Miroslava T. Ivanova1, Tzenka I. Radoukova2, Lilko K. Dospatliev3 and Maria N. Lacheva4
1 Trakia University, Department of Informatics and Mathematics, Faculty of Economics, 6000 Stara Zagora, Bulgaria
2 University of Plovdiv “Paisii Hilendarski”, Department of Botany and Methods of Biology Teaching, Faculty of Biology, 4000 Plovdiv, Bulgaria
3 Trakia University, Department of Pharmacology, Animal Physiology and Physiological Chemistry, Faculty of Veterinary Medicine, 6000 Stara Zagora, Bulgaria
4 Agricultural University, Department of Botany and Agrometeorology, 4000 Plovdiv, Bulgaria
Ivanova, M. T., Radoukova, Tz. I., Dospatliev, L. K. & Lacheva, M. N. (2020). Ordinary least squared linear regression model for estimation of zinc in wild edible mushroom (Suillus luteus (L.) Roussel). Bulg. J. Agric. Sci., 26 (4), 863–869
Suillus luteus(L.) Roussel is a basidial fungus, and the type species of the genusSuillus. A common fungus native to Eurasia, from the British Isles to Korea, it has been introduced widely elsewhere, including North and South America, southern Africa, Australia and New Zealand.The aims of this work were to determine trace elements (Pb, Cd, Co, Cu, Mn, Zn and Fe) contents in the wild edible mushroom S. luteus growing in the Batak Mountain, Bulgaria and to identify the relationship between Zn and the other elements using ordinary least squares multiple linear regression model. Quantitative determination of the concentration of the studied trace elements was carried out in mineralized samples by Perkin Elmer A Analyst 800 atomic absorption spectrometer with deuterium background corrector. All statistical computing, analysis and all charts were performed with the statistical software R program. The ordinary least squares linear regression model was obtained for Zn. Based on the obtained model, the following interpretations for Zn contents in the wild edible mushroom S. luteus growing in the Batak Mountain, Bulgaria could be made: if Fe and Cd increase by 1%, the effect of this increase would result in an increase in Zn by 15.245% on the average; if Mn, Cu, Co and Pb decreases by 1%, the effect of this decrease would result in an decrease in Zn by 3.582% on the average.