Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Osval Antonio Montesinos-Lopez ABELARDO MONTESINOS LOPEZ RICARDO ACOSTA DIAZ Rajeev Varshney Jose Crossa ALISON BENTLEY (2022, [Artículo])

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to

the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA Bayes Theorem Genome Inflammatory Bowel Diseases Models, Genetic Plant Breeding

A Flexible, Extensible, Machine-Readable, Human-Intelligible, and Ontology-Agnostic Metadata Schema (OIMS)

Gideon Kruseman (2022, [Artículo])

Reusability Java Script Object Notation CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA DATA MANAGEMENT INTEROPERABILITY METADATA SOCIOECONOMIC ASPECTS

CIMMYT Eastern Africa early- to intermediate maturity maize breeding pipelines (EA-PP1)

Yoseph Beyene Andrew Chavangi Manje Gowda Suresh L.M. Vijay Chaikam Anani Bruce Berhanu Tadesse Ertiro Walter Chivasa Aparna Das Juan Burgueño Jose Crossa Prasanna Boddupalli (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE BREEDING LINES MARKET SEGMENTATION HYBRIDS GERMPLASM

Big data, small explanatory and predictive power: Lessons from random forest modeling of on-farm yield variability and implications for data-driven agronomy

Martin van Ittersum (2023, [Artículo])

Context: Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency. Objective: The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide. Methods: A large database of 10,940 field-year combinations from three countries in different stages of agricultural intensification was analyzed. Random effects models were used to partition crop yield variability and random forest models were used to explain and predict crop yield within a cross-validation scheme with data re-sampling over space and time. Results: Yield variability in relative terms was smallest for wheat and barley in the Netherlands and for wheat in Ethiopia, intermediate for rice in the Philippines, and greatest for maize in Ethiopia. Random forest models comprising a total of 87 variables explained a maximum of 65 % of cereal yield variability in the Netherlands and less than 45 % of cereal yield variability in Ethiopia and in the Philippines. Crop management related variables were important to explain and predict cereal yields in Ethiopia, while predictive (i.e., known before the growing season) climatic variables and explanatory (i.e., known during or after the growing season) climatic variables were most important to explain and predict cereal yield variability in the Philippines and in the Netherlands, respectively. Finally, model cross-validation for regions or years not seen during model training reduced the R2 considerably for most crop x country combinations, while for wheat in the Netherlands this was model dependent. Conclusion: Big data from farmers’ fields is useful to explain on-farm yield variability to some extent, but not to predict it across time and space. Significance: The results call for moderate expectations towards big data and machine learning in agronomic studies, particularly for smallholder farms in the tropics where model performance was poorest independently of the variables considered and the cross-validation scheme used.

Model Accuracy Model Precision Linear Mixed Models CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MACHINE LEARNING SUSTAINABLE INTENSIFICATION BIG DATA YIELDS MODELS AGRONOMY

Normalización, certificación y evaluación de competencias laborales en el sector agua

ANTONIO ROMERO CASTRO Armando Mendiola (2011, [Documento de trabajo])

Dentro de los objetivos del proyecto están lograr la acreditación como entidad de certificación y evaluación; diseñar y elaborar proyectos de estándar de competencia y sus instrumentos de evaluación, relacionados con funciones del sector hídrico; preparar los documentos y la logística necesaria para realizar sesiones que el Comité de Gestión de Competencias del sector hídrico considere pertinentes; y difundir en el IMTA los trabajos de diseño y elaboración de estándares de competencia laboral para la capacitación, evaluación y certificación de personal del sector hídrico con dichos estándares.

Competencias laborales Certificación Evaluación Informes de proyectos HUMANIDADES Y CIENCIAS DE LA CONDUCTA

Highlight of CIMMYT East Africa maize product profile-3 (EA-PP3, highland)

Adefris Teklewold (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE BREEDING MARKET SEGMENTATION HYBRIDS GENETIC GAIN INBRED LINES

Local markets and food security. The case of the Milpera and Puuc regions in Yucatan

Ana Laura Bojórquez Carrillo Monserrat Vargas Jiménez Mireya Noemi Hernández Islas (2023, [Artículo, Artículo])

Food insecurity is a complex problem worldwide. A major part of this problem is the food supply. Local markets can represent a strategy for building social capital, as well as strategies for subsistence and sustainability of food value chains, contributing to food security and its effects. The objective of this research is to determine if the existence of a municipal market in the Milpera and Puuc regions of Yucatán favors the existence of food security, the consumption or the expense of natural foods. The population is located in 18 municipalities of Yucatán, Mexico. To carry out this study, a cross-sectional, non-experimental study, with a quantitative approach and correlational scope. The main techniques that were applied were descriptive statistics and contingency tables with respect to 6 hypotheses. This work shows that the existence of markets in the communities makes a significant difference because it positively impacts the food security of the inhabitants, since it allows them to have access to a wider variety of products and at the same time, favors the active dynamics of the economy of the community.

Local markets Food safety Local development Food sovereignty Rural areas Mercados locales Seguridad alimentaria Desarrollo local Soberanía alimentaria Zonas rurales CIENCIAS SOCIALES CIENCIAS SOCIALES

Agricultural value chains in Sudan: an annotated bibliography

Hugo De Groote Paswel Marenya (2023, [Libro])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL VALUE CHAINS CASH CROPS FOOD CROPS LIVESTOCK SOCIOECONOMIC ASPECTS GENDER SOCIAL INCLUSION POSTHARVEST LOSSES BIBLIOGRAPHIES

Impacto de COVID-19 sobre el consumo eléctrico de las PYMES de la Zona Metropolitana de Aguascalientes

Alonso Darío Pizarro Lagunas (2021, [Tesis de maestría])

La irrupción de COVID-19 en el escenario mundial no sólo se convirtió en una crisis de salud pública sino una crisis económica que tuvo efectos heterogéneos en muchos países en el mundo. En particular, muchas economías experimentaron una fuerte contracción en su producto interno bruto debido en gran parte a las medidas de distanciamiento social y restricción de actividades no esenciales que los países adoptaron para proteger la salud de sus habitantes. Esto afectó al sector eléctrico, ya que muchas industrias disminuyeron su consumo energético. En México, las pequeñas y medianas empresas representan una parte importante del consumo eléctrico de la industria. En este sentido, tomando una muestra representativa de pequeños y medianos establecimientos de la Zona Metropolitana de Aguascalientes estudiamos el comportamiento del consumo eléctrico de estas empresas notando que hubo caídas significativas del consumo eléctrico cuando irrumpió la pandemia en marzo de 2020 en la ZMA. Además, notamos que la caída en consumo eléctrico fue más pronunciada para establecimientos en el sector de servicios que establecimientos en el sector de comercios durante la pandemia. Además, se concluye que las disminuciones en la jornada laboral jugaron un papel importante en esta contracción, mientras que las medidas como digitalización y reducción de empleados no estuvieron relacionadas con la variación de consumo eléctrico en estos pequeños y medianos establecimientos.

Small business -- Energy consumption -- Effect of COVID-19 Pandemic, 2020- on -- Aguascalientes (Mexico) -- Econometric models. COVID-19 Pandemic, 2020- -- Aguascalientes (Mexico) -- Economic aspects. CIENCIAS SOCIALES CIENCIAS SOCIALES

Local markets and food security. The case of the Milpera and Puuc regions in Yucatan

Ana Laura Bojórquez Carrillo Monserrat Vargas Jiménez Mireya Noemi Hernández Islas (2023, [Artículo, Artículo])

Food insecurity is a complex problem worldwide. A major part of this problem is the food supply. Local markets can represent a strategy for building social capital, as well as strategies for subsistence and sustainability of food value chains, contributing to food security and its effects. The objective of this research is to determine if the existence of a municipal market in the Milpera and Puuc regions of Yucatán favors the existence of food security, the consumption or the expense of natural foods. The population is located in 18 municipalities of Yucatán, Mexico. To carry out this study, a cross-sectional, non-experimental study, with a quantitative approach and correlational scope. The main techniques that were applied were descriptive statistics and contingency tables with respect to 6 hypotheses. This work shows that the existence of markets in the communities makes a significant difference because it positively impacts the food security of the inhabitants, since it allows them to have access to a wider variety of products and at the same time, favors the active dynamics of the economy of the community.

Local markets Food safety Local development Food sovereignty Rural areas Mercados locales Seguridad alimentaria Desarrollo local Soberanía alimentaria Zonas rurales CIENCIAS SOCIALES CIENCIAS SOCIALES