Application of K-means Clustering Algorithm to Commercial Parameters of Pleurotus spp. Cultivated on Representative Agricultural Wastes from Province of Guayas

Author: mycolabadmin
2021-07-04
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Summary

This research explored how to optimize mushroom production using agricultural waste materials in Ecuador’s Guayas province. The study used advanced data analysis techniques to determine the best combinations of mushroom strains and agricultural waste mixtures for growing nutritious edible mushrooms. Impacts on everyday life: • Provides a sustainable way to convert agricultural waste into valuable food products • Offers potential income opportunities for local farmers through mushroom cultivation • Demonstrates methods for producing nutritious, protein-rich food from waste materials • Contributes to reducing agricultural waste and environmental impact • Helps identify optimal growing conditions for commercial mushroom production

Background

The province of Guayas in Ecuador has a significant agricultural sector generating various agricultural wastes. The cultivation of edible mushrooms like Pleurotus species offers an innovative way to utilize these wastes while producing nutritious food products. Pleurotus mushrooms are known for their high nutritional value and medicinal properties, requiring tropical or subtropical climates similar to Guayas for cultivation.

Objective

To analyze commercial parameters of Pleurotus ostreatus and Pleurotus djamor strains using K-means clustering algorithm when cultivated on agricultural wastes from Guayas province. The study aimed to verify the influence of two mixtures of agricultural wastes on mushroom production viability, nutritional profiles, and antioxidant/antimicrobial properties.

Results

The K-means clustering analysis grouped the data into three distinct clusters for both species, showing normal distribution patterns. Mixture M1 demonstrated higher correlation with productivity parameters. The analysis revealed strains with optimal performance in terms of biological efficiency, yield ratios, and biological properties. PCA biplots showed accumulated inertia of 91.5% for P. ostreatus and 93.0% for P. djamor.

Conclusion

The K-means clustering algorithm successfully grouped the data into three clusters, providing clear visualization of relationships between mushroom strains and their commercial parameters when cultivated on agricultural wastes from Guayas province. Mixture M1 showed better results for cultivation of both Pleurotus species. The analysis effectively identified optimal strain-substrate combinations for maximizing productivity and biological properties.

Published in:Journal of Fungi,
Study Type:Experimental Research,
Source: 10.3390/jof7070537