Pulses are important crops in India because of their low cost and high quality protein. They play a major role in providing a balanced protein component in the diet of the people. Among pulses, blackgram [Vigna mungo
], occupies a unique place. It is grown both as a pure and mixed crop along with maize, cotton, sorghum and other millets (Ajaykumar et al., 2022a).
The yield of blackgram is low due to various reasons including poor management practices, physiological, biochemical and inherent factors associated with the crop. Insufficient partitioning of assimilates, flower dropping and poor pod setting are mainly due to lack of nutrients during critical crop growth resulting in poor yield. Fertilizer application is an important practice to increase the yield of blackgram (Ajaykumar et al., 2022b).
Organic substances are known to influence a wide array of physiological parameters like alteration of plant architecture, assimilate partitioning, promotion of photosynthesis, uptake of nutrients (mineral ions), enhancing nitrogen metabolism, promotion of flowering, uniform pod formation, increased mobilization of assimilates to defined sinks, improved seed quality, induction of synchrony in flowering and delayed senescence of leaves (Pradeep and Elamathi 2007)
The role of foliar applied panchagavya and dhasagavya in the production of many plantation crops has been well documented in India (Selvaraj, 2003)
. The use of fermented, liquid organic fertilizers and effective microorganisms (EM) as foliar fertilizers have been introduced to modern agriculture in recent years to produce food with good quality and safety (Galindo et al., 2007).
Fish amino acid (FAA) is a liquid and great value to both plants and microorganisms in their growth. It has abundant amount of nutrients and various types of amino acids. Seaweed concentrates benefit plants as they contain growth-promoting hormones (IAA, IBA and cytokinins), trace elements, vitamins and amino acids (Khan et al., 2009).
Integrated use of seaweed liquid fertilizer in combination with chemical fertilizer and their proper management for better growth and yield is very essential. In green gram, foliar application of liquid bio fertilizers during vegetative and flower bud initiation stages increased number of flowers, pods and seeds per plant and seed yield. Foliar application of organic substance increased the chlorophyll content and promoted epicotyls elongation of soybean, mungbean and pea (Senthil et al., 2003).
Exogenous application of pink-pigmented facultative methylotrophs (PPFM) produces some benefits in alleviating the adverse effects of drought stress and also improves germination, growth, development, quality and yield of crop plants (Hayat et al., 2010).
Agronomists frequently assess a great diversity of characteristics for appraisal and characterization. In such situations, principal component analysis (PCA) is used to reduce massive data sets containing multiple variables into their principal components to acquire a deeper understanding of the data (Amy and Pritts, 1991)
. This statistical technique is frequently utilised for data compression, reduction and transformation (Mishra et al., 2017).
Principle component analysis is a mathematical procedure that transforms a number of (possibly related) variables into a (smaller) number of principal component variables (García and García, 2010)
. The eigenvalue of a specific principal component represents the degree of variance in attributes that is explained by that principal component, which is extremely valuable for crop production trait selection (Singh et al., 2020).
The PCA is widely utilized in examining elite growth and physiological features, it simultaneously analyses several parameters of each individual under investigation. PCA evaluates the significance and contribution of each variable to the overall variance (Leonard and Peter, 2009)
When evaluating materials based on a variety of characteristics, there are numerous crucial factors to consider. Consequently, PCA is used to study the relationships between traits and efficiently visualise the similarities between individuals or treatments in which various factors exert strong effects on growth, yield and physiological traits. Under these conditions, it is considerably more difficult to visually summarise a set of agronomic data by describing agronomic features; hence, multivariate methods should be employed. In recent years, numerous research efforts have been focused on agronomic physiological characters that influence yield. PCA is a useful technique for the reduction of large data set with many variables into important principal components for a better understanding of information. Keeping these points in view, the present investigation was conducted to assess the relationship among characters of blackgram under irrigated conditions.