Fast online evaluation of vegetable freshness using single turnover chlorophyll fluorescence

Author:

Shi Chaoyi1,Yin Gaofang2,Gao Xianhe1,Yu Shaohui3,Lu Cuiping1,Wang Zhongma1,Gu Yanhong1,Zhang Sheng1

Affiliation:

1. Hefei University

2. Chinese Academy of Sciences, Anhui Institute of Optics and Fine Mechanics

3. Hefei Normal University

Abstract

Vegetable freshness evaluation is of great significance to ensure the quality of vegetables and realize fine production. Existing vegetable freshness evaluation methods have difficulty realizing rapid online evaluation and industrial applications due to such disadvantages as being susceptible to subjective factors, complicated operation, large computation, and high hardware cost. To solve the above problems, a rapid online vegetable freshness evaluation method was developed based on the single turnover chlorophyll fluorescence parameters F o , F v / F m and σ P S I I . A freshness evaluation model for spinach and swamp cabbage was established based on a classification and regression tree algorithm, using F o , F v / F m and σ P S I I as sample features. The model divided the freshness of spinach and swamp cabbage into three grades: good, medium, and poor, and the leave-one-out cross validation results showed that the freshness evaluation accuracies of spinach and swamp cabbage reached 98.1% and 94.3%, respectively.

Funder

National Natural Science Foundation of China

Science and Technology Major Project of Anhui Province

The Foundation of President of Hefei Institute of Physical Science, Chinese Academy of Sciences

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics,Engineering (miscellaneous),Electrical and Electronic Engineering

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