2016The Philippine Agricultural ScientistOpen access

Multivariate Analysis of Yield Components and Some Morphological Traits of Safflower (Carthamus tinctorius L.) Genotypes

Ramin Baljani, F. Shekari, Naser Sabaghnia

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Abstract

The study determined the relationships among yield, yield components and other morphological traits using 64 genotypes of safflower (Carthamus tinctorius L.). Leaf area (LA), dry weight of plant (DWP), plant height (PH), main capitulum diameter (MCD), lateral capitulum diameter (LCD), number of capitulum per plant (NCP), number of seeds per capitulum (NSC), seed yield (SY), thousand seed weight (TSW), oil content percent (OP), harvest index (HI), total biomass (TB) and oil yield (OY) were evaluated. Principal component analysis (PCA) and factor analysis (FA) were used for a better understanding of the data structure and trait relations. PCA indicated that four components explained 91% of the total variation among traits. The first principal component (PC) was assigned 71% and the second PC component was assigned 9% of the total variation among traits. The first PC was named as yield potential; the second PC was named as height and biomass; and the selection may be done according to the first PC for the development of high-yielding safflower cultivars. According to the plot of the first two PCs, the most prominent relations were a strong positive association between seed yield with number of seeds per capitulum, leaf area and dry weight of plant traits. Factor analysis divided the traits into four factors and the factors were similar to the above-mentioned PCs. Finally, based on the obtained results of PCA and FA methods, number of capitulum per plant, dry weight of plant, main and lateral capitulum diameter and harvest index are the traits to be considered by breeders for the improvement of safflower seed yield.

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The study determined the relationships among yield, yield components and other morphological traits using 64 genotypes of safflower (Carthamus tinctorius L.). Leaf area (LA), dry weight of plant (DWP), plant height (PH), main capitulum diameter (MCD), lateral capitulum diameter (LCD), number of capitulum per plant (NCP), number of seeds per capitulum (NSC), seed yield (SY), thousand seed weight (TSW), oil content percent (OP), harvest index (HI), total biomass (TB) and oil yield (OY) were evaluated. Principal component analysis (PCA) and factor analysis (FA) were used for a better understanding of the data structure and trait relations. PCA indicated that four components explained 91% of the total variation among traits. The first principal component (PC) was assigned 71% and the second PC component was assigned 9% of the total variation among traits. The first PC was named as yield potential; the second PC was named as height and biomass; and the selection may be done according to the first PC for the development of high-yielding safflower cultivars. According to the plot of the first two PCs, the most prominent relations were a strong positive association between seed yield with number of seeds per capitulum, leaf area and dry weight of plant traits. Factor analysis divided the traits into four factors and the factors were similar to the above-mentioned PCs. Finally, based on the obtained results of PCA and FA methods, number of capitulum per plant, dry weight of plant, main and lateral capitulum diameter and harvest index are the traits to be considered by breeders for the improvement of safflower seed yield.

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Available abstract

The study determined the relationships among yield, yield components and other morphological traits using 64 genotypes of safflower (Carthamus tinctorius L.). Leaf area (LA), dry weight of plant (DWP), plant height (PH), main capitulum diameter (MCD), lateral capitulum diameter (LCD), number of capitulum per plant (NCP), number of seeds per capitulum (NSC), seed yield (SY), thousand seed weight (TSW), oil content percent (OP), harvest index (HI), total biomass (TB) and oil yield (OY) were evaluated. Principal component analysis (PCA) and factor analysis (FA) were used for a better understanding of the data structure and trait relations. PCA indicated that four components explained 91% of the total variation among traits. The first principal component (PC) was assigned 71% and the second PC component was assigned 9% of the total variation among traits. The first PC was named as yield potential; the second PC was named as height and biomass; and the selection may be done according to the first PC for the development of high-yielding safflower cultivars. According to the plot of the first two PCs, the most prominent relations were a strong positive association between seed yield with number of seeds per capitulum, leaf area and dry weight of plant traits. Factor analysis divided the traits into four factors and the factors were similar to the above-mentioned PCs. Finally, based on the obtained results of PCA and FA methods, number of capitulum per plant, dry weight of plant, main and lateral capitulum diameter and harvest index are the traits to be considered by breeders for the improvement of safflower seed yield.

Key concepts: Carthamus, Biology, Yield (engineering), Multivariate statistics, Agronomy, Genotype, Crop yield, Multivariate analysis

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