The work describes the results of studying the main yield’s elements of sweet corn collection samples in the arid conditions of the Saratov region, taking into account the requirements of standards for the further creation of new genetic forms. An assessment of paired correlation coefficients between economically important characteristics of collection varieties in the phase of technical ripeness was carried out. The strong positive correlation (r>ǀ70ǀ%) was revealed between weight of corn cob in wrapper and its weight without wrapper; between the number of kernels in a row and the number of kernels on the ear cob, the number of kernels on the ear cob and its diameter, the grained part’s length and the length of the cob. We’ve found the strong correlations between yield and weight of the cob in a wrapper and without it (r = 0.78 and r = 0.88 respectively) and the middle correlation with the number of cobs (r =0.61). The middle correlations were revealed between yield and plant height, grain content of the cob, the number of kernels in a row and the number of kernels on the cob. Using the method of factor analysis, significant weights of the variables on the components were established. Most of the features we studied accounted for about the half of the accumulated dispersion and attributed to the first factor: the weight of the cob in the wrapper, the number of grains in the cob, the diameter of the cob, the number of rows of grains, grain yield, the length of the grained part of the cob, the weight of the cob without the wrapper and the height of its attachment. These features contribute most to the overall variance. We think that the assessment of these particular features should not be neglected when creating future variety model. Of the studied genotypes of the collection, the samples of Tsukerka, k-4471, k-4840 correspond to the proposed model of the variety to the greatest extent. We’ll included them in the selection process for creation the varieties, lines and heterotic hybrids.
sweet corn, correlation coefficient, main components method, yield, valuable features, model population
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