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Morphological characteristics, chemical and genetic diversity of kenaf (Hibiscus cannabinus L.) genotypes
J Plant Biotechnol 2017;44:416-430
Published online December 31, 2017
© 2017 The Korean Society for Plant Biotechnology.

Jaihyunk Ryu, Soon-Jae Kwon*, Dong-Gun Kim, Min-Kyu Lee, Jung Min Kim, Yeong Deuk Jo, Sang Hoon Kim, Sang Wook Jeong, Kyung-Yun Kang, Se Won Kim, Jin-Baek Kim, and Si-Yong Kang*

Advanced Radiation Technology Institute, Korea Atomic Energy Research Institute, Jeongup, Jeonbuk 56212, Korea,
Jangheung Research Institute for Mushroom Industry, Jangheung 59338, Korea,
Suncheon Research Center for Natural Medicines, Suncheon, Republic of Korea
Correspondence to: E-mail: soonjaekwon@kaeri.re.kr, sykang@kaeri.re.kr
Received October 16, 2017; Revised November 9, 2017; Accepted November 9, 2017.
cc This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

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.

Keywords : Kenaf, Morphological chracteristics, Phenolic compounds, SSR markers, Correlation analysis
Introduction

Kenaf (Hibiscus cannabinus L.), an annual herbaceous crop of the family Malvaceae (2n = 36), is a short-day annual herbaceous plant that tolerates a broad range of soil types and climates (Dempsey 1975). Kenaf has traditionally been used to make rope but the plant is used in many different ways, including as pulp, potting media, a bioplastic, and cellulosic biofuel (Alexopoulou et al. 2013). Recently, kenaf being used valuable dual-purpose crop for fiber and medicinal. Its leaves contain large amounts of a variety of compounds including polyphenols (Jin et al. 2013; Ryu et al. 2017a). The most common phenolic compounds in kenaf are the kaempferol glycoside, caffeic acid, myricetin glycoside, and p-hydroxybenzoic acid (Ryu et al. 2017a). In ayurvedic medicine, the kenaf are used for bilious, blood, diabetes, biliousness, coughs and throat disorders (Alexopoulou et al. 2013; Ryu et al. 2017a).

Kenaf has erect, tall plants with few or no branches that may reach 3~5 m in height depending on climatic conditions (Alexopoulou et al. 2013; Ryu et al. 2013). Its leaves may be non-lobed (entire), shallow-lobed, or deeply lobed (palmate). Kenaf flowers, are bell-shaped, open with five petals, and have colors ranging from light cream to dark purple (Alexopoulou et al. 2013). Korean Kenaf cultivars are divided into three maturation groups depending on flowering date; early- maturing, mid-late maturing, and late maturing. Early-maturing groups mature in 70~80 days after seeding and it allow seed harvests, but the lower biomass. Late-maturing groups grow vegetatively for 130~140 days and yield significantly higher biomass. However, late maturation reduces seed quality (Ryu et al. 2016a; Jeong et al. 2017). Breeding selection of new kenaf cultivars is the most effective measure to increase biomass and seed yields per unit area (Alexopoulou et al. 2013). Mutation breeding has the merits of creating new mutant characteristics and adding only very few traits without disturbing the other characteristics of a cultivar (Kang et al. 2016; Ryu et al., 2017b). Mutagenic agents, such as radiation, can be used to induce mutations and generate genetic variants from which desired mutants may be selected (Visser et al. 1971). This process offers the possibility of inducing desirable attributes that either have not developed in nature or have been lost during evolution. In crops, mutagenesis has already been used to introduce many useful traits affecting plant size, blooming time or color, and resistance to pathogens (IAEA 2016; Kang et al. 2016; Ryu et al. 2016b; Ryu et al. 2017b).

To cultivate kenaf in a tropical environment, it is necessary to evaluate the available genotypes in terms of their morphological characters (Faruq et al. 2013). Moreover, the identification of genetic relationships and diversity is one of the most important factors in the selection of cultivars for a breeding program (Jeong et al. 2017; Thakur et al. 2017). Simple sequence repeats (SSRs) are one of the most commonly used types of DNA molecular markers for revealing genetic diversity among genotypes (Varshney et al. 2005). Knowledge of level of genetic diversity, morphological and chemical relationships among genotypes essential for establishing, managing, and ensuring the long-term success of crop-improvement programs (Varshney et al. 2005; Jeong et al. 2017; Thakur et al. 2017). In this study, we compared morphological, phytochemical, and genetic characteristics among kenaf cultivars from eight countries (Bangladesh, China, India, Iran, Italy, Korea, USA, and Russia). We examined morphological and chemical characteristics to establish relationships, and compared these relationships to genetic relationships. In addition, we used SSR markers to evaluate genetic diversity, and demonstrated significant associations between the SSR markers and morphological and phytochemical characteristics.

Materials and Methods

Plant materials

Thirty-two cultivars were studied. These included six mutant genotypes (Jangdae, Jeokbong, RS1, RS2, WFM1-2 and Baekma), two original cultivars (Jinju and C14), and 24 accessions collected worldwide from the Genebank of Rural Development Administration (RDA) in Korea and the Bangladesh Jute Mills Corporation (BJC). The Jangdae cultivar combines high biomass and seed yield and has been tested by the Korea Seed and Verity Service (KSVS). Five of the morphological mutants exhibiting changes in flower color (Baekma, WFM1-2) and stem color (Jeokbong, RS1, RS2) were derived from the same kenaf cultivar (C14) introduced from Italy. The whole plant and leaves of the genotypes were harvested at the flowering time of each genotype for dry matter (DM) yield and phenolic compounds analysis. Seeds were planted in plots (3 × 4.2 m) with row spacings of 20 and 60 cm, respectively. Fertilizer (N:P:K 4:2:2 w/w/w) was applied at 550 kg/ha shortly after seeding. Manure was spread before planting, but the plants were not fertilized after planting. The experiment was conducted at the Korea Atomic Energy Research Institute.

Morphological and agronomic characteristics

All genotypes were planted on mid-May and measured for morphological and agronomic characteristics during 2012 to 2015. The cultivars were divided into three different flowering groups, early flowering (70~84 day after seeding), mid-late flowering (101~134 day after seeding), and non-flowering. We measured the morphological traits of each sampled individual: leaf shape (palmate 1, entire 2), leaf color (green 1, purple 2), branch color (green 1, brown 2, purple 3), vein color (green 1, purple 2), hypocotyl colors (green 1, purple 2), stem colors (brown 1, green 2, purple 3) corolla color (green 1, purple 2, non 3), and petal colors (Ivory 1, white 2, non 3).

UPLC analysis

Phenolic compounds were analyzed using a ultra-high performance liquid chromatography (UPLC) system (CBM-20A, Shimadzu Co., Kyoto, Japan) with two gradient pump systems (LC-30AD, Shimadzu), a UV-detector (SPD-M30A, Shimadzu), an auto sample injector (SIL-30AC, Shimadzu), and a column oven (CTO-30A, Shimadzu). Separation was achieved on an XR-ODS column (3.0 × 100 mm, 1.8 µm, Shimadzu, Japan) using a linear gradient elution program with a mobile phase containing solvent A (0.1%, v/v, trifluoroacetic acid in distilled deionized water) and solvent B (0.1%, v/v, trifluoroacetic acid in acetonitrile). Samples for UPLC analysis of phenolic compound contents were ground using a grinder immediately prior to analysis. All samples were ground to achieve a particle size that would pass through a 500 mL sieve. For UPLC analysis, ground samples (1 g) were extracted in 5 mL water for 16 h and filtrated through a 0.45 µm membrane filter. The phenolic compounds were separated using the following gradient: 0~5 min, 10~15% B; 5~10 min, 15~20% B; 10~15 min, 20~30% B; 15~20 min, 30~50% B; 20~25 min, 50~75% B; 25~30 min, 75~100% B; 30~32 min, 100~5% B; 32~35 min, 5~0% B. The phenolic compounds were detected at 280 nm. Identification of kaempferitrin (KAPT) was determined based on the retention times of commercial standards (UV spectrum) and the Chlorogenic acid isomer (CAI), Chlorogenic acid (CA), Kaempferol glucosyl rhamnoside isomer (KGRI), Kaempferol rhamnosyl xyloside (KRX) were identified using retention time, UV-visible spectral characteristics.

DNA extraction and simple sequence repeat analysis

DNA was extracted from young leaves of each cultivar using the cetyltrimethylammonium bromide (CTAB) method. A total of 70 EST-SSR primers set were synthesized based on published sequence information (Jeong et al. 2017) and 10 genomic SSR primer sets were obtained from the US National Center for Biotechnology Information (NCBI, http://www.ncbi.nlm.nih.gov/) Hibiscus cannabinus database. SSR sequence PCR reactions were carried out in 25 µL of a mixture containing 20 ng genomic DNA, 10 pmol primer, 1 unit Taq polymerase, 10× PCR reaction buffer, and 0.2 mM dNTP. The PCR cycling conditions were as follows: 94°C for 5 min (initial denaturation), followed by 40 cycles at 94°C for 45 s (predenaturation), 55°C for 45 s (annealing), 72°C for 90 s (extension), with a final 7 min extension at 72°C and cooling to 4°C. The samples were fractionated using a LabChip GX electrophoresis system (Caliper Life Science, USA).

Statistical analysis

The chemical analysis data were subjected to analysis of variance using a multiple comparisons method with the statistical software package SPSS version 12 (SPSS Institute, USA). Differences were determined to be significant at p < 0.05. When the treatment effect was significant, means were separated using Duncan’s multiple range tests. The correlation coefficients between the morphological and agronomics characteristics and the phenolic compound contents were obtained using Pearson’s correlation coefficients (P < 0.01) to examine the degree among kenaf genotypes.

All of the SSR bands were scored as 0 or 1 for the absence or presence of the band, respectively. The polymorphism information content (PIC), mean gene diversity (GD), and Shannon’s information index (SI) for each SSR marker were calculated using Power Marker Ver. 3.25.

The morphological, chemical and genetic dendrogram were constructed using the phylogenetic tree using the Neighbor Joining method (Saitou and Nei 1987) with the statistical software package Power Marker Ver. 3.25.

We determined correlation between morphological characteristics, phenolic compound contents and SSR markers using TASSEL 3.0.1 software (Bradbury et al. 2007). We performed three tests for significance. First, the Q general linear model (GLM) was used on the chosen Q-matrix derived from STRUCTURE with 10,000 permutations to test marker significance and determine the experiment-wise P value for each marker’s significance. Second, the Q-mixed linear model (Q-MLM) method was used to determine a kinship matrix. SPAGeDi was used to calculate kinship (K) coefficients.

Results

Morphological and agronomic characteristics

Selected results of the evaluation of morphological characteristics are presented in Table 1 and Figure 1. The leaf shapes of the kenaf cultivars were divided into two types: 11 cultivars with entire and 21 cultivars with palmate leaves. All kenaf cultivars had green leaves, except for the Jeokbong cultivar, which had greenish purple leaves. The colors of branches and stems were green, brown, or purple. Veins, hypocotyls, and corollas were green or purple. Finally, flower petals were ivory (18 genotypes) or white (2 genotypes), while 12 genotypes were non-flowering.

The origin and morphological characteristics of kenaf genotypes used in this study

No. NameOriginSourceFloweringLeafLeafBranchVeinHypocotylStemCorollaPetal
(cultivar or accession number)dateshapecolorcolorcolorcolorcolorcolorcolor
1C9RussiaIT202789zEarlyPalmateGreenGreenGreenPurpleBrownGreenIvory
2C10IndiaIT202790EarlyPalmateGreenGreenGreenGreenBrownGreenIvory
3C11IranIT202791EarlyEntireGreenBrownGreenPurpleBrownGreenIvory
4C12ItalyIT202792EarlyPalmateGreenBrownGreenPurpleBrownGreenIvory
5C13RussiaIT202793EarlyPalmateGreenBrownGreenPurpleBrownGreenIvory
6C14ItalyIT202794EarlyPalmateGreenBrownGreenPurpleBrownGreenIvory
7C15AfricaIT202795EarlyPalmateGreenGreenGreenPurpleBrownGreenIvory
8C16ChinaIT202796EarlyPalmateGreenGreenGreenGreenBrownGreenIvory
9C17ChinaIT202797EarlyPalmateGreenGreenGreenPurpleBrownGreenIvory
10C18ChinaIT202798EarlyPalmateGreenBrownGreenGreenBrownGreenIvory
11C19IndiaII202799EarlyPalmateGreenBrownGreenPurpleBrownGreenIvory
12C20IndiaIT202800EarlyPalmateGreenBrownGreenGreenBrownGreenIvory
13C22RussiaIT202802EarlyPalmateGreenBrownGreenPurpleBrownGreenIvory
14RS1C14Mutant lineEarlyEntireGreenPurplePurplePurplePuplePurpleIvory
15RS2C14Mutant lineEarlyPalmateGreenPurplePurplePurplePuplePurpleIvory
16JeokbongC14CultivarEarlyEntirePurplePurplePurplePurplePuplePurpleIvory
17BaekmaC14CultivarEarlyEntireGreenGreenGreenGreenGreenGreenWhite
18WFM1-2C14Mutant lineEarlyEntireGreenBrownGreenPurpleBrownGreenWhite
19JangdaeJinjuCultivarMid-latePalmateGreenGreenGreenGreenGreenGreenIvory
20JinjuUnknownAccessionMid-lateEntireGreenGreenGreenGreenGreenGreenIvory
21Hongma300ChinaCultivarLatePalmateGreenBrownGreenGreenBrown-xIvory
22Hongma74-3ChinaCultivarLatePalmateGreenGreenGreenPurpleGreen-Ivory
23Everglades41USACultivarLatePalmateGreenBrownGreenPurpleBrown-Ivory
24ACC3748UnknownBJCyLateEntireGreenBrownGreenGreenBrown-Ivory
25ACC4111UnknownBJCLateEntireGreenBrownGreenGreenBrown-Ivory
26ACC4153UnknownBJCLateEntireGreenBrownGreenGreenBrown-Ivory
27ACC4139UnknownBJCLatePalmateGreenBrownGreenGreenBrown-Ivory
28ACC4443UnknownBJCLatePalmateGreenPurplePurplePurplePurple-Ivory
29ACC4751UnknownBJCLateEntireGreenBrownGreenGreenBrown-Ivory
30ACC4985UnknownBJCLatePalmateGreenGreenGreenGreenGreen-Ivory
31ACC5014UnknownBJCLatePalmateGreenGreenGreenPurpleGreen-Ivory
32ACC5072UnknownBJCLateEntireGreenGreenGreenGreenGreen-Ivory

zIT No. : Genebank, National Agro Biodiversity Center, Rural Development Administration,

yBJC: Bangladesh Jute Mills Corporation

xnon-flowering


Fig. 1.

Comparison of morphological characteristics of kenaf genotypes. A: Entire leaf, B: palmate leaf, C: leaf color (purple), D: Ivory petal, E: white petal, F: branch color (purple), G: branch color (brown), H: branch color (green), I: Hypocotyl color (green), J: Hypocotyl Color (purple), K: stem color (green), L: stem color (brown), M: stem color (purple)


The growth characteristics of the kenaf genotypes are shown in Table 2. We observed significant differences for most of the growth and yield characteristics including plant height, fresh mater yield (FM) and seed yield. The plant height of all the genotypes ranged from 234.4 to 415.9 cm. The Hongma300 had the highest FM yield and lowest yield was found in C20 genotype. The highest seed yield was recorded for the Jangdae cultivar and twelve late flowering genotypes were impossible seed harvest.

Growth characteristics of kenaf genotypes

Genotype Plant height (cm)  Dry matter yield (ton/ha)  Seed yield (kg/ha) 
C9247.5±05.2k74.8±1.6h588.7±06.0f
C10238.8±08.7l75.3±2.7h514.2±09.2j
C11274.5±03.6gh77.7±1.1gh636.5±04.3e
C12272.5±01.6h76.0±0.5gh652.3±02.1d
C13252.7±01.7k74.0±0.5h538.5±01.7hi
C14268.1±02.9h76.0±0.8gh641.0±03.3de
C15276.9±02.9gh76.7±0.8gh669.1±03.3c
C16257.7±16.6j71.9±4.6hi545.1±17.9h
C17254.3±17.4j71.9±5.0hi566.2±20.3g
C18253.6±24.6j69.9±6.8hij457.1±23.4k
C19231.2±10.2l68.4±3.0hij426.9±09.4l
C20248.2±11.8k63.6±3.4j412.1±09.3m
C22234.4±05.6l65.9±1.5j325.1±03.7n
RS1261.6±00.4i70.2±0.0hi536.9±00.2hi
RS2255.8±03.8j69.4±1.0hij529.1±03.8i
Jeokbong268.9±09.3h73.1±2.5h579.5±09.8f
Baekma288.4±01.1fg80.7±0.3g686.8±01.2b
WFM1-2293.3±02.0f80.7±0.6g687.0±02.4b
Jangdae345.8±11.8de117.0±4.0f847.5±14.2a
Jinju350.5±08.9de125.7±3.2e180.0±02.2o
Hongma300406.2±03.4ab144.1±1.2ab0.0p
Hongma74-3394.3±02.1b139.9±0.8bc0.0p
Everglades41415.9±03.7a148.1±1.3a0.0p
ACC3748369.5±02.8c133.6±1.0d0.0p
ACC4111352.4±08.9d139.9±3.5bc0.0p
ACC4153357.7±02.9cd138.6±3.3c0.0p
ACC4139385.4±03.6b134.6±1.2cd0.0p
ACC4443390.1±02.4b133.1±0.8d0.0p
ACC4751382.4±03.4bc136.0±1.2c0.0p
ACC4985338.2±05.9e135.9±2.3c0.0p
ACC5014365.6±08.6cd138.8±3.3c0.0p
ACC5072352.5±03.0d138.1±1.2c0.0p

The letters above each point indicate a significant difference at the 5% level (Duncan’s multiple range tests, n=3)


We generated a phylogenetic tree using the Neighbor Joining method (Saitou and Nei 1987) for morphological and agronomic characteristics relationships (Fig. 2A). The keanf genotypes were divided into six groups based on phylogenetic tree the morphological and agronomic characteristics. Group 1 consisted of two genotypes (C10 and C16) with concurrent flowering date and morphological phenotype (palmate and green leaf, green vein, coroll and hypocotyl color, brown stem, ivory flower). Group 2 contained three genotypes (C18, C20 and C22) with same flowering date, leaf shape, leaf, branch, vein, stem, corolla and petal colors. Group 3 contained 9 early flowering genotypes (C9, C11, C12, C13, C14, C15, C17, C19 and WFM1-2). Group 5 included three purple stem mutant (Jeokbong, RS1 and RS2) and ACC4443 genotypes. Group 5 consists of 11 late flowering genotypes (Hongma300, Hongma74-3, Everglades41, ACC3748, ACC4111, ACC4153, ACC4139, ACC4751, ACC4985, ACC5014 and ACC5072). Group 6 included two mutant cultivars (Jangdae and Baekma) and Jinju with leaf, branch, vein, hypocotyl, stem and collroa were all green.

Fig. 2.

Dendrogram showing the phenotypic relationship among the kenaf genotypes based on Pearson’s correlation coefficients generated by morphological traits


Phenolic compounds

The phenolic compound contents of the kenaf cultivars are shown in Table 3 and Figure 3. Five compounds, chlorogenic acid isomer (CAI), chlorogenic acid (CA), kaempferol glucosyl rhamnoside isomer (KGRI), kaempferol rhamnosyl xyloside (KRX), kaemperitrin (KAPT) were isolated. Significant differences in phenolic compound contents were observed among cultivars. The CAI content for all genotypes ranged from 18.0 to 64.0 mg/100 g. The ACC5072 genotypes had contained higher levels of CAI compounds than other genotypes. The highest CA content was observed in C22 (153.8 mg/100 g), and lowest levels were found in C20 (64.4 mg/100 g). The KGRI levels of all genotypes ranged from 29.8 mg/100 g for C9 to 108.6 mg/ 100 g for ACC4111. The KRX contents ranged from 8.7 to C22 mg/100 g, with the highest amounts being in the C22. The KAPT content ranged from 97.8 to 306.1 mg/100 g. The highest KAPT content was observed in cultivar C22, and the lowest values were found in C9 (Fig. 3). The total polyphenol content (TPC) differed significantly among the cultivars, with the highest level found in C22 (766.8 mg/100 g-1). The C9 cultivar had the lowest content (317.0 mg/100 g-1).

Phenolic compound constituents in different kenaf genotypes

GenotypesCAIzCAyKGRIxKRXwKAPTvTPCu
C9 27.0±4.8e 69.8±0.2ij 29.8±4.2h 11.1±2.2gh 97.8±1.7t 317.0±18.8l
C1027.7±5.0e90.8±6.9de45.1±5.6g15.8±1.7ef152.1±2.5l451.6±28.1e
C1126.7±4.1e77.6±3.2gh41.1±5.6g14.5±2.2fg136.4±2.0p387.9±20.5i
C1233.5±5.0c96.3±3.8d69.8±9.6cd21.5±3.1c180.9±0.9i531.9±22.2d
C1330.7±4.9d80.7±2.5fg48.9±6.7f16.5±2.5e140.6±1.8o411.2±19.3h
C1426.2±4.3e76.8±2.9hi45.2±5.3g16.5±2.0e146.0±2.5m409.4±21.2h
C1523.2±3.4fg80.2±3.6fg47.0±6.5f15.7±3.6ef127.3±0.9q387.7±13.5i
C1620.9±3.5g66.4±4.5lm33.7±4.5g10.6±0.5hi112.4±0.8r332.0±16.3k
C1725.5±3.8e69.0±2.7ij35.3±4.9g12.8±2.8g100.6±0.1t330.3±13.0k
C1827.4±4.3e76.7±0.1ih39.0±5.2g14.4±1.9fg123.8±1.3q376.1±18.3j
C1931.4±5.3d78.8±1.6fg43.5±5.3g16.9±2.8ef150.8±1.2l410.8±19.7h
C2026.9±4.1e60.4±2.0m32.7±4.4g11.9±2.1gh106.2±0.5s318.8±13.3l
C2218.0±1.8g153.8±10.7a98.9±14.6ab33.2±3.1a306.1±1.1a766.8±47.9a
C14RS130.8±4.0d74.1±0.5i37.0±5.9g10.0±0.1hi98.7±3.0t364.8±16.8j
C14RS231.5±4.9d73.4±1.3i36.9±5.4g13.1±2.4fg113.4±0.6r280.4±8.3m
Jeokbong7.4±0.3h19.0±0.8n43.3±5.7g10.9±2.5hi139.1±5.3o371.8±9.5j
Baekma24.0±1.6ef67.2±9.7kl33.4±5.8g9.1±0.0i146.2±2.9m364.2±1.0j
WFM1-222.0±1.5f64.9±12.1lm32.3±6.9g8.7±0.3i194.6±2.6h441.3±4.8f
Jangdae26.6±3.7e88.3±8.8de75.7±9.6c16.3±2.3ef145.1±4.0m504.5±11.4d
Jinju32.8±4.5c91.5±1.1de86.3±10.3b21.5±4.5c191.0±2.8h546.5±11.1d
Hongma30026.4±3.5e88.8±7.9d75.9±9.2c16.3±2.2ef146.6±2.4m444.2±8.5f
Hongma74-325.5±3.2e94.3±5.6d79.2±10.2c18.9±2.1de174.7±3.4j492.3±8.8d
Everglades4125.5±3.7e83.2±2.8efg75.9±11.2c19.0±2.1de182.1±2.3i729.5±8.1a
ACC374841.5±7.3bc113.7±0.6c107.5±12.7a26.0±3.7bc241.4±0.5d672.2±25.7b
ACC411144.7±6.7b113.2±9.4c108.6±16.2a30.8±3.6ab263.9±2.8b694.8±15.6a
ACC415339.2±6.4c91.2±2.3de63.4±8.8de19.5±3.6de217.5±0.0f517.4±7.3d
ACC413936.7±5.8c96.2±3.3d86.2±11.4c22.7±2.7c164.2±0.0k571.5±19.2c
ACC444320.0±2.5fg82.1±2.7efg70.1±9.8cd18.9±2.4de165.7±0.5k482.5±1.8d
ACC475128.1±4.4de71.5±2.6ij86.9±12.7b27.4±3.3b229.0±0.5e571.0±3.6c
ACC498526.1±3.8e68.4±1.0jk61.7±7.5de15.9±3.3ef142.1±0.3n421.0±1.1g
ACC501440.3±5.3bc114.0±13.0c89.1±14.4b30.6±4.9ab246.7±4.9c647.2±8.2b
ACC507264.0±10.9a130.4±2.6b68.3±9.9d30.5±8.1ab202.8±4.0g707.1±17.5a

zCAI: Chlorogenic acid isomer,

yCA: Chlorogenic acid,

xKGRI: Kaempferol glucosyl rhamnoside isomer,

wKRX: Kaempferol rhamnosyl xyloside,

uKAPT: Kaemperitrin, The letters above each point indicate a significant difference at the 5% level (Duncan’s multiple range tests, n=3).


Fig. 3.

Ultra-high performance liquid chromatography (UPLC) chromatogram of kenaf phenolic compounds detected at 280 nm. Peaks 1, 2, 3, 4, and 5 are chlorogenic acid isomer (CAI), chlorogenic acid (CA), kaempferol glucosyl rhamnoside isomer (KGRI), kaempferol rhamnosyl xyloside (KRX), and kaemperitrin (KAPT), respectively. A: C9, B: C20, C: C22, D: ACC4111, and E: ACC5072


Fig. 4.

Caliper LabChip GX II patterns following PCR amplification for polymorphic SSR markers in kenaf genotypes. A: KU896464, B: KU896435, C: KU896449. Primer sequences are listed in Table 5


Analysis of the phylogenetic tree showed that the 32 kenaf genotypes divided into three groups with the exception of the C13 genotypes, based on the six phenolic compounds (Fig. 2B). Group 1 included eleven early flowering genotypes (C9, C11, C15, C16, C17, C18, C20, Jeokbong, RS1, RS2 and Baekma). Group 2 included four early flowering genotypes (C10, C12, C22 and WFM1-2), two mid-late flowering genotypes (Jangdae and Jinju) and eleven late flowering genotypes (Hongma300, Hongma74-3, Everglades41, ACC3748, ACC4111, ACC4153, ACC4139, ACC4751, ACC4985, ACC 5014 and ACC5072). Group 3 contained two genotypes (C19 and C16) with same morphological phenotype. C13 genotype was not belonging to any groups.

Pearson’s correlation coefficients based on average quantified values for morphology and phenolic compound data are shown in Table 4. KGRI, KRX and TPC contents were correlated with flowering date, corolla color and petal color. CAI content was correlated with flowering date. Plant height, DM yield and seed yield were correlated with flowering date, KGRI, KRX, KAPT.

Correlation coefficients between flavonoid content, yield and morphological characteristics of kenaf genotypes (P<0.01)

  TraitR2
CAIz content and flowering date 0.460 
CAy content and leaf color0.507
KGRIx content and flowering date0.750
KRXw content and flowering date0.597
KAPTu content and flowering date 0.553
TPCt content and flowering date0.638
KGRI and corolla color0.611
KRX and corolla color0.496
KAPT and corolla color0.462
TPC and corolla color0.516
KGRI and petal color0.616
KRX and petal color0.499
KAPT and petal color0.521
TPC and petal color0.576
Plant height and flowering date0.940
DMs yield and flowering date0.985
Seed yield and flowering date0.901
KGRI and Plant height0.697
KGRI and DM yield0.741
KGRI and Seed yield0.705
KRX and Plant height0.456
KRX and DM yield0.557
KRX and Seed yield0.644
KAPT and Plant height0.469
KAPT and DM yield0.526
KAPT and Seed yield0.597

zCAI: Chlorogenic acid isomer,

yCA: Chlorogenic acid,

xKGRI: Kaempferol glucosyl rhamnoside isomer,

wKRX: Kaempferol rhamnosyl xyloside,

uKAPT: Kaemperitrin,

tTPC: Total phenolic content,

sDM: Dry matter


Genetic diversity and relationships

The marker attributes for the SSR primers were summarized as number of allele (NA), number of polymorphic allele (NPA), fraction of polymorphic markers (FPM), GD, PIC, EMR, and MI (Table 5). A total of 229 SSR allele were detected overall, and there were 217 polymorphic allele (94.8%) among the cultivars. The NA for each of the SSR primers ranged from 2 to 8, with a mean of 2.90. The NPA of the SSR primers ranged from 2 to 8, with a mean of 2.75. The average FPM was 0.94 per marker, and the range was from 0.5 to 1. The GD ranged from 0.09 to 0.83, with an average of 0.44, and the PIC values ranged from 0.09 to 0.81, with a mean value of 0.37. The maximum values of GD and PIC occurred with the KU896464, whereas the minimum values were generated by the DQ068364. The SI values of the SSR primers ranged from 0.02 to 0.73, with a mean of 0.45. The maximum values of SI occurred with KU896449 (Table 5).

Characteristics of SSR markers for the identification of kenaf genotypes

Genbank ID  Primer sequences (5’-3’)OriginNAzNPAyFPMxGDwPICvSIu
DQ068360F CTAGTTTTTGCAGAGGCCAAGTGenomic SSR Markers331.000.510.460.46
R AGAAGAATTGTTGGCCATGTCT
DQ068361F ACTAGTTTTTGCAGAGGCCAAG551.000.770.680.73
R GATTACTCATTTGGCCATGTCTC
DQ068362F TTACTACCGTTTGAGCGGAGA320.670.360.220.33
R CGAATGCCAAGAAAGTTTCAG
DQ068364F GAGGCACTTCAGTGTCGTAGC210.500.090.090.02
R CCAATAGGCAGGTTTTTCCTC
DQ068366F TGCCCATTTTTGAGTTTTCAC210.500.120.110.12
R TCCTCGAGAAAAAGGATTGTG
DQ068373F ACTAGTTTTTGCAGAGGCCAAG320.670.540.480.42
R GAGTGTTGTGCATGAAAGGAAA
DQ068374F CACTCCAATCACCATTCACG210.500.090.090.02
R CTGATCGAATCCAACCCCTA
DQ068376F CAGTAGCGGACCGTTATTTGA331.000.490.430.24
R TTACAGCCTTGGGACTTCAGA
DQ068377F GAATGCAACATTTTTAAATGCAA330.500.470.420.38
R GTCTACAAAAGCCAAAGCATACC

KU896377F CCGAAGCTCCTGCTTTTATCEST-SSR Markers331.000.560.500.47
R GTCTCAGATGAAGCCACCAC
KU896380F GAAGAAACGGGTCATTCCTC320.670.530.420.65
R GTAGTCGTAGTCATCCTCTGCTC
KU896381F GTGATATCCGAGCACCTTTG221.000.500.370.58
R GCGATGATATCAGAACCTCGTC
KU896382F GGTTTTCGGCTCTTGGTT331.000.360.290.48
R CTGGACAATTGCGAGAAGAG
KU896383F GCTGAGCAGAGGAGTAGAAGAA221.000.580.490.60
R TTCAGCTCAAGCAGTATCCC
KU896384F ATCCTAGTGGATCCCTGAACTC221.000.430.340.66
R GACGATGAGGAGCAGAAAGA
KU896385F GCTGCCATGCTCATGATT221.000.480.370.63
R AGCTCACCCTCCACTTCTCTAT
KU896386F ACAGCTTTGACTGTCGTCACTG221.000.450.350.41
R AAGTATCTTGTGGGCTGTGG
KU896387F GCCTTCGGAGTAAATGGGT771.000.320.270.27
R CACCCAAACATTCTCTCTGG
KU896388F GTTGGTCGTAAAAGCCGAG221.000.740.720.35
R AACCCCGTCTTTAACCTCAG
KU896389F GAAACGAAGGGTAGAGTACGGT331.000.170.160.44
R GCAGTGTAAACAAACAGCCC
KU896390F AGATTGATCTCGTCACCCCT221.000.490.380.55
R CCAAACTGGATCGTAATCCG
KU896391F CAGAAAAGTAGCGGGATGAG221.000.410.330.54
R CCACTCGACATTAAACCCAC
KU896395F TACTGGATGAAGGAGTAGCAGC221.000.380.310.36
R CTTGATAGGCATCCCTTACCC
KU896397F CCATATAGTTTGGGGGAAGG221.000.190.180.61
R CAGTGAGAAGTGAGTGGCTACA
KU896399F AGCCTGTGCTGAAAGCTAGA331.000.460.350.38
R GGAGGGAGCATAAGTGAGTTTG
KU896400F CCGACAAGAACAAGTCCA331.000.420.350.41
R CAACCCGTGTGCATTGAG
KU896404F GATGGTTTCTCCCAACAACC221.000.520.410.62
R CAACGACATCGTCGTCTTC
KU896405F GTCGTCATCATCGTCCAATC441.000.470.360.39
R AGATCTCTCTTCACAGTGTCCC
KU896406F CAGTCTGCATCGTCCAATC331.000.660.610.33
R AGATCTCTCTTCACAGTGTCCC
KU896407F GCCTTCAGAGAATAGATGTGGG320.670.330.300.49
R CAGTTCATCGACTTGGCTTG
KU896408F CTAACACGTCCGGCAACA320.670.220.190.62
R GGAGTTCAAGAGGACGTAGTTG
KU896409F CCTCAAGCTCCTCGTAATACAC221.000.470.360.49
R GGGTACCAGTGAAGAGAACAAG
KU896410F GTACTTGACGTAGGAAAGGCAG331.000.220.190.42
R TTATACGACTCCCCACGGA
KU896411F GTTCCTATGAAGAATCCGGC221.000.520.450.56
R ACTTTGAGAGGTTGCAAGGG
KU896412F GTAATCGTTGTTGGCGTTGG771.000.400.320.31
R GTCAAACACAAGCTCCAGTCC
KU896417F CCCTCTACCTCTAGGATGATTCTC221.000.790.760.43
R ACTAGGTTTCTCTTCAGCGGC
KU896418F GTTCCTTGAGAGAAAGGAGAGG331.000.200.180.55
R GTGTTAGTGAGGAGAAGCAAGG
KU896419F GGTAAACTGTTGAAGCGGGT221.000.650.580.42
R GCAGAGCATTTCAACCAG
KU896420F CCCCTTTTGATCTCTTGC221.000.260.230.52
R AGGAGGGAGAGAGAGCTTCA
KU896422F GGCTGCCCTTGCTAATAAGT221.000.380.300.59
R ACTCGCTTCTTCATGCTCC
KU896423F GGTGGTTTAAACGAGCACC331.000.430.340.27
R GTCTCCCCATTGTTCCTGA
KU896424F CATCCCGTCTAACACTACATCC221.000.170.170.66
R GCACCGAGTATATCCTTCCAC
KU896426F GGAGTCGTATAATGGGGTGA331.000.500.370.44
R CTCCCTCTCGAAAATACGTAGC
KU896427F GGTATGGCAGACGAGATGTT221.000.440.400.39
R GTGTTAGTAGGCACTGGTGAAG
KU896428F GCTCCTGCACTGTTTGTTGT221.000.220.190.45
R CTAGGCTTATGTGTGGACCG
KU896429F GGAGTGTCTTGTAATAGCCCAC441.000.300.260.39
R CTCCAACCTCCCATTGTTC
KU896430F GATCCGAAGGTAAATGGGTC221.000.640.600.40
R CAGACACCTTTAGCCCCAC
KU896431F AATCCAGGGAAGCAGCTC441.000.220.200.39
R GCATATCTCTGAAGTGTCTCCG
KU896434F CACTAAGAGCCCAGAAAGAAGC221.000.610.550.27
R GAGACTCTTGTGGAGTTTCTGC
KU896435F GTAGTCACCGCCGTCACAATAG221.000.120.110.44
R CTATTCTGGCTCTCCCAACA
KU896436F CGGCTGTTACTCCATCAAAG331.000.220.190.44
R GGTCGTCTTACAATGGTTCC
KU896438F ATTCAGAAACCGATGCCC331.000.490.410.59
R GGAATGTCACTGGTCCGAG
KU896439F AGCTCCGGGGATAAGTTAAG331.000.610.530.42
R GCCTTCTCTCCTTGACCAGTA
KU896440F GGCACAATAGAAGAGGCAGACT331.000.480.390.43
R CTTCGAATTTCAGCGTCG
KU896441F GAGATGTTTGATGCTCCAGG221.000.390.330.46
R TCACGAAACCAAAGCAGC
KU896442F CACAGTTTCACGAGGCTAACTC881.000.280.240.22
R GAGAAGAGCTTCCAACCAGG
KU896443F GTACACAAAGTGCAACCTCTCC221.000.730.690.60
R TTCTCCCCTAATTCCTCACC
KU896444F CGTTCAACATCTCCAGAACC221.000.430.340.61
R GAGTACGAGTTCAGCTGTAGCA
KU896445F AACGTCGGCTGCAACTTT221.000.480.360.51
R GGGCTTGAAAGTGTCGAGAA
KU896447F GGTGATCAGCTCGAGTCC331.000.500.370.46
R AAATCCACCTCATCTCCAGC
KU896449F CTCCTCAATCTAAGCCGTCC320.670.530.440.66
R ACGATCACGACTTGCTCTTC
KU896452F TTCACTTCAGCAGACTTCCC331.000.480.370.38
R GATGCTCCTGGGTTGTTAGA
KU896454F GCTTGGCTTCAACTCATCTC441.000.280.250.37
R CGGCGGCTTTTATAAGGA
KU896455F GGAGTGTCTTGTAATAGCCCAC661.000.570.520.30
R CTCCAACCTCCCATTGTTC
KU896456F GAAACCGTGTTGGTCTTGTC320.670.690.660.63
R AAAGGCCCGATCCAAATC
KU896457F GACCACCTCGAGAATAAGCA221.000.500.370.53
R CTCCCAGGTAACGTCGAAT
KU896458F CTCTGGAGAAGCTAAGGAGTGA221.000.400.320.54
R CCATGTTCTCAAACCCTTCC
KU896459F ACAGCGTGTGGAGGTTCATA221.000.400.320.51
R AGCAGCCACCGTCTAAAAG
KU896461F GGCAGGATATTCGACGGT331.000.360.290.49
R GGAGATGGTTCTCCTGTTAAGG
KU896462F CAAGGCTTAGGTCGTAGGTATC430.750.620.540.45
R AAGAGAAGCCAAGATCAGCC
KU896463F CCATGGTCATATTGCTCTCC771.000.520.410.28
R TGTACTACTCTCTCTCTGCTCTCC
KU896464F CCAGGAATCTATTGTCGGG221.000.830.810.56
R CAATAATTCAGCCCTCCCTC
KU896466F GCTGTTTCTTAACAGGAGCAGG441.000.400.320.35
R GGTGTAGCTCAGGCTGTTGTA
KU896468F CGGGTCTTACGTTCCCTAGTA331.000.330.310.48
R CCAGCTCCATTGATCTTTCC
KU896471F GGATCGAAACAACCCAGTC320.670.590.520.60
R TCAACCAAACCCAACTCC
KU896473F ATCGCAGGATCTCTCCAAG221.000.500.390.59
R GATGGATTACTTCCCCTAGGAC
KU896476F CTCTCTTCTCCTCAAACACCC441.000.460.350.34
R GGGTAAGAAAAGGGCAGACA
KU896477F CTCATCCTCTGCACTTCCAT221.000.380.330.46
R GGCAATTGCATCGTCAAG
KU896478F GTCTTGGGAGTGGCTTTTGT221.000.280.240.58
R CTCATCATTTACCTCCGACG

Mean2.902.750.940.440.370.45

NA: Number of alleles,

yNPA: Number of polymorphic alleles,

xFPM: Fraction of polymorphic marker,

wGD: Gene diversity,

vPIC: Polymorphism information content,

uSI: Shannon’s Information index.


A phylogenetic tree was constructed based on the 80 SSR markers in 32 kenaf genotypes (Fig. 2C). The genotypes divided into early flowering, mid-late flowering, and non-flowering groups were grouped into four distinct groups with the exceptions of the two (ACC3748 and ACC5072) genotypes. Group 1 consisted of eighteen early flowering genotypes. Group 2 included both of the non-flowering genotypes (ACC4443 and ACC4751). Group 3 contained eight non-flowering genotypes (Hongma300, Hongma74-3, ACC5014, Everglades41, ACC4985, ACC4135, ACC4111 and ACC4139). Group 4 included mid-late mutant cultivar (Jangdae) and these of original genotype (Jinju).

We explored correlation analysis among the SSR markers, chemical components and morphological characteristics of the kenaf cultivars by applying Q GLM and Q + K MLM statistical methods (Table 6). A total of 15 significant correlations (p < 0.05) were revealed using the Q GLM and Q + K MLM statistical approaches. We discovered four (KU896387, KU896399, KU896441 and KU896449) significant correlated with leaf color. The lowest p-value was observed for the KU896449 with leaf color (P = 2.34E−204, R2 = 0.974) in Q GLM. Three SSR markers (KU896384, KU896438 and KU896440) had highly significant correlated with petal color. The KU896440 marker had the lowest p-value (P = 1.36E-07, R2 = 0.206) by Q MLM. The KU896377 and KU896423 markers had significant correlated with vein color. The KU896426 marker had significant correlated (P = 0.004, R2 = 0.159) with KGRI contents. The KU896408 and KU896449 markers had significant correlated with stem color. KU896408 had the lowest p-value (P = 0.001, R2 = 0.166) by Q GLM. KU896449 markers had significant (Q GLM: P = 0.002, R2 = 0.367 and Q+K MLM: P = 0.023, R2 = 0.289) correlated with corolla color.

Association analyses between SSR markers and morphological characteristics and phenolic compound contents of the kenaf genotypes

MarkerTraitQ GML P-valueR2Q+K MLM P-valueR2
 KU896377 Vein color* 0.266 * 0.248 
KU896382 Total polyphenol *0.123*0.131
KU896384Petal color***0.142*0.363
KU896387Leaf color***0.303*0.247
KU896399Leaf color*0.203*0.231
KU896408Stem color*0.166*0.187
KU896423Vein color*0.258*0.233
KU896426KGRI**0.159*0.160
KU896438Petal color***0.140*0.309
KU896440Petal color***0.206*0.246
KU896441Leaf color***0.973**0.999
KU896447Leaf shape**0.235*0.181
KU896449Leaf color***0.974***0.999
KU896449Corolla color***0.172*0.289
KU896449Stem color*0.219*0.248

*P < 0.05;

**P < 0.01;;

***P < 0.001.


Discussion

Kenaf is promising potential to exploit and utilize, but identification of kenaf genotypes and understanding of morphological, chemical and genetic characteristics and relationships is limited, thus significantly hinders their effective utilization (Alexopoulou et al. 2013; Faruq et al. 2013; Jeong et al. 2017). Genetic analyses of the complex quantitative traits involved in morphology and functional compounds are limited (Alexopoulou et al. 2013; Faruq et al. 2013; Zhang et al. 2015). This preliminary study aimed to understand the morphological, chemical and genetic characteristics of these economically important traits, and it is the first exploration of the morphological, chemical and genetic diversity and relationship of kenaf genotype.

Kenaf is considered an important medicinal crop in India and South Africa (Alexopoulou et al. 2013). The leaf has been reported to be anodyne, aperitif, aphrodisiacal, fattening, purgative, and stomachic and has long been used as a traditional medicine in Africa and India (Kubmarawa et al., 2009; Alexopoulou et al. 2013; Jin et al., 2013). The leaf contains large amounts of polyphenols, tannins, and other mineral compounds (Kobaisy et al., 2001; Ryu et al., 2017a). Most of the medicinal benefits attributed to kenaf are due to the presence of phenolic compounds (Jin et al. 2013; Zhao et al. 2014; Ryu et al. 2017). The major bioactive compounds in kenaf include the CAI, CA, KGRI, KRX and KAPT. In this study, their content and TPC had a high correlation with flowering date, hypocotyl color corolla color and petal color. KAPT is the main compound present in kenaf leaf. The compound has an acute lowering effect on the blood glucose level of diabetic rats (Jorge et al., 2004). In other studies, KAPT has shown high reactivity with 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radicals, angiotensin I converting enzyme (ACE) inhibition and also decreased lipid peroxidation (Cazarolli et al. 2006; Jin et al., 2013). The highest level of KAPT content was observed in the C22 genotypes (306.1 mg/100 g) and the lowest level was observed in the C9 genotypes (97.8 mg/100 g). Ryu et al. (2017) reported that the KAPT content ranged from 10 to 178 mg/ 100 g with different solvent extract of kenaf leaves, and that water has the highest KAPT content. The high levels of these compounds observed in the present study, especially for the C22 genotypes, indicate promising commercial potential for kenaf as a source of phenolic compounds.

Analyses of genetic diversity provide for the selection of genotypes in breeding programs and provide useful genetic information (Zhang et al. 2015; Jeong et al., 2017). In this study, high levels of genetic diversity were found for the various kenaf genotypes. PIC and GD detected in this study for kenaf are higher than those previously observed using other marker (SRAP, ISSR, RAPD and AFLP) systems (Cheng et al. 2004; Chen et al. 2011; Zhang et al. 2013). In additions, these results are higher than the findings of Li et al. (2016) in 28 kenaf cultivars using 72 EST-SSR markers. Especially, the maximum values of GD and PIC occurred with the KU896464 and the maximum values of SI occurred with KU896449. This suggests that KU896464 and KU896449 markers could be used to assess genetic diversity in genotypes.

The correlation analysis showed flowering time and DM yield, seed yield and phenolic compounds were significantly correlated. Also, comparison of three phylogenetic tree based on morphological and chemical characteristics with those based on SSR data showed that the groups formed by the six early flowering genotypes (C9, C11, C14, C15, C17, C19) grouped similarly in SSR phylogenetic tree. Ultimately, early flowering, mid-late flowering and non-flowering groups were clearly divided by genotypes in SSR phylogenetic tree. Similarly, Jeong et al. (2017) reported that phylogenetic and population structure showed that the 45 accessions could be clearly divided into three groups based on different days to flowering by EST-SSR markers through de novo RNA sequencing. The flowering period has been reported to be an indication of sensitivity of kenaf genotypes to photoperiod, later flowering genotypes being photo-insensitive (Webber et al. 2001). Korean Kenaf cultivars are divided into three maturation groups depending on flowering date; early-flowering, mid-late flowering, and late flowering (Kang et al., 2016). Early- flowering cultivars bloom in 70~80 day after sowing. Such varieties allow seed harvested in Korea, but the brief vegetative growth period produces shorter plants of lower biomass (Webber and Bledsoe, 2002; Kang et al., 2016). Late-flowering cultivar grows vegetative for 130~140 days and yield significantly higher biomass. However, late flowering increases the risk of seed shattering (Kang et al., 2016). To achieve profitability, the selection of the best cultivar for each country is important. The breeding of kenaf cultivars for yield and economic important with adaptation to local conditions has been conducted actively using these genetic resources (Alexopoulou et al., 2013; Kang et al., 2016). Breeding selection of kenaf starts mostly from the introduction of new cultivars, and the breeding selection of new cultivars is the most effective measure for increasing yield and improving functional quality (Ryu et al., 2016; Jeong et al., 2017). The Jangdae and Jeokbong cultivars were derived by gamma ray (300 Gy) treatment. The mid-late cultivar Jangdae, which affords both high biomass and high seed yield, has been registered in Korea (Kang et al., 2016). The Jeokbong cultivar has distinctive morphological characteristics such as dark purple color. The low levels of phenolic compounds observed in the present study for the Jeokbong cultivar, but their antioxidant and antioxidant and ACE inhibition activity are approximately 4~5 times higher than other cultivars caused by anthocyanin (Ryu et al., 2017b). Based on the flowering time, the morphological and chemical phylogenetic tree revealed an unclear pattern of division between mutant cultivars (Jangdae, Baekma and Jeokbong) and these original genotypes (Jinju and C14), while the genetic phylogenetic tree showed that the mutant cultivars grouped with the those original genotypes (Jinju and C14). Thus, these results could be used for the selection of kenaf cultivars with improved yield and functional compounds. Our results of morphological, chemical and genetic phylogenetic trees were no related with the origin. In previous studies on the origin, many studies agree that kenaf originated from Africa (Dempsey 1975; Alexopoulou et al. 2013). However, the knowledge of how kenaf was introduced in Asia is limited but it is known that it came from Africa (Dempsey 1975; Alexopoulou et al. 2013; Zhang et al. 2013). In additions, it is likely that cluster analysis using country of origin was not able to differentiate among all cultivars because of the limited number of accessions.

The SSR phylogenetic tree clearly showed that the genotypes divided into flowering time, but the genomic and EST SSR markers not significant correlated with flowering time. Marker assisted selection has the potential to improve the efficiency of plant breeding because of its increased accuracy and liability. However, with this large average distance, greater saturation would be needed for practical application especially for marker assisted selection (Varshney et al. 2005; Varshney and Tuberosa, 2007; Zhang et al. 2011). To the best of our knowledge, this is the first report on the correlation of molecular markers with phenolic compounds, morphology and agronomic traits in kenaf. These 15 SSR markers could be used for selection of kenaf cultivars with improved morphological characteristics and functional compounds (total polyphenol and KGRI). The mapping of genes controlling agronomic traits and functional compounds coupled with the widespread availability of easy to use simple sequence repeat (SSR) markers (Varshney et al. 2005; Varshney and Tuberosa, 2007). These results could be used for the selection of kenaf cultivars with improved yield and may be a good candidate for pharmaceutical products.

Acknowledgements

This work was supported by grants from the Nuclear R&D Program by the Ministry of Science and ICT (MSIT), and the research program of KAERI, Republic of Korea.

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