GWAS identifies genetic loci underlying nitrogen responsiveness in the climate resilient C4 model Setaria italica (L.)

Tirthankar Bandyopadhyay Stéphanie M. Swarbreck Vandana Jaiswal Rajeev Gupta Alison Bentley Manoj Prasad (2022, [Artículo])

C4 Model Crop Climate Resilience CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE RESILIENCE FOOD SECURITY GENE EXPRESSION NITROGEN

Enhancing maize yield in a conservation agriculture-based maize (Zea mays)- wheat (Triticum aestivum) system through efficient nitrogen management

C.M. Parihar Hari Sankar Nayak Dipaka Ranjan Sena Shankar Lal Jat Mahesh Gathala Upendra Singh (2023, [Artículo])

This study evaluated the impact of contrasting tillage and nitrogen management options on the growth, yield attributes, and yield of maize (Zea mays L.) in a conservation agriculture (CA)-based maize-wheat (Triticum aestivum L.) system. The field experiment was conducted during the rainy (kharif) seasons of 2020 and 2021 at the research farm of ICAR-Indian Agricultural Research Institute (IARI), New Delhi. The experiment was conducted in a split plot design with three tillage practices [conventional tillage with residue (CT), zero tillage with residue (ZT) and permanent beds with residue (PB)] as main plot treatments and in sub-plots five nitrogen management options [Control (without N fertilization), recommended dose of N @150 kg N/ha, Green Seeker-GS based application of split applied N, N applied as basal through urea super granules-USG + GS based application and 100% basal application of slow release fertilizer (SRF) @150 kg N/ha] with three replications. Results showed that both tillage and nitrogen management options had a significant impact on maize growth, yield attributes, and yield in both seasons. However, time to anthesis and physiological maturity were not significantly affected. Yield attributes were highest in the permanent beds and zero tillage plots, with similar numbers of grains per cob (486.1 and 468.6). The highest leaf area index (LAI) at 60 DAP was observed in PB (5.79), followed by ZT(5.68) and the lowest was recorded in CT (5.25) plots. The highest grain yield (2-year mean basis) was recorded with permanent beds plots (5516 kg/ha), while the lowest

was observed with conventional tillage (4931 kg/ha). Therefore, the study highlights the importance of CA practices for improving maize growth and yield, and suggests that farmers can achieve better results through the adoption of CA-based permanent beds and use of USG as nitrogen management option.

Green Seeker Urea Super Granules CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE UREA YIELDS ZERO TILLAGE NITROGEN

Crop performance and nitrogen use-efficiency in maize under conservation agriculture coupled with sub-surface drip fertigation

C.M. Parihar Hari Sankar Nayak Renu Pandey ML JAT (2021, [Artículo])

Biological Yield Permanent Beds Yield Attributes CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA YIELDS NITROGEN NUTRIENT UPTAKE CROP PERFORMANCE MAIZE

Influence of residue type and method of placement on dynamics of decomposition and nitrogen release in maize-wheat-mungbean cropping on permanent raised beds: a litterbag study

ML JAT Rajeev Gupta (2022, [Artículo])

Decomposition Rate Nitrogen Release Placement Effect CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP RESIDUES DEGRADATION NITROGEN PLACEMENT

Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Zea mays. L) under optimum and low nitrogen conditions

Noel Ndlovu Vijay Chaikam Berhanu Tadesse Ertiro Biswanath Das Yoseph Beyene Charles Spillane Prasanna Boddupalli Manje Gowda (2023, [Artículo])

Grain Yield Low Soil Nitrogen CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN NITROGEN SOIL CHEMICOPHYSICAL PROPERTIES MAIZE QUANTITATIVE TRAIT LOCI

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

Preliminary dissection of grain yield and related traits at differential nitrogen levels in diverse pre-breeding wheat germplasm through association mapping

Achla Sharma Juan Burgueño Prashant Vikram Nitika Sandhu Satinder Kaur Parveen Chhuneja (2023, [Artículo])

Plant Nitrogen Use Efficiency Pre-Breeding Lines Genome-Wide Association Study Marker Trait Association CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PRE-BREEDING BREEDING LINES NITROGEN LANDRACES GENETIC MARKERS

Low nitrogen narrows down phenotypic diversity in durum wheat

Tesfaye Geleta Aga Bekele Abeyo (2023, [Artículo])

Clusters Durum Wheat Nitrogen Efficiency CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA HARD WHEAT GENETIC DIVERGENCE NORMALIZED DIFFERENCE VEGETATION INDEX NITROGEN PRINCIPAL COMPONENT ANALYSIS

Accumulation of wheat phenolic acids under different nitrogen rates and growing environments

Wenfei Tian Yong Zhang Zhonghu He (2022, [Artículo])

Functional Wheat Trans-Ferulic Acid Nitrogen Management Environment Interaction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PHENOLIC ACIDS NITROGEN ENVIRONMENT ANTIOXIDANTS

Genética de la resistencia al complejo mancha de asfalto en 18 genotipos tropicales de maíz

George Mahuku Ignacio Benítez-Riquelme Serafin Cruz-Izquierdo (2015, [Artículo])

Horizontal Resistance Tar Spot Complex CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FUNGI MONOGRAPHELLA PHYLLACHORALES ZEA MAYS DIALLEL ANALYSIS DISEASE RESISTANCE