Genetic Divergence Studies for Yield Components  in Blackgram (Vigna mungo L.) Genotypes

Sridhar, V.; Prasad, BV Vara; Shivani, D.; Rao, Srinath

doi:10.20546/ijcmas.2020.901.203

Cited by 3 publications

(1 citation statement)

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“…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).…”

Section: Resultsmentioning

confidence: 99%

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

Ajaykumar

Harishankar

Chandrasekaran

et al. 2022

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Background: Blackgram [Vigna mungo (L.) Hepper] has significant agronomic and nutritional significance. Its productivity is insufficient to fulfil the expanding local demand in India. Increasing its productivity using appropriate agronomic practices is crucial. With this background, an experiment was conducted to study the effect of foliar application of liquid organic bio-stimulants on development, production and physiological characteristics of blackgram under irrigated conditions. Methods: Seven treatments comprising recommended dose of fertilizers (RDF) with foliar spray of dhasagavya, liquid rhizobium, fish amino acid, panchagavya, PPFM and seaweed extract at 1% and 3%, respectively were tested in randomised block design with three replications. The dimension of blackgram quantitative characters, viz., grain yield, plant height, number of branches per plant, dry matter production (DMP), leaf area index (LAI), number of pods per plant, number of seeds per pod, pod weight per plant, pod length, crop growth rate, total chlorophyll content, soluble protein content and nitrate reductase activity were reduced using principal component analysis (PCA). Result: The PCA was performed on all the attributes as correlation between the quantitative characters was found to be stronger among most of the biometric observations. It was noticed that almost 67% of the data’s total variability, as reflected by the first two principal components. It demonstrated that grain production, DMP, nitrate reductase activity, pods per plant and leaf area index were the primary contributors.

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Section: Resultsmentioning

confidence: 99%

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

Ajaykumar

Harishankar

Chandrasekaran

et al. 2022

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Evaluation of black gram (Vigna mungo (L.) Hepper) genotypes for coastal saline tolerance using microsatellite markers

Priyadharshini,

Anandan,

Manikandan

et al. 2023

Braz. J. Bot

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Principal Component Analysis for Yield in Blackgram(Vignamungo L. Hepper) under Organic and Inorganic Fertilizer Managements

Reddy¹,

Priya²,

Reddy³

et al. 2021

IJPSS

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The present investigation on thirty black gram diverse genotypes for 12 yield and yield attributing traits under organic and inorganic fertilizer managements was carried out to study genetic variation among traits and genotypes in the respective environments that would equip the selection criteria using principal Component Analysis. First four vectors with threshold Eigen value greater than one (>1) contributed to 77.56% and 70.74% variation under organic and inorganic fertilizer managements respectively. Characters viz., number of clusters per plant (0.395), number of seeds per pod (0.354), days to maturity (0.336), number of pods per plant (0.300), harvest index (0.244), plant height (0.073) and seed yield per plant (0.015), whereas under inorganic fertilizer management number of primary branches per plant (0.43), followed by number of pods per plant (0.43), seed yield per plant (0.31), number of pods per cluster (0.29), number of clusters per plant (0.29) explained the maximum variance in first principal component (PC1) under organic conditions. Based on comparison of trait contribution to total variability under PC1 under both the managements it can be concluded that the traits viz., number of clusters per plant, number of pods per plant and seed yield per plant were the potential traits that accounted for maximum share towards variability. These traits may be taken into consideration as selection criteria in breeding programmes aimed at developing high yielding varieties.

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Genetic Divergence Studies for Yield Components in Blackgram (Vigna mungo L.) Genotypes

Cited by 3 publications

References 1 publication

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

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

Evaluation of black gram (Vigna mungo (L.) Hepper) genotypes for coastal saline tolerance using microsatellite markers

Principal Component Analysis for Yield in Blackgram(Vignamungo L. Hepper) under Organic and Inorganic Fertilizer Managements

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