여름딸기 품종의 잡종교배 1세대에서
Characteristics of Quantitative Traits in the F1 Generation of Ever-bearing Strawberry
- 주제(키워드) ever-bearing strawberry , morphological , quantitative trait , principal component analysis , K-means clustering
- 발행기관 강릉원주대학교 일반대학원
- 지도교수 용영록
- 발행년도 2015
- 학위수여년월 2015. 2
- 학위명 석사
- 학과 및 전공 일반대학원 원예학과
- 원문페이지 vi, 58
- 실제URI http://www.dcollection.net/handler/kangnung/000000006998
- 본문언어 한국어
초록/요약
Domestic ever-bearing strawberry is one of the major subjects for export with cultivation area of 22 ha and export volume of 200 ton in 2013. Strawberry has been under variety protection because it was registered under the International Union of Protection of New Varieties of Plant (UPOV) in 2002. Royalty issues have been raised regarding foreign varieties. For this reason, high quality and new ever-bearing strawberry variety needs to be developed in Korea where cultivation rate of foreign varieties is high. Therefore, this study is to provide fundamental data for breading by developing high quality strawberry genetic resources and improving utility of collected genetic resources through analyzing correlation between superior crossing breeds. Superior cross breeds are selected among the single breeds extracted by using ‘Charlotte’ variety which has the highest cultivation rate among ever-bearing strawberries in Korea as a pollen recipient and ‘Flamenco’ variety as a pollen donor. Artificial crossing was performed by using ‘Charlotte’ and ‘Flamenco’ varieties and 300 seeds were collected. 158 seedlings were transplanted and 20 seedlings were selected to analyze morphological quantitative traits by following UPOV TG (Test Guideline) (UPOV, 2008). All values were standardized and positive process was addressed by reducing and compressing variables. Also principal component analysis (PCA) was performed to find out correlation. K-means clustering analysis was conducted to analyze the clustering of breeds and characteristics of main components were investigated by using analysis of variance (ANOVA) for each clustering. Scheffe Post-Hoc test was performed when positive difference was shown. According to main component analysis, correlation coefficient in PC1 was high with fruit component which is related to fruit sugar contents while PC2 was highly related to growth traits of strawberry and PC3 was related to size and shape of fruit. Evaluated main component grades were arranged on the axis of 1-2 and 2-3 main components to show classification relations. GWEBS-61, GWEBS-66, GWEBS-130 and GWEBS-12 were high in fruit traits while GWEBS-116 and GWEBS-69 were high in growth traits and GWEBS-8, GWEBS-12, GWEBS-61, GWEBS-127, GWEBS-128 and GWEBS-130 were high in terms of size. Clustering was arranged with K-means clustering method by using factor grades of PC1, PC2 and PC3 of main components along with 20 breeds and 2 ever-bearing strawberry varieties. As a result, first clustering had a significantly higher value than others regarding PC2, second clustering had a high value regarding PC3 and third clustering had a high value regarding PC1. Based on result above, this study suggested fundamental data as new variety with developing high quality horticultural traits.
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ABSTRACT i
TABLE OF CONTENTS iii
LIST OF TABLES v
LIST OF FIGURES vi
Ⅰ. 서 언 1
Ⅱ. 재료 및 방법 5
1. 실험 장소 5
2. 육종소재 및 계통선발 6
3. 양적형질 분석 7
4. 통계분석 8
4.1. 주성분 분석 (principal component analysis, PCA) 8
4.2. 요인점수를 이용한 상관도표 분석(Scatter diagram) 8
4.3. K-평균 군집분석(K-means clustering) 8
4.4. 분산분석(ANOVA) 8
Ⅲ. 결과 및 고찰 10
1. 양적형질 분석 10
1.1. 계통들의 식물체 특성 10
1.2. 계통들의 엽 특성 12
1.3. 계통들의 화방특성 16
1.4. 계통들의 과실특성 26
2.1. 주성분 분석(principal component analysis, PCA) 39
2.2. 요인점수를 이용한 상관도표 분석(Scatter diagram) 42
3.1. K-평균 군집분석(K-means Clustering) 46
3.2. 분산분석(ANOVA) 46
Ⅳ. 적요 51
Ⅴ. 참 고 문 헌 58
감사의 글 60
