Короткий опис(реферат):
Today, an important direction in the scientific support
of crop production is the creation of highly adaptive varieties for agro-ecological activities with a high degree of
genetic protection against adverse environmental factors. It
also involves the development of scientific foundations for
creating genetically programmed wheat varieties with specific biological and economic characteristics. Objective.
The aim of the article is to determine the effectiveness of
using indices to predict yield in progeny at early stages
of winter wheat selection under different growing conditions. Methods. The research was conducted from 2019
to 2021 at the experimental field of Kherson Agrarian and
Economic University. The research material consisted of
typical winter and alternative wheat varieties of various
genetic and ecological origins. Wheat varieties with different growth types were studied under late sowing conditions
(October 10, October 20, November 10). The analysis of
variance was conducted according to the guidelines provided by Rokytskyi P.F. Results and Conclusions. Along
with studying the genetic correlations between the index of
linear spike density and the main traits of selection lines,
the interrelationship between this index and other classical indices was also of interest: Harvest index (HI) – the
ratio of grain mass to plant mass; Attraction index (AI) –
the ratio of ear mass with seeds to stem mass; Maximum
index (MI) – the ratio of grain mass from the spike to plant
height; Intensity index (II) – the ratio of stem mass to plant
height; Potential productivity index (PPI) – the ratio of grain
mass from the spike and ear mass with seeds to the number of grains per spike, the characteristics of which are presented in this publication. The linear spike density index
(LSDI) should be used as a marker for selecting valuable
genotypes by grain mass from the spike at early stages of
breeding. The LSDI and the "1000 grain weight" trait are
controlled by relatively independent genetic systems, creating a favorable situation for the positive selection of morphobiotypes for both the index and the 1000 grain weight.
By the value of LSDI, it is possible to select short-stemmed
morphobiotypes with a larger number of grains per spike,
and consequently, increased grain mass from the spike
