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Autor: Francisco Javier Pinera-Chavez
Facundo Tabbita Iván Ortíz-Monasterios Francisco Javier Pinera-Chavez Maria Itria Ibba Carlos Guzman (2023)
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.
Artículo
Wheat Quality Bread Wheat Bread-Making CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA SOFT WHEAT QUALITY FARMING SYSTEMS
On-farm assessment of yield and quality traits in durum wheat
Facundo Tabbita Iván Ortíz-Monasterios Francisco Javier Pinera-Chavez Maria Itria Ibba Carlos Guzman (2023)
BACKGROUND: Durum wheat is key source of calories and nutrients for many regions of the world. Demand for it is predicted to increase. Further efforts are therefore needed to develop new cultivars adapted to different future scenarios. Developing a novel cultivar takes, on average, 10 years and advanced lines are tested during the process, in general, under standardized conditions. Although evaluating candidate genotypes for commercial release under different on-farm conditions is a strategy that is strongly recommended, its application for durum wheat and particularly for quality traits has been limited. This study evaluated the grain yield and quality performance of eight different genotypes across five contrasting farmers’ fields over two seasons. Combining different analysis strategies, the most outstanding and stable genotypes were identified. RESULTS: The analyses revealed that some traits were mainly explained by the genotype effect (thousand kernel weight, flour sodium dodecyl sulfate sedimentation volume, and flour yellowness), others by the management practices (yield and grain protein content), and others (test weight) by the year effect. In general, yield showed the highest range of variation across genotypes, management practices, and years and test weight the narrowest range. Flour yellowness was the most stable trait across management conditions, while yield-related traits were the most unstable. We also determined the most representative and discriminative field conditions, which is a beneficial strategy when breeders are constrained in their ability to develop multi-environment experiments. CONCLUSIONS: We concluded that assessing genotypes in different farming systems is a valid and complementary strategy for on-station trials for determining the performance of future commercial cultivars in heterogeneous environments to improve the breeding process and resources.
Artículo
Wheat Quality GGE Analysis Flour Yellowness CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA FLOURS WHEAT QUALITY YIELDS FIELD EXPERIMENTATION
Phenotypic data of HIBAP I panel under yield potential and heat stress conditions
Gemma Molero Benedict Coombes Ryan Joynson Francisco Pinto Francisco Javier Pinera-Chavez Carolina Rivera-Amado Anthony Hall Matthew Paul Reynolds (2022)
Phenotypic data of HIBAP I panel evaluated under yield potential and heat stress conditions during Obregon wheat seasons 2015-16 and 2016-17. Combined data across years per environment. The HIBAP I panel is comprised of 149 high biomass spring wheat lines of a variety of elite and exotic backgrounds. It was demonstrated how strategic integration of exotic material significantly increases yield under heat stress compared to elite lines, with no significant yield penalty under favourable conditions. Through genome wide association analysis three marker trait associations were revealed. The yield increase was associated with lower canopy temperature. An Aegilops tauschii introgression was identified as the most significant of these associations. Publicly available sequencing data used in this study is available at the European Nucleotide Archive (ENA). More information about the location of sequencing data can be found in the section 'Data availability' of the referenced manuscript at https://doi.org/10.1101/2022.02.09.479695.
Dataset
Replication Data for: Exotic alleles contribute to heat tolerance in wheat under field conditions
Gemma Molero Benedict Coombes Ryan Joynson Francisco Pinto Francisco Javier Pinera-Chavez Carolina Rivera-Amado Anthony Hall Matthew Paul Reynolds (2023)
Plant breediers must respond to the threats posed by climate change in order to help ensure global food security in the short and long term. A better understanding of the genetic underpinnings of heat tolerance can contribute to efforts to develop more resilient crops. The exome capture data from 149 spring wheat lines provided in this dataset were used to search for loci, including loci from an exotic wheat relative, that could contribute to enhanced heat tolerance. The HIBAP_Germplasm file provides a HIBAP_NUMBER that appears in name of the exome capture files to link them to specific germplasm.The methods and results of the study are described in the accompanying article.
Dataset
Multimodal deep learning methods enhance genomic prediction of wheat breeding
Carolina Rivera-Amado Francisco Pinto Francisco Javier Pinera-Chavez David González-Diéguez Matthew Paul Reynolds Paulino Pérez-Rodríguez Huihui Li Osval Antonio Montesinos-Lopez Jose Crossa (2023)
Artículo
Conventional Methods Genomic Prediction Accuracy Deep Learning Novel Methods CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT BREEDING MACHINE LEARNING METHODS MARKER-ASSISTED SELECTION
Replication Data for: Multimodal Deep Learning Methods Enhance Genomic Prediction of Wheat Breeding
Carolina Rivera-Amado Francisco Pinto Francisco Javier Pinera-Chavez David González-Diéguez Paulino Pérez-Rodríguez Huihui Li Osval Antonio Montesinos-Lopez Jose Crossa (2023)
In plant breeding research, several statistical machine learning methods have been developed and studied for assessing the genomic prediction (GP) accuracy of unobserved phenotypes. To increase the GP accuracy of unobserved phenotypes while simultaneously accounting for the complexity of genotype × environment interaction (GE), deep learning (DL) neural networks have been developed.These analyses can potentially include phenomics data obtained through imaging. The two datasets included in this study contain phenomic, phenotypic, and genotypic data for a set of wheat materials. They have been used to compare a novel DL method with conventional GP models.The results of these analyses are reported in the accompanying journal article.
Dataset