1Department of Agronomy, Vanavarayar Institute of Agriculture, Pollachi-642 103, Tamil Nadu, India.
2Department of Agriculture Economics, S. Thangapazham Agricultural College, Tenkasi-627 758, Tamil Nadu, India.
3Department of Crop Physiology, SRM College of Agricultural Sciences, Chengalpattu-603 201, Tamil Nadu, India.
4Department of Agro-Meteorology, Vanavarayar Institute of Agriculture, Pollachi-642 103, Tamil Nadu, India.
5Department of Entomology, RVS Agricultural College, Thanjavur-613 402, Tamil Nadu, India.
6Department of Agricultural Extension, Krishi Vigyan Kendra, Theni-625 520, Tamil Nadu, India.
7Department of Plant Protection, Krishi Vigyan Kendra, Acharya NG Ranga Agricultural University, Ananthapuramu-515 701, Andhra Pradesh, India.
*Corresponding Author: R. Ajaykumar, Department of Agronomy, Vanavarayar Institute of Agriculture, Pollachi-642 103, Tamil Nadu, India, Email: ajaykumar.tnau@gmail.com
Online Published on 06 April, 2023.
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.
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).
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.
Blackgram, Correlation, Growth, Physiological characters, Principal component analysis (PCA)
