scholarly journals Improvement of yield and yield stability in safflower using multivariate, parametric and non-parametric methods under different irrigation treatments and planting date

2020 ◽  
Vol 115 (2) ◽  
pp. 315
Author(s):  
Pooran GOLKAR ◽  
Nasrin RAHMATABADI ◽  
Seyyed Ali Mohammad MIRMOHAMMADY MAIBODY
Keyword(s):  
Seed Yield ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Genotype By Environment Interaction ◽  
Planting Date ◽  
Environment Interaction ◽  
Stability Parameters ◽  
Breeding Programs ◽  
Growing Seasons ◽  
Non Parametric

<p>Development of superior genotypes with high adaptability to different environments is considered as one of the most important goals in safflower breeding programs. In this study, ten parametric and six non-parametric measures along with the additive main effects and the relevant multiplicative interaction (AMMI) model were used to evaluate genotype by environment interaction (GE) in 15 safflower genotypes across 12 test environments ) combination of year, planting date and moisture conditions) during growing seasons in 2016 and 2017. AMMI analysis revealed significant differences among the genotypes and their GE interactions. The different stability statistics were substantiated by rank correlation coefficient. Rank-correlation coefficients revealed positive and significant correlations between mean seed yield and superiority index (r = 0.99**), and significant and negative correlation with bi, R2, Dij and non- parametric measures (NPi(2), NPi(3) and NPi(4)). Based on most stability parameters, the Mex.295 genotype (G10) was found to be the most stable for seed yield. IL.111 genotype (G9) recorded the highest mean yielding genotype regarded as the most favorable safflower genotype. In conclusion, both stability and seed yield should be simultaneously considered to exploit useful effects of G × E interactions in safflower breeding programs.</p>

scholarly journals Yield Components Stability Assessment of Peas in Conventional and Low-Input Cultivation Systems

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 805
Author(s):  
Vasileios Greveniotis ◽  
Elisavet Bouloumpasi ◽  
Stylianos Zotis ◽  
Athanasios Korkovelos ◽  
Constantinos G. Ipsilandis
Keyword(s):  
Seed Yield ◽  
Stability Index ◽  
Farming Systems ◽  
Farming System ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Low Input ◽  
Cultivation Systems ◽  
Biplot Analysis ◽  
Stable Performance

The primary purpose of this study was to explore yield stability of pea (Pisum sativum L.) cultivars based on stability index, with specific aim at studying cultivar behavior regarding yield of peas under both conventional and low-input cultivation systems. Five cultivars of peas were used in a strip-plot design. Correlations showed a significant positive relation between seed yield and some other traits. Indirect seed yield improvement may be implemented by improving pod length, which generally showed high stability indices in Greek mega-environment. Comparisons between conventional and low-input farming systems generally did not affect stability estimations, but revealed cultivars that exhibited stable performance, even in low-input farming systems. The additive main effects and multiplicative interaction (AMMI) biplot analysis, genotype by environment interaction (GGE) biplot analysis and analysis of variance (ANOVA) showed statistically significant differences between genotypes and environments, and also the farming system. This way, we have certain cultivars of peas to recommend for specific areas and farming system, in order to achieve the most stable performance. Vermio proved to be a stable cultivar for seed yield performance, in Giannitsa, Trikala and Kalambaka area, in low-inputs farming systems, while Olympos was the best in Florina area and low-input farming.

scholarly journals Genotype by Environment Interaction for Grain Yield of Barley Mutant Lines

2019 ◽  
Vol 65 (2) ◽  
pp. 51-58
Author(s):  
Boryana Dyulgerova ◽  
Nikolay Dyulgerov
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Winter Barley ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Growing Seasons ◽  
Stable Mutant ◽  
Check Variety ◽  
Mutant Lines

Abstract The aim of this study was to examine the genotype by environment interaction for grain yield and to identify high-yielding and stable mutant lines of 6-rowed winter barley under different growing seasons. The study was carried out during 7 growing seasons from 2010 – 2011 to 2016 – 2017 in the experimental field of the Institute of Agriculture – Karnobat, Southeastern Bulgaria. Fourteen advanced mutant lines and the check variety Vesletc were studied using a complete block design with 4 replications. The AMMI analysis of variance indicated that 20.54% of the variation for grain yield was explained by the effect of genotype and 37.34% and 42.12% were attributable to the environmental effects and genotype by environment interaction. The magnitude of the genotype by environment interaction was two times larger than that of genotypes, indicating that there was a substantial difference in genotype response across environments. The AMMI and GGE biplot analyses identified G9 as the highest yielding and stable genotype. This mutant line can be recommended for further evaluation for variety release. The mutant lines G6, G13 and G15 were suggested for inclusion in the breeding program of winter barley due to its high grain yield and intermediate stability.

scholarly journals Adaptability and stability of maize varieties using mixed model methodology

2012 ◽  
Vol 12 (2) ◽  
pp. 111-117 ◽  
Author(s):  
Flávia Ferreira Mendes ◽  
Lauro José Moreira Guimarães ◽  
João Cândido Souza ◽  
Paulo Evaristo Oliveira Guimarães ◽  
Cleso Antônio Patto Pacheco ◽  
...  
Keyword(s):  
Mixed Models ◽  
Mixed Model ◽  
Relative Performance ◽  
Environment Interaction ◽  
Maize Breeding ◽  
Breeding Programs ◽  
Genotype X Environment ◽  
Growing Seasons ◽  
Maize Varieties ◽  
Harmonic Means

The objective of this study was to evaluate the performance, adaptability and stability of corn cultivars simultaneously in unbalanced experiments, using the method of harmonic means of the relative performance of genetic values. The grain yield of 45 cultivars, including hybrids and varieties, was evaluated in 49 environments in two growing seasons. In the 2007/2008 growing season, 36 cultivars were evaluated and in 2008/2009 25 cultivars, of which 16 were used in both seasons. Statistical analyses were performed based on mixed models, considering genotypes as random and replications within environments as fixed factors. The experimental precision in the combined analyses was high (accuracy estimates > 92 %). Despite the existence of genotype x environment interaction, hybrids and varieties with high adaptability and stability were identified. Results showed that the method of harmonic means of the relative performance of genetic values is a suitable method for maize breeding programs.

scholarly journals Identification of stable genotypes and genotype by environment interaction for grain yield in sorghum (Sorghum bicolor L. Moench)

2018 ◽  
Vol 17 (1) ◽  
pp. 81-86 ◽  
Author(s):  
Massaoudou Hamidou ◽  
Oumarou Souleymane ◽  
Malick N. Ba ◽  
Eric Yirenkyi Danquah ◽  
Issoufou Kapran ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genotype By Environment Interaction ◽  
Planting Date ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Food Crop ◽  
Planting Dates ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Sorghum Bicolor L

AbstractSorghum is a staple food crop in Niger and its production is constrained by sorghum midge and the use of low yielding, local sorghum varieties. To improve sorghum productivity, it is crucial to provide farmers with high yielding sorghum cultivars that are resistant to midge. We evaluated 282 genotypes in four environments of Niger Republic. Alpha (0.1) lattice with two replications was the experimental design. Genotype and genotype by environment (GGE) biplot analysis was used to study grain yield (GY) stability and G × E interactions. The results revealed that two distinct mega environments were present. Genotype L232 was the best genotype for GY in the first planting date at Konni and the first and second planting dates (PDs) at Maradi. Genotype L17 was the best for GY in the second PD at Konni. The second PD at Konni was the most discriminating environment while the first PD at Konni is suitable for selecting widely adapted genotypes for GY.

Grain yield stability of spring safflower (Carthamus tinctorius L.)

2008 ◽  
Vol 59 (6) ◽  
pp. 546 ◽  
Author(s):  
Reza Mohammadi ◽  
Sayyed Saeid Pourdad ◽  
Ahmed Amri
Keyword(s):  
Coefficient Of Variation ◽  
Rank Correlation ◽  
Type A ◽  
Carthamus Tinctorius ◽  
Coefficient Of Determination ◽  
Environment Interaction ◽  
Type B ◽  
Stability Parameters ◽  
Spearman’S Rank Correlation ◽  
Genotype Environment Interaction

The additive main effect and multiplicative interaction (AMMI) model and the phenotypic stability parameters, ecovalence (W2), regression coefficient (b), coefficient of determination (R2), coefficient of variation (CV), stability variance (S2), AMMI stability value (ASV), and TOP (proportion of environments in which a genotype ranked in the top third), were used to evaluate simultaneously the yield performance and stability of 17 spring safflower genotypes and to evaluate 26 rainfed environments during 2003–05 in Iran. These parameters were designated as Type-A and Type-B for genotypes and environments, respectively. Among Type-B parameters, Spearman’s rank correlation showed that the AMMI stability value (ASVj), ecovalence (Wj2), genotypic variance (Sj2), and coefficient of variation (CVj) were significantly and positively associated (P < 0.01), indicating that one of these parameters can be used as an alternative to the others, but were significantly and negatively correlated with the genotypic selectivity (bj) parameter. The results showed that none of the Type-A statistics per se was useful for selecting high-yielding and stable genotypes. Based on these parameters, the genotypes G9, G10, and G11 combined high and stable yields while the highest yielding genotypes G1 and G17 were the most instable. Type-A and Type-B stability parameters are useful to identify genotypes with specific and large adaptations and the contrasting environments with high contribution to genotype × environment interaction.

scholarly journals Phenotypic Stability Analysis for Seed Yield and its Associated Traits in Advanced Lines of Indian Mustard (Brassica juncea L. Czern and Coss)

2021 ◽  
Vol 10 (11) ◽  
pp. 133-141
Author(s):  
Danisa Dube Th. Renuka Devi ◽  
Ph. Ranjit Sharma N. B. Singh
Keyword(s):  
Stability Analysis ◽  
Brassica Juncea ◽  
Seed Yield ◽  
Indian Mustard ◽  
Climatic Conditions ◽  
Environment Interaction ◽  
Phenotypic Stability ◽  
Stability Parameters ◽  
Gxe Interaction ◽  
Main Component

Phenotypic Stability Analysis for Seed Yield and its Associated Traits In advanced lines of Indian Mustard (Brassica juncea L. Czern and Coss)” was carried out to study the effects of different environments on seed yield and its associated traits, to estimate the magnitude of Genotype x Environment interaction and to find out the most stable and high yielding genotype among the selected lines of Indian mustard under different environments of different topography, soil texture and prevailing climatic conditions of Manipur. Fifteen genotypes were evaluated in 3 different locations (Andro, Iroisemba and Senapati) in RBD with 3 replications over two seasons viz; Rabi 2018-19 and 2019-20. The environment wise ANOVA revealed highly significant differences among all the genotypes studied for all the 11 characters of seed yield and its associated traits. The pooled ANOVA also indicated significant differences among the environments, genotypes as well as genotype by environment (GXE) interaction for all the traits. Genotype X Location interaction was observed as the main component for GXE interaction. Genotypes performed better in 2019-20 rabi season as compared to rabi 2018-19. Environment (E-5) i.e. Iroisemba, valley area was the best for expression of most of the characters studied. Stability Analysis using Eberhart and Russell indicated the significance of GXE (linear) for no. of siliqua/plant, no. of seeds/siliqua, siliqua length, no. of primary branches, no. of secondary branches, days to first flowering, days to 50% flowering, days to 80% maturity and 1000 seed weight except for plant height and seed yield per plot which shows the substantial amount of predictable G X E interaction for the expression of these characters in the selected genotypes. All the 15 genotypes were tested for 3 stability parameters, viz mean, bi and S2 di. The genotypes CAURMM-3, CAURMM-4, CAURM- 5, CAURM-4, PM- 25, CAURMM-1 and JM-1 were identified to be the high yielding and stable, hence they can be recommended for general cultivation under varied environments of Manipur. CAURM-1 CAURM-2, CAURM-3 had more stable characters although their yield was below the population mean, Therefore, proposed as promising genotypes for general cultivation under intensive input supply as they performed best in favourable environments, while NRCHB 101 found to be suitable for cultivation under poor environments.

scholarly journals Assessment of Genotype × Environment Interaction of Safflower (Carthamus tinctorius L.) Genotypes by Parametric and Non-Parametric Methods

2021 ◽  
Vol 3 (1) ◽  
pp. 112-118
Author(s):  
İlhan Subaşı ◽  
Dilek Başalma
Keyword(s):  
Seed Yield ◽  
Positive Association ◽  
Stability Index ◽  
Oil Yield ◽  
Coefficient Of Determination ◽  
Mean Deviation ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Stability Parameters ◽  
Genotype Environment Interaction

Genotype-environment interaction is a significant factor for finding and selecting stable and productive varieties in safflower breeding programs. This study was conducted at three locations over two years (2016-2017) to determine the extent of genotype by environment (GE) interaction in seed and oil yield. 20 safflower lines and cultivars were evaluated in terms of stability in 3 environments. Considering the stability and performance, the most suitable genotypes were determined as Remzibey-05 and Genotype-125 in seed yield, Genotype-8 and Genotype-155 in oil yield. In terms of stability and performances of genotypes, the environment of Ikizce 2017 (E4) was prominent. Correlation analysis among parametric and nonparametric features was given only for seed yield. The following stability parameters were calculated: the coefficient of variation (CV), regression constant (ai), regression coefficient (bi), mean deviation squares from regression (S2di), coefficient of determination (Ri2), stability variance (σi2), ecovalance value (Wi), stability index (Pi) and as nonparametric stability measures Si(1) and Si(2) values. This analysis indicated that seed yield was significantly positively correlated only with Pi (P<0.01). CV showed a positively significant correlation with ai. S2di and ri2 had a positive association with Ri2, σi2, Wi, Pi, Si(1), Si(2), and between each other.

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