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http://dx.doi.org/10.17576/jsm-2020-4903-01
Multivariate Analysis of Superior
Helianthus annuus L. Genotypes Related
to Metric Traits (Analisis Multivariat Genotip Superior
Helianthus annuus L. berkaitan Sifat Metriks) ADEEL
RIAZ1,2*, MUHAMMAD SHAHID IQBAL3, SAJID FIAZ4,
SADARUDDIN CHACHAR2,
RAI MUHAMMAD AMIR5 & BISMA RIAZ6 1Department of Plant Breeding and Genetics, University
of Agriculture Faisalabad, Pakistan 2Biotechnology Research Institute, Chinese Academy
of Agricultural Sciences, Beijing, 100081, China 3Cotton Research Institute, Chinese Academy of
Agricultural Sciences, Anyang, China 4State Key Laboratory of Rice Biology, China
National Rice Research Institute, Hangzhou, 310006, China 5Institute of Food and Nutritional Sciences,
PMAS-ARID Agriculture University. Rawalpindi, Pakistan 6Institute of Crop Sciences, Chinese Academy
of Agricultural Sciences, Beijing, 100081, China Diserahkan:
26 November 2018/Diterima: 11 November 2019 ABSTRACT To increase seed yield and oil contents,
variability in breeding material is a pre-requisite. Plant material
was comprised of forty-nine sunflower genotypes to investigate the
variability and identification of superior genotypes by multivariate
analysis. The data were recorded for ten quantitative traits; days
to maturity (DM), plant height (PH), stem diameter (SD), head diameter
(HD), number of leaves (NOL), achene per head (APH), achene yield
per plant (AYP), 100- achene weight (100AW), filled achene percentage
(FA) and oil contents (OC). The genotypes showed significant variation
for all traits except OC. A
highly significant association of achene yield was observed with
100AW. Principal component analysis (PCA) separated into four components
(PC-I, II, III, IV) with Eigenvalue greater than one accounting
for 62.63% of the total variation. Total variance percentage was
maximum in PC-I (24.4%) followed by PC-II (14.70%). Cluster analysis
further classified the sunflower genotypes in three clusters based
on seed yield and its related traits. A maximum number of genotypes
were included in cluster I (26 genotypes) followed by cluster III
(11 genotypes) contributing 65.30%, 24.48%, respectively of total
genotypic strength. In addition, maximum number of traits were included
in cluster III followed by cluster II. PH and NOL were closest of
all the ten traits suggesting their strong correlation. Taken together,
these results can be useful for breeders to develop high yielding
sunflower hybrids. Keywords: Biplot; cluster analysis; multivariate; PCA; sunflower ABSTRAK Dalam
usaha meningkatkan hasil benih dan kandungan minyak, kepelbagaian
bahan pembiakan adalah pra-syarat. Bahan tumbuhan terdiri daripada
49 genotip bunga matahari untuk mengkaji kepelbagaian dan pengenalpastian
genotip superior oleh analisis multivariat. Data direkodkan untuk
sepuluh ciri kuantitatif; hari kepada kematangan (DM), ketinggian
tumbuhan (PH), diameter stem (SD), diameter kepala (HD), bilangan
daun (NOL), aken setiap kepala (APH), hasil aken setiap tumbuhan
(AYP), berat 100-aken (100AW), peratusan aken tetisi (FA) dan kandungan
minyak (OC). Genotip menunjukkan variasi ketara bagi semua ciri
kecuali OC. Satu pertalian yang sangat signifikan untuk hasil aken
diperhatikan dengan 100AW. Analisis komponen utama (PCA) dipisahkan
kepada empat komponen (PC-I, II, III, IV) dengan nilai eigen lebih
besar daripada satu untuk mewakili 62.63% daripada jumlah ubahan.
Peratus jumlah varians adalah maksimum dalam PC-I (24.4%) diikuti
dengan PC-II (14.70%). Analisis kelompok seterusnya mengelaskan
genotip bunga matahari dalam tiga kelompok berdasarkan hasil benih
dan ciri berkaitan. Bilangan maksimum genotip telah dimasukkan dalam
kelompok I (26 genotip) diikuti oleh kelompok III (11 genotip),
masing-masing menyumbang kepada 65.30% dan 24.48% daripada jumlah
kekuatan genotip. Tambahan pula, bilangan ciri maksimum dimasukkan
dalam kelompok III diikuti oleh kelompok II. PH dan NOL adalah paling
hampir daripada semua sepuluh ciri yang menunjukkan korelasi mereka
yang kukuh. Dengan mengambil kira keputusan ini, penternak boleh
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