scholarly journals Genotype-by-Environment Interactions Affecting Heterosis in Maize

2017 ◽  
Author(s):  
Zhi Li ◽  
Lisa Coffey ◽  
Jacob Garfin ◽  
Nathan D. Miller ◽  
Michael R. White ◽  
...  
Keyword(s):  
Reproductive Traits ◽  
Inbred Lines ◽  
Hybrid Performance ◽  
Environmental Response ◽  
Molecular Processes ◽  
Genotype By Environment Interactions ◽  
Maize Hybrids ◽  
Genotype By Environment ◽  
Specific Hybrid ◽  
Comparable Magnitude

ABSTRACTThe environment can influence heterosis, the phenomena in which the offspring of two inbred parents exhibits phenotypic performance beyond the inbred parents for specific traits. In this study we measured 25 traits in a set of 47 maize hybrids and their inbred parents grown in 16 different environments, and each had varying levels of average productivity. By quantifying 25 vegetative and reproductive traits across the life cycle we were able to analyze interactions between the environment and multiple distinct instances of heterosis. The magnitude and rank among hybrids of better-parent heterosis (BPH) varied for the different traits and environments. Across the traits, a higher within plot variance was observed for inbred lines compared to hybrids. However, for most traits, variance across environments was not significantly different for inbred lines compared to hybrids. Further, for many traits the correlations of BPH to hybrid performance and BPH to better parent performance were of comparable magnitude. These results indicate that inbreds and hybrids are showing similar trends in environmental response and are both contribute to genotype-by-environment interactions for heterosis. This study highlights that degree of heterosis is not an inherent trait of a specific hybrid, but varies depending on the trait measured and the environment where that trait is measured. Studies that attempt to correlate molecular processes with heterosis are hindered by the fact that heterosis is not a consistent attribute of a specific hybrid.

Genotype by Environment Interactions in Hereford Cattle: I. Reproductive Traits

1979 ◽  
Vol 49 (2) ◽  
pp. 396-402 ◽  
Author(s):  
M. Koger ◽  
W. C. Burns ◽  
O. F. Pahnish ◽  
W. T. Butts
Keyword(s):  
Reproductive Traits ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Hereford Cattle

scholarly journals The Importance of Dominance and Genotype-by-Environment Interactions on Grain Yield Variation in a Large-Scale Public Cooperative Maize Experiment

2021 ◽  
Author(s):  
Anna R Rogers ◽  
Jeffrey C Dunne ◽  
Cinta Romay ◽  
Martin Bohn ◽  
Edward S Buckler ◽  
...  
Keyword(s):  
Grain Yield ◽  
High Throughput ◽  
Genomic Prediction ◽  
Environmental Data ◽  
Environment Interaction ◽  
Hybrid Performance ◽  
Interaction Patterns ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Main Effect

Abstract High-dimensional and high throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

A study on genotype‐by‐environment interactions for the multiple traits of maize hybrids in China

2021 ◽  
Author(s):  
Haiwang Yue ◽  
Xuwen Jiang ◽  
Jianwei Wei ◽  
Junliang Xie ◽  
Shuping Chen ◽  
...  
Keyword(s):  
Multiple Traits ◽  
Genotype By Environment Interactions ◽  
Maize Hybrids ◽  
Genotype By Environment

scholarly journals Assessing Genotype-By-Environment Interactions in Aspergillus Ear Rot and Pre-Harvest Aflatoxin Accumulation in Maize Inbred Lines

Agronomy ◽  
2017 ◽  
Vol 7 (4) ◽  
pp. 86 ◽  
Author(s):  
Sheila Okoth ◽  
Lindy Rose ◽  
Abigael Ouko ◽  
Nakisani Netshifhefhe ◽  
Henry Sila ◽  
...  
Keyword(s):  
Inbred Lines ◽  
Ear Rot ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Maize Inbred Lines ◽  
Aflatoxin Accumulation ◽  
Aspergillus Ear Rot

Identifying Inbred Lines Capable of Improving Ear and Stover Yield and Quality of Superior Silage Maize Hybrids

Crop Science ◽  
2002 ◽  
Vol 42 (2) ◽  
pp. 365 ◽  
Author(s):  
Luis M. Bertoia ◽  
Ruggero Burak ◽  
Marcelo Torrecillas
Keyword(s):  
Inbred Lines ◽  
Maize Hybrids ◽  
Silage Maize ◽  
Yield And Quality ◽  
Stover Yield

Genotype by environment interactions and combining ability for strawberry families grown in diverse environments

Euphytica ◽  
2017 ◽  
Vol 213 (5) ◽  
Author(s):  
Megan M. Mathey ◽  
Sonali Mookerjee ◽  
Lise L. Mahoney ◽  
Kazim Gündüz ◽  
Umesh Rosyara ◽  
...  
Keyword(s):  
Combining Ability ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment

Genetic Parameters and Genotype-by-Environment Interactions in Regional Progeny Tests of Pinus taeda L. in the Southern USA

2020 ◽  
Author(s):  
Edwin Lauer ◽  
Andrew Sims ◽  
Steven McKeand ◽  
Fikret Isik
Keyword(s):  
Genetic Variation ◽  
Pinus Taeda ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Breeding Program ◽  
Model Fit ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Progeny Tests ◽  
Pinus Taeda L

Abstract Genetic parameters were estimated using a five-series multienvironment trial of Pinus taeda L. in the southern USA. There were 324 half-sib families planted in five test series across 37 locations. A set of six variance/covariance matrices for the genotype-by-environment (G × E) effect for tree height and diameter were compared on the basis of model fit. In single-series analysis, extended factor analytical models provided generally superior model fit to simpler models for both traits; however, in the combined-series analysis, diameter was optimally modeled using simpler variance/covariance structures. A three-way compound term for modeling G × E interactions among and within series yielded substantial improvements in terms of model fit and standard errors of predictions. Heritability of family means ranged between 0.63 and 0.90 for both height and diameter. Average additive genetic correlations among sites were 0.70 and 0.61 for height and diameter, respectively, suggesting the presence of some G × E interaction. Pairs of sites with the lowest additive genetic correlations were located at opposite ends of the latitude range. Latent factor regression revealed a small number of parents with large factor scores that changed ranks significantly between southern and northern environments. Study Implications Multienvironmental progeny tests of loblolly pine (Pinus taeda L.) were established over 10 years in the southern United States to understand the genetic variation for the traits of economic importance. There was substantial genetic variation between open-pollinated families, suggesting that family selection would be efficient in the breeding program. Genotype-by-environment interactions were negligible among sites in the deployment region but became larger between sites at the extremes of the distribution. The data from these trials are invaluable in informing the breeding program about the genetic merit of selection candidates and their potential interaction with the environment. These results can be used to guide deployment decisions in the southern USA, helping landowners match germplasm with geography to achieve optimal financial returns and conservation outcomes.

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