A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Stability and adaptability of promising maize hybrids in terms of three agronomic traits (grain yield, ear weight and 100-kernel weight) in multi-environments trials were evaluated. The analysis of AMMI model indicated that the all three agronomic traits showed highly significant differences (p < 0.01) on genotype, environment and genotype by environment interaction. Results showed that genotypes Hengyu321 (G9), Yufeng303 (G10) and Huanong138 (G3) were of higher stability on grain yield, ear weight and 100-kernel weight, respectively. Genotypes Hengyu1587 (G8) and Hengyu321 (G9) showed good performance in terms of grain yield, whereas Longping208 (G2) and Weike966 (G12) showed broad adaptability for ear weight. It was also found that the genotypes with better adaptability in terms of 100-kernel weight were Zhengdan958 (G5) and Weike966 (G12). The genotype and environment interaction model based on AMMI analysis indicated that Hengyu1587 and Hengyu321 were the ideal genotypes, due to extensive adaptability and high grain yield under both testing sites. Bangladesh J. Bot. 50(2): 343-350, 2021 (June)

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Genotype-by-environment interaction analysis across three crop cycles in sugarcane

Journal of Crop Improvement ◽

10.1080/15427528.2020.1817220 ◽

2020 ◽

pp. 1-15

Author(s):

Aliya Momotaz ◽

R. Wayne Davidson ◽

Duli Zhao ◽

P.H. McCord ◽

Hardev S. Sandhu ◽

...

Keyword(s):

Interaction Analysis ◽

Genotype By Environment Interaction ◽

Environment Interaction ◽

Genotype By Environment

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Biplot pattern interaction analysis and statistical test for crossover and non-crossover genotype-by-environment interaction in peach

Scientia Horticulturae ◽

10.1016/j.scienta.2019.03.024 ◽

2019 ◽

Vol 252 ◽

pp. 298-309

Author(s):

Julia Angelini ◽

Gabriela Soledad Faviere ◽

Eugenia Belén Bortolotto ◽

Luis Arroyo ◽

Gabriel Hugo Valentini ◽

...

Keyword(s):

Interaction Analysis ◽

Genotype By Environment Interaction ◽

Statistical Test ◽

Environment Interaction ◽

Genotype By Environment

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Recurrent selection in inbred popcorn families

Scientia Agricola ◽

10.1590/s0103-90162004000600008 ◽

2004 ◽

Vol 61 (6) ◽

pp. 609-614 ◽

Cited By ~ 14

Author(s):

Máskio Daros ◽

Antônio Teixeira do Amaral Jr. ◽

Messias Gonzaga Pereira ◽

Fabrício Santana Santos ◽

Ana Paula Cândido Gabriel ◽

...

Keyword(s):

Genetic Variability ◽

Recurrent Selection ◽

Agronomic Traits ◽

Block Design ◽

Genotype By Environment Interaction ◽

Small Scale ◽

Environment Interaction ◽

Genotype By Environment ◽

Randomized Complete Block Design ◽

Superior Genotypes

Although much appreciated in Brazil, commercial popcorn is currently cropped on a fairly small scale. A number of problems need to be solved to increase production, notably the obtaintion of seeds with good agronomic traits and good culinary characteristics. With the objective of developing superior genotypes in popcorn, a second cycle of intrapopulation recurrent selection based on inbred S1 families was carried out. From the first cycle of selection over the UNB-2U population, 222 S1 families were obtained, which were then divided into six sets and evaluated in a randomized complete block design with two replications within the sets. Experiments were carried out in two Brazilian localities. The analysis of variance revealed environmental effects for all evaluated traits, except popping and stand, showing that, for most traits, these environments affected genotype behavior in different ways. In addition, the set as source of variation was significant for most of the evaluated traits, indicating that dividing the families into sets was an efficient strategy. Genotype-by-environment interaction was detected for most traits, except popping expansion and stand. Differences among genotypes were also detected (1% F-test), making viable the proposition of using the genetic variability in the popcorn population as a basis for future recurrent selection cycles. Superior families were selected using the Smith and Hazel classic index, with predicted genetic gains of 17.8% for popping expansion and 26.95% for yield.

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Genotype-by-environment interaction analysis of nutritional composition in newly-developed sweetpotato clones

Journal of Food Composition and Analysis ◽

10.1016/j.jfca.2020.103426 ◽

2020 ◽

Vol 88 ◽

pp. 103426

Author(s):

Fekadu Gurmu ◽

Hussein Shimelis ◽

Mark Laing ◽

Jacob Mashilo

Keyword(s):

Interaction Analysis ◽

Genotype By Environment Interaction ◽

Nutritional Composition ◽

Environment Interaction ◽

Genotype By Environment

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Genotype by environment interaction analysis of wheat (Triticum aestivum L.) grain yield under rain-fed conditions in Zambia

SABRAO Journal of Breeding and Genetics ◽

10.54910/sabrao2021.53.4.5 ◽

2021 ◽

Vol 53 (4) ◽

pp. 609-619

Author(s):

B. Tembo

Keyword(s):

Grain Yield ◽

Agricultural Research ◽

Interaction Analysis ◽

Crop Improvement ◽

Genotype By Environment Interaction ◽

Research Station ◽

Environment Interaction ◽

Wheat Genotypes ◽

Lattice Design ◽

Genotype By Environment

Understanding genotype by environment interaction (GEI) is important for crop improvement because it aids in the recommendation of cultivars and the identification of appropriate production environments. The objective of this study was to determine the magnitude of GEI for the grain yield of wheat grown under rain-fed conditions in Zambia by using the additive main effects and multiplicative interaction (AMMI) model. The study was conducted in 2015/16 at Mutanda Research Station, Mt. Makulu Research Station and Golden Valley Agricultural Research Trust (GART) in Chibombo. During2016/17, the experiment was performed at Mpongwe, Mt. Makulu Research Station and GART Chibombo, Zambia. Fifty-five rain-fed wheat genotypes were evaluated for grain yield in a 5 × 11 alpha lattice design with two replications. Results revealed the presence of significant variation in yield across genotypes, environments, and GEI indicating the differential performance of genotypes across environments. The variance due to the effect of environments was higher than the variances due to genotypes and GEI. The variances ascribed to environments, genotypes, and GEI accounted for 45.79%, 12.96%, and 22.56% of the total variation, respectively. These results indicated that in rain-fed wheat genotypes under study, grain yield was more controlled by the environment than by genetics. AMMI biplot analysis demonstrated that E2 was the main contributor to the GEI given that it was located farthest from the origin. Furthermore, E2 was unstable yet recorded the highest yield. Genotype G47 contributed highly to the GEI sum of squares considering that it was also located far from the origin. Genotypes G12 and G18 were relatively stable because they were situated close to the origin. Their position indicated that they had minimal interaction with the environment. Genotype 47 was the highest-yielding genotype but was unstable, whereas G34 was the lowest-yielding genotype and was unstable.

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