The potato tuber is known as a rich source of essential nutrients, used throughout the world. Although potatobreeding programs share some priorities, the major objective is to increase the genetic potential for yield through breeding or to eliminate hazards that reduce yield. Glycoalkaloids, which are considered a serious hazard to human health, accumulate naturally in potatoes during growth, harvesting, transportation, and storage. Here, we used the AMMI (additive main effects and multiplicative interaction) and GGE (Genotype main effect and genotype by environment interaction) biplot model, to evaluate tuber yield stability and glycoalkaloid content in six potato cultivars across three locations during 2012/2013. The environment on tuber yield had the greatest effect and accounted for 33.0% of the total sum squares; genotypes accounted for 3.8% and G×E interaction accounted for 11.1% which is the nest highest contribution. Conversely, the genotype on glycoalkaloid had the greatest effect and accounted for 82.4% of the total sum squares), whereas environment and G×E effects on this trait accounted for only 0.4% and 3.7%, respectively. Furthermore, potato genotype ‘Superior’, which covers most of the cultivated area, exhibited high yield performance with stability. ‘Goun’, which showed lower glycoalkaloid content, was the most suitable and desirable genotype. Results showed that, while tuber yield was more affected by the environment, glycoalkaloid content was more dependent on genotype. Further, the use of the AMMI and GGE biplot model generated more interactive visuals, facilitated the identification of superior genotypes, and suggested decisions on a variety of recommendations for specific environments.

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 × 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 × 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 × 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.

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 x 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 x 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.

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.

With the aim to analyze stability performance of six promising barley genotypes, eleven yield related characters were evaluated employing varied irrigation treatments under the tropical climate of Northern part in Bangladesh. Analysis of variance(ANOVA), phenotypic index, regression co-efficient(bi) and deviation from regression(s2d ) of the individual genotypes were estimated to evaluate the stable performance of the genotypes. A significant interaction was observed between the genotypes and irrigation period(G~timesT ). Among all the genotypes, BSH-2 showed stable performance for plant height under different irrigation period, where P>~barX,~;bi~1~;and~;s2d~0. High phenotypic index, lower bi value and low deviations from regression were observed in case of spikelet number per spike and grain number per spike for genotype BSH-2 and plant height, spike length and harvest index per plant for BB-2 which suggest that those parameters were not usually affected by irrigation. On the other hand the genotype BSH-2 for tiller number and BB-1 for the fertile tiller number were not suitable for favorable moisture content, where P<~barX,~;bi>1.0~;and~;low~;s2d. Thus we suggest that genotype BSH-2 might have transmit high mean and increased phenotypic stability to the next progenies, which may consider as an ideal genotype for developing improved barely cultivars.

GE interaction is the expression of differential genotypic adaptation across environments. GE interactions through different stability parameters and performance of the traits of genotypes were studied. The traits were days to maturity, pod length, number of pods/ plant, 100-seed weight and seed yield/plant in ten soybean genotypes across five environments. Significant differences were observed for genotypes, environments and GE interactions. Stability analysis after Eberhart and Russell's model suggested that the genotypes used in this study were all more or less responsive to environmental changes. Most of the genotypes perform better in Env.3. Based on phenotypic indices(Pi), regression (S2di) genotype Garurab was found fairly stable for days to maturity. BS-23 and G-2120 may be considered as stable genotype for pod length. All the genotypes except G-2120 showed that the genotypes were relatively unstable under environmental fluctuation for the number of pod/plant. Genotype BS-23 was found most stable among all the genotypes for 100-seed weight. BS-3 and Gaurab was the most stable and desirable genotypes for seed yield in soybean.

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.

Regional Adaptability Test (RAT) was conducted to select promising breeding lines of rice for cultivation in specif ic regions. Analysis of genotype (G) and genotype by environment (G×E) interaction observed in RAT was carried out to test their adaptabili

강원도 지역에 적응성이 있는 품종을 선정하기 위해서 5개 시험지에서 11개 품종으로 1997년부터 2000년 동안에 수행된 결과를 분석하였다. 품종이 가지고 있는 유전적 특성은 환경요인과의 상호작용을 거쳐 발현되므로 장려품종을 선정하기 위하여 수행하는 다지역검정에서 이 유전자-환경간 상호작용을 평가하는 것은 품종의 환경안정성과 지역적응성을 올바르게 파악하는 데 매우 중요하다. 이를 위해서 기존에 활용되어 온 회귀분석모델로서 안정성을 분석하였고 AMMI model로서 지역별 수량성 반응의 변화양상을 토대로 유전자-환경간간의 상호작용을 해석하면서 각 시험지별 적응성 품종과 지역적 특성을 검토하였다. 1. 각 시험지에 대한 수량안정성 평가를 위한 회귀분석 결과 오봉벼, 진미벼, 신운봉벼, 운봉벼 등이 안정성이 있는 품종이었다. 2. AMMI 분석에 의한 수량성에 대한 분산분석 결과 전 변이중 품종변이가 66％, 품종-환경간 상호작용변이가 21％, 지역간 변이가 13％였다. 21％의 품종-환경간 상호작용 변이는 주성분분석을 통하여 제1주성분치(IPCAl)와 제2주성분치 (IPCA2)에 의해서 거의(92％) 해석되었다. 3. 품종들의 지역간 수량성 변화패턴은 육성모지나 시험지 등에 영향을 받았고, 5개 시험지의 수량변화 양상은 철원과 정선, 춘천과 고성이 비슷하였고 강릉은 다르게 구분되었다. 품종-환경간 상호작용 양상이 축약된 주성분분석치와 시험지별 재배기간동안의 순별 평균 기상자료와의 상관분석 결과를 기준으로 품종과 환경간의 상호작용에 관여하는 주요 기상요인은 초상최저온도, 최소상대습도, 일조시수 강수량 등이었다. 4. 비교적 환경안정성이 있는 품종으로는 오대벼, 오봉벼, 진부벼 등이었다. 철원에 적응성이 있는 품종은 진부벼, 신운봉벼, 오대벼, 오봉벼 등에었고, 춘천에는 진미벼 상주벼, 오대벼, 오봉벼가 정선, 강릉, 고성에는 진부찰벼, 삼천벼, 둔내벼 , 운봉벼, 진부올벼가 적응성이 있었다. 0.57, Fe 0.414, p 94.68, fat 3.74, protein 3.08, lactose 4.68,4. In case of processed market cow′s milk ; Ca 134.72, K 142.74, Mg 10.33, Na 45.07, Zn 0.50, Fe 0.650, p 92.48, fat 3.72, protein 3.07, lactose 4.74. According to the group of market milk(milk, fortified market row′s milk, processed market cow′s milk), the mean concentration of Ca and Fe were significantly higher in fortified and processed milk than milk(p<0.05). There were no significant differences in macronutrient(fat, protein, lactose) and mineral contents between pasteurized milk and UHT(ultra high temperature) treated milk(α =0.05). The labeled "Nutritional Facts" of market milk were satisfied with "Labeling Standards for Livestock Products of Korea". The measured mean concentrations of Ca, Fe, Zn were generally higher than lower limit of labeled value(above 80% of labeled value). The mean concentration of sodium was lower than upper limit of labeled value(below 120％