scholarly journals Evaluation of the performance of some white seeded sesame (Sesamum Indicum L.) genotypes using GGE biplot analysis in Northern Ethiopia

2018 ◽  
Vol 9 (1) ◽  
pp. 1-9
Author(s):  
Belay Fantaye ◽  
Meresa Hintsa ◽  
Gebreslasie Atsbha
Keyword(s):  
Sesamum Indicum ◽  
Northern Ethiopia ◽  
Gge Biplot ◽  
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.

Genotype × environmental interaction by AMMI and GGE biplot analysis for the provenances of Michelia chapensis in South China

2015 ◽  
Vol 27 (3) ◽  
pp. 659-664 ◽  
Author(s):  
Runhui Wang ◽  
Dehuo Hu ◽  
Huiquan Zheng ◽  
Shu Yan ◽  
Ruping Wei
Keyword(s):  
South China ◽  
Gge Biplot ◽  
Environmental Interaction ◽  
Biplot Analysis

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).

GGE Biplot Analysis of Yield Associations with Root Traits in a Mesoamerican Bean Diversity Panel

Crop Science ◽  
2016 ◽  
Vol 56 (3) ◽  
pp. 1081-1094 ◽  
Author(s):  
V. Hoyos-Villegas ◽  
E.M. Wright ◽  
J.D. Kelly
Keyword(s):  
Root Traits ◽  
Gge Biplot ◽  
Biplot Analysis ◽  
Diversity Panel

scholarly journals GGE biplot analysis of multi-location yield trial of ginger (Zingiber Officinale Rosc.) Genotypes in South-Eastern, Nigeria

2020 ◽  
Vol 10 (1) ◽  
pp. 485-503
Author(s):  
Abua Mary Njei ◽  
Iwo Godfery Akpan ◽  
Ittah Macauley Asim ◽  
Obok Ekemini Edet ◽  
Edugbo Richmond Emu
Keyword(s):  
Zingiber Officinale ◽  
Gge Biplot ◽  
Biplot Analysis ◽  
South Eastern ◽  
Yield Trial
Sign in / Sign up

Export Citation Format

Share Document