System identification of quality evaluations for vegetable seedlings

摘要

The model of fuzzy inference was successfully developed and identified to simulate human's decision in evaluating seedling quality of cabbage. Physical properties of seedling stalks and leaves were measured while seedling quality, in terms of score, determined by a human expert was recorded. Fuzzy analyses showed that weight-to-height ratio, sturdiness quotient, leaf thickness, stalk height, stem diameter and chlorophyll content are important parameters related to seedling quality. The inference scheme gives predicted scores in good agreement with human expert. The method developed would contribute to a better sorting algorithm for seedlings being transplanted to the field, and would also form a basis for an expert system or decision support for evaluating seeding quality.