The impact of genotype‐by‐environment interaction on the dry matter yield and chemical composition in timothy ( Phleum pratense L.) examined by using the additive main effects and multiplicative interaction model

2021 ◽  
Author(s):  
Jan Bocianowski ◽  
Adam Radkowski ◽  
Kamila Nowosad ◽  
Iwona Radkowska ◽  
Andrzej Zieliński
Keyword(s):  
Dry Matter ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Phleum Pratense ◽  
Environment Interaction ◽  
Dry Matter Yield ◽  
Genotype By Environment ◽  
Main Effects ◽  
The Impact ◽  
Phleum Pratense L

scholarly journals Genotype by environment interaction for physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids using additive main effects and multiplicative interaction model

2021 ◽  
Author(s):  
Zahra Abbasi ◽  
Jan Bocianowski
Keyword(s):  
Sugar Beet ◽  
Beta Vulgaris ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Physiological Traits ◽  
Environment Interaction ◽  
Extraction Coefficient ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Main Effects

AbstractThe objective of this study was to assess genotype by environment interaction for 21 physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids grown in Rodasht Agricultural Research Station in Iran by the additive main effects and multiplicative interaction model. The study comprised of 51 sugar beet genotypes [10 multigerm pollen parents, four monogerm seed parents and 36 F1 hybrids], evaluated at four environments in a randomized complete block design, with three replicates. The additive main effects and multiplicative interaction analyses revealed significant environment main effects with respect to all observed traits, except extraction coefficient of sugar. The additive main effects and multiplicative interaction stability values ranged from 0.009 (G17 for leaf Ca2+) to 9.698 (G09 for extraction coefficient of sugar). The parental forms 2 7233-P.29 (G38) and C CMS (G49) as well as hybrids 2(6)*C (G27) and 5*C (G33) are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.

scholarly journals Genotype by environment interaction for seeds yield in pea (Pisum sativum L.) using additive main effects and multiplicative interaction model

Euphytica ◽  
2019 ◽  
Vol 215 (11) ◽  
Author(s):  
Jan Bocianowski ◽  
Jerzy Księżak ◽  
Kamila Nowosad
Keyword(s):  
Pisum Sativum ◽  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Randomized Complete Block Design ◽  
Main Effects

Abstract The objective of this study was to evaluate the genotype by environment interaction using the additive main effects and multiplicative interaction model for seeds yield of pea cultivars grown in Poland. Twelve pea (Pisum sativum L.) cultivars: Bohun, Boruta, Cysterski, Ezop, Kavalir, Lasso, Medal, Santana, Tarchalska, Terno, Wenus and Zekon were evaluated in 20 environments (ten locations in 2 years). The experiment was laid out as randomized complete block design with three replicates. Seeds yield ranged from 26.10 dt ha−1 (for Wenus in Radostowo 2011) to 79.73 dt ha−1 (for Lasso in Słupia 2010), with an average of 50.70 dt ha−1. AMMI analyses revealed significant genotype and environmental effects as well as genotype-by-environment interaction with respect to seeds yield. In the analysis of variance, 89.19% of the total seeds yield variation was explained by environment, 1.65% by differences between genotypes, and 8.33% by GE interaction. The cultivar Terno is the highest stability. The cultivar Tarchalska is recommended for further inclusion in the breeding program because its stability and the highest averages of seeds yield.

scholarly journals Genotype-by-environment interaction for seed glucosinolate content in winter oilseed rape (Brassica napus L.) using an additive main effects and multiplicative interaction model

2018 ◽  
Vol 55 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Jan Bocianowski ◽  
Kamila Nowosad ◽  
Alina Liersch ◽  
Wiesława Popławska ◽  
Agnieszka Łącka
Keyword(s):  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Glucosinolate Content ◽  
Environment Interaction ◽  
Brassica Napus L ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Winter Rapeseed ◽  
Main Effects

Summary The objective of this study was to assess genotype-by-environment interaction for seed glucosinolate content in winter rapeseed cultivars grown in western Poland using the additive main effects and multiplicative interaction model. The study concerned 25 winter rapeseed genotypes (15 F1 CMS ogura hybrids, parental lines and two European cultivars: open pollinated Californium and F1 hybrid Hercules), evaluated at five locations in a randomized complete block design with four replicates. The seed glucosinolate content of the tested genotypes ranged from 5.53 to 16.80 μmol∙g-1 of seeds, with an average of 10.26 μmol∙g-1. In the AMMI analyses, 48.67% of the seed glucosinolate content variation was explained by environment, 13.07% by differences between genotypes, and 17.56% by genotype-by-environment interaction. The hybrid PN66×PN07 is recommended for further inclusion in the breeding program due to its low average seed glucosinolate content; the restorer line PN18, CMS ogura line PN66 and hybrids PN66×PN18 and PN66×PN21 are recommended because of their stability and low seed glucosinolate content.

scholarly journals Genotype by environment interaction for area under the disease-progress curve (AUDPC) value in spring barley using additive main effects and multiplicative interaction model

2020 ◽  
Vol 49 (5) ◽  
pp. 525-529 ◽  
Author(s):  
Jan Bocianowski ◽  
Anna Tratwal ◽  
Kamila Nowosad
Keyword(s):  
Spring Barley ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Disease Progress Curve ◽  
Genotype By Environment ◽  
Disease Progress ◽  
Progress Curve ◽  
Main Effects

Abstract The objective of this study was to assess genotype by environment interaction for area under disease progress curve values in spring barley grown in South-West Poland by the additive main effects and multiplicative interaction model. The study comprised of 25 spring barley genotypes (five cultivars: Basza, Blask, Antek, Skarb and Rubinek as well as all possible 10 two-way mixtures and 10 three-way mixtures combinations), evaluated at two locations in 4 years (eight environments) in a randomized complete block design, with four replicates. Area under disease progress curve (AUDPC) value of the tested genotypes ranged from 75.3 to 614.3, with an average of 175.3. In the AMMI analyses, 13.43% of the AUDPC value variation was explained by environment, 37.85% by differences between genotypes, and 18.20% by genotype by environment interaction. The mixture Basza/Skarb is recommended for further inclusion in the breeding program due to its low average AUDPC value (98.8) and is stable (AMMI stability value = 6.65).

scholarly journals Genotype × environment interactions and phenotypic stability for wheat grown in stressful conditions

Genetika ◽  
2014 ◽  
Vol 46 (3) ◽  
pp. 799-806 ◽  
Author(s):  
Borislav Banjac ◽  
Velimir Mladenov ◽  
Miodrag Dimitrijevic ◽  
Sofija Petrovic ◽  
Jan Bocanski
Keyword(s):  
Interaction Model ◽  
Triticum Aestivum L ◽  
Genotype By Environment Interaction ◽  
Control Treatment ◽  
Environment Interaction ◽  
Phenotypic Stability ◽  
Genotype By Environment ◽  
Growing Seasons ◽  
Sources Of Variation ◽  
Main Effects

The objective of this study was to present the results of experiment conducted on 11 cultivars of wheat (Triticum aestivum L.) and 1 cultivar of triticale (Triticosecale W) on stressful conditions of halomorphic solonetz in Kumane, Banat, Serbia. Across three growing seasons genotypic variability, monitoring of phenotypic variation and genotype by environment interaction (GEI) for number of grains per spike and yield was studied. The cultivar were grown in field trails of control treatment and treatments with measures repairs solonetz using phosphogypsum in the amount of 25 t?ha-1 and 50 t?ha-1. GEI was tested using AMMI (Additive Main Effects and Multiplicative Interaction) model. The expression of tested traits were statistically significant and showed additive and non-additive sources of variation. The first source of variation, quantified IPCA1 axis explained most of the structure of GEI.

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