scholarly journals Response and yield stability of canola (Brassica napus L.) genotypes to multi-environments using GGE biplot analysis

2021 ◽  
Vol 33 (2) ◽  
pp. 105-114
Author(s):  
Mehmet Sincik ◽  
Abdurrahim T. Goksoy ◽  
Emre Senyigit ◽  
Yahya Ulusoy ◽  
Mustafa Acar ◽  
...  
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Data Matrix ◽  
Gge Biplot ◽  
Brassica Napus L ◽  
Yield Data ◽  
Essential Information ◽  
Biplot Analysis ◽  
Gxe Interaction ◽  
Main Effects

he GxE interaction (GEI) provides essential information for selecting and recommending cultivars in multi-environment trials. This study aimed to evaluate genotype (G) and environment (E) main effects and GxE interaction of 15 canola genotypes (10 canola lines and 5 check varieties) over 8 environments and to examine the existence of different mega environments. Canola yield performances were evaluated during 2015/16 and 2016/17 production season in three different locations (Southern Marmara, Thrace side of Marmara, and Black Sea regions) of Turkey. The trial in each location was arranged in a randomized complete block design with four replications. The seed yield data were analyzed using GGE biplot and the yield components data were analyzed using ANOVA. The agronomical traits revealed that environments, genotypes, and GEI were significant at 1 % probability for all of the characters. The variance analysis exhibited that genotypes, environments, and GEI explained 21.6, 21.7, and 25.7 % of the total sum of squares for seed yield, respectively. The GGE biplot analysis showed that the first and second principal components explained 57.3 and 18.3 % of the total variation in the data matrix, respectively. GGE biplot analysis showed that the polygon view of a biplot is an excellent way to visualize the interactions between genotypes and environments.

Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Area 5 ◽  
Randomized Complete Block Design ◽  
Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

scholarly journals THE ANALYSIS OF GENOTYPE × ENVIRONMENT INTERACTION USING RAPESEED (BRASSICA NAPUS L.) BY GGE BIPLOT METHOD

2020 ◽  
Vol 51 (5) ◽  
pp. 1337-1349
Author(s):  
Motahhari & et al.
Keyword(s):  
Seed Yield ◽  
Agricultural Research ◽  
Environment Interaction ◽  
Block Designs ◽  
Gge Biplot ◽  
Ge Interaction ◽  
Brassica Napus L ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Selection Of

This study was aimed to asses seed yield performances of 16 rapeseed genotypes  in randomized complete block designs (RCBD) with three replications at four Agricultural Research Stations of cold and mid-cold regions over two years in Iran (2015-2017). GGE biplot analysis indicated that the first two components explained 83% of seed yield variations. Genotype, location and their interaction explained 18%, 52% and 30%of the total GE variation, respectively. In this research, a graphically represented GGE biplot analysis enabled selection of stable and high-yielding genotypes for all investigated locations, as well as genotypes with specific adaptability. The GGE biplot analysis was adequate in explaining GE interaction for seed yield in rapeseed. It can be concluded that genotypes G2, G4 and G13 had the highest mean seed yield and stability in four investigated locations. For specific adaptability, G13 was recommended for Isfahan, Karaj and Kermanshah and G4 for Mashhad.

scholarly journals Study the Seed and Oil Yield Stability of Sunflower Hybrids across Environments

2020 ◽  
pp. 28-42
Author(s):  
M. A. Ahmed ◽  
Kh. A. Morad ◽  
M. A. Attia ◽  
Zeinab E. Ghareeb
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Heritability Estimate ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Oil Yield ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Wide Range ◽  
Main Effects

Aims: This study was conducted to investigate the nature of genotypes-environments interaction (GEI) and identify the most stable sunflower hybrids that can give high seed yield with high oil yield under a wide range of environmental conditions in Egypt. Place and Duration of Study: Fifteen hybrids were evaluated across three years (2017 to 2019) and three locations (Giza, Ettay El-Barod and Shandaweel). Study Design: The experiments were laid out in Randomized Complete Block Design (RCBD) with three replications. Methodology: Analysis of variance, some stability methods as additive main effects and multiplicative interaction (AMMI) and genotype main effects and genotype-by-environment interaction effects (GGE-biplot) were conducted. Results of stability indices were ranked as AMMI Stability Value (ASV), yield stability (YSI) and rank-sum (RSI) and heritability was estimated. Results: Combined analysis revealed that GEI was highly significant, indicating the possibility of selection for stable ones. AMMI analysis confirmed that the seed yield performance of sunflower hybrids was largely influenced by the environment. On the contrary, environments recorded less impact on oil yield as compared to the effect of hybrids (genetics). Then, heritability estimate of oil yield trait (93.86%) was higher than the seed yield one (31.10%). Indices of YSI and RSI presented that hybrids (H15, H7 and H11) and (H7, H8 and H15) were the best stable promising ones in seed and oil yield, respectively. GGE-biplot analysis indicated that hybrids (H15, H7, H4 and H11) and (H7, H15, H8 and H15) were considered as the most ideal for seed and oil yield, respectively whereas Shandweel was the ideal environment for both. Conclusion: Therefore, all analyses agreed on hybrids H15, H7 and H11 were considered as the most desirable and stable ones. These hybrids can be recommended for wider cultivation due to better seed and oil yield with stable performance across the test environments.

scholarly journals Biological and Chemical Phosphorus Fertilizers Effect on Yield and P Accumulation in Rapeseed (Brassica napus L.)

2012 ◽  
Vol 40 (2) ◽  
pp. 210 ◽  
Author(s):  
Hamid MADANI ◽  
Mohammad Ali MALBOOBI ◽  
Kioomars BAKHSHKELARESTAGHI ◽  
Agnieszka STOKLOSA
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Ammonium Phosphate ◽  
Phosphate Fertilizer ◽  
Fertilizer Application ◽  
Interaction Effects ◽  
Brassica Napus L ◽  
Sowing Time ◽  
Plant Seed ◽  
Plant Seed Oil

A field experiment was conducted for investigation of different phosphorus fertilizer sources and their importance in rapeseed farms on 2007 at Arak, Iran. Ammonium phosphate fertilizer with 50% P2O5 (APF) was as chemical phosphorus sources with 3 rates of application and Phosphor solublizing bacteria (PSB) was as biological phosphorus surcease in 4 levels. Experiment was factorial arrangement in randomized complete block design with 3 replications. APF levels were control (AP0), 125kg/ha APF (AP1) and 250kg/ha (AP2) application and PSB levels were, control (PSB0), PSB at sowing time only (PSB1), PSB as top dress fertilizer after over wintering only (PSB2) and PSB at dual fertilizing in sowing time and also after over wintering (PSB3). The statistical analyses were showed that the PSB3 treatment was a great treatment for increasing seed yield. The heist rate of seed yield was recorded at 9.9t/ha under dual fertilizing in sowing time and after rosette over wintering stage. The interaction effects of phosphorus solublizing bacteria and ammonium phosphate fertilizer application had not significant effect on plant height, biomass yield, number of silique per plant, seed oil percent and seed yield. Interaction effects of phosphorus solublizing bacteria and ammonium phosphate fertilizer application were significant for plant tissues phosphorus content.

scholarly journals Biplot analysis of seed yield and oil content combining ability in rapeseed (Brassica napus L.)

2016 ◽  
Vol 10 (9) ◽  
pp. 1238-1243
Author(s):  
Gul Ghani ◽  
◽  
Raziuddin ◽  
Antonio Teixeira do Amaral Júnior ◽  
Ibni Amin Khalil ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Seed Yield ◽  
Combining Ability ◽  
Oil Content ◽  
Brassica Napus L ◽  
Biplot Analysis

scholarly journals AMMI and GGE Biplot Analysis for Seed Yield and Oil Content of Sesame (Sesamum indicum L.) Genotypes in Tigray Northern Ethiopia

2020 ◽  
pp. 58-67 ◽  
Author(s):  
Yirga Belay Kindeya ◽  
Firew Mekbib ◽  
Eyasu Abraha Alle
Keyword(s):  
Seed Yield ◽  
Oil Content ◽  
Northern Ethiopia ◽  
Block Designs ◽  
Gge Biplot ◽  
Local Varieties ◽  
Biplot Analysis ◽  
Cropping Seasons ◽  
Ideal Genotype ◽  
Sesame Genotypes

Seventeen sesame genotypes were tested at ten environments in Tigray, Northern Ethiopia during 2014-2015 cropping seasons. Randomized Complete Block Designs (RCBD) with three replications was used in the study. According to the GGE bi-plot different sesame growing environments grouped into two mega-environments: The first mega-environment contained the favorable environments Dansha area with a vertex G4 and Sheraro area with winner G3 and the second environment included medium to low environments E2 (Humera-2), E4 (Dansha-2), E5 (Sheraro-1), E7 (Wargiba-1), E8 (Wargiba-2) and E9 (Maykadra) for seed yield. Three mega-environments identified for oil content: The 1st environment contained G12, G7 and G2 in the mega-environment group of Humera, Dansha and Gendawuha, The 2nd environment, Sheraro location contained G9 and the 3rd environment Wargiba, was containing G17. G1 (HuRC-4) identified as an “ideal” genotype and E1 (Humera-1) also identified as an ideal environment the most representative of the overall environments and the most powerful to discriminate genotypes. The multivariate approaches AMMI and GGEbi-plot were better for partitioning the GEI into the causes of variation. According to different stability models, G1, G7, and G3 were high yielder and the most stable both in terms of seed yield and oil content. Moreover, showed yield advantages over the released and local varieties. The stable genotypes recommended for wider areas while G14 and G4 were for specific favorable environments Sheraro and Dansha, respectively.

Relationship between Seed Yield and Yield Chracteristics in Faba Bean (Vicia faba L.) by GGE-Biplot Analysis

2018 ◽  
Vol 12 (2) ◽  
Author(s):  
Sinem Koç ◽  
Adnan Orak ◽  
Hazım Serkan Tenikecier ◽  
Nezihi Sağlam
Keyword(s):  
Vicia Faba ◽  
Seed Yield ◽  
Faba Bean ◽  
Gge Biplot ◽  
Biplot Analysis ◽  
Vicia Faba L

AMMI and GGE biplot analysis of multi environment yield trial of soybeanin North Western Himalayan state Uttarakhand of India

2016 ◽  
Author(s):  
Anuradha Bhartiya ◽  
J. P. Aditya ◽  
Kamendra Singh ◽  
Pushpendra Pushpendra ◽  
J. P. Purwar ◽  
...  
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Principal Component ◽  
High Yield ◽  
Gge Biplot ◽  
Soybean Genotype ◽  
Genotype By Environment ◽  
Yield Trial ◽  
Soybean Genotypes ◽  
Ideal Genotype

The investigation was carried out to study Genotype × Environment (G×E) interaction for seed yield in 36 soybean genotypes including check PS1092 over 3 diverse environments represented by different altitudes in Uttarakhand. Grain yield performances of soybean genotypes were evaluated during Kharif 2013 season using a randomized complete block design. The AMMI analysis indicated that environment, genotypes and genotype by environment interactions had significantly affected seed yield and accounted for 9.76, 28.97 and 47.55% of the total variation, respectively. GGE biplot clearly displayed interrelationships between test locations as well as genotypes and facilitated visual comparisons based on Principal Component Analysis (PCA). The first two principal components PCI and PCII were used to create a two-dimensional GGE biplot that accounted for 45.68 and 38.88% variations respectively and based on discriminating and representative ability, E2 (Majhera) was most suitable location for selecting generally adapted genotypes. Soybean genotype C1 (PS1539) was identified as ideal genotype with high yield and low G×E interaction i.e. high stability.

scholarly journals Stability analysis of bread wheat landraces and lines using biometrical genetic models

Genetika ◽  
2018 ◽  
Vol 50 (2) ◽  
pp. 449-464
Author(s):  
Fatemeh Bavandpori ◽  
Jafar Ahmadi ◽  
Sayyed Hossaini
Keyword(s):  
Bread Wheat ◽  
Block Design ◽  
Gge Biplot ◽  
Breeding Programs ◽  
Biplot Analysis ◽  
Genotype Effect ◽  
Randomized Complete Block Design ◽  
Main Effect ◽  
Ammi Analysis ◽  
Ammi Model

In order to evaluate yield stability of twenty genotypes of bread wheat, an experiment was conducted in randomized complete block design (RCBD) with three replications under irrigated and rainfed conditions in Razi University of Kermanshah for three years (2011-2013). Combined analysis of variance showed highly significant differences for the GEI. Stability determined by AMMI analysis indicated that the first two AMMI model (AMMI1-AMMI2) were highly significant (P<0.01). The GEI was three times higher than that of the genotype effect. The results of Biplot AMMI2 showed that, genotypes WC-47359, WC-47472, WC-4611, WC-47388 and WC-47403 had general adaptability. Based on the ASV and GSI, the genotypes number WC-47403 and WC-47472 revealed the highest stability. GGE biplot analysis of yield displaying main effect G and GEI justified 57.5 percent of the total variation. The first two principal components (PC1 and PC2) were used to create a 2-dimensional GGE biplot and explained 34.3, 23.2 of GGE sum of squares (SS), respectively. Genotypes WC-47403, PISHGAM2 exhibited the highest mean yield and stability. Based on the results obtained the best genotypes were WC-47403, PISHGAM2, WC-4968, WC-47472 and WC-47528 for breeding programs.

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