Evaluation of the effect of Reni preparations application on some essential amino acids in alfalfa (Medicago sativa L.) biomass by correlation and factor analysis

Atanas Sevov1, Velika Kuneva2 and Antoniya Stoyanova2
1 Agricultural University, Faculty of Agronomy, Department of Plant Production, 4000 Plovdiv, Bulgaria
2 Agricultural University, Faculty of Economy, Department of Mathematics and Informatics, 4000 Plovdiv, Bulgaria
3 Trakia University, Faculty of Agriculture, Department of Plant Production, 6000 Stara Zagora, Bulgaria

Abstract

Sevov, A., Kuneva, V. & Stoyanova, A. (2021). Evaluation of the effect of Reni preparations application on some essential amino acids in alfalfa (Medicago sativa L.) biomass by correlation and factor analysis. Bulg. J. Agric. Sci., 27 (Suppl. 1), 130–133

The present study aims to evaluate the influence of different Reni preparations on essential amino acids in biomass of Mnogolistna 1 variety, using a mathematical approach (correlation and factor analysis). Three-year data, based on a field experiment, conducted at the Agricultural University – Plovdiv experimental field in the period 2017-2019 was analysed. The study is part of University project for establishing the influence of Reni preparation on the yield and quality as well as the relations between the researched indicators.
The proposed mathematical approach allows increasing the objectivity when evaluating the complex effect of Reni preparations on the main chemical components in alfalfa Mnogolistna 1. Reni treatment improves the biological value of proteins – increases the total amount of essential amino acids and changes the ratio of essential amino acids to other proteinogenic amino acids in favour of the essential ones. As a result of the conducted analysis, correlations between the studied indicators were established. The strongest positive correlation was found between the amino acids lysine and leucine (r = 0.960), threonine and phenylalanine (r = 0.980) and valine and isoleucine (r = 0.981), respectively. By using Factor analysis according to the method of Principal Component Analysis, the amino acids lysine, threonine and leucine correlated themselves only were combined in two new factors that explain 73% of the total variance of the variables.

Keywords: alfalfa; correlations; factor analysis

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