• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.3
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• pp.297-302
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• 2008

Application of genotype by environment ($G\;{\times}\;E$) interaction would be used for identifying optimum test condition of the varietal adaptation in the establishment of breeding purpose. Yield and yield components were used to perform additive main effect and multiplicative interaction (AMMI) analysis. Significant difference for $G\;{\times}\;E$ interaction were observed for all variable examined. For yield, 0.18 of total sum of squares corresponded to $G\;{\times}\;E$ interaction. Correlation analysis was carried out between genotypic scores of the first interaction principal component axis (IPCA 1) for agronomic characters. Significant correlations were observed between IPCA 1 for yield and capsule bearing stem length (CBSL), number of capsule per plant (NOC). The biplot of grain yield means for IPCA1 which accounted for 34% of the variation in total treatment sums of squares showed different reaction according to $G\;{\times}\;E$ interaction, genotypes and environments. Taegu showed relatively lower positive IPCA1 scores, and it also showed smaller coefficient variation of yield mean where it is recommendable as a optimal site for the sesame cultivar adaptation and evaluation trial. In case of variables, Yangbaek and M1 showed relatively lower IPCA1 scores, but the score direction showed opposite each other on the graph. Ansan, Miryang1, Miryang4, and Miryang6 seemed to be similar group in view of yield response against IPCA1 scores. These results will be helpful to select experimental site for sesame in Korea to minimize $G\;{\times}\;E$ interaction for the selection of promising genotype with higher stability.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.48 no.2
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• pp.65-67
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• 2003

This study was conducted to analyze the effects of genotypes, environments and interaction of G$\times$E on yields of sesame grown in seven different environments by AMMI analysis. Environments accounted for the largest (91 %) proportion of the sums of squares, followed by G$\times$E (8%) and genotypes (1%) Therefore, G$\times$E effects are theoretically eight times as important as G effects. G2 (Yanghukkae) has the largest IPCAI scores indicating higher G$\times$E interaction. G3 (Suwon 171) was near zero score of IPCAI suggesting higher stability than others in yield component. Most of environments except for Iksan area shows different G$\times$E effects by years, which means Iksan is optimal area for multi-environmental adaptation evaluation in sesame breeding programs. According to this experiment, it is concluded that maximization of grain yield through environments can be achieved by specific genotypes in specific environments.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.5
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• pp.316-321
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• 2000

Blast severity data of 39 rice varieties at 11 sites in Korea from 1997 to 1999 were analyzed using AMMI model and pattern analysis. Genotype x Environment (G$\times$E) interaction sum of squares (SS) accounted for 12 % of the total SS. Eight genotype groups and seven location groups were identified based on blast reaction pattern. The data obtained from over 21 sites with 44 test varieties from 1981 to 1996 were also considered. These were compared with the 1997-1999 data using the G$\times$E analysis results. Majority of the variability in the Korean Rice Blast Nursery (KRBN) were attributable to variations due to genotypes. Variations of G$\times$E interaction were maintained though test sites were reduced from 21 to 11 sites. Broadly compatible biological discriminative varieties identified were Nagdongbyeo and Akibare while broadly incompatible biological discriminative varieties identified were Hangangchalbyeo and Seogwangbyeo. Key sites for future evaluation work could be selected from location groups. Each location group should be represented by the site with the strongest interaction pattern. Blast responses in Cheolwon, Gyehwa, Suwon, Iksan, and Icheon showed different patterns from other locations.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.3
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• pp.349-354
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• 2015

The AMMI (additive main effects and multiplicative interaction) and GGE (genotype main effect and genotype by environment interaction) biplot which were accounted for a substantial part of total sum of square in the analysis of variance suggested to be more appropriate models for explaining G $\times$ E interaction. The grain yield of total ten sesame genotypes was significantly affected by environment which explained 61% of total variation, whereas genotype and genotype x environment interaction (G $\times$ E) were explained 16%, 24% respectively. From the results of experiment, three genotypes Miryang49, Koppoom and Ansan were unstable, whereas other three genotypes Kyeongbuk18, Miryang50 and Kanghuk which were shorter projections to AEA ordinate were relatively stable over the environments. Yangbak which was closeness to the mean yield and short projection of the genotype marker lines was regarded as genotype indicating good performance with stability. Ansan, Miryang48 and Yangbaek showed the best performance in the environments of Naju, Suwon, Iksan and Andong. Similarly, genotype Miyrang47 exhibited the best performance in the environments of Chuncheon and Miryang. Andong is the closest to the ideal environment, and therefore, is the most desirable among eight environments.

• Asian-Australasian Journal of Animal Sciences
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• v.5 no.3
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• pp.401-409
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• 1992

Genotype $\times$ environment (G $\times$ E) interactions must be understood if they are to be exploited to improve animal production, particularly in production systems associated with large environmental variations. The measurement and evaluation of G $\times$ E are discussed. Examples are presented that demonstrate G $\times$ E in different breeds of beef cattle for high temperatures, internal and external parasites and changes in quantity and quality of nutrition. It is demonstrated that productivity differences between genotypes or breeds under grazing conditions arise because of differences between genotypes in the combination of production potential and resistance to environmental stresses in relation to the levels of the relevant environmental stresses that are operating at the time. The $F_1$ cross between genotypes with high production potential (e.g. European Bos Taurus breeds) and those with high resistance to environmental stress (e.g. Asian and African Bos indicus and sanga breeds) is an exceptional genotype with a unique combination of these two sets of attributes. The principles for G $\times$ E developed for beef cattle are briefly discussed in relation to dairy cattle, pigs, poultry and buffalo.

• Magazine of the Korean Society of Agricultural Engineers
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• v.15 no.4
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• pp.3147-3152
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• 1973

The factors to influence the travelling distance of sprayed particles for the medium range nozzle may by the groove depth of swirl plate, the cap slope, the diameter of cap hole, and pressure. 1. This study was conducted to examine Interaction effects among four factors to the travelling distance. The results of this study are summarized as followa; a) Interaction effects among four factors the groove depth(G), cap slope(C), diameter of cap hole(D), and pressure (P), were significant to influence the travelling distance except for $G{\times}P,\;C{\times}D{\times}P\;and\;G{\times}C{\times}D{\times}P$. b) Interaction effects with the pressure were very smaller than interaction effects among the other factors. c) Effect of change of the groove depth of swirl plate on the travelling distance of sprayed particles was generally a linear, the increasing rate of the change was about 0.345, which was very significant. d) Effect of change of cap slope on the travelling distance was generally a linear or a dull quadratic, the increasing rate was very small. e) Main effect of change of cap slope in the medium range nozzle was very smaller than that of the close range nozzle on the travelling distance, which was estimated by the changing of turning radius of flowing course in nozzle. f) Interaction effect between two factors in the medium range nozzle was more significant than that of the close range nozzle on the travelling distance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.62 no.4
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• pp.317-324
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• 2017

The purpose of this study was to provide basic data on the genetic and environmental effects of stickiness in glutinous rice varieties. In our study, we analyzed the genotype-by-environment ($G{\times}E$) interactions of the stickiness using six glutinous rice varieties under six environmental conditions. AMMI (Additive Main Effects and Multiplicative Interaction) analysis results showed that genotype (variety, G), environment (cultivation region, E) and $G{\times}E$ interaction were highly significant (P < 0.001). Among all the variations of stickiness for glutinous rice varieties, the environmental effect was 24.5%, the genetic effect was 37.1%, and the $G{\times}E$ interaction effect was 28.9%. From the AMMI analysis, the IPCA1 scores of Aranghangchal (G6, IPCA1: 3.85) and Hwaseonchal (G4, IPCA1: -5.24) was lower than other varieties. On the other hand, the Sangjuchal (G1, IPCA1: -61.23) and Boseogchal (G2, IPCA1: 41.21) were highly affected by environmental effects. In this study, there were large differences in stickiness according to region of cultivation. In the future, it is considered that a precise study should be carried out on the environmental factors that may increase the stickiness of glutinous rice varieties.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.6
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• pp.453-458
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• 2001

The Rural Development Administration (RDA) of Korea now operates a system called Rice Variety Selection Tests (RVST), which are now being implemented in eight Agricultural Research and Extension Services located in eight province RVST's objective is to provide accurate yield estimates and to select well-adapted varieties to each province. Systematic evaluation of entries included in RVST is a highly important task to select the best-adapted varieties to specific location and to observe the performance of entries across a wide range of test sites within a region. The rice yield data in RVST for ordinary transplanting in Kangwon province during 1997-2000 were analyzed. The experiments were carried out in three replications of a random complete block design with eleven entries across five locations. Additive Main effects and Multiplicative Interaction (AMMI) model was employed to examine the interaction between genotype and environment (G$\times$E) in the biplot form. It was found that genotype variability was as high as 66％, followed by G$\times$E interaction variability, 21％, and variability by environment, 13％. G$\times$E interaction was partitioned into two significant (P＜0.05) principal components. Pattern analysis was used for interpretation on G$\times$E interaction and adaptibility. Major determinants among the meteorological factors on G$\times$E matrix were canopy minimum temperature, minimum relative humidity, sunshine hours, precipitation and mean cloud amount. Odaebyeo, Obongbyeo and Jinbubyeo were relatively stable varieties in all the regions. Furthermore, the most adapted varieties in each region, in terms of productivity, were evaluated.

• The Plant Pathology Journal
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• v.30 no.3
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• pp.261-268
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• 2014

This work was conducted to identify mungbean genotypes showing yield stability and resistance to mungbean yellow mosaic virus (MYMV) disease. Sixteen genotypes were evaluated in a randomized complete block design with two replications for two years (2011 and 2012) at three locations (Gazipur, Ishurdi and Madaripur) of the Bangladesh Agricultural Research Institute. An analysis of variance exhibited significant effects of genotype (G), environment (E), and genotype ${\times}$ environment ($G{\times}E$) on grain yield. Among eight agronomic characters, the principal component 1 (PC1) was always higher than the PC2. Considering $G{\times}E$ interaction, BM6 was the best genotype at all three locations in both years. Based on grain yield and stability performance, BM6 ranked first while the worst performing genotypes were BM1 and G10. Based on discrimination and representation, Gazipur was identified as an ideal environment for these mungbeans. Relationship between soil-plant analysis developments (SPAD) value was positive with yield but negative with MYMV severity. BM6, G1 and G2 were considered as promising sources of resistance for low disease score and stable response across the environments. The environment proved to have an influence on MYMV infection under natural infestation. A positive correlation was observed between disease score and the temperature under natural growing condition.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.45 no.1
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• pp.38-43
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• 2000

The environment in which a given genotype is grown may influence its grain quality characteristics. When varieties are $\times$ evaluated over numerous environments, a variety environment interaction usually is observed, but the relative magnitude of environmental(E), genetic(G), and G $\times$ E effects on quality is unclear. In order to determine relative contribution of genotype, environment, and G $\times$ E interaction to the variations observed in grain quality characteristics, 18 Korean wheat cultivars and experimental lines were evaluated in two environments in 1998 and 1999. Correlation coefficients between grain quality and agronomic characteristics were also estimated. The analysis of variance for the optical density obtained by reaction bet- ween gliadin and anti-gliadin polyclonal antibody (AGPab) indicated that gliadin content measured by Enzyme-Linked Immunosorbent Assay(ELISA) was significantly in- fluenced by environment and cultivar differences. The significant differences of year and year $\times$ location were also found. The ratio of the variances associated with environmental effects to the variances associated with genetic effect gave relatively greater influence of environmental factor on gliadin content. The different protein content from same genotype grown in different environment might be associated with degree of storage protein accumulations. Significant relationships between ELISA and protein content, yield, ten spike weight, and ten spike number were detected. Polyphenol oxidase (PPO) activity was significantly influenced by year, location, cultivar and year $\times$ location. The variance in grain PPO activities among growing years appeared larger than the variation produced by the cultivar examined. This suggested that the growing environment contributed more to variability in grain PPO concentration.