DIVERSITAS GENETIK  KERABAT LIAR UBI JALAR IPOMOEA TRIFIDA (H.B.K.) G.DON. BERUMBI ASAL CITATAH JAWA BARAT BERDASARKAN KARAKTER KROMOSOM (Genetic Diversity Of Wild Relative Of Sweet Potato  Tubered-Ipomoea Trifida (H.B.K.) G.don. Originated From Citatah West Java  Based On Chromosome  Characters)

AbstrakKerabat liar ubi jalar Ipomoea trifida asal Citatah Jawa Barat potensial digunakan dalam program pemuliaan tanaman ubi jalar (Ipomoea batatas (L.) Lam.) Untuk mengetahui diversitas genetik I. trifida dilakukan pengamatan terhadap karakter kromosom. Bahan tanaman yang digunakan adalah 10 spesies I. trifida berumbi. Hubungan kekerabatan antar spesies diketahui melalui analisis klaster dan Analisis Komponen Utama/Principal Component Analysis (PCA). Hasil pengamatan menunjukkan pengujian pada 10 aksesi I. trifida berumbi dengan menggunakan 9 karakter kromosom menghasilkan jarak ketidakmiripan (Euclidean coeffisien) yang berkisar 1,75 – 6,22 dan menunjukkan diversitas yang luas. Dendogram yang dihasilkan pada jarak ketidakmiripan 5,23 menunjukkan terbentuknya 3 klaster utama. Analisis Komponen Utama (PCA) menghasilkan 2 komponen utama pertama (PC1 dan PC2) yang telah dapat menjelaskan 89,64% dari total variasi. Kata kunci : Ipomoea trifida, Analisis Klaster, Analisis Komponen UtamaAbstractWild relatives of sweet potato, Ipomoea trifida originated from Citatah West Java was potential use in plant breeding programs of Ipomoea batatas (L.) Lam. To determine the genetic diversity of I. trifida, observation on characters of chromosomes of I.trifida was conducted. Plant materials used ten accessions of tubered-I. trifida. Relationship between species identified by cluster analysis and Principal Component Analysis (PCA). The results showed that the observation on the 10 accession of tubered-I. trifida using 9 characters chromosome produces dissimilarities distance (Euclidean coefficient) ranging from 1.75 to 6.22. Dendogram generated at a dissimilarity distance of 5.23 showed the formation of three main clusters. Principal Component Analysis (PCA) produced first two principal component (PC1 and PC2), which has been able to explain 89.64% of the total variation.Keyword : Ipomoea trifida, Clustering Analysis, Principal Component Analysis

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Morphological Variability and Storage Root Productivity of Some Sweet Potato (Ipomoea Batatas (L.) Lam) Genotypes in An Ultisol

International Journal Of Scientific Advances ◽

10.51542/ijscia.v2i6.20 ◽

2021 ◽

Vol 2 (6) ◽

Author(s):

Gamaliel I. Harry ◽

Joseph I. Ulasi

Keyword(s):

Principal Component Analysis ◽

Sweet Potato ◽

Ipomoea Batatas ◽

Principal Component ◽

Component Analysis ◽

The Other ◽

Storage Root ◽

Root Yield ◽

Cropping Seasons ◽

And Storage

Ten sweet potato (Ipomoea batatas (L.) Lam) genotypes sourced from National Root Crops Research Institute, Umudike were evaluated under rainfed condition in 2020 and 2021 cropping seasons at the Teaching and Research Farm of the University of Uyo, Uyo, Akwa Ibom State to ascertain variability among ten sweet potato genotypes and identify traits which are positively and significantly associated with yield and also identify genotypes with high yield potential for cultivation on an ultisol of Akwa Ibom State, Nigeria. The ten genotypes: TIS87/0087, Naspoy-12, Umuspo-4, Umuspo-1, Naspoy-11, Lourdes, Erica, Delvia, Ex-Igbariam and Umuspo-3 were used as treatments and the experiment was laid out in a randomized complete block design with three replications. Data collected were subjected to analysis of variance, correlation and principal component analysis. The genotype differs significantly (P≤ 0.05) for number of marketable roots, weight of marketable roots and fresh roots yield. UMUSPO-3 was superior over all the other genotypes for the following character; number of marketable roots, weight of marketable root yield and fresh root yield. Umuspo-3 produced the highest storage root yield (28.78t/ha, 27.09t/ha) in 2020 and 2021 cropping seasons, respectively. The result of the correlation analysis also revealed that vine length, number of marketable roots, weight of marketable were highly significantly and positively (P<0.01) correlated with fresh root yield. Principal component analysis (PCA) had four main principal components explaining 81.55% of the total variation with number of marketable roots, weight of marketable tuber and storage root yield contributing the most to the first PCA. Umuspo-3 outperformed the other nine sweet potato genotypes in yield and yield related characters. Therefore, Umuspo-3 been a high yielding genotype adaptable to Uyo agro-ecology, could be recommended to sweet potato growers for fresh storage root production.

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Yield Determinants of Some Sweet Potato (Ipomoea batatas L) Clones Using Principal Component Analysis

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/828/1/012006 ◽

2021 ◽

Vol 828 (1) ◽

pp. 012006

Author(s):

M W Lestari

Keyword(s):

Principal Component Analysis ◽

Sweet Potato ◽

Ipomoea Batatas ◽

Principal Component ◽

Component Analysis ◽

Yield Determinants

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Pengelompokan Klon-Klon Ubi Jalar Berdasarkan Analisis Gerombol, Komponen Utama dan Biplot dari Karakter Morfologi

Jurnal Agronomi Indonesia (Indonesian Journal of Agronomy) ◽

10.24831/jai.v46i3.18215 ◽

2019 ◽

Vol 46 (3) ◽

pp. 276-282

Author(s):

Helen Hetharie ◽

Simon Hadi Teguh Raharjo ◽

Dan Edizon Jambormias

Keyword(s):

Principal Component Analysis ◽

Sweet Potato ◽

Ipomoea Batatas ◽

Principal Component ◽

Component Analysis ◽

Morphological Characters ◽

Similarity Coefficients ◽

Biplot Analysis ◽

Tuber Flesh ◽

Descriptive Method

Sweet potato is a food crop with high genetic and phenotypic diversities. The objective of this study was to cluster sweet potato clones based on their morphological characters. This research used descriptive method using 25 morphological characters on 28 sweet potato clones and clustered using dice coefficient, principal component analysis and biplot analysis. The results showed that the clones were grouped into two clusters and 14 sub-clusters. Three sub-clusters had high similarity coefficients, i.e., 0.68-0.96, one clone was eliminated, and 11 sub-clusters had a low similarity, i.e., 0.41-0.52. The principal component analysis showed 14 of 25 morphological characters determined the diversity in 27 sweet potato clones with cumulative variance of 70.79%. Biplot analysis showed that 12 characters contributed to cumulative variance of 61.3%. Twelve morphological characters had weak contribution on the characteristics of the clones in quadrant I; meanwhile, characteristics of clones in quadrant II were orange, yellow and white tuber flesh, in quadrant III was dark purple tuber flesh, and in quadrant IV were purple tuber flesh and cortex. Result of the grouping analysis identified clones that were closely related and those distantly related for improvement purposes.Keywords: Ipomoea batatas, cumulative variance, Maluku province, morphology, relationship

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Assessment of genetic diversity in pea (Pisum sativum L.) landraces based on physico-chemical and nutritive quality using cluster and principal component analysis

Pakistan Journal of Botany ◽

10.30848/pjb2020-2(2) ◽

2019 ◽

Vol 52 (2) ◽

Author(s):

Uzma Arif ◽

Muhammad Jamil Ahmad ◽

Malik Ashiq Rabbani ◽

Ayaz Ahmed Arif

Keyword(s):

Genetic Diversity ◽

Principal Component Analysis ◽

Pisum Sativum ◽

Principal Component ◽

Component Analysis ◽

Pisum Sativum L ◽

Nutritive Quality ◽

Physico Chemical

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Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

Legume Research - An International Journal ◽

10.18805/lr-4561 ◽

2021 ◽

Author(s):

S.R. Singh ◽

S. Rajan ◽

Dinesh Kumar ◽

V.K. Soni

Keyword(s):

Genetic Diversity ◽

Principal Component Analysis ◽

Cluster Analysis ◽

Principal Component ◽

Component Analysis ◽

Single Linkage ◽

Pod Yield ◽

Diversity Assessment ◽

Single Linkage Cluster ◽

Linkage Cluster

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

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↵Genetic Diversity and Principal Component Analysis in Mungbean [Vigna radiata (L.) Wilczek] under Rainfed Condition

Legume Research - An International Journal ◽

10.18805/lr-4568 ◽

2021 ◽

Author(s):

Deepak Gupta ◽

Suresh Muralia ◽

N.K. Gupta ◽

Sunita Gupta ◽

M.L. Jakhar ◽

...

Keyword(s):

Genetic Diversity ◽

Principal Component Analysis ◽

Cluster Analysis ◽

Seed Yield ◽

Agricultural Research ◽

Principal Component ◽

Component Analysis ◽

Grain Legume ◽

Research Station ◽

Rainfed Condition

Background: Mungbean is a short duration grain legume widely grown in south and Southeast Asia. The extent of variability through Principal Component Analysis (PCA) and cluster analysis in promising mungbean genotypes should be known for possible yield improvement. A study was undertaken to work out the extent of variability among twenty four mungbean genotypes through cluster analysis and Principal Component Analysis (PCA). Methods: The experiment was laid out in a randomized block design with three replications during kharif 2018 and 2019 at the experimental field of Agricultural Research Station, Navgaon (Alwar) under rainfed condition. Result: Principal component analysis revealed that the first three main PCAs amounted 78.80% of the total variation among genotypes for different traits. Out of total principal components, PC1 accounts for maximum variability in the data with respect to succeeding components. Number of branches per plant (28.62%), number of clusters per plant (23.55%) and seed yield (15.58%) showed maximum per cent contribution towards total genetic divergence on pooled basis. Cluster analysis showed that genotypes fall into seven different clusters and their inter and intra cluster distance showed genetic diversity between different genotypes. The maximum number of genotypes i.e., 8 was found in cluster II followed by cluster III comprising of 6 genotypes. Genotypes RMG-1138 and IPM-02-03 representing the mono genotypic cluster signifies that it can be the most diverse variety and it would be the appropriate genotype for hybridization with ones present in other clusters to tailor the agriculturally important traits and ultimately to boost the seed yield in mungbean under rainfed conditions.

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Comparative study of the physicochemical, compositional and functional properties of eight flours obtained from different plant materials found in Colombia

Food Science and Technology International ◽

10.1177/1082013216642611 ◽

2016 ◽

Vol 22 (8) ◽

pp. 699-707 ◽

Cited By ~ 2

Author(s):

Seneida Lopera-Cardona ◽

Cecilia Gallardo ◽

Jairo Umaña-Gallego ◽

Lina María Gil

Keyword(s):

Principal Component Analysis ◽

Functional Properties ◽

Principal Component ◽

Component Analysis ◽

Ananas Comosus ◽

Whole Grain ◽

Plant Materials ◽

Pineapple Peel ◽

Yellow Peas ◽

Oyster Mushrooms

The physicochemical, compositional and functional properties of flour from green plantains ( Musa acuminata) of the large green plantain variety, oyster mushrooms ( Pleorotus ostreatus), pineapple peel ( Ananas comosus) of the ‘apple pineapple’ variety, yellow peas ( Pisum sativum), chickpeas ( Cicer arietinum), whole grain rice ( Oryza sativa), whole grain corn ( Zea mays) and whole grain white quinoa (Chenopodium quinoa) were evaluated by using one-way analysis of variance, Pearson correlations and principal component analysis chemical composition of the eight flours, statistically differed ( p < 0.05). Oyster mushroom and yellow pea flours had the greatest protein content (28.92 and 21.02%, respectively), whereas the pineapple peel, peas and corn stood out for their high contents of Fe and Zn. All flours exhibited emulsifying and foaming activities, while hydration and interfacial properties showed statistically significant negative correlations. There was a clear relationship between levels of protein and carbohydrates and gelation and syneresis phenomena in thermally treated flour suspensions. According to principal component analysis of functional, physicochemical and compositional properties, flours were classified into five groups of raw materials: (1) yellow peas, (2) chickpeas, rice, corn and quinoa, (3) green plantain, (4) pineapple peel and (5) oyster mushrooms. Results are promising to formulate mixes and composite flours for fortification and/or enrichment of food products by using different technological processes.

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