scholarly journals Genotype by environment interaction analysis of wheat (Triticum aestivum L.) grain yield under rain-fed conditions in Zambia

2021 ◽  
Vol 53 (4) ◽  
pp. 609-619
Author(s):  
B. Tembo
Keyword(s):  
Grain Yield ◽  
Agricultural Research ◽  
Interaction Analysis ◽  
Crop Improvement ◽  
Genotype By Environment Interaction ◽  
Research Station ◽  
Environment Interaction ◽  
Wheat Genotypes ◽  
Lattice Design ◽  
Genotype By Environment

Understanding genotype by environment interaction (GEI) is important for crop improvement because it aids in the recommendation of cultivars and the identification of appropriate production environments. The objective of this study was to determine the magnitude of GEI for the grain yield of wheat grown under rain-fed conditions in Zambia by using the additive main effects and multiplicative interaction (AMMI) model. The study was conducted in 2015/16 at Mutanda Research Station, Mt. Makulu Research Station and Golden Valley Agricultural Research Trust (GART) in Chibombo. During2016/17, the experiment was performed at Mpongwe, Mt. Makulu Research Station and GART Chibombo, Zambia. Fifty-five rain-fed wheat genotypes were evaluated for grain yield in a 5 × 11 alpha lattice design with two replications. Results revealed the presence of significant variation in yield across genotypes, environments, and GEI indicating the differential performance of genotypes across environments. The variance due to the effect of environments was higher than the variances due to genotypes and GEI. The variances ascribed to environments, genotypes, and GEI accounted for 45.79%, 12.96%, and 22.56% of the total variation, respectively. These results indicated that in rain-fed wheat genotypes under study, grain yield was more controlled by the environment than by genetics. AMMI biplot analysis demonstrated that E2 was the main contributor to the GEI given that it was located farthest from the origin. Furthermore, E2 was unstable yet recorded the highest yield. Genotype G47 contributed highly to the GEI sum of squares considering that it was also located far from the origin. Genotypes G12 and G18 were relatively stable because they were situated close to the origin. Their position indicated that they had minimal interaction with the environment. Genotype 47 was the highest-yielding genotype but was unstable, whereas G34 was the lowest-yielding genotype and was unstable.

scholarly journals Genotype by Environment Interaction and Grain Yield Stability of Drought Tolerant Cowpea landraces in Ethiopia

2021 ◽  
Author(s):  
Tesfaye Walle Mekonnen ◽  
Firew Mekbib ◽  
Berhanu Amsalu ◽  
Melaku Gedil ◽  
Maryke Labuschagne
Keyword(s):  
Grain Yield ◽  
Primary Source ◽  
Genotype By Environment Interaction ◽  
Climatic Conditions ◽  
Yield Stability ◽  
Environment Interaction ◽  
Lattice Design ◽  
Genotype By Environment ◽  
Drought Tolerant ◽  
Wide Range

Abstract Cowpea is one of the most important indigenous food and forage legumes in Africa. It serves as a primary source of protein for poor farmers in drought-prone areas of Ethiopia. The crop is used as a source of food, and insurance crop during the dry season. Cowpea is adaptable to a wide range of climatic conditions. Despite this, the productivity of the crop is generally low due to lack of stable and drought tolerant varieties. In this study, 25 cowpea genotypes were evaluated in five environments using a triple lattice design during the 2017 and 2018 main cropping seasons. The objectives of this study were to estimate the magnitude of genotype by environment interaction (GEI) and grain yield stability of selected drought tolerant cowpea genotypes across different environments. The additive main effect and multiplicative interaction (AMMI) model indicated the contribution of environment, genotype and GEI as 63.98 6%, 2.66% and 16.30% of the total variation for grain yield, respectively. The magnitudes of the GEI sum of squares were 6.12 times that of the genotypes for grain yield. The IPCA1, IPCA2 and IPCA3 were all significant and explained 45.47%, 28.05% and 16.59% of the GEI variation, respectively. The results from AMMI, cultivar superior measure (Pi), genotype plus genotype-by-environment (GGE) biplot yield stability index (YSI), and AMMI stability value (ASV) analyses identified NLLP-CPC-07-145-21, NLLP-CPC-103-B and NLLP_CPC-07-54 as stable and high yielding genotypes across environments. Thus, these genotypes should be recommended for release for production for drought prone areas. NLLP-CPC-07-143, Kanketi and CP-EXTERETIS were the least stable. The AMMI1 biplot showed that Jinka was a high potential and favorable environment while Babile was an unfavorable environment for cowpea production.

Using AMMI approach to delineate genotype by environment interaction and stability of barley (Hordeum vulgare L.) genotypes under northern Indian shivalik hill conditions

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Om Prakash Yadav ◽  
A. K. Razdan ◽  
Bupesh Kumar ◽  
Praveen Singh ◽  
Anjani K. Singh
Keyword(s):  
Hordeum Vulgare ◽  
Grain Yield ◽  
Principal Component ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Hordeum Vulgare L ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Principal Component Axis ◽  
Ammi Analysis

Genotype by environment interaction (GEI) of 18 barley varieties was assessed during two successive rabi crop seasons so as to identify high yielding and stable barley varieties. AMMI analysis showed that genotypes (G), environment (E) and GEI accounted for 1672.35, 78.25 and 20.51 of total variance, respectively. Partitioning of sum of squares due to GEI revealed significance of interaction principal component axis IPCA1 only On the basis of AMMI biplot analysis DWRB 137 (41.03qha–1), RD 2715 (32.54qha–1), BH 902 (37.53qha–1) and RD 2907 (33.29qha–1) exhibited grain yield superiority of 64.45, 30.42, 50.42 and 33.42 per cent, respectively over farmers’ recycled variety (24.43qha–1).

scholarly journals Genotype and environment interaction of sweetpotato varieties

2019 ◽  
Vol 44 (3) ◽  
pp. 501-512
Author(s):  
S Sultana ◽  
HC Mohanta ◽  
Z Alam ◽  
S Naznin ◽  
S Begum
Keyword(s):  
Tuber Yield ◽  
Agricultural Research ◽  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
Environment Interaction ◽  
Dry Matter Content ◽  
Genotype By Environment ◽  
Discriminating Power ◽  
Study Results ◽  
Main Effect

The article presents results of additive main effect and multiplicative interaction (AMMI) and genotype (G) main effect and genotype by environment (GE) interaction (G × GE) biplot analysis of a multi environmental trial (MET) data of 15 sweetpotato varieties released from Bangladesh Agricultural Research Institute conducted during 2015–2018. The objective of this study was to determine the effects of genotype, environment and their interaction on tuber yield and to identify stable sweetpotato genotypes over the years. The experimental layout was a randomized complete block design with three replications at Gazipur location. Combined analysis of variance (ANOVA) indicated that the main effects due to genotypes, environments and genotype by environment interaction were highly significant. The contribution of genotypes, environments and genotype by environment interaction to the total variation in tuber yield was about 60.16, 10.72 and 12.82%, respectively. The first two principal components obtained by singular value decomposition of the centred data of yield accounted for 100% of the total variability caused by G × GE. Out of these variations, PC1 and PC2 accounted for 71.5% and 28.5% of variability, respectively. The study results identified BARI Mistialu- 5, BARI Mistialu- 14 and BARI Mistialu- 15 as the closest to the “ideal” genotype in terms of yield potential and stability. Varieties ‘BARI Mistialu- 8, BARI Mistialu- 11 and BARI Mistialu- 12’ were also selected as superior genotypes. BARI Mistialu- 3 and BARI Mistialu- 13 was comparatively low yielder but was stable over the environment. Among them BARI Mistialu-12, BARI Mistialu-14 and BARI Mistialu-15 are rich in nutrient content while BARI Mistialu-8 and BARI Mistialu-11 are the best with dry matter content and organoleptic taste. Environments representing in 1st and 3rd year with comparatively short vectors had a low discriminating power and environment in 2nd year was characterized by a high discriminating power. Bangladesh J. Agril. Res. 44(3): 501-512, September 2019

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