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Effects of Abiotic Stress Associated with Climate Change on Potato Yield and Tuber Quality Under a Multi-environment Trial in New Zealand
In the 2018/19 growing season, a multi-environment trial in Opiki, Hastings, and Ohakune located in three different regions of the North Island of...
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Enviroty** within a multi-environment trial allowed identifying genetic determinants of winter oilseed rape yield stability
Key messageA comprehensive environmental characterization allowed identifying stable and interactive QTL for seed yield: QA09 and QC09a were detected...
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Enviromic-based kernels may optimize resource allocation with multi-trait multi-environment genomic prediction for tropical Maize
BackgroundSuccess in any genomic prediction platform is directly dependent on establishing a representative training set. This is a complex task,...
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Multi-environment Genomic Selection in Rice Elite Breeding Lines
BackgroundAssessing the performance of elite lines in target environments is essential for breeding programs to select the most relevant genotypes....
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On two-stage analysis of multi-environment trials
Two-stage analysis methods are often used in multi-environment trials (MET) for plant variety selection, when a single-stage approach is not feasible...
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Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat
With abundant available genomic data, genomic selection has become routine in many plant breeding programs. Multispectral data captured by UAVs...
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Identification of genetic loci associated with five agronomic traits in alfalfa using multi-environment trials
Key MessageThe use of multi-environment trials to test yield-related traits in a diverse alfalfa panel allowed to find multiple molecular markers...
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Phenomic selection in wheat breeding: prediction of the genotype-by-environment interaction in multi-environment breeding trials
Key messagePhenomic prediction of wheat grain yield and heading date in different multi-environmental trial scenarios is accurate. Modelling the...
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Fully efficient, two-stage analysis of multi-environment trials with directional dominance and multi-trait genomic selection
Key messageR/StageWise enables fully efficient, two-stage analysis of multi-environment, multi-trait datasets for genomic selection, including...
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Identification of environment types and adaptation zones with self-organizing maps; applications to sunflower multi-environment data in Europe
Key messageWe evaluate self-organizing maps (SOM) to identify adaptation zones and visualize multi-environment genotypic responses. We apply SOM to...
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Multi-model approach for optimizing cold-wave resilient maize selection: unveiling genotype-by-environment interaction and predicting yield stability
Cold waves both significantly reduce yield & damage crops as well; unforeseeable nature of cold waves makes it challenging for farmers to manage...
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Effects of orange rust on sugarcane yield traits in a multi-environment breeding program
Orange rust caused by Puccinia kuehnii is a major emerging disease in many sugarcane-producing countries. Breeding for resistant varieties is the...
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Multi-environment testing revealed the effect of yield genes on the grain yield stability in diverse rice germplasm
Diverse rice germplasm comprising 112 genotypes was evaluated for yield traits across three environments. Pooled and environmentwise analysis of...
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Optimizing multi-environment testing in potato breeding: using heritability estimates to determine number of replications, sites, and years for field trials
Multi-environment trials (METs) of potato breeding clones and cultivars allow to precisely determine their performance across testing sites over...
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Leveraging probability concepts for cultivar recommendation in multi-environment trials
Key messageWe propose using probability concepts from Bayesian models to leverage a more informed decision-making process toward cultivar...
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Assessment of genomic prediction reliability and optimization of experimental designs in multi-environment trials
Key messageNew forms of the coefficient of determination can help to forecast the accuracy of genomic prediction and optimize experimental designs in...
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Models to estimate genetic gain of soybean seed yield from annual multi-environment field trials
Key messageSimulations demonstrated that estimates of realized genetic gain from linear mixed models using regional trials are biased to some degree....
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Genetic variability analyses considering multi-environment trials in maize breeding
Clustering techniques are widely adopted in genetic variability assessments. Aiming to understand the genotypes contrasting and complementarity,...
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Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment
Globally, over 2 billion people suffer from malnutrition due to inadequate intake of micronutrients. Genomic-assisted breeding is identified as a...
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Impact of the complexity of genotype by environment and dominance modeling on the predictive accuracy of maize hybrids in multi-environment prediction models
The prediction accuracy of multi-environment prediction models can be affected by the complexity of the genotype by environment interaction (G×E)....
