Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability.

Genetics and molecular research : GMR - 3 Nov 2016

Barroso L M A, Teodoro P E, Nascimento M, Torres F E, Nascimento A C C, Azevedo C F, Teixeira F R F

Abstract excerpt

Cowpea (Vigna unguiculata) is grown in three Brazilian regions: the Midwest, North, and Northeast, and is consumed by people on low incomes. It is important to investigate the genotype x environment (GE) interaction to provide accurate recommendations for farmers. The aim of this study was to identify cowpea genotypes with high adaptability and phenotypic stability for growing in the Brazilian Cerrado, and to...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Analysis of Variance
Share to Brazil

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Environment

Share to Genotype

Share to Neural Networks, Computer

Share to Phenotype

Source

Identifiers

PMID: 27820651
DOI: 10.4238/gmr15049049

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Using artificial neural networks to select upright cowpea (Vigna unguiculata) genotypes with high productivity and phenotypic stability.PMID 27820651Read ↗

Artificial intelligence in the selection of common bean genotypes with high phenotypic stability.Semantic proximity Read ↗

Simultaneous selection for cowpea (Vigna unguiculata L.) genotypes with adaptability and yield stability using mixed models.Semantic proximity Read ↗

Bayesian approach increases accuracy when selecting cowpea genotypes with high adaptability and phenotypic stability.Semantic proximity Read ↗

Genetic divergence for adaptability and stability in sugarcane: Proposal for a more accurate evaluation.Semantic proximity Read ↗

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI.Semantic proximity Read ↗

Phenotype adaptability and stability of sugarcane genotypes in the sugarcane belt of the state of Pernambuco, Brazil.Semantic proximity Read ↗

Measurements of experimental precision for trials with cowpea (Vigna unguiculata L. Walp.) genotypes.Semantic proximity Read ↗

Genetic parameters and path analysis in cowpea genotypes grown in the Cerrado/Pantanal ecotone.Semantic proximity Read ↗

Evaluation of High Yielding Maize Hybrids Based on Combined Stability Analysis, Sustainability Index, and GGE Biplot.Semantic proximity Read ↗

Genetic analyses, phenotypic adaptability and stability in sugarcane genotypes for commercial cultivation in Pernambuco.Semantic proximity Read ↗

Adaptability and stability of Coffea canephora to dynamic environments using the Bayesian approach.Semantic proximity Read ↗

Selection for wide adaptability and high phenotypic stability of Brazilian soybean genotypes.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.