Heterologous expression of the Haynaldia villosa pattern-recognition receptor CERK1-V in wheat increases resistance to three fungal diseases

Xu Zhang Jian Hua Ravi Singh (2022, [Artículo])

LysM PRR Haynaldia villosa CERK1-V CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FUNGAL DISEASES DASYPYRUM VILLOSUM WHEAT DISEASE RESISTANCE

Types of resistance

sridhar bhavani (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE WHEAT GENETIC DIVERSITY (AS RESOURCE) ADULT PLANT RESISTANCE

Gender, rainfall endowment, and farmers’ heterogeneity in wheat trait preferences in Ethiopia

Hom Nath Gartaula Moti Jaleta (2024, [Artículo])

Wheat is a vital cereal crop for smallholders in Ethiopia. Despite over fifty years of research on wheat varietal development, consideration of gendered trait preferences in developing target product profiles for wheat breeding is limited. To address this gap, our study used sex-disaggregated survey data and historical rainfall trends from the major wheat-growing regions in Ethiopia. The findings indicated heterogeneity in trait preferences based on gender and rainfall endowment. Men respondents tended to prefer wheat traits with high straw yield and disease-resistance potential, while women showed a greater appreciation for wheat traits related to good taste and cooking quality. Farmers in high rainfall areas seemed to prioritize high straw yield and disease resistance traits, while those in low rainfall areas valued good adaptation traits more highly. Most of the correlation coefficients among the preferred traits were positive, indicating that farmers seek wheat varieties with traits that serve multiple purposes. Understanding men's and women's preferences and incorporating them in breeding and seed systems could contribute to the development of more targeted and effective wheat varieties that meet the diverse needs of men and women farmers in Ethiopia.

Trait Preferences Multivariate Probit Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT AGRONOMIC CHARACTERS GENDER RAINFALL PROBIT ANALYSIS

Types of resistance

sridhar bhavani (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA RUSTS DISEASE RESISTANCE WHEAT

Mapping QTL for phenological and grain-related traits in a mapping population derived from high-zinc-biofortified wheat

Gopalareddy Krishnappa Govindan Velu (2023, [Artículo])

DArT-Seq Gene Mapping Yield Component Traits CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT QUANTITATIVE TRAIT LOCI CANDIDATE GENES QUANTITATIVE TRAIT LOCI MAPPING YIELD COMPONENTS BIOFORTIFICATION

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

Evaluation of Kenya stem rust observation nursery wheat genotypes for yield and yield components under artificial rust conditions

Mandeep Randhawa (2021, [Artículo])

Grain Yield Yield Stability Genotype x Season Interaction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT HERITABILITY YIELDS RUSTS GENOTYPES

Wheat seed demand assessment assisted by genotyping in Ethiopia

Moti Jaleta Kindie Tesfaye Olaf Erenstein (2023, [Artículo])

This study examines the extent to which wheat varieties supplied by the formal seed system align with the varieties demanded and used by farmers in Ethiopia. The framework of stated and revealed preferences drawn from the consumer preference theory is used to analyze farmer demand for different wheat varieties. We used official data from the formal seed sector and representative survey data from wheat farm households in Ethiopia. The survey data allow to contrast the farmer reported varietal use with genotyping by sequencing (also known as DNA fingerprinting). Farmers' reliance on informal seed sources and own saved seed, among others, contributes to the misidentification of the varieties they grow. Consequently, farmers are likely to misinform the formal seed demand assessment leading to either an over- or underestimation of actual seed demand for specific wheat varieties. Genotyping by sequencing, as opposed to farmer reports, established the persistence of old varieties. This also implies vulnerability of wheat production to disease dynamics depending on the longevity of disease resistance by the variety in use. Apart from narrowing the gap between the actual and stated demand and ensuring timely replacement of wheat varieties, genotyping-assisted estimates can save seed carry-over cost. Genotyping by sequencing is increasingly used as the new benchmark and gold standard for identifying and tracking the adoption of crop varieties. The technique has potential to enhance the performance of the seed sector through effective planning that can optimize resource commitments and accelerate the rate of varietal replacement.

Seed Demand Varietal Replacement CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPING-BY-SEQUENCING SEEDS WHEAT

Genetic improvement of global wheat, including progress for enhancing insect resistance

Leonardo Abdiel Crespo Herrera (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENETIC IMPROVEMENT WHEAT BREEDING CLIMATE CHANGE DISEASE RESISTANCE YIELDS

2022 Advanced wheat improvement course: Global wheat rust surveillance

&

monitoring

David Hodson (2022, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT RUSTS DISEASE SURVEILLANCE NEW TECHNOLOGY REMOTE SENSING