Contributions to the Optimization of the Medicinal Plant Sorting Process into Size Classes

This study aims to optimize and assess the quality of the sorting process into homogeneous size classes of dried and chopped medicinal plants, by obtaining multivariate regression functions of polytropic and polynomial forms. Assessment of sorting quality was carried out by calculating the average coefficient of separation. The influence of several important factors (material feed rate on the sieve, sieve dimensions, sieve inclination angle, sieve oscillation frequencies) on the sorting process was followed. Research was carried out on dried nettle herb (Urtica dioica) using a plant sorter with plane sieves, which allowed for modifying some constructive and functional parameters, making it possible to obtain optimal values. The results showed that the dry nettle herb chopped in bulk at 4 mm, with a moisture of 11.45%, was optimally sorted (index of average separation coefficient, 0.922) if the following parameters were met: drive mechanism speed n = 1000 rpm; sieve inclination angle alpha = 12.08 degrees; material-specific flow q = 4 kg/dm center dot h; recommended sieve length L = 1.4 m. It was observed that at high rates, the average coefficient of separation decreased with the decrease in the sieve drive mechanism speed, and when the inclination angle of the sieve decreased, the average coefficient of separation increased. The maximum average deviation of the average separation coefficient was 5.5% for the polytropic function. The new advanced processing technologies of medicinal plants involve the short-term production of quality-finished products, thus supporting the processors of medicinal plants and the consumers of phytotherapeutic products with beneficial effects for health.

Automated summary

This study aims to optimize and assess the quality of sorting dried and chopped medicinal plants into homogeneous size classes. The results showed that optimal sorting of dry nettle herb could be achieved at specific parameters. The research has important implications for advanced processing technologies of medicinal plants.