Morphological characteristics, chemical and genetic diversity of kenaf (Hibiscus cannabinus L.) genotypes

• 발행기관: (사)한국식물생명공학회
• 저자명: Jaihyunk Ry Soon-Jae Kwon Dong-Gun Kim Min-Kyu Lee Jung Min Kim Yeong Deuk Jo Sang Hoon Kim Sang Woo
• 간행물 정보: 『Journal of Plant Biotechnology』44권 4호, 416~430쪽, 전체 15쪽
• 주제분류: 농수해양 > 기타농수해양
• 파일형태: PDF
• 발행일자: 2017.12.31

영문 초록

The kenaf plant is used widely as food and in traditional folk medicine. This study evaluated the morphological characteristics, functional compounds, and genetic diversity of 32 kenaf cultivars from a worldwide collection. We found significant differences in the functional compounds of leaves from all cultivars, including differences in levels of chlorogenic acid isomer (CAI), chlorogenic acid (CA), kaempferol glucosyl rhamnoside isomer (KGRI), kaempferol rhamnosyl xyloside (KRX), kaemperitrin (KAPT) and total phenols (TPC). The highest TPC, KAPT, CA, and KRX contents were observed in the C22 cultivars. A significant correlation was observed between flowering time and DM yield, seed yield, and four phenolic compounds (KGRI, KRX, CAI, and TPC) (P < 0.01). To assess genetic diversity, we used 80 simple sequence repeats (SSR) primer sets and identified 225 polymorphic loci in the kenaf cultivars. The polymorphism information content and genetic diversity values ranged from 0.11 to 0.79 and 12 to 0.83, with average values of 0.39 and 0.43, respectively. The cluster analysis of the SSR markers showed that the kenaf genotypes could be clearly divided into three clusters based on flowering time. Correlations analysis was conducted for the 80 SSR markers; morphological, chemical and growth traits were found for 15 marker traits (corolla, vein, petal, leaf, stem color, leaf shape, and KGRI content) with significant marker-trait correlations. These results could be used for the selection of kenaf cultivars with improved yield and functional compounds.

목차

Introduction

Materials and Methods

Results

키워드

Kenaf Morphological chracteristics Phenolic compounds SSR markers Correlation analysis