Effect of Different Indole Butyric Acid (IBA) Concentrations in Various Rooting Media on the Rooting Success of Loropetalum chinense var. rubrum Yieh Cuttings and Its Modeling with Artificial Neural Networks

This study aimed to evaluate the rooting success of Loropetalum chinense var. rubrum Yieh cuttings in three different rooting media: 100% peat, 100% perlite, and a 50% peat–50% perlite mixture. Additionally, three concentrations of Indole Butyric Acid (IBA)—1000 ppm, 3000 ppm, and 6000 ppm—were tested, along with a control group consisting of non-hormone-treated cuttings. The chlorophyll content of the leaves was measured in µmol/m2, and its relationship with rooting success was examined. Measurements were conducted every 15 days over a 120-day period. The collected data were analyzed using both an artificial neural network (ANN) and SPSS 29.0.2 statistical software. Results indicated that perlite medium yielded the highest rooting rate and chlorophyll concentration, whereas the peat medium performed the poorest. While 1000 ppm IBA led to the greatest improvement in rooting rate, 6000 ppm resulted in the highest chlorophyll concentration. The highest chlorophyll levels were observed during measurement periods M7, M8, and M9. Analyses of peat moisture and pH indicated that the physicochemical properties of the rooting media significantly influenced cutting development. This study aims to support the identification of optimal propagation methods for this species and to contribute to the literature by developing an ANN model based on the measured parameters.