Principal Component Analysis Approach for Yield Attributing Traits in Chilli (Capsicum annum L.) Genotypes

Chilli (Capsicum annuum L.) (2n = 24) is one of the most important vegetables as well as spice crop of the Solanaceae family is a dicotyledonous flowering plant grown worldwide [1] and the fruits are rich in vitamin A, E, C and P [2]. Green fruits of chilli are used as a vegetable whereas ripe dried fruits as a spice because of its pungency and pleasant flavour [3] and the green fruits are one of the richest sources of anti-oxidant. The origin of this spice and vegetable crop can be traced to South and Central America [4]. The capsaicin present in the placenta and pericarp is responsible for chilli pungency. Capsaicin has high diverse prophylactic and therapeutic uses in Allopathic and Ayurvedic medicine values [5]. It has very high export potential as a spice crop. Its export value is due to the presence of 69 % capsaicin with 22 % DHC (dihydro-capsaicin). India ranks first in the world in terms of production, consumption and exports. The average productivity of chilli is very low (1.11 t/ha dry chilli) as compared to countries like the USA, China, South Korea, Taiwan, where the average yield ranged from three to four tons per hectare. The lack of improved genotypes is the main constraint to low yield. On the other hand, a wide range of variability is observed in respect of morpho-physiological traits in chilli. Assessment of different desirable traits spread over diverse genotypes is important to rapid advance in yield improvement of any crop. A logical way to start any breeding program is to collect precise information on the nature and degree of genetic divergence that would help the plant breeder in choosing the right type of parents for purposeful hybridization in heterosis breeding [6]. The genetic diversity may arise due to the environmental influence and may be determined by the magnitude and nature of their genetic variability in which they are grown [7]. Wide variability in chilli fruit morphology, pungency, bearing habit and crop duration is found throughout India [8]. Moreover, the evaluation of genetic diversity is important to know the source of genes for a particular trait within the available germplasm [9]. Principal component analysis (PCA) involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables called principal component [10]. PCA is an important statistical method through which we can easily identify important polygenic characters which are of great importance in a plant breeding programme. PCA provides an idea for how to reduce a complex data set to a lower dimension to reveal the sometimes hidden, simplified structures that often underlie it. The eigenvalue of a particular principal component depicts the amount of variation present in traits and explained by that principal component which is very useful for the further breeding programme. Abstract The present investigation entitled was carried out at Horticulture Complex, Maharajpur, Jabalpur (M.P) during Rabi season of 2015-16 with eighteen genotypes in order to study the genetic diversity for different yield attributing characters of chilli by principal component analysis. In this study, out of ten principal components, only five components exhibited >0.5 eigenvalue and showed about 88.85% variability among the traits within the axes exhibited great influence on the phenotype of genotypes. The PC1 accounted for the highest variability (36.93%) to the total variability, followed by 22.87% (PC2), 15.62% (PC3), 7.46% (PC4) and 5.97% (PC5). Thus the results of the principal component analysis revealed, wide genetic variability exists in this chilli genotype accessions.