Variability of the test weight and 1000-kernel weight of brewing barley cultivars depending on the genotype and weather conditions

Abstract

The study purpose is to create highly adaptive brewing barley cultivars, for which it is advisable to evaluate the variability of the 1000-kernel weight and test weight as indicators of the brewing raw material quality, depending on the genotype and growing conditions.Materials and methods. The study was conducted in 2014–2017. The experimental plot area was 10 m2, in four replications. The plot arrangement was randomized. Twenty six two-row chaffy spring barley cultivars of different origin were taken as starting material.The test weight was measured with a liter grain-unit scale. The significance of differences was determined by ANOVA. Post hoc comparison was performed by the Homogenous groups method (Fisher LSD). The coefficients of variation and correlation were calculated in the STATISTICA 10 application.Results and discussion. In the study, cultivars with the highest (Etyket -51.0 g and Podyv -50.7 g) and the lowest 1000-kernel weight (Kozvan and Sebastian -43.6 g) were identified. Similar comparisons were carried out for the test weight, and cultivars with high (Khadar, Sofiara - 715 g/L, Avhur and Sebastian - 713 g/L) and low (Pasadena - 686 g/L, Kozvan and Arikada - 691 g/L) values were identified. There was a close linear relationship between the 1000-kernel weight and test weight(r = 0.63).The vegetation period of 2014 with the optimal balance of air temperature and rainfall was the most favorable for fulfillment of the barley genotype potential in terms of the 1000-kernel weight and test weight.Technologically valuable cultivars have been distinguished: Podyv, Sofiara and Sebastian, which can provide a high yield of product per unit of marketable raw materials during processing.Conclusions. In the studied sample of barley cultivars, the ranking by 1000-kernel weight and test weight did not change from year to year, indicating a strong role of the genotype in the control of these parameters. An increase in the 1000-kernel weight and test weight is possible with optimal watering during the development phases from emerging to filling.The variability of the 1000-kernel weight was weak or medium; the variability of the test weight was very weak, also indicating a strong genetic control of these parameters.