Influence of weather conditions on yield and protein content in winter wheat grain

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The results of three-year studies (2020–2022) conducted in the forest-steppe zone of the Samara region in the agrocenosis of winter wheat are presented. The purpose of the work was to study the influence of natural and climatic conditions of the research area on the formation of yield indicators, protein content in winter wheat grain. The material was 10 varieties from the Vavilov All-Russian Institute of Plant Genetic Resources (VIR) collection and 5 varieties of selection of the Povolzhsky Scientific Research Institute of Selection and Seed Growing named after P.N. Konstantinov. Yield, grain protein content and protein yield per hectare were determined. Varieties characterized by high yield and high amount of protein in grain, showing maximum protein yield in different weather conditions of the years were identified. Over the years of research, the year 2022 was the most favorable for the formation of high yields (between 6 and 8.5 t/ha were harvested in the indicated year), where a large amount of precipitation was observed in May – the first ten-day period of June. The protein content in grain was the highest in 2021 (14–19%), when high temperatures were observed during the grain filling period in the absence of precipitation. For each variety, the correlation dependence of the sum of active temperatures and the amount of precipitation during the spring-summer vegetation period with the studied indicators was established. There was a negative correlation between the sum of active temperatures and yield (from –0.553 to –0.981) and a positive correlation with the protein content indicator (from 0.605 to 0.984) depending on the variety. The amount of precipitation was in a positive correlation with the yield index, the dependence on the protein content in the grain was ambiguous and depended on the variety. The studied indicators were influenced not only by natural and climatic conditions, but also by the genotypic features of the studied varieties, which explains the diverse correlation dependence.