In this paper, we evaluate strawberry varieties of different geographical origin in terms of anthocyanin content in fruits under the conditions of a particular region with the purpose of identifying valuable genotypes for inclusion in further breeding work and practical use. The research was conducted in 2015–2020 at the Kokino collection site of the Federal Research Center for Gardening, located 24 km south-west of the city of Bryansk, in the village of Kokino, Vygonichsky district, Bryansk region. The effect of genotype and weather conditions on the accumulation of anthocyanins in strawberry fruits was studied. The research objects included 35 strawberry varieties of domestic and foreign breeding. Observations were carried out in accordance with the conventional methodology for varietal study of fruit, berry and nut crops. Fruits for the analysis were collected in dry sunny weather, at the stage of optimum maturity. Anthocyanin content in fruits was determined according to the color scale developed by A. A. Zubov and K. V. Stankevich in Michurin Research Institute of Genetics and Fruit Plant Breeding. Most of the varieties (57.1%) were characterized by medium variability of the indicator by year (V = 10–20%). The varieties Sudaruska (24.9%), Darselekt (24.2%), Polka (20.2%), Mieze Schindler (34.1%), Tenira (28.3%) showed a high dependency of fruit anthocyanin content on climatic conditions during the ripening period. The varieties with dark-coloured fruits were found to be Rubinovy Kulon, Barynya, Tsaritsa and Amulet. Their coloring was associated with high anthocyanin levels (more than 80 mg/100 g). These varieties comprise a valuable source material for further breeding and practical use.

The paper considers the main problems and solutions reported in literature concerning the formation and use of clonal rootstocks for cherry varieties in Russia, Europe and America. Examples of certain species are given (Cerasus fruticosa Pall., C.incisa Thunb., C.canescens (Bois) Erem. et Yushev, C.pseudocerasus Fr. Schmidt.), which were previously involved in hybridization for forming clonal rootstock of stone fruit crop. Following the performed research, the authors propose an approach to forming innovative vegetatively propagated rootstocks for species of the genus Cerasus Mill. (cherry, sweet cherry, Oriental cherry) based on distant hybridization and using germ preselection and cultivation in vitro. The obtained results confirm the importance of including previously selected sources and donors in the breeding process for forming clonal rootstocks with the following essential features: resistance to adverse environmental factors, low and high air temperatures, main harmful diseases – coccomycosis (causative agent Coccomyces hiemalis Higg.), monilial burn (Monilia cinerea Bon.), clasterosporiosis (Clasterosporium carpophilum Aderch.), and easy rooting of shoots (rooting ability). Such sources were isolated from collection representatives of cherry species: C.sachalinensis (Fr. Schm.) Komar. et Klob.-Alis. – 49 specimens, C.serrulata (Lindl.) G. Don. – 35, C.kurilensis (Miyabe) Kaban et Vorobiev – 43, (C.maximowiczii (Rupr.) Komar) – 34, C.lannesiana Carr – 4. The above forms, selected for breeding traits for the rootstock, were used for hybridization. Forms were isolated from F₁ hybrid progeny from crossing them with sweet cherry (both forward and backward), and 25 F₂ hybrids were obtained from all representatives. Germ cultivation in vitro enabled the breeding process to be accelerated by 2–3 years, and micropropagation of hybrid clones in vitro, transfer of microplants ex vitro and their subsequent cultivation in vivo under laboratory conditions enabled the necessary amount of breeding plant material (75 hybrids and 650 clones) to be obtained for further tests in a nursery.

The paper presents the results of a long-term test of eight scab-immune apple varieties of domestic and foreign breeding under the conditions of North Caucasus region of Russia. The study was aimed at improving the assortment of apple trees in the Southern region of Russia on the basis of a comprehensive assessment of promising varieties of domestic and foreign breeding. The study objects included scab-immune apple varieties (Malus x domestica Borkh.) of various ecological and genetic origin: Carmen, Nika, Orphey and Margo (North Caucasian Federal Scientific Center of Horticulture, Viticulture, Wine-making together with Nationwide Research Institute for Horticultural Breeding, Russia), Mikhsan and Zarya Stavropoliya (Stavropol Experimental Horticulture Station together with Nationwide Research Institute for Horticultural Breeding, Russia), Modi (Italy), Florina (France). The common and up-to-date breeding programs and techniques developed with the assistance of Nationwide Research Institute for Horticultural Breeding were applied. Based on the long-term results of ecological testing of new scab-immune apple varieties of different origins under the conditions of the Republic of North Ossetia-Alania and Krasnodar Krai, the most valuable varieties for industrial use and for breeding process were identified. The following varieties were identified as promising for industrial use and breeding: varieties with a late flowering time – Margo and Orphey; varieties with a high average flowering score (4.5–5.0 points): Carmen, Modi, Orphey, Nika, Florina, Margo. It was found that all investigated varieties of apple trees can be attributed to the annual fruit-bearing; the periodicity of fruiting varied within 22.6–28.8 %. In 2020, in the conditions of North Ossetia-Alania the maximum yield was observed for the following scab-immune varieties: Margo (24.1 t/ha) and Modi (25.2 t/ha) on rootstock СK2; Mikhsan (19.2 t/ha) and Nika (20.6 t/ha) on rootstock MM106. In order to improve the assortment of the Southern region of Russia and to create modern intensive orchards, new varieties of apple of domestic breeding were recommended: Margo, Nika, Orphey and Modi (foreign breeding), which have high productivity, immunity to scab (based on Rvi-6 gene), better commerciality and a long period of fruit storage.

Herbaceous peony is an ancient ornamental and medicinal crop, cultivated for thousands of years in China and Japan. Numerous varieties are popular garden plants in different continents and countries, and recently peony has gained a new reputation as cut flowers. Only in Europe, in last 30 years, trade in cut peony has increased 50-fold. This demand has led to biological research and the development of production technologies. Today, more than 25 countries produce cut peony flowers, with primary markets in Europe, Asia and the USA. However, several factors still restrict peony production - challenges in mass propagation, a complicated flowering physiology, and postharvest handling. Here we summarize the contribution of research in plant physiology to the development of new technologies of peony production and flowering. Further research of molecular and biochemical mechanisms, breeding of new cultivars will contribute to the further development of peony industry. Biotechnological applications and long-term postharvest technologies will facilitate creation of Global Peony Chain for successful marketing of this flower.

Nutrient management of high-density apple orchards remains to be a serious problem in central Russia. Enhancing apple productivity by applying higher fertilizer rates leads to an increased environmental burden and undesired consequences. Although the transition to organic farming may solve many horticultural problems, conventional methods still produce higher crop yields. One of the most pressing issues consists in reducing mineral fertilizer use by applying more organic substances. This approach allows soil fertility to be preserved while maintaining high levels of plantation productivity. In the present research, particular attention was paid to potassium nutrition of apple trees. During 2020 and 2021, we studied the effect of potassium fertilizers in various standard amounts and silicon-modified potassium humate on the state of apple trees cv. Ligol grafted on 62-396 rootstock in the experimental orchard of I.V. Michurin Federal Research Center. The orchard was planted in 2018 according to a 1.2×4.5 m pattern (1852 trees per hectare). The experimental design was as follows: control (irrigation); full standard amount of N₂₀P₆K₂₈ fertilizers; ¾ standard amount of N₁₅P₄K₂₁ mineral fertilizers + ½ standard amount of potassium humate, ½ standard amount of N₁₀P₃K₁₄ mineral fertilizers + ½ standard amount of potassium humate; full standard potassium humate amount of 10 L/ha. In 2020, the introduction of potassium humate provided the maximum yield, although without significant differences compared to the use of mineral fertilizers. In 2021, the yield was also at the level achieved with mineral fertilizers. Potassium humate provided a higher nitrogen content in the leaves as compared to mineral fertilizers, largely due to a significant increase in the availability of nitrogen and potassium in the soil. The content of available phosphorus was not significantly affected. This assumes that the effectiveness of humates depends on the soil type. The combined application of reduced standard amounts of mineral fertilizers and potassium humate contributed to maintenance of high yields under with a less dramatic increase in soil acidity.

The paper presents a soft ware and hardware complex with a mobile application based on a neural network, designed to identify apple fruits on tree canopy, to count their number, to determine the quantity of fruits affected by diseases, as well as to estimate the growth rate of apple fruits and, thus, to calculate the total yield during the growing season. The developed soft ware and hardware complex consists of a photo (image) collection unit with client soft ware (a mobile application, a digital camera), a unit for processing the obtained images, which includes a database and a neural network, and a unit for interpretation of the obtained data. A neural network based on VGG-16 and SSD architecture was developed to identify apple fruits on the tree canopy for evaluating apple fruits and distinguishing sound fruits and those affected by disease. Training of the neural network was based on the selected classes of sound red and green apple fruits, and apple fruits affected by diseases – scab, powdery mildew, fruit rot, as well as mechanical damage. The soft ware runs and operates on Ubuntu operating system, a mobile application – on Android. The soft ware package and mobile application are capable of processing incoming photos (images) online, as well as to use previously captured photos. The generated database collects structured information about all field measurements and calculations of the number of apple fruits on the planting rows under study. The experiments conducted on an industrial apple plantation showed that the accuracy of estimating the total number of fruits on the tree canopy compared to the true value was 94.7%, the accuracy of calculating the number of affected fruits was 90.4%. When technical requirements for the server and requirements for images are met, the average recognition rate does not exceed 0.6 seconds per image, the average segmentation rate of the apple fruits from the background does not exceed 0.8 seconds per image, the average speed of analyzing one image and obtaining the recognition result does not exceed 1.5 seconds.