Application of Principal Component Analysis (PCA) for Blackgram [Vigna mungo (L.) Hepper] Germplasm Evaluation under Normal and Water Stressed Conditions

Abstract

Background: Blackgram [Vigna mungo (L.) Hepper] is a popularly known pulse crop in India for its nutritional quality and adaptability to many cropping systems. The crop is mostly cultivated in areas experiencing water stress which reduces the yield potential. Thus, it is imperative to assess the genetic variability present in the existing blackgram germplasm under drought condition. For this, principal component analysis was carried to visualize the complex dataset. This study was aimed to identify key traits and drought tolerant genotypes. Methods: Twenty-one blackgram genotypes were screened in the field condition for water stress where the experiment was laid out in RBD with two replications. Principal component analysis was carried out with thirteen traits in twenty-one genotypes of blackgram under normal and water stressed conditions.Result: In T0 and T1, more than 75% of total variability among thirteen traits was explained by five and four principal component axes respectively. Under water stress, pod length was highly correlated with seed yield per plant. Based on the interaction vectors and PC scores of genotypes, VBG-12062 had a positive interaction with seed yield. Thus, VBG-12062 can be a reliable candidate for breeding high yielding drought tolerant variety.

Principle Component Analysis (PCA) and Character Interrelationship of Irrigated Blackgram [Vigna mungo (L.) Hepper] Influenced by Liquid Organic Biostimulants in Western Zone of Tamil Nadu

“…Overall, PCA was able to identify the crucial agronomic characteristics responsible for population variability. Jeberson et al (2018), Sridhar et al (2020), Girgel (2021) Several researchers utilised the PCA biplot to investigate the link between traits in various crops (Mohanlal et al, 2020;Aslam et al, 2017;and Maqbool et al, 2016). The length of the vector was determined by the character's contribution to the primary component (Fig 3).…”