USING BIOMETRIC METHODS FOR EVALUATION OF MODEL POPULATION OF SWEET CORN
Abstract
The creation of new lines of sweet corn with a high combinational ability and the production of high-heterosis hybrids suitable for mechanical harvesting on their basis is associated with the constant search for a new source material and its improvement.
Biometric methods were used to evaluate the gene pool of sweet corn. The variation of the traits of 45 varieties of sweet corn, correlation coefficients and factor loads on variables are examined. During the two years of research, high variability was revealed in the traits of "the height of the fixing of the cob" and "the number of grains on the cob", low variability – "the ear of the cob". According to the number of grains in a row and the diameter of the cob, unstable variability was established. The average coefficient of variation was registered for the traits: plant height, cob length, length of the ear, number of rows.
Two years of research also revealed a significant strong connection (>70%) between the length of the cob and the length of the lacerated part; the length of the cob and the number of grains in a row; the length of the lacerated part and the number of grains in a row, as well as the number of grains on the cob; between the number of grains in a row and the number of grains on the cob.
The following traits made a significant contribution to the first hypothetical factor: the length of the cob, the length of the ear of the cob, the diameter of the cob, the number of grains in a row, the number of grains on the cob. The number of rows had a significant impact on the formation of the dispersion of 3 factors in 2021 and the average in 2020. The height of plants in 2020 (the average share of plant height was noted) made an average contribution to the second and third hypothetical factors, and the ear of the cob – the second and fourth. In 2021, the share of the influence of these traits was more than 70% – the height of plants – on the formation of the dispersion of the second hypothetical factor, and the ear of the cob – the fourth.
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References
ГОСТ 32882-2014. Кукуруза свежая в початках для промышленной переработки. – Введ. 2016-01-01. – М. : Стандартинформ, 2018. – 5 с.
Лиепа И.Я. Математические методы в биологических исследованиях. Факторный и компонентный анализы / И.Я. Лиепа. – Рига : Издательство Латвийского государственного университета, 1980. – 194 с.
Sokal R.R. Biometry: the principles and practice of statistics in biological research / R.R. Sokal, F.J Rolf. – NY, USA, 1995. – 347 p.
Бююль А. SPSS: искусство обработки информации. Анализ статистических данных восстановление скрытых закономерностей / А. Бююль, П. Цефель. – СПб. : Техническая книга, 2005. – 603 с.
Бебякин В.М. Корреляционно-факторный анализ показателей состояния углеводно-амилазного комплекса и хлебопекарных качеств озимой ржи / В.М. Бебякин, Т.Б. Кулеватова, Н.М. Великанова // Хранение и переработка сельхозсырья. – 2004. – № 12. – С. 29-32
Гудова Л.А. Использование методов многомерной статистики для оценки модельной популяции кукурузы / Л.А Гудова, С.А. Зайцев, В.И. Жужукин и др. // Аграрный научный журнал. – 2021. – № 7. – С. 9-15.
Вишнякова М.А. Местные сорта нута из центров происхождения: разнообразие и различия / М.А. Вишнякова, М.О. Бурляева, С.В. Булынцев и др. // Сельскохозяйственная биология. – 2017. – № 5. – С. 976-985.
Жужукин В.И. Оценка исходного материала для селекции нута / В.И. Жужукин, Ж.Н. Мухатова, А.Г. Субботин и др. // Успехи современного естествознания. – 2022. – № 4 – С.14-20.
Методика государственного сортоиспытания сельскохозяйственных культур. Вып. 1. Общая часть // ФГБУ «Госсорткомиссия». – М., 2019. – 329 с.
Доспехов Б.А. Методика полевого опыта (с основами статистической обработки результатов исследований) / Б.А. Доспехов. – М. : Книга по требованию, 2012. – 352 с.