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Autor: Maria Itria Ibba
Wheat Blast Data for seven CIMMYT wheat nurseries during the 2022 cropping cycle
Pawan Singh Xinyao He Maria Itria Ibba (2023)
Wheat head blast index (%) data for seven CIMMYT nurseries (12HPAN, 13HLBSN, 13HZAN, 38SAWSN, 52IDSN, 53IBWSN, 54IBWSN) is presented. Field trials took place in Quirusillas and Okinawa (Bolivia) and Jashore (Bangladesh) during the 2022 cycles. Two sowings were made in each location/cycle.
Dataset
Alon Cna'ani Vered Tzin Maria Itria Ibba Hector Gonzalez-Santoyo (2023)
Artículo
Wheat Landraces Wholemeal Flour Aroma Compounds Sourdough Bread CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AMINO ACIDS FLAVOUR COMPOUNDS HARD WHEAT ORGANIC ACIDS WHOLE GRAIN FLOUR
Wenfei Tian Maria Itria Ibba Govindan Velu Shuanghe Cao Zhonghu He (2024)
Artículo
CIMMYT Germplasm CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GERMPLASM FERULIC ACID FUNCTIONAL FOODS PHYTOCHEMICALS YIELD POTENTIAL WHEAT FOOD PRODUCTION
Susanne Dreisigacker Jose Crossa Leonardo Abdiel Crespo Herrera Maria Itria Ibba (2024)
This dataset is derived from a study focused on developing an efficient method for arabinoxylan quantification, called PentoQuant. It includes phenotypic and molecular characterization data from 606 bread wheat samples developed through the spring bread wheat breeding program. The dataset comprises total and water-extractable arabinoxylan content values measured using the PentoQuant protocol. Furthermore, it incorporates results obtained from analyzing the same 606 lines with four molecular markers associated with two major QTLs for arabinoxylan content variation in wheat, located on chromosomes 1B and 6B.
Dataset
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
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
Response to heat stress and glutenins allelic variation effects on quality traits in durum wheat
Facundo Tabbita Karim Ammar Maria Itria Ibba MARCO MACCAFERRI ROBERTO TUBEROSA Carlos Guzman (2024)
Artículo
Gluten Quality Sedimentation Volume Wheat Quality CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA GLUTEN QUALITY GLUTENINS HEAT STRESS WHEAT
Daniel Runcie Maria Itria Ibba Osval Antonio Montesinos-Lopez Leonardo Abdiel Crespo Herrera Alison Bentley Jose Crossa (2021)
Several different genome-based prediction models are available for the analysis of multi-trait data in genomic selection. The supplemental files included in this dataset provide six extensive multi-trait wheat datasets (quality and grain yield) that enable the comparison of performance of genomic-enabled-prediction when calculating the prediction accuracy using different methods. The related article describes the results of the analysis and reports that trait grain yield prediction performance is better under a multi-trait model as compared with the single-trait model.
Dataset
Replication Data for: Genome-based prediction of multiple wheat quality traits in multiple years
Maria Itria Ibba Jose Crossa Osval Antonio Montesinos-Lopez Philomin Juliana Carlos Guzman Susanne Dreisigacker Jesse Poland (2020)
The use of genomic prediction could greatly help to increase the efficiency of selecting for wheat quality traits by reducing the cost and time required for this analysis. This study contains data used to evaluate the prediction performances of 13 wheat quality traits under two multi-trait models [Bayesian multi-trait multi-environment (BMTME) and multi-trait ridge regression (MTR)]. Separate files are provided for each year of data. An additional supplemental data file provides R code for running the analyses as well as a table describing the Average Pearson´s correlation (APC) and mean arctangent absolute percentage error (MAAPE) for the testing sets for each dataset and trait.
Dataset