The primary objective of this research was to ascertain the optimal circumstances for the successful growth of black chokeberry (Aronia melanocarpa (Michx.) Elliott) using tissue culture techniques. Additionally, the study aimed to explore the potential use of machine learning algorithms in this context. The present research investigated a range of in vitro parameters such as total number of roots (TNR), longest root length (LRL), average root length (ARL), number of main roots (NMR), number of siblings (NS), shoot length (SL), shoot diameter (SD), leaf width (LW), and leaf length (LL) for Aronia explants cultivated in different media (Murashige and Skoog (MS) and woody plant medium (WPM)) with different concentrations (0, 0.5, 1, 1.5, and 2 mg L⁻¹) of indole-3-butyric acid (IBA). The study showed that IBA hormone levels may affect WPM properties, affecting the LRL and ARL variables. Aronia explant media treated with 2 mg L⁻¹ IBA had the greatest TNR, NMR, NS, SL, and SD values; 31.67 pieces, 2.37 pieces, 5.25 pieces, 66.60 mm, and 2.59 mm, in that order. However, Aronia explants treated with 1 mg L⁻¹ IBA had the highest LW (9.10 mm) and LL (14.58 mm) values. Finally, Aronia explants containing 0.5 mg L⁻¹ IBA had the greatest LRL (89.10 mm) and ARL (57.57 mm) values. In general, the results observed (TNR, LRL, ARL, NMR, NS, SL, SD, LW, and LL) indicate that Aronia explants exhibit superior growth and development in WPM (25.68 pieces, 68.10 mm, 51.64 mm, 2.17 pieces, 4.33 pieces, 57.95 mm, 2.49 mm, 8.08 mm, and 14.26 mm, respectively) as opposed to MS medium (20.27 pieces, 59.92 mm, 47.25 mm, 1.83 pieces, 3.57 pieces, 49.34 mm, 2.13 mm, 6.99 mm, and 12.21 mm, respectively). In the context of the in vitro culturing of Aronia explants utilizing MS medium and WPM, an analysis of machine learning models revealed that the XGBoost and SVM models perform better than the RF, KNN, and GP models when it comes to making predictions about those variables. In particular, the XGBoost model stood out due to the fact that it had the greatest R-squared value, and showed higher predictive ability in terms of properly forecasting values in comparison to actual outcomes. The findings of a linear regression (LR) analysis were used in order to conduct an efficacy study of the XGBoost model. The LR results especially confirmed the findings for the SD, NS, and NMR variables, whose R-squared values were more than 0.7. This demonstrates the extraordinary accuracy that XGboost has in predicting these particular variables. As a consequence of this, it is anticipated that it will be beneficial to make use of the XGboost model in the dosage optimization and estimation of in vitro parameters in micropropagation studies of the Aronia plant for further scientific investigation.

This study aimed to investigate changes in fruit characteristics, total phenolics, total antioxidant capacity, organic acids, sugar content, and fatty acid composition in ten walnut genotypes and three cultivars grown at different altitudes under Mediterranean climate conditions. At altitudes of 500 m and 1200 m, total phenolics ranged between 237.51 and 412.96 mg GAE/100 g dw and 234.94 and 392.31 mg GAE/100 g dw, respectively. According to DPPH radical inhibition, the total antioxidant capacity varied between 47.65% and 64.99% at an altitude of 500 m and between 57.76% and 68.92% at an altitude of 1200 m. The oil content demonstrated variations between 53.44% and 76.17% at an elevation of 500 m and between 43.11% and 67.03% at an altitude of 1200 m. At both 500 m and 1200 m altitudes, linoleic acid emerged as the predominant fatty acid and ranged from 58.82% to 62.44% at 500 m altitude and from 57.33% to 59.38% at 1200 m altitude. Notably, malic acid was identified as the primary organic acid, with concentrations ranging from 1.35% to 7.33% at both altitudes. In conclusion, this study demonstrates that walnut seeds are abundant in oil, protein, total phenolics, antioxidants, and fatty acids, with variations influenced by the cultivar or genotype and notably affected by altitude.

This study was conducted to investigate the intake of micro plant nutrients of promising genotypes in the selection study of some wild plums that can be rootstock for apricots in Malatya and Elazığ region. The study was carried out in 2020 on the land of Malatya Apricot Research Institute and in the Soil, Plant and Water Analysis Laboratory of the Kahramanmaraş Eastern Mediterranean Transitional Zone Agricultural Research Institute. Soil samples were conducted from 0-30 cm and 30-60 cm depths in order to determine the micronutrients in the soil from the area where the trial was established. According to the analysis results, it was determined that the micronutrient elements examined in the top soil (0-30 cm), except boron, were at sufficient levels. As a result of the analysis of leaf samples taken from 69 rootstocks selected in June, scoring was made by applying weighted grading to the amounts obtained. This method has been applied for the first time in the world with this study. At the end of the study, in the leaf contents, iron 33.65-101.00 mg kg-1, manganese 19.01-106.27 mg kg-1, copper 4.15-13.03 mg kg-1, zinc 9.25-35.55 mg kg-1 and boron 19.54-35.55 mg kg-1 varied between. It has been determined that obtained these values are highly similar to the reference values, and when compared with other literature data, manganese is high, iron is relatively low, and other micronutrients elements are sufficient.