Comprehensive evaluation of the DSSAT‐CSM‐CERES‐Wheat for simulating winter rye against multi‐environment data in Germany
Sign Up to like & getrecommendations! Published in 2024 at "Agronomy Journal"
DOI: 10.1002/agj2.21590
Abstract: Crop models are valuable tools for simulating and assessing genotype‐by‐environment interactions. In most studies, these models are parameterized based on crop data from a few sites and years, which often limits their applicability to a… read more here.
Keywords: winter rye; environment; crop; csm ceres ... See more keywords
Impact of the complexity of genotype by environment and dominance modeling on the predictive accuracy of maize hybrids in multi-environment prediction models
Sign Up to like & getrecommendations! Published in 2021 at "Euphytica"
DOI: 10.1007/s10681-021-02779-y
Abstract: The prediction accuracy of multi-environment prediction models can be affected by the complexity of the genotype by environment interaction (G×E). Moreover, depending on the trait genetic architecture, accounting for non-additive effects, such as dominance effects,… read more here.
Keywords: multi environment; prediction accuracy; prediction; complexity ... See more keywords
META-R: A software to analyze data from multi-environment plant breeding trials
Sign Up to like & getrecommendations! Published in 2020 at "Crop Journal"
DOI: 10.1016/j.cj.2020.03.010
Abstract: Abstract META-R (multi-environment trial analysis in R) is a suite of R scripts linked by a graphical user interface (GUI) designed in Java language. The objective of META-R is to accurately analyze multi-environment plant breeding… read more here.
Keywords: plant breeding; environment; multi environment;
Multi-environment PDF modeling for non-catalytic partial oxidation process under MILD oxy-combustion condition
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Hydrogen Energy"
DOI: 10.1016/j.ijhydene.2017.12.034
Abstract: Abstract The multi-environment probability density function approach has been applied to numerically investigate the Moderate or Intense Low-Oxygen (MILD) oxy-combustion processes encountered in the non-catalytic partial oxidation (POX) gasifier. The multi-environment PDF approach has the… read more here.
Keywords: combustion; chemistry; mild oxy; oxy combustion ... See more keywords
Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.
Sign Up to like & getrecommendations! Published in 2024 at "Journal of agricultural and food chemistry"
DOI: 10.1021/acs.jafc.4c07017
Abstract: Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/malt quality. In this study, 79 barley grain samples (genotype-location-year combinations) from Californian multi-environment trials (2017-2022)… read more here.
Keywords: barley; machine learning; barley grain; multi environment ... See more keywords
Multi-model-based validation of multi-environment trial results in horse gram (Macrotyloma uniflorum Lam. Verdc.)
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-25093-2
Abstract: Analysis of genotype-by-environment interactions (GEI) is critical for evaluating the yield and stability of genotypes in multi-environment experiments (METs). Either fixed models (AMMI and GGE biplots) or random effect models (Linear mixed models: LMM) are… read more here.
Keywords: horse gram; analysis; multi environment; environment ... See more keywords
Estimation of Additive and Dominance Effects in an Acacia crassicarpa Multi-Environment Progeny Trial Using Genomic Pedigree Reconstruction
Sign Up to like & getrecommendations! Published in 2024 at "Forest Science"
DOI: 10.1093/forsci/fxae004
Abstract: Acacia crassicarpa is an important tree species in Southeast Asia, where hundreds of thousands of hectares of planted forests are supported by advancements in silviculture and genetic improvement. Although possible, controlled pollination is impractical for… read more here.
Keywords: additive dominance; pedigree reconstruction; acacia crassicarpa; reconstruction ... See more keywords
Improving genomic predictions with inbreeding and non-additive effects in two admixed maize hybrid populations in single and multi-environment contexts.
Sign Up to like & getrecommendations! Published in 2022 at "Genetics"
DOI: 10.1093/genetics/iyac018
Abstract: Genetic admixture, resulting from the recombination between structural groups, is frequently encountered in breeding populations. In hybrid breeding, crossing admixed lines can generate substantial non-additive genetic variance and contrasted levels of inbreeding which can impact… read more here.
Keywords: non additive; multi environment; inbreeding non; prediction ... See more keywords
Multi-environment genome -wide association mapping of culm morphology traits in barley
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Plant Science"
DOI: 10.1101/2022.03.30.486427
Abstract: In cereals with hollow internodes, lodging resistance is influenced by morphological characteristics such as internode diameter and culm wall thickness. Despite their relevance, knowledge of the genetic control of these traits and their relationship with… read more here.
Keywords: lodging resistance; environment; culm; environment genome ... See more keywords
Accurate genomic prediction for grain yield and grain moisture content of maize hybrids using multi-environment data.
Sign Up to like & getrecommendations! Published in 2025 at "Journal of integrative plant biology"
DOI: 10.1111/jipb.13857
Abstract: Incorporating genotype-by-environment (GE) interaction effects into genomic prediction (GP) models with multi-environment climate data can improve selection accuracy to accelerate crop breeding but has received little research attention. Here, we conducted a cross-region GP study… read more here.
Keywords: prediction; climate data; genomic prediction; multi environment ... See more keywords
Evaluation of finger millet (Eleusine coracana (L.) Gaertn.) in multi-environment trials using enhanced statistical models
Sign Up to like & getrecommendations! Published in 2023 at "PLOS ONE"
DOI: 10.1371/journal.pone.0277499
Abstract: Spatial variation and genotype by environment (GxE) interaction are common in varietal selection field trials and pose a significant challenge for plant breeders when comparing the genetic potential of different varieties. Efficient statistical methods must… read more here.
Keywords: finger millet; environment; multi environment; evaluation finger ... See more keywords