ArticlePloS one2018
Multi-trait multi-environment Bayesian model reveals G x E interaction for nitrogen use efficiency components in tropical maize.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review.Frontiers in plant science · 2021Pooled it
- Inheritance of root morphology in tropical maize under contrasting nitrogen levels.Scientific reports · 2026Article
- Leveraging probabilistic models to enhance soybean cultivar recommendation in Zimbabwe.BMC plant biology · 2026Article
- Gene action, combining ability, heterotic grouping and hybrid performance of tropical maize inbred lines from a public breeding program in Brazil.Frontiers in plant science · 2026Article
- Enhanced Bayesian model for multienvironmental selection of winter hybrids maize: assessing grain yield using 'ProbBreed'.Plant methods · 2025Article
- A Bayesian optimization R package for multitrait parental selection.The plant genome · 2024Article
- Genetic diversity, relationships among traits and selection of tropical maize inbred lines for low-P tolerance based on root and shoot traits at seedling stage.Frontiers in plant science · 2024Article
- Exploring the Potential of Heterosis to Improve Nitrogen Use Efficiency in Popcorn Plants.Plants (Basel, Switzerland) · 2023Article
- Multi-trait and multi-environment genomic prediction for flowering traits in maize: a deep learning approach.Frontiers in plant science · 2023Article
- Phenotypic and molecular characterization of a set of tropical maize inbred lines from a public breeding program in Brazil.BMC genomics · 2022Article
- Multi-trait and multi-environment Bayesian analysis to predict the G x E interaction in flood-irrigated rice.PloS one · 2022Article
- Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy.PloS one · 2021Article
- Optimizing the P balance: How do modern maize hybrids react to different starter fertilizers?PloS one · 2021Article
- Machine learning and statistics to qualify environments through multi-traits in Coffea arabica.PloS one · 2021Article
- SNP and Haplotype-Based Genomic Selection of Quantitative Traits inPlants (Basel, Switzerland) · 2019Article
- Genotype by environment interactions for performance and thermoregulation responses in growing pigs1,2.Journal of animal science · 2019Article
- Luxury Vegetative Nitrogen Uptake in Maize Buffers Grain Yield Under Post-silking Water and Nitrogen Stress: A Mechanistic Understanding.Frontiers in plant science · 2019Article
- Multi-trait multi-environment models in the genetic selection of segregating soybean progeny.PloS one · 2019Article
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7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Identifying maize inbred lines that are more efficient in nitrogen (N) use is an important strategy and a necessity in the context of environmental and economic impacts attributed to the excessive N fertilization. N-uptake efficiency (NUpE) and N-utilization efficiency (NUtE) are components of N-use efficiency (NUE). Despite the most maize breeding data have a multi-trait structure, they are often analyzed under a single-trait framework. We aimed to estimate the genetic parameters for NUpE and NUtE in contrasting N levels, in order to identify superior maize inbred lines, and to propose a Bayesian multi-trait multi-environment (MTME) model. Sixty-four tropical maize inbred lines were evaluated in two experiments: at high (HN) and low N (LN) levels. The MTME model was compared to single-trait multi-environment (STME) models. Based on deviance information criteria (DIC), both multi- and single-trait models revealed genotypes x environments (G x E) interaction. In the MTME model, NUpE was found to be weakly heritable with posterior modes of heritability of 0.016 and 0.023 under HN and LN, respectively. NUtE at HN was found to be highly heritable (0.490), whereas under LN condition it was moderately heritable (0.215). We adopted the MTME model, since combined analysis often presents more accurate breeding values than single models. Superior inbred lines for NUpE and NUtE were identified and this information can be used to plan crosses to obtain maize hybrids that have superior nitrogen use efficiency.
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