Application of K-Means Clustering Algorithm to Commercial Parameters of <i>Pleurotus</i> spp. Cultivated on Representative Agricultural Wastes from Province of Guayas

• Main Authors: Fabricio Guevara-Viejó, Juan Diego Valenzuela-Cobos, Purificación Vicente-Galindo, Purificación Galindo-Villardón
• Format: Article
• Language: English
• Published: MDPI AG 2021-07-01
• Series: Journal of Fungi
• Subjects: K-means clustering algorithm; <i>Pleurotus ostreatus</i>; <i>Pleurotus djamor</i>; commercial parameters; visualization
• Online Access: https://www.mdpi.com/2309-608X/7/7/537

Data of the commercial parameters of <i>Pleurotus ostreatus</i> and <i>Pleurotus djamor</i> were analyzed using the data mining technique: K-means clustering algorithm. The parameters evaluated were: biological efficiency, crop yield ratio, productivity rate, nutritional composition, antioxidant and antimicrobial activities in the production of fruit bodies of 50 strains of <i>Pleurotus ostreatus</i> and 50 strains of <i>Pleurotus djamor</i>, cultivated on the most representative agricultural wastes from the province of Guayas: 80% sugarcane bagasse and 20% wheat straw (M1), and 60% wheat straw and 40% sugarcane bagasse (M2). The database of the parameters obtained in experimental procedures was grouped into three clusters, providing a visualization of the strains with a higher relation to each parameter (vector) measured.