scholarly journals Genotype-environment interaction for production characteristics in cherry tomato (Solanum spp.)

2021 ◽  
Vol 15 (2) ◽  
Author(s):  
Nelson Ceballos-Aguirre ◽  
Franco Alirio Vallejo-Cabrera ◽  
Yacenia Morillo-Coronado
Keyword(s):  
Fruit Weight ◽  
Natural Environments ◽  
Environment Interaction ◽  
Cherry Tomato ◽  
Breeding Programs ◽  
Tomato Species ◽  
Yield And Quality ◽  
Genotype Environment Interaction ◽  
Experiment Unit ◽  
The Stability

Much of the tomato diversity is found in cherry-type populations. There are promising wild cherry tomato species with good behavior in terms of yield and quality that can be produced with a minimum of agro-inputs. The genetic expression of genotypes is influenced by the optimal environment they can develop in. The genotype-environment interaction must be known to estimate the phenotypic adaptability in different environments. The objective of this research was to evaluate the genotype-environment interaction for 10 cherry tomato introductions in nine environments, four of which were artificial environments (0, 60, 120 and 180 kg ha-1 of potassium) established in natural environments on the Farms Montelindo, Tesorito and CEUNP. The experiment design used randomized complete blocks with four replicates; the experiment unit consisted of five effective plants per introduction. The evaluated variables were production per plant (PFT) (kg/pl), number of fruits per plant (NFT), and average fruit weight (AWF) (g/fruit). The genotype×environment interaction and the stability of the 10 genotypes were estimated with the AMMI multivariate model. The environments for T120K and T180K were optimal for the variables associated with production (PFT, NFT and AWF), with IAC1621, IAC426 and IAC1624 being the most promising genotypes per environment on the Farms Tesorito, Montelindo and CEUNP, respectively. The results are useful for the identification of genotypes in key locations for selection and evaluation in breeding programs.

Stability Analysis of Some Novel Cytoplasmic Male Sterile Sources of Sunflower and Their Hybrids

Helia ◽  
2018 ◽  
Vol 41 (69) ◽  
pp. 153-200 ◽  
Author(s):  
Vikrant Tyagi ◽  
S. K. Dhillon ◽  
Prashant Kaushik
Keyword(s):  
Stability Analysis ◽  
Environment Interaction ◽  
Spring Season ◽  
Male Sterile ◽  
Cross Combination ◽  
Yield And Quality ◽  
Genotype Environment Interaction ◽  
Standard Procedures ◽  
Wide Range ◽  
The Stability

AbstractGenetic makeup along with environmental stimuli affect the expression of a trait in plants. Drought tolerance in addition to stability of characters over a wide range of environmental conditions is not well studied in sunflower. Therefore, here we have performed a stability analysis study of sunflower genotypes. The experimental material comprised of 19 lines of sunflower comprising 9 alloplasmic cms lines from different wild sources along with one common maintainer from petiolaris source, 4 cms lines and one maintainer from cultivated source (cytoplasm from H. petiolaris), 4 restorer lines and 60 F1 hybrids (developed in line x tester design). The experiment was conducted over two years i. e. spring season 2011 and spring season 2012 over the two environments one normal irrigated and another water stress environment at Punjab Agricultural University, Ludhiana, India. The data were recorded for different morphophysiology, yield and quality trais and analysis as per standard procedures. The genotype×environment interaction was further partitioned into linear and non-linear components according to Eberhart and Russel model. Eleven sunflower hybrids were found to be stable across the environments for seed yield. While, sufficient variability was also recorded for the oil content with the highest oil percentage in the cross combination ARG-2A×P100R (34.61). Overall, this study provides useful information regarding the stability of newly developed and cytoplasmically diverse sunflower hybrids under north Indian conditions.

scholarly journals Genotype Environment Interaction in Grass Pea (Lathyrus sativusL.) Lines

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Author(s):  
G. B. Polignano ◽  
V. Bisignano ◽  
V. Tomaselli ◽  
P. Uggenti ◽  
V. Alba ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Plant Height ◽  
Seed Yield ◽  
Principal Components ◽  
Environment Interaction ◽  
Grass Pea ◽  
Genotype Environment Interaction ◽  
Marginal Areas ◽  
Different Seasons ◽  
The Stability

Eight grass pea lines grown in three different seasons were evaluated for the stability of seed yield, 100 seeds weight, flowering time, plant height, and biomass. Significant differences existed among years, lines, and lines years interaction for all traits except for 100 seeds weight. Two methods of multivariate analysis cluster and principal components were utilized to determine: firstly, whether a pattern existed among lines in their response across years and secondly to examine the relationships among them. In both analyses, each line was presented as a vector whose elements were given by the performance of lines in each year. The analyses used arranged the lines into groups that were differentiable in terms of performances and stability. Our results provide useful information to aid the choice of grass pea lines in the Mediterranean marginal areas.

scholarly journals Interaksi Genotipe x Lingkungan Hasil dan Komponen Hasil 14 Genotipe Tomat di Empat Lingkungan Dataran Rendah

2015 ◽  
Vol 43 (1) ◽  
pp. 59
Author(s):  
Suprayanti Martia Dewi ◽  
Sobir , ◽  
Muhamad Syukur
Keyword(s):  
Stability Analysis ◽  
Block Design ◽  
Fruit Weight ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Gxe Interaction ◽  
Superior Genotype ◽  
Ammi Model ◽  
The Stability

Genotype x environment interaction (GxE) information is needed by plant breeders to assist the identification of superior genotype. Stability analysis can be done if there is a GxE interaction, to show the stability of a genotype when planted in different environments. This study aimed to estimate the effects of genotype x environment interaction on yield and yield components of fruit weight per plant as well as to look at the stability of 14 tomato genotypes at four lowland locations. The study was conducted at four locations, namely Purwakarta, Lombok, Tajur and Leuwikopo. Experiments at each location was arranged in a randomized complete block design with three replications. Stability analysis was performed using the AMMI model. Fruit weight, fruit diameter, number of fruits per plant and total fruit weight per plant characters showed highly significant genotype x environment interactions. Variability due to the effect of GxE interaction based on a AMMI2 contributed by 88.50%. IPBT3, IPBT33, IPBT34, IPBT60 and Intan were stable genotypes under AMMI model.<br />Keywords: AMMI, multilocation trials

scholarly journals DESEMPENHO DE CULTIVARES DE SOJA EM DIFERENTES AMBIENTES DE CULTIVO

Nativa ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 390-396
Author(s):  
Paulo Henrique Cerutti ◽  
Marcio Dos Santos ◽  
Anne Tietjen Muniz ◽  
Arthur Ribeiro Rodrigues ◽  
Luan Tiago dos Santos Carbonari ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Grain Yield ◽  
Linear Regression Analysis ◽  
Relevant Information ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Soybean Cultivars ◽  
Genotype Environment Interaction ◽  
Analogous Behavior

Anualmente, inúmeros cultivares de soja são desenvolvidos por programas de melhoramento genético. Desse modo, é importante obter informações sobre o comportamento desses cultivares em distintos ambientes. Objetivou-se com a elaboração do trabalho avaliar o efeito da interação genótipo*ambiente no desempenho de cultivares de soja em diferentes ambientes de cultivo. O delineamento experimental utilizado foi de blocos ao acaso com três repetições. Durante a execução dos experimentos, foi avaliado o desempenho produtivo de seis cultivares de soja em seis ambientes. A variável considerada foi o rendimento de grãos (kg ha-1). As informações foram submetidas a análise de variância, análise de regressão linear simples e teste de comparação de médias. A média geral de produtividade de grãos foi de 2960 kg ha-1. Aanálise de regressão indicou dois cultivares com adaptabilidade ampla, três cultivares com adaptabilidade específica a ambientes desfavoráveis e um cultivar com adaptabilidade específica a ambientes favoráveis. Dentre os cultivares avaliados, quatro apresentaram comportamento esperado ao longo dos ambientes de cultivo. Os cultivares exibiram comportamento análogo quanto ao rendimento de grãos. Por meio da aplicação da metodologia da regressão linear, foi possível obter informações relevantes para cultivo de soja em ambientes subsequentes.Palavras-chave: Glicine max L.; interação genótipo*ambiente; adaptabilidade; estabilidade. PERFORMANCE OF SOYBEAN CULTIVARS IN DIFFERENT GROWING ENVIRONMENTS ABSTRACT:Annually, numerous soybean cultivars are developed by breeding programs. Thus, is important to obtain information about of these cultivars behavior in different environments. The objective of this work was to evaluate the effect of the genotype * environment interaction on the performance of soybean cultivars in different growing environments. The experimental design used was randomized blocks with three replications. During the execution of the experiments, was evaluated the productive performance of six soybean cultivars in six environments. The trait considered was grain yield (kg ha-1). The information was submitted to analysis of variance, simple linear regression analysis and means comparison test. The overall mean grain yield was 2960 kg ha-1. Regression analysis indicated two cultivars with broad adaptability, three cultivars with specific adaptability to unfavorable environments and one cultivar with specific adaptability to favorable environments. Among the evaluated cultivars, four showed prospective behavior throughout the cultivation environments. The cultivars exhibited analogous behavior regarding grain yield. The application of the linear regression methodology provided relevant information for soybean cultivation in subsequent environments.Keywords: Glicine max L.; genotype*environment interaction; adaptability; stability.

scholarly journals Models for multi-environment yield trials with fixed and random block effects and homogeneous and heterogeneous residual variances.

1969 ◽  
Vol 91 (3-4) ◽  
pp. 117-131
Author(s):  
Fernando Casanoves ◽  
Raúl Macchiavelli ◽  
Mónica Balzarini
Keyword(s):  
Analysis Of Variance ◽  
Block Design ◽  
Breeding Program ◽  
Residual Variance ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Heterogeneous Variances ◽  
Genotype Environment Interaction ◽  
Random Block ◽  
Residual Variances

Multi-Environment Trials (METs) are used to make recommendations about genotypes at many stages of plant breeding programs. Because of the genotype-environment interaction, METs are usually conducted in various environments (locations and/or years), using designs which involve several repetitions (plots) for each genotype at each environment. The stratification or blocking of plots within each environment enables one to consider part of the variability due to differences between plots. The objective of this study was to see how frequently the problem of heterogeneous variances across environments appears in Peanut Breeding Program METs, and to evaluate the effects of diverse spatial modeling strategies on the comparison of genotype means in each environment. A series of 18 METs in a peanut breeding program with randomized complete block design in each environment were simultaneously adjusted by using 1) classic analysis of variance models (fixed and random block effects); 2) mixed models adjusted with homogenous and heterogeneous residual variances to take into account that experiments conducted in different environments may vary in precision (residual variances). The results suggest that the analysis of variance models with a block design and heteroscedastic errors between locations are more appropriate than their homogeneous residual variance versions.

Selecting stable and high-yielding sorghum cultivars for the semi-arid tropics

1994 ◽  
Vol 74 (4) ◽  
pp. 759-762
Author(s):  
O. P. Dangi ◽  
R. I. Hamilton ◽  
C. S. Lin ◽  
D. Andre ◽  
J. J. Johnson
Keyword(s):  
High Yield ◽  
Annual Rainfall ◽  
Environment Interaction ◽  
Mean Square ◽  
Stability Parameters ◽  
The North ◽  
Genotype Environment Interaction ◽  
Northern Cameroon ◽  
The Stability ◽  
Extreme North

A sorghum breeding program was reactivated in 1981 and selected cultivars, along with local checks, were evaluated in two experiments in the sorghum growing region of northern Cameroon. Experiment 1 was conducted in the Extreme North Province where annual rainfall ranges from 450 to 850 mm. Experiment 2 was conducted in the North Province where annual rainfall exceeds 850 mm. The objective of the study was to select a high yield and high stability sorghum cultivar for each region. The cultivar's responses were investigated using two analyses: the adaptability analysis and the stability analysis. The former used the method of superiority measure, defined by distance mean square between the test cultivar and the maximum (the highest yield in the location), and the latter used type 4 stability parameter, defined by the years within location mean square averaged over all locations. The conceptual separation of adaptability and stability facilitated the cultivars assessment. The results showed that in exp. 1, three cultivars S–35, CS–54 and CS–61 had similar adaptability and stability, while in the exp. 2, S–34 was best in terms of yield but was unstable due to susceptibility to grain mold. In contrast, the second best cultivar CS–63 was poorer in the high-yielding environments but was more stable than S–34. Key words: Sorghum, genotype-environment interaction, adaptability, stability parameters

THE DESIGN AND ANALYSIS OF GENETIC EXPERIMENTS TO MODIFY GENOTYPE-ENVIRONMENT INTERACTION. I. SINGLE PAIR MATINGS AND SELECTION USING ONE SIMPLE QUANTITATIVE ATTRIBUTE MEASURED IN TWO ENVIRONMENTS

1973 ◽  
Vol 15 (3) ◽  
pp. 635-645 ◽  
Author(s):  
Eliyahu Scheinberg
Keyword(s):  
Indirect Selection ◽  
Single Pair ◽  
Environment Interaction ◽  
Breeding Programs ◽  
Designed Experiments ◽  
Genetic Groups ◽  
Genotype Environment Interaction ◽  
Quantitative Changes ◽  
The One ◽  
Theoretical Considerations

Most breeding programs are aimed at producing quantitative changes in the genetic structure of the population in question. Available theory and designed experiments have failed to show how to modify the expression of genotype-environment interaction and assume that it is negligible or is not present.This paper considers the design of an experiment to test the feasibility of modifying this interaction and gives the necessary formulae to evaluate the results. It suggests that a number of genetic groups, say each with 2n full-sibs, should be equally divided into two random sub-groups and placed in different environments, e.g., two nutritional or climatic levels. One environment is where the parents and the first group of n randomly chosen offspring are reared continuously and the other environment is the one in which the second group of offspring is reared from birth. A criterion is then established for a selection program based on the performance differential of the same simple quantitative attribute measured in full-sibs reared in the two environments. This scheme can be employed for selecting for this criterion in three directions. Extensions of these theoretical considerations for the cases of more than one simple quantitative attribute, part-whole correlated attributes, indirect selection and more complicated designs will follow.

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