Genetics and Plant Breeding

Models to Estimate Genetic Gain of Soybean Seed Yield from Annual Multi-Environment Field Trials

The paper evaluates models to estimate genetic gain in soybean seed yield from multi-environment trials and finds all models are biased, recommending multiple models for accurate estimation.

Bayesian Additive Regression Trees for Genotype by Environment Interaction Models

The paper introduces AMBARTI, a Bayesian additive regression tree model for genotype by environment interactions in plant genetics, showing it is competitive or superior to existing methods.

Extending Finlay-Wilkinson regression with covariates

This paper extends Finlay-Wilkinson regression by replacing the environmental index with synthetic covariates derived from observable environmental factors, enabling predictions for new environments.

Reciprocal recurrent selection based on genetic complementation: An efficient way to build heterosis in diploids due to directional dominance

This paper proposes reciprocal recurrent selection based on genetic complementation to enhance dominance-based heterosis in diploids, showing it is cheaper than GCA-based approaches and effective in hybrid maize.

Multi-location trials and population-based genotyping reveal high diversity and adaptation to breeding environments in a large collection of red clover

This study analyzes genetic and phenotypic diversity in red clover accessions across Europe, revealing geographic genetic structure and local adaptation to breeding environments.

learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data

learnMET is an R package that uses machine learning to predict genomic traits from multi-environment trial data by integrating genomic and environmental factors.

Enviromic prediction is useful to define the limits of climate adaptation: A case study of common beans in Brazil

This paper develops an enviromic prediction approach using GAM to analyze climate impacts on common bean yield in Brazil, identifying key environmental drivers and optimal conditions for different regions and seasons.

Theobroma grandiflorum breeding optimization based on repeatability, stability and adaptability information

This study estimates the optimal number of harvests for genetic selection of Theobroma grandiflorum progenies and identifies the most promising ones based on productivity, stability, and adaptability.

INCORPORATING A DYNAMIC GENE-BASED PROCESS MODULE INTO A CROP SIMULATION MODEL

This paper integrates a gene-based module into a crop simulation model to simulate time-to-flowering in common bean, showing improved accuracy compared to traditional genotype-specific parameter approaches.

New genotypic adaptability and stability analyses using Legendre polynomials and genotype-ideotype distances

The paper introduces a new methodology for analyzing genotypic adaptability and stability using Legendre polynomials and genotype-ideotype distances, showing improved accuracy in predicting cultivar performance across environments.

Quantitative genetic architecture of adaptive phenology traits in the deciduous tree, Populus trichocarpa (Torr. & Gray).

This study estimates the genetic basis of spring and autumn phenology in Populus trichocarpa to assess its capacity for climate adaptation.

metan: an R package for multi-environment trial analysis

The paper introduces the metan R package for analyzing multi-environment trial data in plant breeding, providing tools for data manipulation, modeling, and visualization.

Image-based Phenotyping and Genetic Analysis of Potato Skin Set and Color

The paper uses image analysis to quantify potato skin color and set, finding high heritability and environmental correlations, and highlights collinearity among color traits.

Modelling spatial variation in agricultural field trials with INLA

This paper compares spatial models for agricultural field trials using INLA, showing AR1⊗AR1 and SPDE models provide best predictive performance with or without genomic data.

Integrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in temperate areas

The paper predicts rice yield and quality traits using molecular markers and environmental covariates, finding that PLS models outperform reaction norm models in predicting future performance.

Genetic Variability and Correlation Coefficients of Major Traits in Early Maturing Rice under Rainfed Lowland Environments of Nepal

Deciphering hybrid larch reaction norms using random regression

This study uses random regression to analyze reaction norms of hybrid larch traits in response to water availability, finding hybrids to be more plastic than parental species.

Genetic control of transition from juvenile to mature wood with respect to microfibril angle (MFA) in Norway spruce (Picea abies) and lodgepole pine (Pinus contorta)

This study evaluates genetic control of microfibril angle transition from juvenile to mature wood in Norway spruce and lodgepole pine using heritability estimates and regression functions.

Genotype-by-Environment Interactions Affecting Heterosis in Maize

This study examines how genotype-by-environment interactions affect heterosis in maize hybrids and their inbred parents across 16 environments and 25 traits.

Dissecting the genetic architecture of shoot growth in carrot (Daucus carota L.) using a diallel mating design

This paper uses a diallel mating design and Bayesian analysis to study the genetic basis of shoot growth in carrot, finding that non-additive effects significantly influence early growth traits.