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

Breeding for native genetic resistance to FAW in Africa-adapted early- and intermediate-maturing tropical maize germplasm

Yoseph Beyene Anani Bruce Manje Gowda Andrew Chavangi Prasanna Boddupalli (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING GENETIC RESISTANCE MAIZE GERMPLASM HYBRIDS

Monitoring the threat of unintentional transgene flow into maize gene banks and breeding materials

Monica Mezzalama Rodomiro Ortiz (2010, [Artículo])

Genetic Integrity Germplasm Enhancement Genetically Modified Maize CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING GERMPLASM MAIZE RECOMBINANT DNA TRANSGENES GENETIC ENGINEERING PLANTS BIOSAFETY

APLICACIÓN DE METAHEURÍSTICAS EN EL PROBLEMA DE ACOMODO DE PATRONES DE CORTE EN MATERIALES FINITOS

Anabel Rodríguez Rodríguez (2023, [Tesis de doctorado])

"En la presente investigación se resuelve el problema de optimización de acomodo de patrones de corte en materiales finitos mediante el uso de estrategias metaheurísticas con la finalidad de aprovechar el material de acomodo y minimizar el desperdicio. Específicamente se implementó un algoritmo genético que al inicio genera soluciones aleatorias que forman la población inicial. La misma está compuesta por individuos o soluciones que son una combinación de patrones que se acomodan dentro del material de manera que se obtenga el menor desperdicio. Durante el proceso evolutivo estas soluciones aleatorias se someten a los operadores genéticos: selección, cruce y mutación, para encontrar nuevas soluciones que hereden la información genética de sus antecesores y evolucionen o mejoren en cada generación para obtener el menor desperdicio posible."

Acomodo de patrones Algoritmos genéticos Algoritmos golosos Muéganos Metaheurísticas Procesamiento digital de imágenes INGENIERÍA Y TECNOLOGÍA CIENCIAS TECNOLÓGICAS OTRAS ESPECIALIDADES TECNOLÓGICAS OTRAS OTRAS

Tackling Maize Lethal Necrosis (MLN) in eastern Africa through effective phytosanitary approaches

Suresh L.M. Yoseph Beyene Dan Makumbi Manje Gowda Prasanna Boddupalli (2023, [Objeto de congreso])

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MAIZE NECROSIS DISEASE MANAGEMENT PLANT HEALTH GENE EDITING GERMPLASM

Nitrogen fertilizer application alters the root endophyte bacterial microbiome in maize plants, but not in the stem or rhizosphere soil

Alejandra Miranda Carrazco Yendi Navarro-Noya Bram Govaerts Nele Verhulst Luc Dendooven (2022, [Artículo])

Plant-associated microorganisms that affect plant development, their composition, and their functionality are determined by the host, soil conditions, and agricultural practices. How agricultural practices affect the rhizosphere microbiome has been well studied, but less is known about how they might affect plant endophytes. In this study, the metagenomic DNA from the rhizosphere and endophyte communities of root and stem of maize plants was extracted and sequenced with the “diversity arrays technology sequencing,” while the bacterial community and functionality (organized by subsystems from general to specific functions) were investigated in crops cultivated with or without tillage and with or without N fertilizer application. Tillage had a small significant effect on the bacterial community in the rhizosphere, but N fertilizer had a highly significant effect on the roots, but not on the rhizosphere or stem. The relative abundance of many bacterial species was significantly different in the roots and stem of fertilized maize plants, but not in the unfertilized ones. The abundance of N cycle genes was affected by N fertilization application, most accentuated in the roots. How these changes in bacterial composition and N genes composition might affect plant development or crop yields has still to be unraveled.

Bacterial Community Structure DArT-Seq Bacterial Community Functionality Genes Involved in N Cycling CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA AGRICULTURAL PRACTICES MAIZE RHIZOSPHERE STEMS NITROGEN FERTILIZERS

Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.)

Filippo Maria Bassi Alison Bentley Rodomiro Ortiz Jose Crossa (2016, [Artículo])

Marker-Aided Breeding CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA BREEDING VALUE GENETIC GAIN GENOTYPE ENVIRONMENT INTERACTION QUANTITATIVE TRAIT LOCI

Genetic diversity and population structure of African sorghum (sorghum bicolor L. moench) accessions assessed through single nucleotide polymorphisms markers

Hussein Shimelis Baloua Nébié Chris Ojiewo Abhishek Rathore (2023, [Artículo])

Heterotic Grouping Breeding Population Development Marker-Assisted Cultivar Development CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA POPULATION STRUCTURE GENE FLOW SINGLE NUCLEOTIDE POLYMORPHISMS SORGHUM BICOLOR BREEDING PROGRAMMES

Preliminary dissection of grain yield and related traits at differential nitrogen levels in diverse pre-breeding wheat germplasm through association mapping

Achla Sharma Juan Burgueño Prashant Vikram Nitika Sandhu Satinder Kaur Parveen Chhuneja (2023, [Artículo])

Plant Nitrogen Use Efficiency Pre-Breeding Lines Genome-Wide Association Study Marker Trait Association CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA WHEAT PRE-BREEDING BREEDING LINES NITROGEN LANDRACES GENETIC MARKERS

Complex traits and candidate genes: estimation of genetic variance components across multiple genetic architectures

GIOVANNY COVARRUBIAS-PAZARAN Hans-Peter Piepho (2023, [Artículo])

Average Semivariance Linear Mixed Model Variance Component Estimation Polygenic Inheritance Oligogenic Inheritance Mendelian Inheritance CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA MENDELISM GENETIC VARIANCE GENOME-WIDE ASSOCIATION STUDIES PHENOTYPES CHROMOSOME MAPPING