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 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 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.

Stability Analysis of Agronomic Traits for Maize (Zea Mays L.) Genotypes Based on Ammi Model

2021 ◽  
Vol 50 (2) ◽  
pp. 343-350
Author(s):  
Meijin Ye ◽  
Zhaoyang Chen ◽  
Bingbing Liu ◽  
Haiwang Yue
Keyword(s):  
Grain Yield ◽  
Agronomic Traits ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Kernel Weight ◽  
Environment Interaction ◽  
Maize Hybrids ◽  
Genotype By Environment ◽  
Ammi Model ◽  
The Ideal

Stability and adaptability of promising maize hybrids in terms of three agronomic traits (grain yield, ear weight and 100-kernel weight) in multi-environments trials were evaluated. The analysis of AMMI model indicated that the all three agronomic traits showed highly significant differences (p < 0.01) on genotype, environment and genotype by environment interaction. Results showed that genotypes Hengyu321 (G9), Yufeng303 (G10) and Huanong138 (G3) were of higher stability on grain yield, ear weight and 100-kernel weight, respectively. Genotypes Hengyu1587 (G8) and Hengyu321 (G9) showed good performance in terms of grain yield, whereas Longping208 (G2) and Weike966 (G12) showed broad adaptability for ear weight. It was also found that the genotypes with better adaptability in terms of 100-kernel weight were Zhengdan958 (G5) and Weike966 (G12). The genotype and environment interaction model based on AMMI analysis indicated that Hengyu1587 and Hengyu321 were the ideal genotypes, due to extensive adaptability and high grain yield under both testing sites. Bangladesh J. Bot. 50(2): 343-350, 2021 (June)

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.

scholarly journals Analysis of Genotype by Environment Interaction on Cocoa Hybrids (Theobroma cacao L.) Resistance to Phytophthora Pod Rot

2016 ◽  
Vol 32 (3) ◽  
pp. 162-170
Author(s):  
Agung Wahyu Soesilo ◽  
Indah Anita Sari ◽  
Bayu Setyawan
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Experimental Station ◽  
Stability Performance ◽  
Stable Performance ◽  
Wet Climate ◽  
The Stability

Phenomenon of genotype by environment interaction was able to influence the stability performance of cocoa resistance to Phytophthora pod rot (PPR). This research had an objective to evaluate the effect of genotype by environment interaction on resistance of cocoa hybrids to PPR. The tested hybrids were F1 crosses between selected clones of TSH 858, Sulawesi 1, Sulawesi 2, NIC 7, ICS 13, KEE 2 and KW 165. There were 14 tested hybrids and an open pollinated hybrid of ICS 60 x Sca 12 was used as control in multilocation trials at four different agroclimatic locations, namely Jatirono Estate ((highland-wet climate), Kalitelepak Estate (lowland-wet climate), Kaliwining Experimental Station (low land-dry climate) and Sumber Asin Experimental Station (highland-dry climate). Trials were established in the randomized complete block design with four replications. Resistance to PPR were evaluated based on the percentage of infected pod for the years during wet climate of 2010 in Jatirono, Kalitelepak and Kaliwining followed in dry climate of 2011–2015 in Kaliwining and Sumber Asin. Variance of data were analyzed for detecting the effect of genotype by environment interaction (GxE) then visualized with a graph of genotype main effect and genotype by environment interaction (a graph of GGE) biplot. There was consistently no interaction effect between hybrid and location to PPR incidence which was affected by single factor of hybrid, year, location and interaction between year and location. The effect of year indicated yearly change of weather was more important to PPR incidence than location difference. A graph of GGE biplot indicated a stable performance of the tested hybrids among locations.

scholarly journals Identification of stable genotypes and genotype by environment interaction for grain yield in sorghum (Sorghum bicolor L. Moench)

2018 ◽  
Vol 17 (1) ◽  
pp. 81-86 ◽  
Author(s):  
Massaoudou Hamidou ◽  
Oumarou Souleymane ◽  
Malick N. Ba ◽  
Eric Yirenkyi Danquah ◽  
Issoufou Kapran ◽  
...  
Keyword(s):  
Grain Yield ◽  
Genotype By Environment Interaction ◽  
Planting Date ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Food Crop ◽  
Planting Dates ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Sorghum Bicolor L

AbstractSorghum is a staple food crop in Niger and its production is constrained by sorghum midge and the use of low yielding, local sorghum varieties. To improve sorghum productivity, it is crucial to provide farmers with high yielding sorghum cultivars that are resistant to midge. We evaluated 282 genotypes in four environments of Niger Republic. Alpha (0.1) lattice with two replications was the experimental design. Genotype and genotype by environment (GGE) biplot analysis was used to study grain yield (GY) stability and G × E interactions. The results revealed that two distinct mega environments were present. Genotype L232 was the best genotype for GY in the first planting date at Konni and the first and second planting dates (PDs) at Maradi. Genotype L17 was the best for GY in the second PD at Konni. The second PD at Konni was the most discriminating environment while the first PD at Konni is suitable for selecting widely adapted genotypes for GY.

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 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.

Sign in / Sign up

Export Citation Format

Share Document