한국작물학회지 제 62권 4호 (p.333-345)

유전형과 재배환경의 상호작용에 따른 감자 수량성과 글리코알카로이드 함량 변화

Genotype x Environment Interaction and Stability Analysis for Potato Performance and Glycoalkaloid Content in Korea
키워드 :
AMMI,GGE,glycoalkaloid,interaction,potato,yield

목차

재료 및 방법
  실험재료 및 환경조건
  PGA 함량 분석
  AMMI와 GGE biplot을 이용한 통계분석
결과 및 고찰
  감자 품종의 환경에 따른 수량성
  괴경 수량성에 대한 유전형(G)과 환경(E)의 상호작용
  감자 품종의 환경에 따른 PGA 함량 변이
  PGA 함량에 대한 유전형(G)과 환경(E)의 상호작용
  괴경 수량성의 AMMI와 GGE 모델을 이용한 G×E 상호작용 biplot 분석
  PGA 함량의 AMMI와 GGE 모델을 이용한 G×E 상호작용biplot 분석
적 요
사 사
인용문헌(REFERENCES)

초록

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.