Results 71 to 80 of about 11,358 (198)

Evaluating camelina genotypes for improved nitrogen use efficiency and yield with reduced nitrogen

Agronomy Journal, Volume 118, Issue 5, September/October 2026.
Abstract Camelina (Camelina sativa L.) is a promising bioenergy crop with wide environmental adaptation, but nitrogen (N) requirements affect the sustainable production. Sixteen camelina genotypes were planted in 3 years in Sideny, MT at high and low N levels to evaluate nitrogen use efficiency (NUE) and yield in response to soil N.
Chengci Chen, Maral Etesami, William Franck, Chrisanne Kuester, Sooyoung Franck, Shreya Gautam, Tehmina Arshad, Chaofu Lu   +7 more
wiley   +1 more source

PbAT: A user‐friendly R/Shiny platform for data‐driven decision support in crop improvement

Applications in Plant Sciences, Volume 14, Issue 5, September-October 2026.
Abstract Premise Modern plant breeding requires robust analysis of complex, multi‐environment datasets to identify superior genotypes. Although R offers powerful statistical packages, their use often requires programming expertise. Existing graphical user interface (GUI)‐based tools are either limited in scope or not openly accessible, leaving breeders
Krishnan P. Abhijith, K. K. Vinod, Ranjith Kumar Ellur, K. T. Ravikiran, Rachit Kumar Saxena, Vignesh Muthusamy, S. Gopala Krishnan   +6 more
wiley   +1 more source

GGE biplot and AMMI analysis of advanced breeding lines of linseed

Electronic Journal of Plant Breeding
Ten advanced breeding lines of linseed were assessed in four environments viz; two locations each during 2016-17 and 2017-18. Analysis of variance exhibited a significant variation for genotype, environment and G X E effects for all the traits. The GGE biplot analysis showed that genotypes LCP 87, LC 2063, LDCP 13 and M 6 are suitable for seed yield ...
null Naresh Kumar, null Vijay Kumar
openaire   +3 more sources

Analysis of stability and adaptation of cotton genotypes using gge biplot method

Trakia Journal of Science, 2018
This research was conducted to study effects of G × E interaction on 38 selected genotypes of cotton with two commercial cultivars Golestan and Sepid (control) in a randomized complete block design with three replications at three locations in Golestan Province in 2014-15.
M. Fathi Sadabadi, G. A. Ranjbar, M. R. Zangi, S. K. Kazemi Tabar, H. Najafi Zarini   +4 more
openaire   +2 more sources

Evaluation of soybean lines and environmental stratification using the AMMI, GGE biplot, and factor analysis methods [PDF]

, 2015
In the final phases of new soybean cultivar development, lines are cultivated in several locations across multiple seasons with the intention of identifying and selecting superior genotypes for quantitative traits.
Hamawaki, R.L, Sousa, L.B, Nogueira, A.P.O, Batista, R.O, Hamawaki, O.T, Oliveira, V.M   +5 more
core   +1 more source

Evaluación del comportamiento productivo de cultivares de caña de azúcar (Saccharum spp.) a través de diferentes ambientes en Tucumán, aplicando la técnica estadística "GGE biplot" Assessment of sugarcane cultivars (Saccharum spp.) productive behaviour through different environments in Tucumán by means of "GGE biplot" technique

Revista Industrial y Agrícola de Tucumán, 2007
En el presente trabajo, se utilizó la técnica estadística "GGE biplot" como herramienta de análisis para explorar el efecto combinado del genotipo y de la interacción genotipo-ambiente en dos grupos de cultivares de caña de azúcar evaluados en seis ...
Ernesto R. Chavanne, Santiago Ostengo, María B. García, María I. Cuenya   +3 more
doaj  

Simulation‐based optimization of mega‐environmental designs for sparse multi‐environment testing

Crop Science, Volume 66, Issue 5, September/October 2026.
Abstract Plant breeding programs aim to identify superior varieties by evaluating potential varieties in a network of locations, and these evaluations are often called multi‐environment trials. It is important to optimize multi‐environment trials in terms of resource allocation to ensure accurate and efficient experiments.
Raegan Hoefler, Lucia Gutierrez
wiley   +1 more source

Bayesian GGE biplot models applied to maize multi-environments trials

Genetics and Molecular Research, 2016
The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x ...
Oliveira, L. A. de, Silva, C. P. da, Nuvunga, J. J., Silva, A. Q. da, Balestre, M.   +4 more
openaire   +2 more sources

Principled use of biplots for crop cultivar trial data analysis and decision‐making

Crop Science, Volume 66, Issue 5, September/October 2026.
Abstract Biplot methods are widely used to analyze crop cultivar trial data, particularly for interpreting multi‐environment trials and supporting breeding selections. However, their widespread adoption has led to frequent misuse and a perceived but false competition with mixed‐model estimation approaches like best linear unbiased prediction (BLUP ...
Weikai Yan, Elroy Cober
wiley   +1 more source

INTERAÇÃO GENÓTIPOS X AMBIENTES EM LINHAGENS DE FEIJÃO-CAUPI PELO MÉTODO GGE BIPLOT [PDF]

, 2017
The GGE Biplot method is efficien to identify favorable genotypes and ideal environments for evaluation. Therefore, the objective of this work was to evaluate the genotype by environment interaction (G×E) and select elite lines of cowpea from genotypes ...
Damasceno-Silva, Kaesel Jackson, Menezes Júnior, José Ângelo Nogueira de, Lima, Laíze Raphaelle Lemos, Sousa, Massaine Bandeira e, Rocha, Maurisrael de Moura   +4 more
core