Научная статья на тему 'Morphological diversity of cotton germplasm in developing selection methods to breed superior cotton variety'

Morphological diversity of cotton germplasm in developing selection methods to breed superior cotton variety Текст научной статьи по специальности «Биологические науки»

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Cotton / identification / morphological character

Аннотация научной статьи по биологическим наукам, автор научной работы — Abdurrakhman, Herwati Anik

Cotton fiber supports the textile industry, folk weaving, and Indonesian paper money. The land suitable for the development of cotton should possess a dry climate. Balittas has 945 cotton germplasm accession derived from the introduction which belongs to the species Gossypium hirsutum, G. Barbadense, G. Arboreum, and G herbaceum. It is very crucial to determine germplasm characteristic. The research was carried out at KP. Karangploso, Balittas altitude of 515 masl, climate type D (moderate) Smith Ferguson, rainfall of 1500 mm/year, and type of soil Gleymosol Gleik / Inceptisol. The material used is 85 accessions, planted March 23, 2016. Fertilizer dosage: 97 kg N + 30 kg P2O5 + 30 kg K2O / ha and insecticides (Confidor, Furadan, Organeem. Each accession was planted 10 m in length, 150 cm X 25 cm space. The study aims to analyze the diversity of morphological characters and cotton germplasm categorizing to ensure it can be used as a basis for selecting genetic resources in assembling new superior varieties. The results of quantitative observations at the age of 120 days exhibited high diversity. The featured characters are: budding age, flowering age, blooming age, generative branch length, number of generative branch joint, and generative branch internot length, number of vegetative branches, number of generative branches, generative branch height, canopy width, number of fruit, length of segment, weight of 40 seeded cotton. KK value were 39%, 59%, 34, 24%, 22%, 24%, 67.22%, 22%, 28%, 24% respectively. As the coefficient of diversity> 20%, the assessment result exhibited significantly different character.

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Текст научной работы на тему «Morphological diversity of cotton germplasm in developing selection methods to breed superior cotton variety»

DOI https://doi.org/10.18551/rjoas.2018-10.32

MORPHOLOGICAL DIVERSITY OF COTTON GERMPLASM IN DEVELOPING SELECTION METHODS TO BREED SUPERIOR COTTON VARIETY

Abdurrakhman*, Herwati Anik

Sweeteners and Fiber Crops Research Institute, Malang, Indonesia *E-mail: abdurrakhman2017@gmail.com

ABSTRACT

Cotton fiber supports the textile industry, folk weaving, and Indonesian paper money. The land suitable for the development of cotton should possess a dry climate. Balittas has 945 cotton germplasm accession derived from the introduction which belongs to the species Gossypium hirsutum, G. Barbadense, G. Arboreum, and G herbaceum. It is very crucial to determine germplasm characteristic. The research was carried out at KP. Karangploso, Balittas altitude of 515 masl, climate type D (moderate) Smith Ferguson, rainfall of 1500 mm/year, and type of soil Gleymosol Gleik / Inceptisol. The material used is 85 accessions, planted March 23, 2016. Fertilizer dosage: 97 kg N + 30 kg P2O5 + 30 kg K2O / ha and insecticides (Confidor, Furadan, Organeem. Each accession was planted 10 m in length, 150 cm X 25 cm space. The study aims to analyze the diversity of morphological characters and cotton germplasm categorizing to ensure it can be used as a basis for selecting genetic resources in assembling new superior varieties. The results of quantitative observations at the age of 120 days exhibited high diversity. The featured characters are: budding age, flowering age, blooming age, generative branch length, number of generative branch joint, and generative branch internot length, number of vegetative branches, number of generative branches, generative branch height, canopy width, number of fruit, length of segment, weight of 40 seeded cotton. KK value were 39%, 59%, 34, 24%, 22%, 24%, 67.22%, 22%, 28%, 24% respectively. As the coefficient of diversity> 20%, the assessment result exhibited significantly different character.

KEY WORDS

Cotton, identification, morphological character

The development of cotton was mainly carried out to support the textile industry, folk weaving, and Indonesian paper money. Suitable land for the development of cotton in Indonesia is widely available, especially in Central and Eastern Indonesia, which is dominated by dry land and climates. The main obstacle in developing national cotton has generally been caused by biotic factors such as pests and diseases, as well as abiotic factors in the form of water shortages (drought) causing low national productivity. Lewis (1982) states that plant productivity could be improved in two ways, namely by changing the environment (amelioration) or improving plant genotypes. Nevertheless conducting environmental improvements is very expensive and may generate negative impacts. On the other hand, improving plant genotypes is relatively cheaper, and does not cause negative impacts on the environment. This approach is conducted by assembling superior varieties. The 'Gene pool' with extensive genetic diversity is needed for building superior cotton varieties. Cotton germplasm stored in Balittas to date is 945 accessions originating from introduction through the exchange of varieties with several cotton research institutions abroad, from germplasm banks such as IRCT France, USDA America United, ICAR India, as well as from several cotton management companies. Most of the germplasm is classified as Gossypium hirsutum species, some are included in G. Barbadense, G. Arboreum, and G herbaceum.

However, until recently the collection of cotton germplasm with genetic information for the traits needed for breeders is lacking, therefore it is necessary to explore as much genetic information as possible from each existing accession through germplasm characterization and screening/evaluation activities. In the effort to improve cotton plants, a diverse

population is needed, especially in the nature of breeding purposes. Assembly of varieties to obtain new superior varieties with desirable traits needs to be supported by germplasm with high genetic diversity (Akhtar et al. 2007). According to Bari & Musa (1974). The availability of genetic resources with several characters that have been identified is information regarding the genetic diversity of germplasm. This aspect is crucial as it is very important to distinguish between genotypes required in the development of plant breeding programs (Bennett, 1993). According to Sumarno (2002), germplasm is a collection of genetic diversity of types of organisms. Bermawi (2005) argues that characterization is an activity to obtain morpho-agronomic characteristics or data which aims to distinguish phenotype from each accession. The characterization uses instructions from The International Union For The Protection Of New Varieties Of Plants (UPOV 2002). The following step is determining genetic diversity by grouping germplasm. The grouping method is an indispensable step in the utilization of the germplasm collection (Bozokalfa et al. 2009; Lule et al. 2012). The degree of variation in the genetic material will determine genetic diversity. Grouping germplasm collections is a strategy in the effort to utilize germplasm collections (Bozokalfa et al. 2009; Lule et al. 2012). The success of crop selection in breeding depends on genetic variation from existing germplasm accessions (Akhtar et al. 2007). Germplasm collections need to be characterized to ensure their properties are known as genetic information in the variety assembly program. This study aims to analyze the diversity of morphological characters and grouping of cotton germplasm of the Balittas collection to ensure it could be utilized as a basis for selecting genetic resources in the assembly of new superior varieties.

MATERIALS AND METHODS OF RESEARCH

The research activities were carried out at KP. Karangploso, Balittas with an altitude of 515 masl possessing type D (moderate) climate Smith Ferguson, rainfall 1500 mm / year, and type of Gleymosol Gleik / Inceptisol soil, from January to December 2016. Research material used were 100 cotton germplasm accessions (Table 1), planted on March 23, 2016. The fertilizer dosage used is 97 kg N + 30 kg P2O5 + 30 kg K2O / ha. Insecticides -Confidor, Furadan, Organeem. Each accession was planted in one row for 10 m. Planting distance of 150 cm X 25 cm, one plant per hole. Fertilization was done twice, 1/3 dose of N and all doses of P2O5 and K2O at the time of planting, and 2/3 doses of N on 30 days after planting. Observation of morphological characters referred to the cotton descriptor list from International Union for the Protection of New Varieties of Plants (UPOV 2001).

The results of correlation analysis exhibited a positive or negative correlation between (1) plant height with canopy width, flowering age, and weight of 100 fruits (2) number of epidermis with flowering age (3) budding age with number of fruits and fiber length (4) flowering age with plant height, budding age, and fiber length (5) number of plant/ fruit with weight of 100 fruits (6) weight of 100 fruits with plant height, flowering age, and number of fruit / plant. It indicates that the characters observed above are related to each other. The descriptive Statistics quantitative character of cotton germplasm referred to (Descriptor list) from the International Union For The Protection of New Varieties of Plants (UPOV 2012), as presented in (Table. 3).

Method of germplasm accession grouping utilized cluster analysis with Euclidian distance and average linkage method (Suhartini & Sutoro 2007; Setyowati et al. 2009; Furat & Uzun 2010). The variables used in the grouping are variables that are mutually independent. In the initial phase, quantitative character data were analyzed using the Pearson correlation coefficient. If there is a correlation, the observed variables are transformed into the main component variables. The main component analysis was done after the quantitative data is standardized by dividing each variable with its standard deviation, therefore it is within the commensurate range due to different data units (Joliffe 2002; Tresniawati & Randriani 2008). The results of the main component analysis were followed by cluster fingerprint analysis. Data analysis was carried out using Minitab 15 software.

The diversity of cotton germplasm based on morphological characters could be predicted through the value of the Diversity Coefficient (CV) of each parameter observed. Nilasari et al. 2013 and Hadi et al. 2014), argues that to estimate the level of difference in the observed germplasm population, CV Value could be utilized. (Table 3). The results of the quantitative morphological characterization exhibited a high diversity in the number of epidermises on the leaves, flowering age, plant height, and canopy width.

Table 1 - 100 cotton germplasm accessions Research material

NO. Accession/Var Population Origin NO. Accession/Var Population Origin

1 Kanesia 8 Var Var 51 KI 123 USA AMERICA

2 Kanesia 10 Var Var 52 KI 124 USA AMERICA

3 Kanesia 14 Var Var 53 KI 240 USA AMERICA

4 Kanesia 15 Var Var 54 KI 845 BRAZIL AMERICA

5 Kanesia 16 VAr Var 55 KI 846 BRAZIL AMERICA

6 Kanesia 20 Var Var 56 KI 847 BRAZIL AMERICA

7 KI 2 USA AMERICA 57 KI 848 BRAZIL AMERICA

8 KI 15 USA AMERICA 58 KI 849 BRAZIL AMERICA

9 KI 17 USA AMERICA 59 KI 850 BRAZIL AMERICA

10 KI 19 USA AMERICA 60 KI 851 BRAZIL AMERICA

11 KI 20 USA AMERICA 61 KI 409 Nicaragua AMERICA

12 KI 23 USA AMERICA 62 KI 30 Yugoslavia EUROPE

13 KI 74 USA AMERICA 63 KI 40 Yugoslavia EUROPE

14 KI 75 USA AMERICA 64 KI 51 Yugoslavia EUROPE

15 KI 76 USA AMERICA 65 KI 38 Bulgaria EUROPE

16 KI 77 USA AMERICA 66 KI 46 Bulgaria EUROPE

17 KI 82 USA AMERICA 67 KI 44 USSR EUROPE

18 KI 85 USA AMERICA 68 KI 448 FRENCH EUROPE

19 KI 86 USA AMERICA 69 KI 951 INDONESIA ASIA

20 KI 88 USA AMERICA 70 KI 952 INDONESIA ASIA

21 KI 89 USA AMERICA 71 KI 339 PHILIPINA ASIA

22 KI 90 USA AMERICA 72 KI 47 INDIA ASIA

23 KI 92 USA AMERICA 73 KI 151 INDIA ASIA

24 KI 94 USA AMERICA 74 KI 320 INDIA ASIA

25 KI 95 USA AMERICA 75 KI 351 INDIA ASIA

26 KI 96 USA AMERICA 76 KI 48 PAKISTAN ASIA

27 KI 97 USA AMERICA 77 KI 58 PAKISTAN ASIA

28 KI 98 USA AMERICA 78 KI 62 CHINA ASIA

29 KI 99 USA AMERICA 79 KI 688 CHINA ASIA

30 KI 102 USA AMERICA 80 KI 689 CHINA ASIA

31 KI 103 USA AMERICA 81 KI 691 CHINA ASIA

32 KI 104 USA AMERICA 82 KI 693 CHINA ASIA

33 KI 105 USA AMERICA 83 KI 36 CAMERON AFRICA

34 KI 106 USA AMERICA 84 KI 39 UGANDA AFRICA

35 KI 107 USA AMERICA 85 KI 43 UGANDA AFRICA

36 KI 108 USA AMERICA 86 KI 45 UGANDA AFRICA

37 KI 109 USA AMERICA 87 KI 135 USA AFRICA

38 KI 110 USA AMERICA 88 KI 168 USA AFRICA

39 KI 111 USA AMERICA 89 KI 268 USA AFRICA

40 KI 112 USA AMERICA 90 KI 289 EGYPT AFRICA

41 KI 113 USA AMERICA 91 KI 711 EGYPT AFRICA

42 KI 114 USA AMERICA 92 KI 364 NIGERIA AFRICA

43 KI 115 USA AMERICA 93 KI 453 NIGERIA AFRICA

44 KI 116 USA AMERICA 94 KI 502 AUSTRALIA AUSTRALIA

45 KI 117 USA AMERICA 95 KI 509 AUSTRALIA AUSTRALIA

46 KI 118 USA AMERICA 96 KI 510 AUSTRALIA AUSTRALIA

47 KI 119 USA AMERICA 97 KI 564 AUSTRALIA AUSTRALIA

48 KI 120 USA AMERICA 98 KI 569 AUSTRALIA AUSTRALIA

49 KI 121 USA AMERICA 99 KI 629 AUSTRALIA AUSTRALIA

50 KI 122 USA AMERICA 100 KI 633 AUSTRALIA AUSTRALIA

The results analyzed by the correlation of quantitative observations are presented in (Table 2).

Table 2 - Correlations between quantitative variables

n/n TT LK JB UK UB JBH B100 PS

TT Pearson Correlation 1 .523 0.168 0.013 .341 -0.043 -.269 -0.132

Sig. (2-tailed) 0 0.096 0.902 0.001 0.672 0.007 0.189

N 100 100 100 100 100 100 100 100

LK Pearson Correlation .523 1 -0.075 0.074 0.146 0.042 -0.052 0.087

Sig. (2-tailed) 0 0.458 0.467 0.147 0.675 0.61 0.388

N 100 100 100 100 100 100 100 100

JB Pearson Correlation 0.168 -0.075 1 .277 0.039 0.009 -0.1 -0.048

Sig. (2-tailed) 0.096 0.458 0.005 0.697 0.927 0.322 0.638

N 100 100 100 100 100 100 100 100

UK Pearson Correlation 0.013 0.074 .277 1 .296 0.087 -0.047 .239

Sig. (2-tailed) 0.902 0.467 0.005 0.003 0.39 0.643 0.017

N 100 100 100 100 100 100 100 100

UB Pearson Correlation .341 0.146 0.039 .296 1 0.007 -.380 0.165

Sig. (2-tailed) 0.001 0.147 0.697 0.003 0.946 0 0.101

N 100 100 100 100 100 100 100 100

JBH Pearson Correlation -0.043 0.042 0.009 0.087 0.007 1 -.236 0.131

Sig. (2-tailed) 0.672 0.675 0.927 0.39 0.946 0.018 0.193

N 100 100 100 100 100 100 100 100

B100 Pearson Correlation -.269 -0.052 -0.1 -0.047 -.380 -.236 1 -0.105

Sig. (2-tailed) 0.007 0.61 0.322 0.643 0 0.018 0.297

N 100 100 100 100 100 100 100 100

PS Pearson Correlation -0.132 0.087 -0.048 .239 0.165 0.131 -0.105 1

Sig. (2-tailed) 0.189 0.388 0.638 0.017 0.101 0.193 0.297

N 100 100 100 100 100 100 100 100

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

Notes:

TT: Plant Height (cm); UB: Flowering age (hr); LK: Canopy Width; JBH: Fruit/plant; JB: Number of epidermis (mm2); B100: Weight of 100 fruits (gram); UK:Flower bud age(day); PS: % fiber.

CV values of the characters were 65%, 59%, 42%, and 45% respectively. The coefficient of diversity was 20% Alnopri & Hermiati (1992). High diversity values indicate that these characters have a wide variety. This provides an opportunity for breeders to make a selection to choose superior accession. The budding age, number of fruits/plants, weight of 100 fruits and percentage of fiber with CV values of 17%, 14%, 5.3%, and 9.4%. These possess low diversity coefficient as the CV value is below 20%.

Table 3 - Descriptive Statistics of quantitative characters of cotton germplasm

n/n N Range Minimum Maximum Mean Std. Error Std. Deviation Variance CV (%)

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Statistic Statistic Statistic Statistic Statistic Statistic Statistic Statistic

TT 100 118.8 86.2 205 1.42E+02 2.57794 25.77937 664.576 65

LK 100 161.5 12.5 174 1.14E+02 2.36365 23.63647 558.683 17

JB 100 296 0 296 40.376 6.21773 62.17734 3.87E+03 59

UK 100 19 40 59 44.5 0.26419 2.64193 6.98 42

UB 100 29 51 80 55.36 0.38938 3.89384 15.162 45

JBH 100 355.6 10.4 366 25.931 3.48925 34.89251 1.22E+03 14

B100 100 468 294 762 5.40E+02 10.18266 101.82656 1.04E+04 5.3

PS 100 37.76 16.67 54.42 37.7625 0.40043 4.00431 16.034 9.4

Valid N (listwise) 100

The density of epidermis is often used by plant breeders to control the attack of sucker piercing insects. Amrasca biguttula (Empoasca sp.) is the main cotton plant pest in Indonesia, which is very detrimental because it can attack cotton plants starting from young plants to old plants. Great attacks occur if the environmental conditions are dry due to lack of rain. These pests attack the plant by sucking the leaf liquid, the plants attacked the leaves

become curly and curved downward. In heavy attacks the leaves are red-brown, dry, then the expression is influenced by the genes H2, H3, H4, and H5, (Hendrizzi et al., 1984). The density of epidermis on Ballitas cotton germplasm varied from 0 - 587 trichomes per 25 mm2. The density of epidermis was calculated using the Robinson method, et al., (1980), 5 mm x 5 mm square was carved on the lower leaf lamina, the number of the epidermises (trichomes) was calculated based the square. The trichome number category per square centimeter (cm2) according to Kartono (1991), is: <121 = no epidermis; 121 - 240 = small number of epidermis; 241 - 360 = medium epidermis; 361 - 480 = large number of epidermis; > 480 = huge number of epidermis. Cotton varieties with epidermisless properties possess high tannin and terpene content. It is capable to reduce Helicoverpa armigera pest attacks up to 50% (Benedict et al., 1992). The diversity of epidermis from 100 accessions observed exhibited a diversity of CV 59%.

Table 4 - Qualitative characteristics of cotton germplasm

Qualitative Characters Percentage (%)

1. Flower position Clustered Not Clustered 2 98

2. Leaf color Green Light Green Green Dark Green Reddish Purple 97 0 0 1 2

3. Leaf shape Palmate Normal Twisted Normal Palmate Normal Twisted 8 84 5 2 1

4. Nectar Exist Nonexistent Exist/Nonexistent 90 9 1

5. Crown color Beige Yellow Beige/Yellow Yellow/Purple 87 4 1 8

6. Spots on the flower crown Exist Non Existent 4 96

7. Pollen colour Beige Yellow Beige Purple Beige Yellow Purple Yellow 72 1 0 27 0

8. Pistil Position Above Parallel 76 24

9. Petal shape Twisted Normal 1 99

10. stem color Reddish Green Dark Green Purplish Red 95 2 3

11. plant shape Compact Cylindric Prostrate 35 5 60

12. fruit shape sharpness Pointy Spiky Sharp Blunt 5 92 1 3

13.Fruit skin texture Smooth Medium Coarse 3 82 15

14.Fiber color White Light Brown Light Green Brown 96 2 1 1

The density of the epidermis is one of the characteristics of a variety of options as accessions resistant to sucker piercing pests, which are the main cotton plant pest in Indonesia. Great attacks occur if the environmental conditions are dry due to lack of rain. Hendrizzi et al., (1984), suggested that the Amasca biguttula attacks plants by sucking in leaf fluid. Attacked plants leaves become curly and curved downward. In heavy attacks the leaves are red-brown, dry, then their expression is influenced by genes H2, H3, H4, and H5. The density of epidermis in Ballitas cotton germplasm varies from 0 - 587 trichomes per 25 mm2. The density of epidermis was calculated using the Robinson, et al., (1980) method, a square of 5 mm x 5 mm was carved in the lower leaf lamina, the number of the epidermises (trichomes) was calculated based on existing epidermis in the square.

Germplasm plasma is observed as a qualitative character, carried out if the conditions have met the requirements in accordance with the reference (Suratman & Setyawan, 2000). The results of the observations exhibited a diversity of all characters observed (Table 4). The observation of the character of the 100 accessions observed: 98% is not clustered and 2% are clustered, meaning that the diversity is very low. The color characteristics of the leaf diversity are very low, such as green (97%), light green (0%), green (0%), dark green (1%), and reddish purple (2%). Plant shape characters are compact (35%), cylindrical (5%), and Prostrate (60%).

From the observation of the character of cotton, leaf shape varies, namely: palmate (8%), normal (84%), normal twisting (5%), normal palmate (2%), and twisting (1%). exhibited that the diversity is quite high. Leaf shape is an important character in the classification of varieties. Wilson and George (1982), suggested that the nature of the okra leaf leaves can reduce the egg deposit of Helioverpa armigera, increase resistance to Peptinopora gossypiella, and reduce fruit rot disease. On average the cotton on the leaves has the nectar glands. Out of the 100 accessions observed, only one accession which nectar existence is unclear, 99% exist and 9% of accessions nonexistent. Wilson (1976), suggested that the nectar is one of the important properties for resistance to flower buds and fruit piercer. The color of the flower crowns on 100 accessions was varied: beige (57%), yellow (3%), yellow/beige (1%) and yellow/purple (8%). The crown color of the Gossypium tetraploid species is controlled by the duplication of Y1 and Y2 Hutchison and Silow genes, 1939. In Kohel and Lewis (1984), it is suggested that yellow is all allotetraploid except yellow in G. From this gene Y1 is controlled by Y2 gene according to Stephens (1954 b In Kohel and Lewis, 1984). Y1 gene in sub-genomics possesses chromosome 18 D Y2 gene. The genome is D. The yellow flower crown is usually found in G. barbadense, (Endrizzi, 1975 In Kohel and Lewis, 1984), but often found in Pima cotton (Turcottte and Feaster, 1963 In Kohel and Lewis, 1984). The beige-colored flower crown is found in G. hirsutum cultivars which are controlled by the y1y1y2y2 gene but also found in yellow flower crowns on wild relatives. The spots on the flower crown possess low diversity. The spotted ones were (5%) and no spot(95%). The color of pollen is quite varied which includes: beige (72%), yellow beige (1%), purple beige (0%), yellow (27%), and purple yellow (0%). Harlan (1929) In Kohel and Lewis (1984), suggested that pollen color is controlled by a pair of P and p genes. Whereas the yellow color is dominant in beige. The position of the pistil is above (76%) and parallel (24%). The petal shape diversity is very low: twisted (1%) and normal (99%). The stem color character diversity is very low: reddish green (95%), dark green (2%) and purplish red (3%). Stephenss, (1974 a), suggested that the red color of the stem was caused by the presence of anthocyanin substances which pigmentation was expressed on the tissues of the leaf sertan on the base of the flower crown which usually occurs in cotton breedd in Asia. The sharpness of the fruit shape, spiked fruit reached (92%), pointy fruit (5%), sharp (1%) and blunt (3%). The fruit skin coarseness exhibited: smooth (3%), medium (82%) and coarse (15%). The variation of fiber color character is also very low, the dominant color is white which reaches 96%, light brown (2%), light green (1%) and brown 1%. Fruit skin texture diversity is smooth (3%), medium (82%), and coarse (15%).

The genetic relationship is an effort to find out the relationship between genotypes in the accession of cotton plants. Furthermore, based on the genetic similarities the character will be classified, by describing the level of genetic variability, used for genetic analysis

based on morphological characters. Prior to carrying out a cluster analysis for germplasm grouping, it is important to determine whether the variables observed are mutually independent. Maji & Shaibu (2012), suggests that if there is a correlation between the variables observed, it is necessary to analyze the main components first, before conducting a cluster analysis. The results of the correlation analysis exhibited no real correlation between the characters observed. Subsequent cluster analysis was carried out using characters that contributed to the diversity of the first six main components because the proportion of diversity reached more than 80% and eigenvalues> 1. Joliffe (1967) gave the limitation that cluster analysis was carried out using characters the proportion of diversity> 80% and eigenvalues> 1. The results of the cluster analysis exhibited that the Balittas cotton germplasm collection was divided into VI levels of similarity that had a relatively high diversity. At the level of similarity I of germplasm is divided into 3 major groups, at the level of similarity II is divided into 4 groups, in similarity III is divided into 5 major groups, in similarity IV is divided into 2 major groups, in similarity V is divided into 2 major groups and in similarity VI is divided into 6 large groups (Figure 1). Grouping based on the country of origin of germplasm consists of Indonesian commercial varieties, United States of America (USA), South America, Europe, Asia, Africa, and Australia with a diversity of 84.90%. Categorized germplasm diversity can be used as an important source of information to assess potential accession. Accession from different groups possess significantly different character, therefore a high diversity of morphological characters in the managed population provides wider opportunities for the improvement of plant varieties. To obtain information on the diversity of crucial agronomic traits, which can later be used as elders selected in cultivation programs. Accessions possessing a genetic distance from different groups can be selected, information on the diversity of morphological characters also opens up opportunities for improved varieties with resistance to biotic and abiotic stresses. Cluster analysis method could be used to determine the characters that contribute to population diversity (Khodadadi et al. 2011). Tresniawati & Randriani (2008), stated that germplasm grouping can describe genetic relationships between accessions. This may provide information regarding character traits from each accession group formed.

II

III

VI

Indonesian Commercial varieti

United State of America (USA) South America Europe

South America

Indonesian Commercial varieties

Africa

Asia

Australia

Figure 1 - Dendrogram average linkage, euclidian distance

CONCLUSION

The results of the qualitative morphological characterization exhibited diverse characters: low (flower position, spots on the flower crown, pollen color, fiber color, and petal shape), medium (nectar, crown color, stem color, and fruit shape sharpness) and height (position of pistil, plant shape and fruit skin coarseness).

The results of the quantitative morphological characterization exhibited high diversity with CV values: number of leaves (65%) flowering age (59%), plant height (42%), and canopy width (45%).

The results of the cluster analysis indicate that the Balittas germplasm collection is divided into 6 large groups of similarity level and possess relatively high diversity. At the level of similarity I of germplasm is divided into 3 major groups, at the level of similarity II is divided into 4 groups, in similarity III is divided into 5 major groups, in similarity IV is divided into 2 major groups, in similarity V is divided into 2 major groups, and in the similarity VI is divided into 6 large groups (Figure 1). Based on country of origin grouping, germplasm consists of Indonesian commercial varieties, United State of America (USA), South America, Europe, Asia, Africa, and Australia with a diversity value of 88.90%.

REFERENCES

1. Akhtar, MS, Oki, Y, Adachi, T & Khan MHR. 2007. Analyses of the genetic parameters: variability, Heritability, Genetic Advance, Relationship of Yield and Yield Contributing Characters) for some plant traits among Brassica cultivars under phosphorus-starved environmental cues. Journal of the Faculty of Environmental Science and Technology, 12:91-98.

2. Alnopri, R.S.S. & Hermiati, N. 1992. Kriteria seleksi berdasarkan sifat morfologi tanaman kopi robusta. Zuriat 3:18-22.

3. Bozokalfa, MK, Esiyok, D & Turhan, K. 2009, Patterns of phenotypic variation in a germplasm collection of pepper (Capsicum annuum L.) from Turkey. Spanish Journal of Agricultural Research, 7(1):83-95.

4. Bari, S & Musa. 1974. Pengantar Pemuliaan Tanaman , Institut Pertanian Bogor. 60p

5. Bermawi, N. 2005. Karakterisasi Plasma Nutfah Tanaman. In Luntungan, H.T., Karmawati, E., Hartati, R.S. (Eds). Buku Pedoman Pengelolaan Plasma Nutfah Perkebunan. Pusat Penelitian dan Pengembangan Perkebunan, Bogor, Indonesia

6. Sumarno. 2002. Penggunaan bioteknologi dalam pemanfaatan dan pelestarian plasma nutfah tumbuhan untuk perakitan varietas unggul. National Seminar on "Pemanfaatan dan Pelestarian Plasma Nutfah". Pusat Penelitian Biologi IPB & Komisi Nasional Plasma Nutfah, Indonesia.

7. Suratman, P.D. & Setyawan, A.D. 2000. Analisis keragaman genus Ipomea berdasarkan karakter morfologi, Biodiversitas, 1(2):72-79.

8. Suhartini, T & Sutoro. 2007, Pengelompokan plasma nutfah spesies padi liar (Oryza spp.) berdasarkan peubah kuantitatif tanaman. Berita Biologi, 8(6):445-453.

9. Setyowati, M., Hanarida, I., & Sutoro. 2009. Pengelompokan plasma nutfah gandum (Triticumaestivum) berdasarkan karakter kuantitatif tanaman. Buletin Plasma Nutfah, 15(1):32-37.

10. Lewis, C.F. 1982. Genetic Engineering for Improving Environmental Resiliency in Crop Species. In Cristianson and Lewis. Breeding Plant for Less Favorable Environments. Interscience Publication, 435-439.

11. Lule, D., Tesfaye, K., Fetene, M., & de Villiers S. 2012. Multivariate analysis for quantitative traits in finger millet (Eleusine coracana subsp. coracana) population collected from Eastern and Southeastern Africa: detection patterns of genetic diversity. International Journal of Agricultural Research, 7(6):303-314.

12. Furat, S & Uzun, B. 2010. The use of agro-morphological characters for the assessment of genetic diversity in sesame (Sesame indicum L.). Plant Omics Journal, 3(3):85-91.

13. Joliffe, I.T. 2002. Principal Component Analysis Second Edition, Springer-Verlag Inc, New York, 518p.

14. Nilasari, A.N., Heddy, J.B.S., & Wardiyati T. 2013, Identifikasi keragaman morfologi daun mangga (Mangifera indica L.) pada tanaman hasil persilangan antara varietas Arumanis 143 dengan Podang Urang umur 2 tahun. Jurnal Produksi Tanaman, 1(1):61-69.

15. Hendrizzi, E.L. Turcotte & R.J. Kohel. 1984. Quantitative genetics cytology and cytogenetics In. R.J. Kohel and C.F. Lewis (Eds). Cotton ASA. Inc. CSSA In. Publisher Madizon. Agronomy Series N0 24. Pp 81-129.Monosomic analysis of 23 mutant loci in cotton. In R.J. Kohel and C.F. Lewis (Eds.). Cotton ASA. Inc. CSSA Ins. Publisher Madison. Agronomy Series N. 24. Pp. 81 - 129.

16. Kohel, R.J. and Lewis. 1984. Growth analysis of cotton with differing maturities. Agron. J. 70: 31 -34.

17. Maji, A.T. & Shaibu, A.A. 2012. Application of principal component analysis of rice germplasm characterization and evaluation, Journal of Plant breeding and Crop Science, 4(6):87-93.

18. Khodadadi, M, Fotokian, MH &Miransari, M 2011, Genetic diversity of wheat (Triticum aesticum L.) genotypes based on cluster and principal component analyses for breeding strategies, Australian Journal of Crop Science, 5(1):17-24.

19. Tresniawati, C & Randriani, E. 2008. Uji kekerabatan koleksi plasma nutfah macadamia(Macadamia integrifolia Maiden & Betche) di Kebun Percobaan Manoko, Lembang, Jawa Barat. Buletin Ristri, 1(1): 25-31.

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