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Autor: Carlos Guzman
PPO activity in bread wheat breeding lines from C53IBWSN
Carlos Guzman (2019)
Breeding lines cultivated in CENEB (C. Obregon) during cropping cycle 17-18 were analyzed for PPO activity
Dataset
Deep kernel of genomic and near infrared predictions in multi-environment breeding trials
Carlos Guzman Jose Crossa (2019)
In genomic prediction deep learning artificial neural network are part of machine learning methods that incorporate parametric, non-parametric and semi-parametric statistical models. Kernel methods are seeing more flexible, and easier to interpret than neural networks. Kernel methods used in genomic predictions comprise the linear genomic best linear unbiased predictor (GBLUP) kernel (GB) and the Gaussian kernel (GK). These kernels have being used with two statistical models, single environment and genomic × environment (GE) models. Recently near infrared spectroscopy (NIR) has being used as phenotype method for prediction of unobserved line performance in plant breeding trials. In this study, we used a non-linear Arc-cosine kernel (AK) that emulates deep learning artificial neural network. We compared AK prediction accuracy with GB and GK kernel methods in four genomic data sets one of them including also pedigree (ABLUP) and NIR (NBLUP) information. Results show that for all four data sets AK and GK kernels gave higher prediction accuracy than the linear GB kernel for single environment as well as GE multi-environment models. In addition, AK gave similar or slightly higher prediction accuracy than the GK kernel.
Dataset
Rigel Hugo Carreón Reyes Juan Carlos Neri Guzmán (2023)
El presente estudio indica de una forma tangible la aplicación de la herramienta FMEA (Failure Mode And Effects Analysis -por sus siglas en inglés) en la aplicación de fabricación de cerámica sanitaria, en donde se evalúan las variables que están relacionadas con el proceso de diseño, procesamiento de piezas cerámicas y de su relación existente para poder alcanzar los requisitos normativos y que estos a su vez sean alcanzables. Dentro del estudio se presenta el análisis y elaboración de la matriz riesgos en modo de fallas, así como una serie de definiciones estadísticas con las cuales son evaluados los procesos de fabricación, así como la explicación clara de la metodología FMEA en donde se indica la adecuación de estos conceptos a este tipo de manufacturas (cerámica sanitaria). Este trabajo también describe a través del estudio de caso de las variables una metodología que detalla los conceptos básicos tales como severidad, detección y ocurrencia combinando el desarrollo de tablas parametrizadas y / o acopladas al tipo de proceso de manufactura cerámica .En los resultados que se obtienen se observa la disminución de la incertidumbre hasta de 85% en los valores de RPN y una mejora en el cpk >1,33 como índice de calidad los riesgos o incertidumbres disminuidos son de forma numérica a través de la comprobación de nuevas acciones y el reanálisis de los conceptos de ocurrencia y detección derivados de la implementación de acciones. Las conclusiones indican como una herramienta adecuada el uso de FMEA para el campo de aplicación de la manufactura de cerámica sanitaria.
The present study indicates in a tangible way the application of the FMEA tool (Failure Mode and Effects Analysis) in the application of sanitary ceramic manufacturing, where the variables that are related to the process of design, processing of ceramic pieces and their existing relationship are evaluated in order to achieve the regulatory requirements and that these in turn are achievable. The study presents the analysis and elaboration of the risk matrix in failure mode as well as a series of statistical definitions with which the manufacturing processes are evaluated as well as the clear explanation of the FMEA methodology (failure mode and effects analysis) where the application and adequacy of these concepts to this type of manufactures (sanitary ceramics) is indicated. This paper also describes through the case study of the variables a methodology that details the basic concepts such as severity, detection and occurrence combining the development of parameterized tables and / or coupled to the type of ceramic manufacturing process. In the results obtained, the decrease in uncertainty of until 85% in the values of RPN and an improvement in the cpk >1.33 as a quality index, the risks or uncertainties decreased are numerically through the verification of new actions and the reanalysis of the concepts of occurrence and detection derived from the implementation of actions. The conclusions indicate as an appropriate tool the use of FMEA for the field of application of the manufacture of sanitary ceramics.
Artículo
AMEF (Análisis de Modo de Efecto y Falla) Productos cerámicos Cerámica sanitaria Procesos cerámicos Severidad Detección Ocurrencia FMEA (Failure Mode and Effects Analysis) Ceramic products Standard ASME Sanitary ceramic Ceramic processess INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS
Phenotypic and genotypic data from the CIMMYT Durum Wheat Breeding Program
Karim Ammar Carlos Guzman Susanne Dreisigacker JULIO HUERTA_ESPINO (2018)
Phenotypic data collected in on-station field trials and genotypic data for breeding materials from the CIMMYT Durum Wheat breeding program are included in this study.
Dataset
Maryke Labuschagne Carlos Guzman Jose Crossa Angeline van Biljon (2023)
Artículo
Loaf Volume Durum Wheat Flour Protein Content CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA ALVEOGRAPHS HARD WHEAT HEAT STRESS DROUGHT STRESS
Thomas Payne Roberto Peña Carolina Saint Pierre Carlos Guzman (2019)
This study contains raw phenotypic data files related to grain quality analyses and morphological characterization of wheat accessions.The trials include: (1) 1SEEDXCT_Batan (2) SEEDXCT_A_B_C_D (3) 2SEEDXCT (4) 3SEED_XCT: TID 52508, 52509 (5) INCBV (6) MXI_2011-2012 (7) MXI_2012-2013. . ** Please note that these data have not been rigorously curated.**
Dataset
Phenotypic and genotypic data from the CIMMYT Durum Wheat Breeding Program
Karim Ammar Carlos Guzman Susanne Dreisigacker JULIO HUERTA_ESPINO (2018)
Phenotypic data collected in on-station field trials and genotypic data for breeding materials from the CIMMYT Durum Wheat breeding program are included in this study.
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
Grain quality data from CIMMYT bread wheat breeding program (2010-2015)
Sarah Battenfield Susanne Dreisigacker Roberto Peña Ravi Singh Carlos Guzman Jesse Poland (2018)
Bread wheat breeding lines from yield and elite yield trials are analyzed annually for grain quality traits at the Wheat Chemistry and Quality Laboratory of CIMMYT. The analysis done are the following: grain morphology (test weight and thousand kernel weight), grain hardness and protein content, flour yield, flour protein content, SDS-sedimentation test, mixograph, alveograph and bread-making. Based on this data breeding lines combining good agronomic performance and desirable processing and end-use quality are selected and move forward in the breeding process.
Dataset
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