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不同产地苹果糖度可见近红外光谱在线检测
引用本文:刘燕德,徐海,孙旭东,姜小刚,饶宇,徐佳,王军政.不同产地苹果糖度可见近红外光谱在线检测[J].中国光学,2020(3):482-491.
作者姓名:刘燕德  徐海  孙旭东  姜小刚  饶宇  徐佳  王军政
作者单位:华东交通大学机电与车辆工程学院;水果智能光电检测技术与装备国家地方联合工程研究中心
基金项目:国家自然科学基金(No.31760344);江西省创新能力建设项目(No.S2016-90)。
摘    要:为了实现不同产地苹果糖度的快速在线无损检测,减少产地差异对近红外光谱检测模型的影响,建立了不同产地苹果糖度的在线检测通用模型。首先,采用水果动态在线检测设备采集了包括栖霞、洛川与会宁3个产地的红富士苹果的漫透射光谱。其次,采用偏最小二乘算法(PLS),结合无信息变量消除(UVE)方法,筛选出58个特征变量,建立了苹果糖度的UVE-PLS通用模型,该模型对个体产地预测集及总预测集的均方根误差分别为0.50~0.74°Brix与0.63°Brix,较原始个体模型分别提高了23.2%~44.4%与35.7%。最后,提出了一个新的外部验证样本集对模型性能进行评价,其残留预测偏差为2.33,预测值在±1.0°Brix和±1.5°Brix误差范围内的占比分别为85%与100%。实验结果表明:建立多个产地苹果糖度的在线检测通用模型,能够提高其他产地样本糖度的预测稳健性,并且采用合适的波长筛选方法能够简化模型。开发不同产地水果内部品质通用模型在波长有限的光谱设备中具有良好的应用潜力。

关 键 词:在线检测  近红外光谱  糖度  偏最小二乘

On-line detection of soluble solids content of apples from different origins by visible and near-infrared spectroscopy
LIU Yan-de,XU Hai,SUN Xu-dong,JIANG Xiao-gang,RAO Yu,XU Jia,WANG Jun-zheng.On-line detection of soluble solids content of apples from different origins by visible and near-infrared spectroscopy[J].Chinese Optics,2020(3):482-491.
Authors:LIU Yan-de  XU Hai  SUN Xu-dong  JIANG Xiao-gang  RAO Yu  XU Jia  WANG Jun-zheng
Institution:(School of Mechatronics&Vehicle Engineering,East China Jiaotong University,Nanchang 330013,China;National and Local Joint Engineering Research Center of Fruit Intelligent Photoelectric Detection Technology and Equipment,Nanchang 330013,China)
Abstract:In order to realize fast,on-line,non-destructive testing of the Soluble Solids Content(SSC)of apples from different origins,and to reduce the effect of origin variability on NIR models,a universal model for predicting the SSC of apples from different origins is established.Firstly,the diffuse transmission spectra of Fuji apples from Qixia,Luochuan and Huining are collected with fruit dynamic online detection equipment.Then,58 characteristic variables are selected and a UVE-PLS universal model for predicting the SSC of apples is established using the Partial Least Squares(PLS)algorithm combined with Uninformative Variable Elimination(UVE).The root mean square errors of single-origin prediction sets and the total-origin prediction set are 0.50~0.74°Brix and 0.63°Brix,respectively,which increase by 23.2%~44.4%and 35.7%re-spectively compared to the original individual model.Finally,a new external sample set is used to assess the performance of the model,showing a residual prediction deviation of 2.33 and ratios of the predicted values within the error range of±1.0°Brix and±1.5°Brix of 85%and 100%,respectively.Experimental results indicate that the establishment of a universal model for on-line detection of the SSC of apples,including those from multiple origins can improve the robustness of predicting the SSC of the samples from other origins.The results also show that an appropriate wavelength screening method can simplify the model.The development of a common model for the internal quality of fruit from different origins has strong potential for applications in wavelength-limited spectroscopy equipment.
Keywords:online detection  near infrared spectroscopy  soluble solids  partial least squares
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