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Kamila Nowosad - One of the best experts on this subject based on the ideXlab platform.
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Genotype by environment Interaction for main winter triticale varieties characteristics at two levels of technology using additive main effects and Multiplicative Interaction model
Euphytica, 2021Co-Authors: Jan Bocianowski, Anna Tratwal, Kamila NowosadAbstract:The aim of this study was to assess genotype by environment Interaction for grain yield, plant height and thousand-grain weight in winter triticale cultivars by the additive main effects and Multiplicative Interaction (AMMI) model. The study comprised of ten winter triticale varieties i.e.: Algoso, Baltiko, Grenado, Magnat, Moderato, Pawo, Todan, Trimester, Trismart and Witon. Field trials were performed at seven locations in three years (21 environments) in a randomized complete block design, with two replicates at two levels of cultivation technology (standard – A1 and intensive – A2). Field experiments were carried out as part of Post Registration Variety Trials in Wielkopolska region. AMMI analyses revealed significant genotype and environmental effects as well as genotype by environmental Interaction with respect to all three observed traits in both levels of cultivation intensity. The cultivars Algoso, Baltiko and Trimester are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.
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Genotype by environment Interaction for area under the disease-progress curve (AUDPC) value in spring barley using additive main effects and Multiplicative Interaction model
Australasian Plant Pathology, 2020Co-Authors: Jan Bocianowski, Anna Tratwal, Kamila NowosadAbstract: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).
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Genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape (Brassica napus L.) using additive main effects and Multiplicative Interaction model
Current Plant Biology, 2020Co-Authors: Jan Bocianowski, Alina Liersch, Kamila NowosadAbstract:Abstract Genotype by environment Interaction is important for quantitative traits in all organisms. All organisms are exposed on the influence of different environmental conditions. Changes in the performance of genotypes across different environments are referred to as genotype by environment Interactions. The objective of this study was to assess genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape cultivars grown in West Poland by the additive main effects and Multiplicative Interaction model. The study comprised of 25 winter oilseed rape genotypes (15 F1 CMS ogura hybrids, eight 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. Across location average alkenyl glucosinolates content of the tested genotypes ranged from 4.13 (for PN66 × PN21) to 8.53 μmol g−1 of seeds (for Californium). The across genotype averages alkenyl glucosinolates content at locations varied substantively from 2.43 μmol g−1 of seeds in Łagiewniki, to 8.85 μmol g−1 of seeds in Borowo. In the AMMI analyses, 53.92 % of the alkenyl glucosinolates content total variation was explained by environments, 13.06 % by genotypes, and 16.02 % by genotype × environment Interaction. The hybrid PN66 × PN21 is recommended for further use in the breeding program due to its low average alkenyl glucosinolates content (4.13 μmol g-1 of seeds) and the best stability across environments (ASV = 0.255).
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Genotype by environment Interaction for seeds yield in pea ( Pisum sativum L.) using additive main effects and Multiplicative Interaction model
Euphytica, 2019Co-Authors: Jan Bocianowski, Jerzy Księżak, Kamila NowosadAbstract: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 Slupia 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.
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genotype by environment Interaction for seed quality traits in interspecific cross derived brassica lines using additive main effects and Multiplicative Interaction model
Euphytica, 2019Co-Authors: Jan Bocianowski, Janetta Niemann, Kamila NowosadAbstract:The aim of this study was to assess genotype by environment Interaction for seed quality traits in interspecific cross-derived Brassica lines by the additive main effects and Multiplicative Interaction (AMMI) model. The study comprised of 25 winter rapeseed genotypes i.e.: B. napus cultivar Californium, twenty three cross-derived Brassica lines and male sterile line of an F8 generation of B. napus (MS8), selected from resynthesized oilseed rape (B. rapa ssp. chinensis × B. oleracea var. gemmifera) using in vitro cultures of isolated embryos. Field trials were performed at three locations in 3 years in a randomized complete block design, with three replicates. AMMI analyses revealed significant genotype and environmental effects as well as genotype by environmental Interaction with respect to all five observed traits. The lines 16 (B. napus line MS8 × B. rapa ssp. pekinensis) and 7 (B. napus line MS8 × B. carinata) are recommended for further inclusion in the breeding programs because their stability and good average values of observed traits, except total glucosinolates content for line 16 (the best total genotype selection indexes were equal to 81 and 97, respectively).
Jan Bocianowski - One of the best experts on this subject based on the ideXlab platform.
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Genotype by environment Interaction for main winter triticale varieties characteristics at two levels of technology using additive main effects and Multiplicative Interaction model
Euphytica, 2021Co-Authors: Jan Bocianowski, Anna Tratwal, Kamila NowosadAbstract:The aim of this study was to assess genotype by environment Interaction for grain yield, plant height and thousand-grain weight in winter triticale cultivars by the additive main effects and Multiplicative Interaction (AMMI) model. The study comprised of ten winter triticale varieties i.e.: Algoso, Baltiko, Grenado, Magnat, Moderato, Pawo, Todan, Trimester, Trismart and Witon. Field trials were performed at seven locations in three years (21 environments) in a randomized complete block design, with two replicates at two levels of cultivation technology (standard – A1 and intensive – A2). Field experiments were carried out as part of Post Registration Variety Trials in Wielkopolska region. AMMI analyses revealed significant genotype and environmental effects as well as genotype by environmental Interaction with respect to all three observed traits in both levels of cultivation intensity. The cultivars Algoso, Baltiko and Trimester are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.
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Genotype by environment Interaction for area under the disease-progress curve (AUDPC) value in spring barley using additive main effects and Multiplicative Interaction model
Australasian Plant Pathology, 2020Co-Authors: Jan Bocianowski, Anna Tratwal, Kamila NowosadAbstract: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).
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Genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape (Brassica napus L.) using additive main effects and Multiplicative Interaction model
Current Plant Biology, 2020Co-Authors: Jan Bocianowski, Alina Liersch, Kamila NowosadAbstract:Abstract Genotype by environment Interaction is important for quantitative traits in all organisms. All organisms are exposed on the influence of different environmental conditions. Changes in the performance of genotypes across different environments are referred to as genotype by environment Interactions. The objective of this study was to assess genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape cultivars grown in West Poland by the additive main effects and Multiplicative Interaction model. The study comprised of 25 winter oilseed rape genotypes (15 F1 CMS ogura hybrids, eight 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. Across location average alkenyl glucosinolates content of the tested genotypes ranged from 4.13 (for PN66 × PN21) to 8.53 μmol g−1 of seeds (for Californium). The across genotype averages alkenyl glucosinolates content at locations varied substantively from 2.43 μmol g−1 of seeds in Łagiewniki, to 8.85 μmol g−1 of seeds in Borowo. In the AMMI analyses, 53.92 % of the alkenyl glucosinolates content total variation was explained by environments, 13.06 % by genotypes, and 16.02 % by genotype × environment Interaction. The hybrid PN66 × PN21 is recommended for further use in the breeding program due to its low average alkenyl glucosinolates content (4.13 μmol g-1 of seeds) and the best stability across environments (ASV = 0.255).
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Genotype by environment Interaction for seeds yield in pea ( Pisum sativum L.) using additive main effects and Multiplicative Interaction model
Euphytica, 2019Co-Authors: Jan Bocianowski, Jerzy Księżak, Kamila NowosadAbstract: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 Slupia 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.
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genotype by environment Interaction for seed quality traits in interspecific cross derived brassica lines using additive main effects and Multiplicative Interaction model
Euphytica, 2019Co-Authors: Jan Bocianowski, Janetta Niemann, Kamila NowosadAbstract:The aim of this study was to assess genotype by environment Interaction for seed quality traits in interspecific cross-derived Brassica lines by the additive main effects and Multiplicative Interaction (AMMI) model. The study comprised of 25 winter rapeseed genotypes i.e.: B. napus cultivar Californium, twenty three cross-derived Brassica lines and male sterile line of an F8 generation of B. napus (MS8), selected from resynthesized oilseed rape (B. rapa ssp. chinensis × B. oleracea var. gemmifera) using in vitro cultures of isolated embryos. Field trials were performed at three locations in 3 years in a randomized complete block design, with three replicates. AMMI analyses revealed significant genotype and environmental effects as well as genotype by environmental Interaction with respect to all five observed traits. The lines 16 (B. napus line MS8 × B. rapa ssp. pekinensis) and 7 (B. napus line MS8 × B. carinata) are recommended for further inclusion in the breeding programs because their stability and good average values of observed traits, except total glucosinolates content for line 16 (the best total genotype selection indexes were equal to 81 and 97, respectively).
Johannes R Anema - One of the best experts on this subject based on the ideXlab platform.
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The moderating role of lifestyle, age, and years working in shifts in the relationship between shift work and being overweight
International Archives of Occupational and Environmental Health, 2020Co-Authors: Gerben Hulsegge, Heleen Paagman, Karin I. Proper, Willem Van Mechelen, Johannes R AnemaAbstract:Purpose This study aimed to investigate the relationship between the moderating role of lifestyle, age, and years working in shifts and, shift work and being overweight. Methods Cross-sectional data were used of 2569 shift and 4848 non-shift production workers who participated between 2013 and 2018 in an occupational health check. Overweight (BMI ≥ 25 kg/m^2) was calculated using measured weight and height; lifestyle was assessed by questionnaires. Multiple-adjusted logistic regression with Interaction terms between shift work and potential moderators assessed Multiplicative Interaction; the relative excess risk due to Interaction assessed additive Interaction (synergism). Results Shift work was significantly related to being overweight (OR 1.53, 95% CI 1.33 1.76). The strength of this association did not differ by level of sleep quality, fruit and vegetable intake, and physical activity ( p ≥ 0.05). Additive and Multiplicative Interaction by smoking status was present ( p
Hanspeter Piepho - One of the best experts on this subject based on the ideXlab platform.
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Multiplicative Interaction in network meta analysis
Statistics in Medicine, 2015Co-Authors: Hanspeter Piepho, L V Madden, E R WilliamsAbstract:Meta-analysis of a set of clinical trials is usually conducted using a linear predictor with additive effects representing treatments and trials. Additivity is a strong assumption. In this paper, we consider models for two or more treatments that involve Multiplicative terms for Interaction between treatment and trial. Multiplicative models provide information on the sensitivity of each treatment effect relative to the trial effect. In developing these models, we make use of a two-way analysis-of-variance approach to meta-analysis and consider fixed or random trial effects. It is shown using two examples that models with Multiplicative terms may fit better than purely additive models and provide insight into the nature of the trial effect. We also show how to model inconsistency using Multiplicative terms. Copyright © 2014 John Wiley & Sons, Ltd.
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Robustness of the simple parametric bootstrap method for the additive main effects and Multiplicative Interaction (AMMI) model
2015Co-Authors: Johannes Forkman, Hanspeter PiephoAbstract:The additive main effects and Multiplicative Interaction (AMMI) model is a statistical model that is used for analysis of series of crop variety trials. This model can be fitted to a matrix of observations from a set of genotypes or crop varieties that have been investigated in a set of varying environments or locations. The model includes additive effects of genotypes and environments, and Multiplicative effects of genotype-by-environment Interaction. The Multiplicative Interaction terms are obtained through singular value decomposition. This paper describes the simple parametric bootstrap method, which can be used for testing significance of Multiplicative terms. The simple parametric bootstrap method assumes that observations are normally distributed. Through simulation it is confirmed that the simple parametric bootstrap method performs well provided that the assumptions of normality and homogeneity of variance are fulfilled. However, when the distribution is non-normal, the frequency of Type I error is not maintained at the nominal significance level. The results of the simulation study suggest that a non-parametric bootstrap method would be needed.
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robustness of statistical tests for Multiplicative terms in the additive main effects and Multiplicative Interaction model for cultivar trials
Theoretical and Applied Genetics, 1995Co-Authors: Hanspeter PiephoAbstract:The additive main effects Multiplicative Interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the Multiplicative Interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, FGH1, FGH2, FR)to departures from these assumptions. It is concluded that, because of its better robustness, the FRtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.
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best linear unbiased prediction blup for regional yield trials a comparison to additive main effects and Multiplicative Interaction ammi analysis
Theoretical and Applied Genetics, 1994Co-Authors: Hanspeter PiephoAbstract:Multilocation trials are often used to analyse the adaptability of genotypes in different environments and to find for each environment the genotype that is best adapted; i.e. that is highest yielding in that environment. For this purpose, it is of interest to obtain a reliable estimate of the mean yield of a cultivar in a given environment. This article compares two different statistical estimation procedures for this task: the Additive Main Effects and Multiplicative Interaction (AMMI) analysis and Best Linear Unbiased Prediction (BLUP). A modification of a cross validation procedure commonly used with AMMI is suggested for trials that are laid out as a randomized complete block design. The use of these procedure is exemplified using five faba bean datasets from German registration trails. BLUP was found to outperform AMMI in four of five faba bean datasets.
Alina Liersch - One of the best experts on this subject based on the ideXlab platform.
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Genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape (Brassica napus L.) using additive main effects and Multiplicative Interaction model
Current Plant Biology, 2020Co-Authors: Jan Bocianowski, Alina Liersch, Kamila NowosadAbstract:Abstract Genotype by environment Interaction is important for quantitative traits in all organisms. All organisms are exposed on the influence of different environmental conditions. Changes in the performance of genotypes across different environments are referred to as genotype by environment Interactions. The objective of this study was to assess genotype by environment Interaction for alkenyl glucosinolates content in winter oilseed rape cultivars grown in West Poland by the additive main effects and Multiplicative Interaction model. The study comprised of 25 winter oilseed rape genotypes (15 F1 CMS ogura hybrids, eight 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. Across location average alkenyl glucosinolates content of the tested genotypes ranged from 4.13 (for PN66 × PN21) to 8.53 μmol g−1 of seeds (for Californium). The across genotype averages alkenyl glucosinolates content at locations varied substantively from 2.43 μmol g−1 of seeds in Łagiewniki, to 8.85 μmol g−1 of seeds in Borowo. In the AMMI analyses, 53.92 % of the alkenyl glucosinolates content total variation was explained by environments, 13.06 % by genotypes, and 16.02 % by genotype × environment Interaction. The hybrid PN66 × PN21 is recommended for further use in the breeding program due to its low average alkenyl glucosinolates content (4.13 μmol g-1 of seeds) and the best stability across environments (ASV = 0.255).
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Genotype-by-environment Interaction for seed glucosinolate content in winter oilseed rape (Brassica napus L.) using an additive main effects and Multiplicative Interaction model
Biometrical Letters, 2018Co-Authors: Jan Bocianowski, Kamila Nowosad, Alina Liersch, Wiesława Popławska, Agnieszka ŁąckaAbstract: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.
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genotype by environment Interaction for oil content in winter oilseed rape brassica napus l using additive main effects and Multiplicative Interaction model
Indian Journal of Genetics and Plant Breeding, 2017Co-Authors: Kamila Nowosad, Alina Liersch, Wieslawa Poplawska, Jan BocianowskiAbstract:The objective of this study was to assess genotype by environment Interaction for oil content in winter rapeseed cultivars grown in West Poland by the additive main effects and Multiplicative Interaction model. The study comprised of 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. Oil content of the tested genotypes ranged from 35.2 to 48.8%, with an average of 44.55%. AMMI analyses revealed significant genotype by environmental Interaction with respect to oil content. The hybrid PN66×PN18 is recommended for further inclusion in the breeding program due to its high oil content, CMS ogura line PN66 and hybrid PN68×PN18 are recommended because of its stability and high oil content.
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Genotype by environment Interaction for seed yield in rapeseed (Brassica napus L.) using additive main effects and Multiplicative Interaction model
Euphytica, 2016Co-Authors: Kamila Nowosad, Alina Liersch, Wiesława Popławska, Jan BocianowskiAbstract:The objective of this study was to assess genotype by environment Interaction for seed yield in rapeseed cultivars grown in West Poland by the additive main effects and Multiplicative Interaction model. The study comprised 25 rapeseed genotypes (15 F_1 CMS ogura hybrids, their parental lines and two varieties: Californium and Hercules F_1), analyzed in five localities through field trials arranged in a randomized complete block design, with four replicates. Seed yield of the tested genotypes varied from 15.9 to 80.99 dt/ha throughout the five environments/localities, with an average of 39.69 dt/ha. In the variance analysis, 69.82 % of the total yield variation was explained by environment, 13.67 % by differences between genotypes, and 8.15 % by genotype by environment Interaction. Seed yield is highly influenced by environmental factors. Due to high influence of the environment on yield high adaptability of the genome is required.
