Parida, Luluk Ayu
Politeknik Negeri Lampung

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Determinasi Kualitas dan Kuantitas Minyak Biji Kapas Berdasarkan Analisis Keragaman Genetik pada 22 Aksesi Plasma Nutfah Kapas Parida, Luluk Ayu; Tahir, M.; Kusuma, Jakty
Jurnal Agro Industri Perkebunan Volume 7 No. 1, 2019
Publisher : Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (0.036 KB) | DOI: 10.25181/jaip.v7i1.1054


Cotton plants belong to the family Malvaceae with the genus Gossypium. The genus Gossypium is very large containing 50 species. Balittas Malang has a collection of cotton germplasm, about 662 accessions consisting of 642 accessions of G. hirsutum, 14 accessions of G. barbadense, 3 accessions of G. arboreum, and 3 accessions of G. herbaceum. In addition to its ability as a producer of fiber, its seeds can also be utilized as a source of oil and is a secondary production. The purpose of this study was to measure and estimate the genetic diversity of cotton germplasm based on the character of superior quality and quantity of cotton seed oil from several cotton plant genotypes and determine which cotton plants have good quality and quantity of cotton seed oil which is subsequently used as breeding sources & national cotton development elders. To achieve this goal, the experiment was conducted with the experimental method Randomized Block Design (RBD) consisting of 2 replications, 22 germplasm accessions as treatment, and 5 samples in each genotype. The observational parameters are the parameters of oil content quality, oil boiling point, oleic content, and linoleic content. Then the cluster analysis shows that there are 3 cluster analysis groups. Extensive genetic diversity will be beneficial in developing better quality and quantity of cottonseed oil, namely in accession of CRISS-665, CRISS-667, and KANESIA-14 which contribute more than accession of other cotton germplasm to the maximum value of quantity and quality parameters cotton seed oil.Keywords: agronomic evaluation, G. barbadense, G. hirsutum, phenotypic data analysis