scholarly journals Grain Yield Stability of Rice Genotypes

2020 ◽  
Vol 3 (2) ◽  
pp. 116-126
Author(s):  
Jiban Shrestha ◽  
Ujjawal Kumar Singh Kushwaha ◽  
Bidhya Maharjan ◽  
Manoj Kandel ◽  
Suk Bahadur Gurung ◽  
...  
Keyword(s):  
Grain Yield ◽  
Climatic Factors ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Soil Conditions ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Rice Genotypes ◽  
B 31

Stability analysis identifies the adaptation of a crop genotype in different environments. The objective of this study was to evaluate promising rice genotypes for yield stability at different mid-hill environments of Nepal. The multilocation trials were conducted in 2017 and 2018 at three locations viz Lumle, Kaski; Pakhribas, Dhankuta; and Kabre, Dolakha. Seven rice genotypes namely NR11115-B-B-31-3, NR11139-B-B-B-13-3, NR10676-B-5-3, NR11011-B-B-B-B-29, NR11105-B-B-27, 08FAN10, and Khumal-4 were evaluated in each location. The experiment was laid out in a randomized complete block design with three replications. The rice genotype NR10676-B-5-3 produced the highest grain yield (6.72 t/ha) among all genotypes. The growing environmental factors (climate and soil conditions) affect the grain yield performance of rice genotypes. The variation in climatic factors greatly contributed to the variation in grain yield. Polygon view of genotypic main effect plus genotype-by-environment interaction (GGE) biplot showed that the genotypes NR10676-B-53 and NR11105-B-B-27 were suitable for Lumle; NR11115-B-B-31-3 and NR11139-B-B-B-13-3 for Pakhribas; and 08FAN10 and NR11011-B-B-B-B-29 for Kabre. The GGE biplot showed that genotype NR10676-B-5-3 was stable hence it was near to the point of ideal genotype. This study suggests that NR10676-B-5-3 can be grown for higher grain yield production in mid-hills of Nepal.

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>

scholarly journals GGE Biplot Analysis of Multi-Environment Yield Trials in Soybean Promising Lines

2019 ◽  
Vol 3 (2) ◽  
pp. 72
Author(s):  
Ayda Krisnawati ◽  
M. Muchlish Adie
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Tropical Regions ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Promising Line ◽  
The Tropics

Soybean in Indonesia is grown in diverse agro-ecological environments. The performance of soybean yield often varies due to significant genotype × environment interaction (GEI), therefore the yield stability of performance is an important consideration in the breeding program. The aim of the research was to exploring the GEI pattern and yield stability of soybean promising lines in the tropics using GGE (Genotype and Genotype by Environment Interaction) biplot method. A total of 16 soybean promising lines were evaluated in ten environments during 2016 growing season. The experiment was arranged in a randomized completely block design with four replicates. The analysis of variance revealed that environments (E) explained the highest percentage of variation (51.45%), meanwhile the genotypes (G) and genotype × environment interactions (GEI) contributed for 3.24%, and 14.59% of the total variation, respectively. Seed yield of 16 soybean promising lines ranged from 2.41 to 2.83 t.ha-1 with an average of 2.74 t.ha-1. Joint effects of genotype and interaction (G+GE) which was partitioned using GGE biplot analysis showed that the first two components were significant, explaining 60.88% (37.89% PC1 and 22.98% PC2) of the GGE sum of squares. Indonesia can be divided into at least four putative mega environments for soybean production. The GGE biplot identified G10 as high yielding and stable promising line, thus recommended to be developed in multi-environment in tropical regions of Indonesia.

scholarly journals Genotype by environment interaction and yield stability analysis of quality protein maize genotypes in Terai Region of Nepal

2013 ◽  
Vol 1 (2) ◽  
pp. 74-78 ◽  
Author(s):  
Jiban Shrestha
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Yield Stability ◽  
Coefficient Of Determination ◽  
Quality Protein Maize ◽  
Environment Interaction ◽  
Maize Breeding ◽  
Maize Genotypes ◽  
Joint Regression Analysis

Grain yield stability for the new maize genotypes is an important target in maize breeding programs. The main objective of this study was to identify stable high yielding quality protein maize (QPM) genotypes under various locations and years in terai region of Nepal. Six quality protein maize genotypes along with Poshilo Makai-1 (Standard Check) and Farmer’s Variety (Local Check) were tested at three different locations namely Ayodhyapuri-2, Devendrapur, Madi, Chitwan; Rajahar-8, Bartandi, Rajahar,  Nawalparasi; Mangalpur-2, Rampur,  Chitwan during  2011 and 2012 spring and winter seasons under rainfed condition.  The experiment was conducted using Randomized Complete Block Design with two replications in farmer’s fields. There was considerable variation among genotypes and environments for grain yield. The analysis of variance showed that mean squares of environments (E) was highly significant and genotypes (G) and genotype x environment interaction (GEI) were non significant. The genotypes S03TLYQ-AB02 and RampurS03FQ02 respectively produced the higher mean grain yield 5422±564 kg/ha and 5274±603 kg/ha across the locations. Joint regression analysis showed that RampurS03FQ02 and S03TLYQ-AB02 with regression coefficient 1.10 and 1.22 respectively are the most stable genotypes over the tested environments. The coefficient of determination (R2) for genotypes Rampur S03FQ02 and S03TLYQ-AB02 were as high as 0.954, confirming their high predictability to stability. Further confirmation from GGE biplot analysis showed that maize genotype S03TLYQ-AB02 followed by Rampur S03FQ02 were more stable and adaptive genotypes across the tested environments. Thus these genotypes could be recommended to farmers for general cultivation.DOI: http://dx.doi.org/10.3126/ijasbt.v1i2.8202 Int J Appl Sci Biotechnol, Vol. 1(2): 75-79

scholarly journals Analysis of Genotype-Environment Interaction and Yield Stability of Introduced Upland Rice in the Groundnut Basin Agroclimatic Zone of Senegal

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ghislain Kanfany ◽  
Mathieu Anatole Tele Ayenan ◽  
Yedomon Ange Bovys Zoclanclounon ◽  
Talla Kane ◽  
Malick Ndiaye ◽  
...  
Keyword(s):  
Grain Yield ◽  
Upland Rice ◽  
Block Design ◽  
Principal Component ◽  
Stability Index ◽  
Rice Production ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype Environment Interaction

Identification of highly performing varieties under Senegalese environment is crucial to sustain rice production. Genotype-environment interaction and stability performance on the grain yield of ten upland rice genotypes were investigated across 11 environments in Senegal during the rainy seasons of 2016 and 2017 to identify adapted varieties. The experiment was conducted using a randomized complete block design with three replications at each environment. Data on grain yield were recorded and analyzed using the additive main effects and multiplicative interaction (AMMI) model. The combined analysis of variance revealed that the grain yield was significantly affected by environment (67.9%), followed by genotype × environment (G × E) interaction (23.6%) and genotype (8.5%). The first two principal component axes were highly significant with 37.5 and 26% of the total observed G × E interaction variation, respectively. GGE biplot grouped the environments into four potential megaenvironments. Based on the yield stability index parameter and ranking GGE biplot, NERICA 8 and ART3-7-L9P8-1-B-B-1 were stable and high-yielding varieties compared to the local check NERICA 6. These varieties should be proposed for cultivation in order to sustain the rice production in the southern part of the groundnut basin of Senegal and used as parental lines in rice breeding program for grain yield improvement.

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 Assessment of yield stability of maize inbred lines in multi-environment trials

2016 ◽  
Vol 51 (1) ◽  
pp. 61-68
Author(s):  
MA Miah ◽  
S Ahmed ◽  
MS Uddin
Keyword(s):  
Grain Yield ◽  
Inbred Line ◽  
High Stability ◽  
Genotype By Environment Interaction ◽  
Inbred Lines ◽  
Yield Stability ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Maize Inbred Lines ◽  
Stable Yield

Stable performance of maize hybrids at a specific growing region is critical for obtaining high and stable yield. The objectives of this study were to assess grain yield stability of fourteen maize inbred lines from five different diverse regions of Bangladesh during 2010 - 2011 growing season (rabi) using genotype main effect plus genotype by environment interaction (GGE) biplot and to identify maize inbred lines that have both high mean yield and stable yield performance across test environments of Bangladesh. The GGE biplot method was effective in recognition that the inbreds G2 and G13 to be the most desirable ones for growing in Jessore (E1), G6 and G8 in Gazipur (E2), G3 in Rahmatpur (E3) and G1, G12, G14 and G9 in Debiganj (E5) region. The inbreds G5 and G7 had average grain yield and high stability, whereas the inbred line G10 had high grain yield and high stability. Besides, the inbred line G13 was the least stable across different environments. This technique can serve as a useful tool for recommendation of maize inbreds for specific growing regions taking into account the specificities of hybrids and growing conditions.Bangladesh J. Sci. Ind. Res. 51(1), 61-68, 2016

scholarly journals Genotype-by-Environment Interaction and Stability Analysis in Grain Yield of Improved Tef (Eragrostis tef) Varieties Evaluated in Ethiopia

2019 ◽  
pp. 1-13
Author(s):  
Habte Jifar ◽  
Kebebew Assefa ◽  
Kassahun Tesfaye ◽  
Kifle Dagne ◽  
Zerihun Tadele
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Eragrostis Tef ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Testing Environments ◽  
One Year ◽  
Main Effects

Aims: To assess the magnitude of genotype by environment interaction; possible existence of different mega-environments; and discriminating ability and representativeness of the testing environments. Study Design: Randomized complete Block Design with three replications. Place and Duration of Study: The study was conducted at Debre Zeit, Holetta and Alem Tena for two years (2015 and 2016) and at Adet, Axum and Bako for one year (2015). Methodology: Thirty-five improved tef varieties were evaluated at nine environments. The G × E interaction were quantified using additive main effects and multiplicative interaction (AMMI) and the genotype and genotype by environment (GGE) biplot models. Results: Combined analysis of variance revealed highly significant (P = 0.01) variations due to genotype, environment and genotype by environment interaction effects. AMMI analysis revealed 4.3%, 79.7% and 16% variation in grain yield due to genotypes, environments and G x E effects, respectively. G6 gave the highest mean grain yield (3.33 t/ha) over environments whereas G29 gave the lowest mean yield (2.49 t/ha). The GGE biplot grouped the nine testing environments and the 35 genotypes into four mega environments and seven genotypic groups. The four mega environments include: G-I (E1, E4 and E6); G-II (E2, E3, E7 and E8); G-III (E9), and G-IV (E5). E5, E6, E7 and E8 which had the longest vector were the most discriminating of all environments while, E1 and E4 which had the smallest angle with the average environmental axis were the most representative of all environments. Regarding genotypes, G6, G25, G34 and G16 were identified as the best yielding and relatively stable genotypes to increase tef productivity. Conclusion: AMMI and GGE were found to be efficient in grouping the tef growing environments and genotypes.

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 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.

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