scholarly journals GENOTYPE BY ENVIRONMENT INTERACTION OF ADVANCED SOYBEAN BREEDING LINES IN LAMPUNG UPLAND SOILS

Zuriat ◽  
2015 ◽  
Vol 19 (1) ◽  
Author(s):  
Darman M. Arsyad ◽  
, Purwantoro
Keyword(s):  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
Environment Interaction ◽  
Breeding Line ◽  
Upland Soil ◽  
Soybean Breeding ◽  
Breeding Lines ◽  
Genotype By Environment ◽  
Upland Soils ◽  
Plot Design

Availability of adapted cultivars is needed for the development of soybean cultivation in upland soil in Lampung, Sumatra. Twelve advanced soybean breeding lines and two check varieties (Tanggamus and Wilis) were tested on upland soils of Lampung Province. The trials were conducted in the District of Tulangbawang, Central Lampung, East Lampung and South Lampung during the late rainy season of 2003/2004. Two sites were selected per district for a total of eight sites for the four districts. A split plot design with three replications was used within each location. Plot size was 2.4 m x 4.5 m, plant spacing of 40 cm between rows and 15 cm within a row, and two plants per hill. The mainplot was fertilizer: A= Low inputs (22.5 kg N, 27 kg P2O5, and 40 kg K2O per ha), and B=Medium inputs (22.5 kg N, 36 kg P2O5, 53 kg K2O and 0.56 t CaO per ha). The fertilizers were applied before planting. The subplots were 12 soybean breeding lines together with two check soybean varieties. Results showed that soybean yields were affected significantly by locations, fertilizers, breeding lines, location x fertilizer and location x breeding line interactions. Plant height was affected siginificantly by locations, fertilizers, breeding lines and location x breeding interaction. Pods per plant  were affected by locations, fertilizers, location x fertilizer and location x breeding line interactions. All breeding lines and varieties were responsive to changing environments. Based on the smallest Pi parameter (the distance mean square between the cultivar’s response and the maximum response averaged over all locations), and the highest frequency of rank, three breeding lines, namely W3465-27-2 (released in 2004 as cv. Ratai), cv. Tanggamus and D3578- 3/K3911-66-3 were identified as wide adaptability genotypes with the yield potential of more than 2.4 t/ha with an average of 1.6 t/ha.

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

scholarly journals Identification of Spring Barley Breeding Lines With Superior Yield Performance and Stability

2020 ◽  
Vol 68 (6) ◽  
pp. 947-958
Author(s):  
Volodymyr Hudzenko ◽  
Tetiana Polishchuk ◽  
Oleksandr Demydov ◽  
Mykola Sardak ◽  
Nataliia Buniak ◽  
...  
Keyword(s):  
Spring Barley ◽  
Genotype By Environment Interaction ◽  
Forest Steppe ◽  
Environment Interaction ◽  
Yield Performance ◽  
Practical Result ◽  
Breeding Lines ◽  
Genotype By Environment ◽  
Barley Breeding ◽  
Main Effects

The aim of the present study was to substantiate theoretically and to test in practice scheme of multi-environment trials at the final stage of spring barley breeding process and to distinguish the genotypes which combine superior yield performance and stability. In the first year of competitive testing (2015) nine promising spring barley breeding lines have been selected under condition of the Central part of Forest-Steppe of Ukraine (latitude 49°64′, longitude 31°08′, altitude 153 m). In 2016 and 2017, the genotypes were additionally tested in two other different agro-climatic zones of Ukraine: Polissia (latitude 50°93′, longitude 31°69′, altitude 126 m) and Northern Steppe (latitude 48°56′, longitude 32°32′, altitude 171 m). In addition to the standard variety Vzirets, the breeding lines were compared with ten widespread spring barley varieties in agricultural production. Significant total yield variability of the genotypes and cross-over genotype by environment interaction has been revealed. It confirmed the validity of proposed combination of spatial (zones) and temporal (years) gradients for more efficient evaluation of the genotype by environment interaction and differentiation of genotypes in terms of yield performance and stability. As a practical result, using additive main effects and multiplicative interaction (AMMI) and genotype main effects plus genotype by environment interaction (GGE) models, four spring barley breeding lines with combination of superior yield performance and high stability have been identified.

scholarly journals Assessment of ecological stability in yield for breeding of spring barley cultivars with increased adaptive potential

2020 ◽  
Vol 11 (3) ◽  
pp. 425-430
Author(s):  
V. M. Hudzenko ◽  
O. A. Demydov ◽  
V. P. Kavunets ◽  
L. M. Kachan ◽  
V. A. Ishchenko ◽  
...  
Keyword(s):  
Spring Barley ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Ecological Stability ◽  
Breeding Lines ◽  
Barley Cultivars ◽  
Genotype By Environment ◽  
Barley Breeding ◽  
Agroclimatic Zones

Increasing crop adaptability in terms of ensuring a stable level of productivity in the genotype – environment interaction is still the central problem of plant breeding theory and practice. The aim of the present study is to theoretically substantiate and practically test a scheme of multi-environment trials, as well as interpret experimental data using modern statistical tools for evaluation of the genotype by environment interaction, and highlight the best genotypes with combining yield performance and ecological stability at the final stage of the spring barley breeding process. For this purpose in the first year of competitive testing (2016) at the V. M. Remeslo Myronivka Institute of Wheat of the National Academy of Agrarian Sciences of Ukraine we selected nine promising spring barley breeding lines. In 2017 and 2018 these breeding lines were additionally tested in two other scientific institutions located in different agroclimatic zones of Ukraine. For a more reliable assessment, the breeding lines were compared not only with standard cultivar, but also with ten spring barley cultivars widespread in agricultural production of Ukraine. Thus, for three years of competitive testing, we received experimental genotype-environmental data from seven environments, which represent a combination of contrasting agroclimatic zones (Central part of the Forest-Steppe, Polissia and Northern Steppe of Ukraine) and different years (2016–2018). Our results revealed significant variability of mean yield of genotypes, as well as cross-over genotype by environment interaction. The first two principal components of both AMMI and GGE biplot explained more than 80% of the genotype by environment interaction. In general, the peculiarities we revealed indicate the effectiveness of the proposed combination of spatial (agroclimatic zones) and temporal (years) gradients to identify the best spring barley genotypes with the optimal combination of yield performance and ecological stability. Using AMMI and GGE biplot models was effective for the comprehensive differentiation of genotypes in terms of wide and specific adaptability, as well as for qualitative characterization of test environments and providing mega-environment analysis. As a practical result of the multi-environment trial, four spring barley breeding lines have been submitted to the State Variety Testing of Ukraine as new cultivars MIP Sharm, MIP Tytul, MIP Deviz and MIP Zakhysnyk, respectively.

scholarly journals Genotype by Environment Interaction Effect on Grain Iron and Zinc Concentration of Indian and Mediterranean Lentil Genotypes

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1761
Author(s):  
Soma Gupta ◽  
Shouvik Das ◽  
Harsh Kumar Dikshit ◽  
Gyan Prakash Mishra ◽  
Muraleedhar S. Aski ◽  
...  
Keyword(s):  
Zinc Concentration ◽  
Selection Index ◽  
Stability Index ◽  
Genotype By Environment Interaction ◽  
Pooled Analysis ◽  
Environment Interaction ◽  
Breeding Lines ◽  
Genotype By Environment ◽  
Iron And Zinc ◽  
The Stability

Lentil grains with high nutritional value qualify as a promising candidate for alleviation of micronutrient malnutrition in South Asia and North Africa. Genetic variation for micronutrient concentration in germplasm is prerequisite for biofortification of this crop. In the present study, ninety-six lentil genotypes consisting of Indian (released varieties, advanced breeding lines and germplasm lines) and Mediterranean (germplasm lines and landraces) line were evaluated for grain iron (Fe) and zinc (Zn) concentrations and the stability of these traits was studied across three different locations in India. The pooled analysis of variance revealed significant genotype, environment and genotype by environment interaction (GEI) mean squares for both the micronutrients. Stability analysis employing the AMMI model elucidated the first two interaction principal components as significant and cumulatively explained 100% of GEI variation. The first two components explained 55.9% and 44.1% of the GEI sum of squares for grain iron and 50.8% and 49.2% for grain zinc concentration, respectively. No correlation between grain iron and zinc concentration was observed. Among 96 lines, genotypes IG 49, P 16214, ILL 147 and P 2118 were found to be relatively stable, having higher mean iron and zinc concentrations with low modified AMMI stability value (MASV), modified AMMI stability index (MASI) and genotype selection index (GSI). The identified promising genotypes (high Fe: P16214, IG 115, P 2127 and IC 560812 and high Zn: P 8115, P3234, LL 461 and IC 560812) can be utilized for studying the genetics of grain Fe and Zn concentration by developing mapping populations and for biofortification of Indian lentil.

scholarly journals Genotype by environment interaction for seed yield per plant in rapeseed using AMMI model

2011 ◽  
Vol 46 (2) ◽  
pp. 174-181 ◽  
Author(s):  
Ana Marjanović-Jeromela ◽  
Nevena Nagl ◽  
Jelica Gvozdanović-Varga ◽  
Nikola Hristov ◽  
Ankica Kondić-Špika ◽  
...  
Keyword(s):  
Seed Yield ◽  
Block Design ◽  
Total Yield ◽  
Interaction Model ◽  
Field Trials ◽  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
High Yield ◽  
Environment Interaction ◽  
Genotype By Environment

The objective of this study was to assess genotype by environment interaction for seed yield per plant in rapeseed cultivars grown in Northern Serbia by the AMMI (additive main effects and multiplicative interaction) model. The study comprised 19 rapeseed genotypes, analyzed in seven years through field trials arranged in a randomized complete block design, with three replicates. Seed yield per plant of the tested cultivars varied from 1.82 to 19.47 g throughout the seven seasons, with an average of 7.41 g. In the variance analysis, 72.49% of the total yield variation was explained by environment, 7.71% by differences between genotypes, and 19.09% by genotype by environment interaction. On the biplot, cultivars with high yield genetic potential had positive correlation with the seasons with optimal growing conditions, while the cultivars with lower yield potential were correlated to the years with unfavorable conditions. Seed yield per plant is highly influenced by environmental factors, which indicates the adaptability of specific genotypes to specific seasons.

Pattern analysis of genotype-by-environment interaction for grain yield in durum wheat

2009 ◽  
Vol 147 (5) ◽  
pp. 537-545 ◽  
Author(s):  
R. MOHAMMADI ◽  
A. AMRI ◽  
R. HAGHPARAST ◽  
D. SADEGHZADEH ◽  
M. ARMION ◽  
...  
Keyword(s):  
Grain Yield ◽  
Durum Wheat ◽  
Pattern Analysis ◽  
Genotype By Environment Interaction ◽  
Interaction Matrix ◽  
Environment Interaction ◽  
Yield Data ◽  
Breeding Lines ◽  
Cold Environments ◽  
Genotype By Environment

SUMMARYPattern analysis, cluster and ordination techniques, was applied to grain yield data of 20 durum wheat genotypes grown in 19 diversified environments during 2005–07 to identify patterns of genotype (G), environment (E) and genotype-by-environment (G×E) interaction in durum multi-environment trials (METs). Main effects due to E, G and G×E interaction were highly significant, and 0·85 of the total sum of squares (SS) was accounted for by E. Of the remaining SS, the G×E interaction was almost 12 times the contribution of G alone. The knowledge of environmental and genotype classification helped to reveal several patterns of G×E interaction. This was verified by ordination analysis of the G×E interaction matrix. Grouping of environments, based on genotype performance, resulted in the separation of different types of environments. Pattern analysis confirmed the cold and warm mega-environments, and allowed the discrimination and characterization of adaptation of genotypes. However, several patterns of G×E interaction in Iran's regional durum yield trials were further discerned within these mega-environments. The warm environments tended to be closer to one another, suggesting that they discriminate among durum genotypes similarly, whereas cold environments tended to diverge more. The dwarf and early maturing breeding lines from ICARDA with low to medium yields and high contribution to G×E interaction were highly adapted to warm environments, whereas the tall and later maturing genotypes with low to high yields were highly adapted to the cold environments of Iran.

scholarly journals Soil moisture induced genotype-by-environment interaction for root volume of upland rice

2018 ◽  
Vol 63 (2) ◽  
pp. 139-152
Author(s):  
Adesola Nassir ◽  
Kayode Adewusi ◽  
Solomon Olagunju
Keyword(s):  
Soil Moisture ◽  
Upland Rice ◽  
Moisture Stress ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Root Volume ◽  
Breeding Lines ◽  
Genotype By Environment ◽  
Screening Condition ◽  
Limited Moisture

Sixteen rice genotypes comprising established cultivars, recent releases and breeding lines were established in the greenhouse under different moisture levels, obtained from a combination of the amount and number of times of moisture application, to study genotype-by-environment interaction (GEI) for root volume (RV), and also probe into the level of moisture imposition, that would be adequate for screening of genotypes for response to soil moisture stress. Across the simulated environments, W880-9-32-1-1-12-HB had the largest root volume of 8.71 cm3, whereas ITA 257 had the lowest (4.89 cm3). Genotype (G) accounted for significant (P < 0.001) 10.6%, environment (E) (P < 0.001) captured 79.0%, and GEI (P < 0.001) 10.4% of the total sum of squares. The GGE biplot captured 82% of the G+GE and clustered the environments into two groups, with OS 6 being the best for RV in the rainfed environment (E10). W880-9-32-1-1- 12-HB recorded the best RV under environments with adequate to limited moisture, but was less stable, and recorded grain production (13.5 g/plant) close to the best mean of 16.0g/plant by ITA 150 and 14.1 g/plant by IRAT 170. Environments were generally positively correlated with vegetative and yield traits, but E2 (100% moisture requirement applied once in two weeks) was more representative of the screening condition while E10 (rainfed) was highly discriminating, and would be appropriate for discarding genotypes with poor RV. Overall, E1, E2, E4 and E7 were identified as moisture conditions that are appropriate for selection of genotypes for general adaptation for RV within the overall goal of developing drought tolerant rice.

scholarly journals Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency

2018 ◽  
Vol 15 (4) ◽  
pp. e0705 ◽  
Author(s):  
Pablo Gonzalez-Barrios ◽  
Marina Castro ◽  
Osvaldo Pérez ◽  
Diego Vilaró ◽  
Lucía Gutiérrez
Keyword(s):  
Experimental Design ◽  
Positive Impact ◽  
Management Strategies ◽  
Grain Filling ◽  
Genotype By Environment Interaction ◽  
Yield Potential ◽  
Environment Interaction ◽  
Network Efficiency ◽  
Genotype By Environment ◽  
And Performance

Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage.  An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars.

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