Genome-wide association study of common resistance to rust species in tetraploid wheat

Daniela Marone Anna Maria Mastrangelo Karim Ammar Filippo Maria Bassi Meinan Wang Xianming Chen Diego Rubiales Oadi Matny Brian Steffenson (2024, [Artículo])

Wheat Rusts Tetraploid Wheat Multi-Location Trials CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA QUANTITATIVE TRAIT LOCI TETRAPLOIDY WHEAT RUSTS GENOME-WIDE ASSOCIATION STUDIES

Indian wheat genomics initiative for harnessing the potential of wheat germplasm resources for breeding disease-resistant, nutrient-dense, and climate-resilient cultivars

Sundeep Kumar Reyaz Mir Pawan Kulwal UTTAM KUMAR suneel kumar Shailendra Sharma Ravinder Singh Amit Singh Dr. Subhash Bhardwaj Manoj Prasad Kuldeep Singh (2022, [Artículo])

Indian Wheat Genomics Initiative Genomic Selection CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT GENETIC RESOURCES MARKER-ASSISTED SELECTION GENE BANKS STRESS ABIOTIC STRESS BIOTIC STRESS

Catching-up with genetic progress: Simulation of potential production for modern wheat cultivars in the Netherlands

João Vasco Silva Frits K. Van Evert Pytrik Reidsma (2023, [Artículo])

Context: Wheat crop growth models from all over the world have been calibrated on the Groot and Verberne (1991) data set, collected between 1982 and 1984 in the Netherlands, in at least 28 published studies to date including various recent ones. However, the recent use of this data set for calibration of potential yield is questionable as actual Dutch winter wheat yields increased by 3.1 Mg ha-1 over the period 1984 – 2015. A new comprehensive set of winter wheat experiments, suitable for crop model calibration, was conducted in Wageningen during the growing seasons of 2013–2014 and of 2014–2015. Objective: The present study aimed to quantify the change of winter wheat variety traits between 1984 and 2015 and to examine which of the identified traits explained the increase in wheat yield most. Methods: PCSE-LINTUL3 was calibrated on the Groot and Verberne data (1991) set. Next, it was evaluated on the 2013–2015 data set. The model was further recalibrated on the 2013–2015 data set. Parameter values of both calibrations were compared. Sensitivity analysis was used to assess to what extent climate change, elevated CO2, changes in sowing dates, and changes in cultivar traits could explain yield increases. Results: The estimated reference light use efficiency and the temperature sum from anthesis to maturity were higher in 2013–2015 than in 1982–1984. PCSE-LINTUL3, calibrated on the 1982–1984 data set, underestimated the yield potential of 2013–2015. Sensitivity analyses showed that about half of the simulated winter wheat yield increase between 1984 and 2015 in the Netherlands was explained by elevated CO2 and climate change. The remaining part was explained by the increased temperature sum from anthesis to maturity and, to a smaller extent, by changes in the reference light use efficiency. Changes in sowing dates, biomass partitioning fractions, thermal requirements for anthesis, and biomass reallocation did not explain the yield increase. Conclusion: Recalibration of PCSE-LINTUL3 was necessary to reproduce the high wheat yields currently obtained in the Netherlands. About half of the reported winter wheat yield increase was attributed to climate change and elevated CO2. The remaining part of the increase was attributed to changes in the temperature sum from anthesis to maturity and, to a lesser extent, the reference light use efficiency. Significance: This study systematically addressed to what extent changes in various cultivar traits, climate change, and elevated CO2 can explain the winter wheat yield increase observed in the Netherlands between 1984 and 2015.

Light Use Efficiency Potential Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CROP MODELLING LIGHT PHENOLOGY MAXIMUM SUSTAINABLE YIELD TRITICUM AESTIVUM WINTER WHEAT

Abiotic stress tolerance: Genetics, genomics, and breeding

Yunbi Xu Rajeev Varshney (2023, [Artículo])

Wheat Ancestors Modern Varieties Agronomic Performance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ABIOTIC STRESS GENETICS GENOMICS BREEDING GERMPLASM DROUGHT STRESS

Visualising the pattern of long-term genotype performance by leveraging a genomic prediction model

Vivi Arief Ian Delacy Thomas Payne Kaye Basford (2022, [Artículo])

Factor Analytic Genotype-By-Year Historical Data Relationship Matrix CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GENOTYPES PLANT BREEDING SPRING WHEAT RESEARCH

Impact of different on-farm management practices on bread wheat quality: a case study in the Yaqui Valley

Facundo Tabbita Iván Ortíz-Monasterios Francisco Javier Pinera-Chavez Maria Itria Ibba Carlos Guzman (2023, [Artículo])

BACKGROUND: Continuous development of new wheat varieties is necessary to satisfy the demands of farmers, industry, and consumers. The evaluation of candidate genotypes for commercial release under different on-farm conditions is a strategy that has been strongly recommended to assess the performance and stability of new cultivars in heterogeneous environments and under different farming systems. The main objectives of this study were to evaluate the grain yield and quality performance of ten different genotypes across six contrasting farmers' field conditions with different irrigation and nitrogen fertilization levels, and to develop suggestions to aid breeding programs and farmers to use resources more efficiently. Genotype and genotype by environment (GGE) interaction biplot analyses were used to identify the genotypes with the strongest performance and greatest stability in the Yaqui Valley. RESULTS: Analyses showed that some traits were mainly explained by the genotype effect, others by the field management conditions, and the rest by combined effects. The most representative and diverse field conditions in the Yaqui Valley were also identified, a useful strategy when breeders have limited resources. The independent effects of irrigation and nitrogen levels and their interaction were analyzed for each trait. The results showed that full irrigation was not always necessary to maximize grain yield in the Yaqui Valley. Other suggestions for more efficient use of resources are proposed. CONCLUSIONS: The combination of on-farm trials with GGE interaction analyses is an effective strategy to include in breeding programs to improve processes and resources. Identifying the most outstanding and stable genotypes under real on-farm systems is key to the development of novel cultivars adapted to different management and environmental conditions.

Wheat Quality Bread Wheat Bread-Making CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT QUALITY FARMING SYSTEMS

Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat

Jose Crossa Osval Antonio Montesinos-Lopez Morten Lillemo (2024, [Artículo])

Multispectral Imaging Grain Yield Genomic Prediction CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GRAIN YIELDS HIGH-THROUGHPUT PHENOTYPING SPRING WHEAT

Climate smart bread wheat (Triticum aestivum L.) variety development for optimum moisture areas of Ethiopia

Bekele Abeyo Ayele Badebo Huluka (2023, [Artículo])

GGE Biplot AMMI Model CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT ENVIRONMENT GENOTYPES GRAIN YIELDS

Molecular markers help with breeding for agronomic traits of spring wheat in Kazakhstan and Siberia

Alexey Morgounov Cecile Ben Susanne Dreisigacker Laurent Gentzbittel awais rasheed Timur Savin Sergey Shepelev Vladimir Shamanin (2024, [Artículo])

DNA Markers Grain Yield CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CEREALS DNA GENOTYPE ENVIRONMENT INTERACTION GRAIN YIELDS SPRING WHEAT

Rust research to enhance resistance durability

sridhar bhavani (2022, [Objeto de congreso])

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