Оцінка взаємодії генотип × середовище сортів ячменю ярого за допомогою GGE biplot аналізу

Abstract

Солонечний П.М., Козаченко М.Р., Васько Н.І., Наумов О.Г., Бондарева О.Б., Логвиненко Ю.В. Оцінка взаємодії генотип × середовище сортів ячменю ярого за допомогою GGE biplot аналізу. Наведено результати екологічного випробування семи сортів ячменю ярого в 2013-2014 рр., проаналізовані за допомогою GGE biplot. Визначено особливості середовищ як тестери для оцінки генотипів. За результатами досліджень виділено сорти ячменю ярого Козван та Алегро, що максимально наближені до «ідеального» генотипу за врожайністю та стабільністю. За результатами досліджень рекомендовано використовувати GGE biplot для аналізу результатів екологічного випробування.

P.M. Solonechnyi, M.R. Kozachenko, N.I. Vasko, A.G. Naumov, O.B. Bondareva, Y.V. Logvinenko. Evaluation of genotype by environment interaction of spring barley varieties using GGE biplot analysis. The article presents of results of a multi environmental trial in seven varieties of spring barley conducted in 2013–2014 using GGE biplot analysis. The objective of this study was to determine the effect of genotype, environment and their interaction for grain yield and identify stable spring barley genotypes. Seven spring barley varieties bred at the Plant Production Institute nd. a V.Ya. Yuryev of NAAS serves as source material. To determine their adaptive potential, in 2013-2014 an environmental trial was carried out in two locations with different soil and climatic conditions: Plant Production Institute nd. a V.Ya. Yuryev of NAAS (Eastern Forest-Steppe) and Donetsk State Agricultural Experiment Station of NAAS (Southern Steppe). The experimental layout was a randomized complete block design with three replications in each environment. Peculiarities of trial locations as testers for estimating genotypes were established. Thus, environments IR2013 and IR2014 with long vectors had a high discriminating power, and environment DDS2014 was characterized by a low discriminating power. The cosine of the angle between environment vectors is used for assessment of approximation between them: the smaller the angle between environment vectors is, the larger correlation between them is. Correspondingly, there is a strong correlation between environments DDS2013 and DDS2014. Location environment IR2014 had long vectors and a large inclination angle with AEC abscissa, indicating their unsuitability as testers for selecting the best genotypes, but at the same time the applicability of their using as tester for selection for stability.According to the biplot of the “ideal” environment it was concluded that IR2013 was the closest to ideal environment and therefore the most desirable of all test environments. The polygon view of GGE biplot showed that variety Modern was the highest yielding in environment IR2013. Moreover, variety Alegro exhibited the highest yield potential in environments DDS2013 and DDS2014, whereas variety Vzirets was the highest in environment IR2014. The varieties Kozvan and Alegro had the highest mean yield, and the variety Etyket – the lowest mean yield. The yields in the varieties Etyket, Modern and Vzirets (G1) had the most variable, while the varieties Kozvan, Agrariy and Alegro were noticeable for their high stability. The varieties Kozvan and Alegro is noticeable for its maximum fidelity to the “ideal” genotype in terms of performance and stability. This study clearly demonstrated that the GGE biplot model was found effective for determining the multi environmental trial data.

П.Н. Солонечный, М.Р. Козаченко, Н.И. Васько, О.Г. Наумов, О.Б. Бондарева, Ю.В. Логвиненко. Оценка взаимодействия генотип × среда сортов ячменя ярового с помощью GGE biplot анализа. Представлены результаты экологического испытания семи сортов ячменя ярового в 2013-2014 гг., проанализированные с помощью GGE biplot. Определены особенности сред в качестве тестеров для оценки генотипов. По результатам исследований выделены сорта ячменя ярового Козван и Алегро, максимально приближенные к «идеальному» генотипу по урожайности и стабильности. По результатам исследований рекомендовано использовать GGE biplot для анализа результатов экологического испытания.