Biological Engineering Analysis of Vermicompost Based on Image Features and Machine Learning

Abstract

Earthworm manure is a soil enhancement product that is homogeneous, permeable, ecological, and organic. It has a particle structure that is substantially greater than the soil’s surface area. Using a suitable quantity of earthworm fertilizer in the soil will improve the nutritional state of the soil surface, as well as the microbial control system and drainage capacity. Bioengineering earthworm dung is now a tough challenge, but picture quality evaluation can help enhance the organic fertilizer treatment process for earthworm manure. Researchers began researching appropriate assessment methods in order to assure the influence of earthworm excrement and to precisely and effectively measure changes in image quality. As a result, we must first determine the consistency qualities, extract the image's color and texture, and then create a comparable vector with 11 dimensions. Finally, we learn how to train the picture quality regression model using the mechanical learning (ML) approach. As a result, an effective and precise image quality evaluation system was created, and earthworm manure bioengineering was effectively applied.