Purpose. Assessment and selection of self-pollinated S5 maize (Zea mays L.) families with high combining ability and wide adaptive capacity obtained on the basis of specially produced hybrids by crossing elite lines of various genetic plasms with the best main agronomic characters. Methods. Field studies, mathematico-statistical evaluation. Results. An amplitude of grain yield ranging from 5.96–10.96 t/ha (x = 8.44 t/ha) in 2013 to 2.67–7.59 t/ha (x = 5.08 t/ha) in 2014 was determined in the course of study of the testcrosses of self-pollinated S5 families. It was found that different response of genotypes of the studied testcrosses to the year conditions significantly affected the average yield level, which decreased in the stressful 2014 by 3.4 t/ha as compared to 2013. The results of the assessment based on the general and specific combining ability of new parent material of mixed germplasm were shown. A significant variability of the estimates of GCA (general combining ability) effects depending on the year conditions was observed in the course of study. A marked difference in the estimates of GCA effects based on the grain yield was revealed. They were persistently high in 19% of the best self-pollinated families in both years, 14% of the families had persistently low estimates of GCA effects, 67% changed their value depending on the genotype and year conditions. Conclusions. 17 best self-pollinated families with persistently high estimates of GCA, 6 families featuring high tolerance to drought and 4 families with persistently high variances of SCA were selected. The selected families will be used as a parent material in selection programs aimed to create new high performance hybrids.

Purpose. Evaluate the introduced samples of soft winter wheat from the international nursery Common Bunt-Resistant Nursery (CBUNT-RES) of different ecological and geographical origin in the southern part of the Forest-Steppe zone of Ukraine according to a set of productivity indicators in order to define the most valuable samples and describe them. Methods. During 2016–2019 on the base of Ustymivka Experimental Station for Plant Production of the V. Ya. Yuriev Plant Production Institute of NAAS the authors studied, evaluated and described 75 new soft winter wheat samples of various eco-geographical origins by productivity traits. In the field and laboratory conditions, indicators of yield and productivi­ty were determined: 1000 grains weight, plant height and ear length, the number of spikelets and grains in the ear, weight of ear and grain and early-ripening. Results. Plant material with increased parameters of economic and biological characters was identified. During studies, it was found that ‘F08347G8’, ‘F00628G34-1’ (Romania), ‘91-142A61/KATIA1//GRISET-4’, ‘SAULESKU#44/TR810200//GRISET-4’, ‘ATTILA/BABAX//PASTOR/4/…’ (IU067591) (Turkey), ‘INTENSIVNAYA//PBW343*2/TUKURU’, ‘SANZAR-8/KKTS’ (Mexico) were the high-yielding varieties. The samples of soft winter wheat as ‘F08347G8’, ‘F00628G34-1’ (Romania), ‘INTENSIVNAYA//PBW343*2/…’ (IU067637) (Mexico), ‘ATAY/GALVEZ87/6/TAST/…’ (IU067587), ‘DE9/MERCAN-2’, ‘KRASNODAR/FRTL/6…’ (IU067595), ‘SAULESKU#44/TR810200//GRISET-4’, ‘GANSU-1/3/AUSGS50AT34/…’ (IU067598), ‘ORKINOS-1*2/3/AUS…’ (IU067608), ‘KAMBARA1/ZANDER-17’ , ‘TAM200/KAUZ/4/CHAM6//…’ (IU067612) (Turkey) contained a large grain weight (more than 5.0 g), plant productivity in these samples was rather high due to increased amount of grains and the thousand kernel weight. Conclusions. The introduced soft winter wheat samples of various eco-geographical origins were adapted to the Southern Forest-Steppe and can be recommended as a source material in breeding to increasing productive capacity.

Unique features of Myronivs’ka 808 variety have provided its triumph in agricultural production in the former Soviet Union and other countries. Myronivs’ka 808 has become one of the most popular varieties in terms of sown areas (in 1971 over 9.5 million hectares) in the world production. Up to now the variety has been cultivated in the Russian Federation and the Republic of Kazakhstan. Myronivs’ka 808 variety gained leadership in the global selection process as a source of high grain quality, high productivity, general adaptability and plasticity. Using germplasm of this variety enabled to develop over 400 wheat varieties including 350 winter varieties and 60 spring varieties.

Unique features of Myronivs’ka 808 variety have provided its triumph in agricultural production in the former Soviet Union and other countries. Myronivs’ka 808 has become one of the most popular varieties in terms of sown areas (in 1971 over 9.5 million hectares) in the world production. Up to now the variety has been cultivated in the Russian Federation and the Republic of Kazakhstan. Myronivs’ka 808 variety gained leadership in the global selection process as a source of high grain quality, high productivity, general adaptability and plasticity. Using germplasm of this variety enabled to develop over 400 wheat varieties including 350 winter varieties and 60 spring varieties.

The results of evaluation and selection of breeding material of mixed germ-plasm corn for early ripeness among self-pollinated families S4 by the length of the «sprouting–flowering of 50% of ears» period are given. A signifi cant infl uence of weather conditions during the years of study on the length of this indicator was determined. Response of studied corn test-crosses on growing conditions are described. Self-pollinated families DK22282111, DK28211111, DK21511111, DK20192321, DK26143111 were singled out which had a high tolerance to growing conditions and stable «sprouting–flowering of 50% of ears» period.

The results of evaluation and selection of breeding material of mixed germ-plasm corn for early ripeness among self-pollinated families S4 by the length of the «sprouting–flowering of 50% of ears» period are given. A signifi cant infl uence of weather conditions during the years of study on the length of this indicator was determined. Response of studied corn test-crosses on growing conditions are described. Self-pollinated families DK22282111, DK28211111, DK21511111, DK20192321, DK26143111 were singled out which had a high tolerance to growing conditions and stable «sprouting–flowering of 50% of ears» period.

Purpose. Comprehensive study, selection, evaluation and systematization of self-pollinated lines of maize (Zea mays L.) obtained on the basis of material of diffe?rent genetic structure from endosperm of flint and dent maize were implemented according to the main economically valuable traits and precocity in order to select the best genotypes for selection.Methods. Hybridization, inbreeding were used in the process of creating the initial material; visual method ? for phenological observations; laboratory and field ? to determine the morphobiological characteristics of self-pollinated lines of maize; measuring and weighing ? to account the harvest and determine the metric characteristics of plants; mathematical and statistical ? to determine the validity of the results, indicators of trait variability, correlation dependence of traits; analysis of variance; comprehensive assessment of morphobiological and economically valuable traits of self-pollinated maize lines of the most common germplasms.Results. As a result of assessment of self-pollinated lines of the most common germplasms, it was revealed that the highest level of grain yield was obtained under both sowing periods ? Iodent germplasm; the minimum grain moisture content ? Flint and Mix germplasms; the shortest average duration of the emergence ? flowering of 50% of male and female inflorescences stage ? Flint germplasm; steadily high va?lues ??of plant height for germplasm Mix ? under the optimal sowing date, and Iodent plasma ? under the late sowing date. Steadily high values ??of the ear insertion height at both sowing dates were obtained for lines based on Iodent germplasm. The number of the most precocious and the best by the economically valuable traits germplasms of self-pollinated lines were identified.Conclusions. The DK239 lines ? Flint germplasm, DK7174, DK2285, DK305, DK2613, DK5568 ? Iodent germplasm, DK2332 and DK2659 ? Mix germplasm were the most precocious and the best by the economically valuable traits. They are promising for the selection of ultra-early hybrids of maize adapted to the conditions of the Steppe of Ukraine. | ????. ?????????? ????????, ?????, ?????????? ? ?????????????? ????????????? ????? ????????? ????????? (Zea mays?L.), ????????? ?? ???? ????????? ?????? ?????????? ????????? ? ??????????? ?? ???????????? ????? ??????????, ?? ????????? ????????????-??????? ??????????? ? ???????? ?????????????? ? ????? ????????? ????????? ????????? ??? ???????? ?????????????????? ????????.??????. ????????????, ?????? ? ? ??????? ????????? ????????? ?????????; ?????????? ? ??????????? ?????????????; ???????????-???????? ? ?????????? ?????-??????????? ????? ????????????? ????? ?????????; ????????????-??????? ? ?????????? ??????????? ?? ????????? ????? ??????; ???????????-??????????? ? ?????????? ????????????? ???????????, ?????????? ?????????????? ?????, ???????????? ?????????? ?????; ???????????? ??????; ?????????? ?????????? ?????-??????????? ?? ????????????-?????? ????????????? ????????????? ????? ????????? ?????????????? ?????????? ?????.??????????. ? ?????????? ?????????? ????????????? ????? ?????????, ????????? ?? ???? ?????? ?????????? ?????, ???????????, ?? ??????? ??????????? ????? ?? ???? ??????? ????? ?????????? ?????? ??? ?????????? ?????? Iodent; ?????????? ????????? ????????? ????? ???? ????? ?????????? ????? Flint ?? Mix; ???????? ??????? ?????????? ??????? ?????????????? (50% ????????? ?? ??????? ??????? ?? ???? ??????? ?????) ???????? ?????? ?????????? ?????? Flint; ????????? ?????? ???????? ????????? ??????? ??????? ?? ???????????? ?????? ????? ?????????? ??? ????? ????????? ???????? ?????????? ?????? Mix, ?? ???????? ?????? ? ??? ????? ?????? Iodent. ????????? ?????? ???????? ????????? ??????? ???????????? ??????? ?? ???? ??????? ????? ?????????? ? ?????, ??? ???????? ?? ?????? ?????? Iodent.????????. ????? ??239 (?????? Flint), ??7174, ??2285, ??305, ??2613 ? ??5568 (?????? Iodent), ??2332 ?? ??2659 (?????? Mix) ???? ???????? ????????????? ?? ?????????? ?? ?????????? ????????????-?????? ?????. ???? ? ?????????????? ??? ???????????? ? ???????? ?????????????????? ???????? ?????????, ??????????? ?? ???? ????? ???????

Мета. Обґрунтувати інформаційно-технічні особливості використання інструментальних засобів IBM SPSS Statistics під час визначення критерію відмінності нових сортів салату посівного Lactuca sativa L. var. capitata на підставі морфологічних кодових формул фенотипів загальновідомих сортів із використанням алгоритму «найближчого сусіда» в групі подібних сортів. Методи. Аналітичний, що ґрунтується на порівнянні методів та засобів інтелектуального аналізу даних, отриманих методом ідентифікації – морфологічний опис сорту з подальшим застосуванням описової та багатовимірної статистики. Відповідно до «Методики проведення експертизи сортів салату посівного Lactuca sativa L. на відмінність, однорідність і стабільність» для групування сортів використовували ознаки, які не варіюють або дуже слабко варіюють. Ці ознаки використовуються окремо або у комбінаціях з іншими. Результати. У результаті моделювання з використанням пакету SPSS було сформовано декілька моделей подібних сортів Lactuca sativa L. var. сapitata. Загальна кількість сортів у вибірці розподілена таким чином: 71,4% репрезентували навчальну вибірку, а 28,6% – конт­рольну. Результативні дані візуалізовано на діаграмах моделі найбільшої подібності. Слід враховувати тип вираження досліджуваної характеристики (ознаки): якісним, кількісним, псевдо-якісним чином. Імітаційний експеримент з моделлю схожих сортів салату головчастого показав залежність результату від обраної цільової змінної. У ролі цільових змінних були ознаки: «рослина: утворення головки», «головка за щільністю», «насінина: забарвлення», «розмір головки». Висновки. Встановлено ефективність технологічних засобів аналізу даних експертизи на відмінність, однорідність і стабільність (ВОС), що значно полегшує пошук закономірностей серед великого набору даних. Розмежування даних на навчальні та контрольні дозволяє провести «тренування» моделі на наборі даних загальновідомих сортів. Під час побудови моделі важливо правильно визначити цільову та фокусні змінні. Як інструментальний засіб рекомендовано використовувати пакет статистичних програм IBM SPSS Statistics.