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.

scholarly journals Analysis of genotype by environment interaction for grain yield of intermediate maturing drought tolerant top-cross maize hybrids under rain-fed conditions

2017 ◽  
Vol 3 (1) ◽  
pp. 1333243 ◽  
Author(s):  
Alidu Haruna ◽  
Gloria Boakyewaa Adu ◽  
Samuel Saaka Buah ◽  
Roger A.L. Kanton ◽  
Amegbor Isaac Kudzo ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Genotype By Environment ◽  
Drought Tolerant

scholarly journals Analysis of Genotype by Environment Interaction of Improved Pearl Millet for Grain Yield and Rust Resistance

2017 ◽  
Vol 9 (2) ◽  
pp. 188
Author(s):  
G. Lubadde ◽  
P. Tongoona ◽  
J. Derera ◽  
J. Sibiya
Keyword(s):  
Grain Yield ◽  
Pearl Millet ◽  
Rust Resistance ◽  
Genotype By Environment Interaction ◽  
Climatic Conditions ◽  
Arid Zones ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Superior Genotypes ◽  
Main Effects

Pearl millet is grown by inhabitants of the semi-arid zones. Due to the unpredictable climatic conditions the genotype-by-environment interaction (GEI) makes it hard to select genotypes adapted to such conditions. The study objectives therefore were to analyse the patterns of GEI and to identify superior genotypes for grain yield and rust resistance. Seventy six genotypes were planted in four environments in 4×19 alpha design with two replications. The ANOVA results showed that main effects of environments were significant (p ≤ 0.05) for grain yield and highly significant (p ≤ 0.001) for rust resistance while the main effects of the genotypes and their interactions with environments were also important for grain yield and rust severity at 50% physiological maturity. The GGE biplot analysis revealed that environments associated with more rains received during vegetative phase performed better than those receiving more rains during post-anthesis phase. The winner in the best environment for grain yield was ICMV3771×SDMV96053 while Shibe×CIVT9206 and Shibe×GGB8735 were the best for rust resistance.

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.

Survival, height and genotype by environment interaction in winter wheat

1993 ◽  
Vol 73 (2) ◽  
pp. 417-427 ◽  
Author(s):  
J. B. Thomas ◽  
G. B. Schaalje ◽  
M. N. Grant
Keyword(s):  
Winter Wheat ◽  
Cold Stress ◽  
Grain Yield ◽  
Plant Height ◽  
High Stress ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Wide Range ◽  
As Stress

This study examines the relationship between plant height, winterhardiness and genotype-by-environment interaction in the grain yield of winter wheat in western Canada. Positive correlations between plant height and winter survival ability (WSA) and between plant height and lodging score have persisted among entries in Western Hard Red Winter Wheat Cooperative Trials (WWC) for 33 yr. Progress has been made in developing winterhardy semidwarfs; however, no short cultivars have yet been isolated in the most hardy group. For Saskatchewan and Manitoba trials, correlations between WSA and yield (WSA:Y) were mostly positive, indicating widespread and intense cold stress. In southwest Alberta trials, WSA:Y ranged from significantly positive to significantly negative, indicating the wide range and unpredictability of cold stress in this area; in North and Central Alberta the distribution of WSA: Y was intermediate between southwest Alberta and Manitoba and Saskatchewan. In high stress trials (WSA:Y > 0.4), cultivar grain yield increased with increased cultivar height (on average, +0.024 tonnes ha−1 for each centimetre increase in height) but as stress levels declined, this relationship was reversed. In trials with WSA: Y < −0.4, cultivar yield was negatively related to cultivar height (average slope of −0.026 tonnes ha−1 per centimetre increase in height). Similar results were found in a trial of six winter wheat cultivars over three sites and 6 years within southern Alberta. In high stress trials, tall and hardy cultivars stabilized grain yield through high rates of survival while non-hardy cultivars performed poorly. Without damaging cold stress, short and non-hardy cultivars showed the highest yields and the greatest response to environmental productivity. Key words: Yield, winterhardiness, coldstress

scholarly journals Evaluasi Stabilitas Hasil Jagung Hibrida Menggunakan Metode Genotype and Genotype by Environment Interaction Biplot (GGE BIPLOT)

2017 ◽  
Vol 1 (2) ◽  
pp. 97
Author(s):  
Slamet Bambang Priyanto ◽  
Roy Efendi ◽  
Bunyamin Z. ◽  
M. Azrai ◽  
M. Syakir
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Maize Hybrids ◽  
Genotype By Environment ◽  
North Sulawesi ◽  
South Sulawesi

<p class="Abstrak">Visualization of GGE biplot analyses was able to explain the genotype by environment interaction. This research was aimed to determine the yield stability of promising experimental maize hybrids in eight locations based GGE biplot method. Ten promising experimental maize hybrids and two commercial hybrid varieties as check, namely: HBSTK01, HBSTK03, HBSTK05, HBSTK06, HBSTK07, HBSTK08, HBSTK09, HBSTK10, HBSTK11, HBSTK13 and Bima 16 and Pertiwi 3 were evaluated in eight locations, ie. Bangka (Bangka Belitung), Probolinggo (East Java), Minahasa Utara (North Sulawesi), Donggala (Central Sulawesi), Soppeng, South Sulawesi, Gowa (South Sulawesi, Konawe (Southeast Sulawesi)and Lombok Barat (West Nusa Tenggara) from May to October 2013. The treatments were arranged in a randomized complete block design (RCBD) with 3 replications. Variable measured was grain yield. Analysis of variance was performed for data from each study site, to determine the performance of each genotype at each location. Yield stability analysis was performed by GGE biplot method using PB tools software. Results showed that genotype H9 (HBSTK11) had the highest biological stability with grain yield of 10.37 t/ha, higer than the overall mean yield. The best hybrid with the highest yield and good stability was hybrid H6 (HBSTK08) of 11.08 t/ha. This experimental hybrid is considered potential to be released as new hybrid variety. North Minahasa is considered the most suitable location for testing, whereas Konawe and West Lombok are least suitable, compared with the other locations.</p>

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).

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