首页 > 分享 > 基于图像处理的菊花收缩率及色泽变化研究

基于图像处理的菊花收缩率及色泽变化研究

花匠小妙招
2025-02-05 19:51

摘要：

外观品质是评价干燥花质量的重要指标。为了实现对干燥过程中菊花外观品质的快速无损检测，本研究将计算机视觉技术应用于菊花的红外辅助热风干燥过程中，基于Python语言开发了一种图像处理算法来获取在不同温度下（35 ℃，50 ℃和65 ℃）的干燥过程中菊花花瓣和花蕊表面收缩率和色泽参数的变化信息，并作为外观品质的评价指标，以此实现对干燥过程的精准控制。干燥动力学研究表明：菊花的干燥过程中始终处于降速干燥阶段，且干燥温度的升高导致了干燥时间的显著（p<0.05）缩短和干燥速率的显著升高。基于平方确定系数（R2）、残差平方和（RSS）、均方误差（MSE）值评估了常用的薄层干燥数学模型与试验数据的拟合程度，发现Henderson and Pabis模型、Page模型、Lewis模型与试验数据拟合度更高，能更好地描述菊花的干燥过程。此外，基于图像处理获取的不同干燥阶段菊花的表面收缩率及亮度值（L*）、红/绿值（a*）和黄/蓝值（b*）发现菊花形态和色泽的变化取决于干燥温度和干燥时间的共同作用，更低的干燥温度和更短的干燥时间更有利于抑制菊花在干燥过程的外观品质的劣变。进一步对零阶、一阶和一阶分数模型预测的收缩率和色泽（L*、a*和b*）值与试验数据进行线性回归分析，发现一阶分数模型能更为精准地预测菊花在干燥过程中收缩率以及色泽的变化规律。

关键词: 菊花, 图像处理, 干燥动力学, 收缩率, 色泽, 预测模型

Abstract:

Appearance quality is an important indicator in assessing the quality of dried chrysanthemums. To achieve rapid and non-destructive detection of the appearance quality of chrysanthemums during drying， this study applied computer vision technology in the infrared-assisted hot air drying of chrysanthemums and developed a Python-based image processing algorithm to acquire information on the changes in the shrinkage and color of petals and stamens of chrysanthemums at different temperatures （35 ℃， 50 ℃， and 65 ℃）. These parameters serve as evaluation indices for the appearance quality and facilitat precise control of the drying process. The kinetic analysis showed that the drying of chrysanthemums had a consistently decreasing drying rate. High drying temperatures significantly reduced drying time and increased drying rates （p<0.05）. Evaluation of the fit of mathematical models for thin-layer drying， including the Henderson and Pabis model， the Page model， and the Lewis model， showed that these models were in better agreement with the experimental data and thus more accurately described the drying process of chrysanthemums. Furthermore， changes in shrinkage rate and lightness （L*）， red/green （a*）， and yellow/blue （b*） values during drying showed that the morphological and color of chrysanthemums depended on drying temperature and time. Lower temperatures and shorter drying times were favorable for maintaining the appearance quality of the chrysanthemums. Linear regression analysis using zero-order， first-order， and first-order fractional models showed that the first-order fractional model provided more accurate predictions of shrinkage and color changes during the drying process of chrysanthemums.

Key words: chrysanthemum, image processing, drying kinetics, shrinkage, color, prediction model

中图分类号:

S37