Calculation of United Quality Latent Indices of Deschampsia antarctica plants adaptability of different origin grown in vitro

Abstract

The research was to develop and describe in detail the algorithm for calculating the United Quality Latent Index (UQLI, Iq i) of plant adaptability from the collection of Deschampsia antarctica Ė. Desv. genotypes obtained from seeds collected at different sites in the Argentine Islands region, the maritime Antarctic, and grown in vitro at the laboratory conditions. Genome size and genetic distances by ISSR and IRAP markers according to data from published articles were used as basic indices of initial genetic heterogeneity for analyzed plant genotypes. To assess individual adaptability indices for eleven D. antarctica genotypes, we used measurement of the leaf length morphometric index and determination of the flavonoids content by rutin and the content of photosynthetic pigments. The spectra of reserve and protective proteins in leaves were investigated by polyacrylamide gel electrophoresis. To obtain the United Quality Latent Index of Adaptability (Iq, UQLI), the method of extreme grouping was i used. The estimation of Iq (UQLI) was performed using pairwise comparisons of indices from differences sets for each pair of i genotypes. We developed and described in detail the algorithm for Iq estimation for eleven D. antarctica genotypes. As an example of application, correlation models of probability relations of the indices are presented. To evaluate the complex adaptability i for eleven D. antarctica genotypes grown in vitro we used developed algorithm for the UQLI calculation. The individuality of the adaptive portrait for all studied genotypes under in vitro cultivation conditions was shown. The influence of basic genetic characteristics (genome size and genetic distances) on auxin metabolism-related indices of leaf length and flavonoid content was shown. Such effect may be carried out by genetic characteristics both individually and together, probably via auxin metabolism. Among the eight genotypes researched, we distinguish four different variants by correlation models and two (positive and negative) by the general Iqvalue. Thus theiIq (UQLI) is proposed to describe a large number of source data at different organization i levels which characterize sample genotypes by reducing the dimensions to one dimensionless number. This genotypes’ individuality and the peculiarities of their grouping by Iq should be taken into account when doing experimental studies using these i genotypes as model plants, especially in experiments studying the regulation of productivity and the effect of the various exogenous factors, etc.