插入式油菜籽叶绿素含量无损检测装置设计与实验

Design and Test of Insertable Non-destructive Testing Device for Chlorophyll Content of Rapeseeds

摘要:

油菜是我国第一大油料作物，生产中常采用联合收获机一次性收获，因此收获的油菜籽叶绿素含量差异较大，影响油品质量和油脂加工成本，油菜籽中的叶绿素含量现场实时检测在油菜籽收购、加工等环节中具有重要意义。以研发便携式、低成本油菜籽叶绿素无损快速检测装置为目的，根据油菜籽堆放储藏等特性，设计插入式检测探头，并研制了一种基于多光谱传感器的低成本油菜籽叶绿素无损检测装置。基于所研制检测装置建立了油菜籽叶绿素含量的偏最小二乘预测模型，经光谱形状特征（Spectral shape feature, SSF）和连续投影算法（Successive projections algorithm, SPA）预处理后预测模型决定系数和均方根误差分别为0.9414和2.0261mg/kg。同时，基于Raspberry Pi 3B和QT5开发工具，采用C++语言开发了实时分析控制软件，实现了一键式人机交互控制。最后，选取25组未参与建模的油菜籽样品对装置检测精度和稳定性进行了外部验证，装置对每个样品重复检测3次叶绿素含量平均变异系数为3.27%，装置预测值与实际理化值决定系数和均方根误差分别为0.9358和1.9071mg/kg。

Abstract:

Rapeseed is the most important oil crop in China. In production practices, combined harvesters are commonly employed for one-time harvesting, resulting in significant variations in chlorophyll content among harvested rapeseeds. These variations adversely affect oil quality and increase processing costs, making real-time, on-site chlorophyll content detection crucial during rapeseed procurement and processing. To develop a portable, low-cost, and non-destructive rapid chlorophyll detection device for rapeseed, an insertion-type probe was specifically designed based on the storage characteristics of bulk rapeseed. A low-cost, non-destructive chlorophyll detection device was developed using a multispectral sensor. A partial least squares (PLS) prediction model for rapeseed chlorophyll content was established based on the developed device. After preprocessing with spectral shape feature (SSF) and successive projections algorithm (SPA), the model achieved a coefficient of determination (R2) of 0.9414 and a root mean square error (RMSE) of 2.0261mg/kg. Additionally, a real-time analysis and control software was developed by using C++ on Raspberry Pi 3B with QT5, enabling one-click human-machine interaction. Finally, the accuracy and stability of the device were externally validated by using 25 rapeseed samples not involved in modeling. Each sample was measured three times, yielding an average coefficient of variation (CV) of 3.27% for chlorophyll content. The predicted values exhibited an R2 of 0.9358 and an RMSE of 1.9071mg/kg compared with that of reference physicochemical measurements. The results demonstrated that the insertion-type non-destructive chlorophyll detection device met the requirements for on-site real-time detection, providing technical support for the industrialization of rapeseed processing.