Modeling the growth, yield and N dynamics of wheat for decoding the tillage and nitrogen nexus in 8-years long-term conservation agriculture based maize-wheat system

C.M. Parihar Dipaka Ranjan Sena Prakash Chand Ghasal Shankar Lal Jat Yashpal Singh Saharawat Mahesh Gathala Upendra Singh Hari Sankar Nayak (2024, [Artículo])

Context: Agricultural field experiments are costly and time-consuming, and their site-specific nature limits their ability to capture spatial and temporal variability. This hinders the transfer of crop management information across different locations, impeding effective agricultural decision-making. Further, accurate estimates of the benefits and risks of alternative crop and nutrient management options are crucial for effective decision-making in agriculture. Objective: The objective of this study was to utilize the Crop Environment Resource Synthesis CERES-Wheat model to simulate crop growth, yield, and nitrogen dynamics in a long-term conservation agriculture (CA) based wheat system. The study aimed to calibrate the model using data from a field experiment conducted during the 2019-20-2020-21 growing seasons and evaluation it with independent data from the year 2021–22. Method: Crop simulation models, such as the Crop Environment Resource Synthesis CERES-Wheat (DSSAT v 4.8), may provide valuable insights into crop growth and nitrogen dynamics, enabling decision makers to understand and manage production risk more effectively. Therefore, the present study employed the CERES-Wheat (DSSAT v 4.8) model and calibrated it using field data, including plant phenological phases, leaf area index, aboveground biomass, and grain yield from the 2019-20-2020-21 growing seasons. An independent dataset from the year 2021–22 was used for model evaluation. The model was used to investigate the relationship between growing degree days (GDD), temperature, nitrate and ammonical 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 wheat yields. The experimental site is situated at ICAR-Indian Agricultural Research Institute (IARI), New Delhi, representing Indian Trans-Gangetic Plains Zone (28o 40’N latitude, 77o 11’E longitude and an altitude of 228 m above sea level). The treatments consist of four nitrogen management options, viz., N0 (zero nitrogen), N150 (150 kg N ha−1 through urea), GS (Green seeker based urea application) and USG (urea super granules @150 kg N ha−1) in two contrasting tillage systems, i.e., CA-based zero tillage (ZT) and conventional tillage (CT). Result: The outcomes exhibited favorable agreement between the model’s simulations and the observed data for crop phenology (With less than 2 days variation in 50% onset of flowering), grain and biomass yield (Root mean square error; RMSE 336 kg ha−1 and 649 kg ha−1, respectively), and leaf area index (LAI) (RMSE 0.28 & normalized RMSE; nRMSE 6.69%). The model effectively captured the nitrate-N (NO3−-N) dynamics in the soil profile, exhibiting a remarkable concordance with observed data, as evident from its low RMSE = 12.39 kg ha−1 and nRMSE = 13.69%. Moreover, as it successfully simulated the N balance in the production system, the nitrate leaching and ammonia volatilization pattern as described by the model are highly useful to understand these critical phenomena under both conventional tillage (CT) and CA-based Zero Tillage (ZT) treatments. Conclusion: The study concludes that the DSSAT-CERES-Wheat model has significant potential to assess the impacts of tillage and nitrogen management practices on crop growth, yield, and soil nitrogen dynamics in the western Indo-Gangetic Plains (IGP) region. By providing reliable forecasts within the growing season, this modeling approach can facilitate better planning and more efficient resource management. Future implications: The successful implementation of the DSSAT-CERES-Wheat model in this study highlights its applicability in assessing crop performance and soil dynamics. Future research should focus on expanding the model’s capabilities by reducing its sensitivity to initial soil nitrogen levels to refine its predictions further. Moreover, the model’s integration with decision support systems and real-time data can enhance its usefulness in aiding agricultural decision-making and supporting sustainable crop management practices.

Nitrogen Dynamics Mechanistic Crop Growth Models Crop Simulation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA NITROGEN CONSERVATION AGRICULTURE WHEAT MAIZE CROP GROWTH RATE SIMULATION MODELS

Hymenopteran parasitoid complex and fall armyworm: a case study in eastern India

Tapamay Dhar PRATEEK MADHAB BHATTACHARYA Mahesh Gathala Alison Laing (2024, [Artículo])

Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) has significantly affected maize crop yields, production efficiency, and farmers’ incomes in the Indian Eastern Gangetic Plains region since it was first observed in India in 2018. A lack of awareness by maize growers of the appropriate selection, method, and timing of insecticide application not only creates a barrier to sustainable FAW control but also contributes to increased environmental pollution, reduced human health and increased production costs. We demonstrated that FAW inflicted the most damage in early whorl growth stage of maize, regardless of whether chemical insecticides were applied. FAW egg masses and larvae collected from maize fields in which no insecticides had been sprayed showed high parasitism rates by parasitoid wasps; in contrast fields that had been sprayed had much lower rates of parasitism on FAW. Ten hymenopteran parasitoids were observed in maize fields across the study region, suggesting a diversity of natural methods to suppress FAW in maize at different growth stages. These included two FAW egg parasitoids and eight FAW larval parasitoids. Microplitis manilae Ashmead was the most abundant FAW larval parasitoid species, and Telenomus cf. remus was the dominant FAW egg parasitoid species. Endemic FAW parasitoids such as those observed in this study have great potential as part of a sustainable, cost-effective agroecological management strategy, which can be integrated with other methods to achieve effective control of FAW.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FALL ARMYWORMS MAIZE INSECTICIDES INSECT CONTROL

Dead level contour technical design parameters required for sustainable crop production in semiarid areas of Zimbabwe

Menas Wuta Isaiah Nyagumbo (2021, [Artículo])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE DRY SPELLS RAINWATER HARVESTING CROP PRODUCTION TECHNOLOGY

New genomic regions identified for resistance to spot blotch and terminal heat stress in an interspecific population of triticum aestivum and T. spelta

Sudhir Navathe Ramesh Chand Mir Asif Iquebal Govindan Velu arun joshi (2022, [Artículo])

Resistance Terminal Heat CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BIPOLARIS SOROKINIANA HEAT STRESS WHEAT RESISTANCE VARIETIES

Population genetic structure of the maize weevil, Sitophilus zeamais, in southern Mexico

Michael Jones Martha Willcox (2023, [Artículo])

Maize Weevil Genetic Structure CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL WORKERS FILTRATION GENE FLOW MAIZE SINGLE NUCLEOTIDE POLYMORPHISM SITOPHILUS ZEAMAIS CURCULIONIDAE

Dead level contour technical design parameters required for sustainable crop production in semi-arid areas of Zimbabwe

Menas Wuta Isaiah Nyagumbo (2021, [Artículo])

Maize Yield Optimum Interval Dead Level Contours CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA TECHNOLOGY DRY SPELLS MAIZE YIELDS RAINWATER HARVESTING

On-farm storage loss estimates of maize in Kenya using community survey methods

Hugo De Groote Anani Bruce (2023, [Artículo])

Maize is the most important staple in sub-Saharan Africa (SSA), with highly seasonal production. High storage losses affect food security, but good estimations are lacking. A new method using focus group discussions (FGDs) was tested with 121 communities (1439 farmers, 52% women) in Kenya's six maize-growing zones, to estimate the maize losses to storage pests and analyze farmer practices. As control strategies, half of the farmers used chemical pesticides (49%), while hermetic bags (16%) and botanicals (15%) were also popular. Relative loss from weevils in the long rains was estimated at 23%, in the short rains 18%, and annually 21%. Fewer farmers were affected by the larger grain borer (LGB) than by maize weevils: 42% in the long rainy season and 32% in the short rainy season; losses from LGB were also smaller: 19% in the long season, 17% in the short season, and 18% over the year. Total storage loss, from both species combined, was estimated at 36%, or 671,000 tonnes per year. The greatest losses occur in the humid areas, especially the moist mid-altitudes (56%), and with smaller loss in the drylands (20–23%). Extrapolating the point data and overlaying with the maize production map shows the geographic distribution of the losses, with the most important area found around Lake Victoria. FGDs provide convenient and cheap tools to estimate storage losses in representative communities, but a total loss estimate of 36% is higher than is found in other studies, so its accuracy and framing effects need to be assessed. We conclude that storage pests remain a major problem, especially in western Kenya, and that the use of environmentally friendly technologies such as hermetic storage and botanicals needs more attention, both by the public extension service and private agrodealers.

Larger Grain Borer Maize Weevil CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE STORAGE LOSSES PESTS SURVEY METHODS

Performance evaluation and identification of highland quality protein maize hybrids in Ethiopia

Adefris Teklewold (2022, [Artículo])

Quality Protein Conventional Maize CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE PROTEIN QUALITY CROSS-BREEDING HYBRIDS

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics

Xu Wang Sandesh Kumar Shrestha Philomin Juliana Suchismita Mondal Francisco Pinto Govindan Velu Leonardo Abdiel Crespo Herrera JULIO HUERTA_ESPINO Ravi Singh Jesse Poland (2023, [Artículo])

New Crop Varieties Plant Breeding Programs Yield Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA LEARNING GRAIN YIELDS WHEAT BREEDING FOOD SECURITY

Multi-omic characterization of the maize GPI synthesis mutant gwt1 with defects in kernel development

Sarah Hearne zhiyuan fu (2023, [Artículo])

Maize Endosperm Development Membrane Proteomics Glycosyl-Phosphatidyl-Inositol Membrane Anchored Proteins CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE ENDOSPERM MEMBRANES PROTEOMICS TRANSCRIPTOMICS