FORMATION OF CHERRY FRUITS QUALITY AND YIELD UNDER THE INFLUENCE OF ABIOTIC FACTORS IN THE SOUTHERN STEPPE OF UKRAINE
Abstract
Purpose. To scientifically substantiate the patterns of yield formation and fruit quality indicators of sour cherry depending on the influence of abiotic factors and genotype- specific characteristics of cultivars under the conditions of the Southern Steppe of Ukraine, as well as to develop reliable approaches for their quantitative prediction using modern statistical and mathematical tools. The relevance of the study is обусловлена the increasing climate variability, which significantly affects the productivity of fruit crops and necessitates the implementation of adaptive cultivation technologies.
Methods. The methodological basis of the research included field, laboratory, and statistical methods. In particular, analysis of variance (ANOVA) was used to assess the effects of factors and their interactions, correlation analysis to determine the strength and direction of relationships between variables, and mathematical modeling methods (ridge regression, LASSO) to identify key predictors of yield and fruit quality formation and to improve prediction accuracy. Results. Significant variability of the main economically valuable traits was established. Sour cherry yield ranged from 6.33 to 9.33 t/ha, representing an increase of 3.00 t/ha or 47.4% relative to the minimum level. The content of polyphenolic compounds varied from 224.6 to 478.6 mg/100 g, with an increase of 254.0 mg/100 g (113.1%), while vitamin C content increased from 12.4 to 25.6 mg/100 g, i.e., by 13.2 mg/100 g (106.5%). It was proven that genotype determines 42.3% of the total variation in polyphenol content, exceeding the influence of weather conditions, which accounted for 30.7%, indicating the dominant role of hereditary factors in shaping the biochemical composition of fruits. At the same time, strong positive correlations between temperature indicators and productivity were revealed (r = 0.63–0.76), confirming the decisive importance of thermal resources under the regional conditions. The application of regularized regression methods, particularly LASSO, ensured high predictive performance of the models (R² = 0.76–0.83), exceeding the accuracy of traditional approaches by 12–18%, thus allowing a more adequate consideration of the multifactorial nature of agroecosystems. It was established that the integration of genotype and climatic parameters into a unified model enhances prediction reliability and improves decision-making efficiency.
Conclusions. The formation of sour cherry yield and fruit quality is determined by a complex interaction between genotype and abiotic factors, with temperature regime playing a dominant role. The practical implementation of the developed models increases production efficiency by 20–35%, which is manifested in yield stabilization and improvement of biochemical fruit quality indicators.
References
2. Ivanova I., Serdiuk M., Malkina V., Kolisnychenko T., Kryvonos I., Ivashyna L. (2024), Formuvannia smakovykh yakostei plodiv vyshni pid vplyvom abiotychnykh chynnykiv v umovakh pivdnia stepovoi zony Ukrainy [Formation of taste qualities of cherry fruits under the influence of abiotic factors in the conditions of the south of the steppe zone of Ukraine], Innovations and Technologies in the Service Sphere and Food Industry, no. 2 (12), pp. 5-16. [in Ukrainian]
3. Makarova D.H., Vasylenko V.I., Trokhymchuk A.I. (2020), Monitorynh pohodnykh zmin ta yikh vplyv na produktyvnist tsinnoho selektsiinoho henofondu vyshni (Cerasus vulgaris Mill.) u Lisostepu Ukrainy [Monitoring of weather changes and their impact on the productivity of the valuable selection gene pool of sour cherry (Cerasus vulgaris Mill.) in the Forest-Steppe of Ukraine], Sadivnytstvo, vol. 75, pp. 92–101. [in Ukrainian]
4. Ivanova I.Ie., Serdiuk M.Ie., Malkina V.M., Shkinder- Barmina A.M., Kryvonos I.A. (2019), Urozhasnist vyshni zalezhno vid klimatychnykh umov rokiv vyroshchuvannia [Cherry yield depending on the climatic conditions of the years of cultivation], Visnyk ahrarnoi nauky Prychornomoria, vol. 4. DOI: https://doi.org/10.31521/2313-092X/2019-4(104 [in Ukrainian]
5. Malkina V.M., Ivanova I.Ie., Serdiuk M.Ie., Krivonos I.A., Bilous E.S. (2019), Rehresiinyi analiz zalezhnosti urozhainosti vyshni vid hidrotermichnykh faktoriv v umovakh multykolinearnosti [Regression analysis of the dependence of cherry yield on hydrothermal factors under conditions of multicollinearity], Naukovi horyzonty, no. 11 (84), pp. 51–60. [in Ukrainian]
6. Ivanova I.Ie., Serdiuk M.Ie., Tymoshchuk T.M., Kryvonos I.A., Pendrak Ya.I. (2024), Prohnozuvannia vmistu vitaminu C u plodakh vyshni u bezvidkhodnomu lantsiuzi vykorystannia plodovoi syrovyny [Predicting the vitamin C content in cherry fruits in a waste-free chain of fruit raw materials use], Visnyk Umanskoho natsionalnoho universytetu sadivnytstva, vol. 2, pp. 89–95. [in Ukrainian]
7. Ivanova I.Ie., Serdiuk M.Ie., Tymoshchuk T.M., Marenych M.M. (2021), Formuvannia fondu vitaminu C u plodakh chereshni pid vplyvom pohodnykh chynnykiv [Formation of the vitamin C fund in sweet cherry fruits under the influence of weather factors], Visnyk Poltavskoi derzhavnoi aharnoi akademii, no. 2, pp. 59–66. DOI: https://doi.org/10.31210/visnyk2021.02.07. [in Ukrainian]
8. Pendrak Ya.I., Ivanova I.Ie., Serdiuk M.Ie., Tymoshchuk T.M., Kryvonos I.A. (2024), Matematychne modeliuvannia vplyvu pohodnykh faktoriv na formuvannia fondu polifenolnykh rechovyn v plodakh vyshni [Mathematical modeling of the influence of weather factors on the formation of the fund of polyphenolic substances in cherry fruits], Visnyk Khmelnytskoho natsionalnoho universytetu, no. 3, vol. 1 (335), pp. 369–376. [in Ukrainian]
9. Bublyk M. O., Fryziuk L. A., Levchuk L. M. (2014), Fruit crop production distribution in Ukraine: A research note. Chemistry and Chemical Biology: Methodologies and Applications, no. 9 (18), pp. 207–218.
10. Kishchak O.A. (2017), Osnovy promyslovoi kultury chereshni v Lisostepu Ukrainy [Fundamentals of industrial sweet cherry culture in the Forest-Steppe of Ukraine], Ahrarna nauka, Kyiv, Ukraine. [in Ukrainian]
11. Chigozie A. K. (2012), Regression and Principal Component Analyses: a Comparison Using Few Regressors. American Journal of Mathematics and Statistics, no. 2 (1), pp. 1–5. DOI: https://doi.org/10.5923/j.ajms.20120201.01.
12. Serdiuk M.Ie. et al. (2020), Doslidnytskyi praktykum. Ch. 1. Metody doslidzhennia plodoovochevoi ta yahidnoi produktsii: pidruchnyk [Research practice. Part 1. Methods of research of fruit, vegetable and berry products: a textbook], Liuks, Melitopol, Ukraine. [in Ukrainian]
13. DSTU ISO 874-2002 (2002), Frukty ta ovochi svizhi. Vidbir prob [Fresh fruits and vegetables. Sampling], Derzhspozhyvstandart Ukrainy, Kyiv, Ukraine. [in Ukrainian]
14. DSTU ISO 2173:2007 (2010), Produkty z fruktiv ta ovochiv. Vyznachennia rozchynnykh sukhykh rechovyn refraktometrychnym metodom [Fruit and vegetable products. Determination of soluble solids by refractometric method], Derzhspozhyvstandart Ukrainy, Kyiv, Ukraine. [in Ukrainian]
15. Ming-ming C., Jing-lian M. (2015), Application of principal component regression analysis in economic analysis. Proceedings of the 3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics, pp. 1205–1208. DOI: https://doi.org/10.2991/msetasse-15.2015.255.
16. Gujarati D. N. (2004), Basic econometrics. 4th ed. McGraw-Hill, New York, USA.
This work is licensed under a Creative Commons Attribution 4.0 International License.
