Hence, this study was conducted to address the impacts of conservation agriculture (CA) practices like permanent broad beds (PBB), permanent narrow beds (PNB) and zero tilled flat beds (ZT) with residue retention on soil organic carbon (SOC) protection within aggregates in the Indo-Gangetic Plains (IGP). Compared to conventionally tilled (CT) plots, the total SOC content was ∼27%–33% higher in the CA plots on equivalent mass basis. The soil physical properties, such as soil aggregation and mean weight diameter were considerably improved under the CA practices. The macroaggregates were ∼41, 37% and 27% higher in the PBB with residue (PBB + R), PNB with residue (PNB + R) and ZT with residue (ZT + R) plots (CA plots), respectively, than the CT plots in the surface soil (0–15 cm). The plots under PBB + R had ∼31% higher microaggregates within macroaggregates than the CT plots (24.4 g 100 g−1) soil. An increase in SOC content by ∼72, 55% and 69% was observed in the PBB + R, PNB + R and ZT + R plots over the CT plots in microaggregates within macroaggregates (3.02 Mg ha−1). However, plots under PBB + R, PNB + R and ZT + R had only ∼11, 3% and 23% more SOC within silt + clay fraction, respectively, than CT plots (5.85 Mg ha−1). Thus, SOC stabilization within microaggregates inside macroaggregates was the major mechanism, and not the chemical stabilization within silt + clay, of C sequestration under CA. As aggregate-associated carbon is an ecosystem property that strongly affects organic carbon stabilization, water holding capacity and resistance to erosion, growing maize/cotton–wheat system under PBB + R practice is a viable option for carbon sequestration in the IGP and similar agro-ecologies

The impact of different fertiliser management options and cultivars on nitrogen use efficiency and yield for rice cropping in the Indo-Gangetic Plain: two seasons of methane, nitrous oxide and ammonia emissions

This study presents detailed crop and gas flux data from two years of rice production at the experimental farm of the ICAR-Indian Agricultural Research Institute, New Delhi, India. In comparing 4 nitrogen (N) fertiliser regimes across 4 rice cultivars (CRD 310, IR-64, MTU 1010, P-44), we have added to growing evidence of the environmental costs of rice production in the region. The study shows that rice cultivar can impact yields of both grain, and total biomass produced in given circumstances, with the CRD 310 cultivar showing consistently high nitrogen use efficiency (NUE) for total biomass compared with other tested varieties, but not necessarily with the highest grain yield, which was P-44 in this experiment. While NUE of the rice did vary depending on experimental treatments (ranging from 41% to 73%), 73%), this did not translate directly into the reduction of emissions of ammonia (NH3) and nitrous oxide (N2O). Emissions were relatively similar across the different rice cultivars regardless of NUE. Conversely, agronomic practices that reduced total N losses were associated with higher yield. In terms of fertiliser application, the outstanding impact was of the very high methane (CH4) emissions as a result of incorporating farmyard manure (FYM) into rice paddies, which dominated the overall effect on global warming potential. While the use of nitrification and urease inhibiting substances decreased N2O emissions overall, NH3 emissions were relatively unaffected (or slightly higher). Overall, the greatest reduction in greenhouse gas (GHG) emissions came from reducing irrigation water added to the fields, resulting in higher N2O, but significantly less CH4 emissions, reducing net GHG emission compared with continuous flooding. Overall, genetic differences generated more variation in yield and NUE than agronomic management (excluding controls), whereas agronomy generated larger differences than genetics concerning gaseous losses. This study suggests that a mixed approach needs to be applied when attempting to reduce pollution and global warming potential from rice production and potential pollution swapping and synergies need to be considered. Finding the right balance of rice cultivar, irrigation technique and fertiliser type could significantly reduce emissions, while getting it wrong can result in considerably poorer yields and higher pollution