摘要
糖度是评价脐橙内部品质的重要指标之一,由于水果自身尺寸差异,造成糖度预测模型稳健性差,预测精度不高,因此消除水果尺寸差异带来的影响,对提高水果分选模型精度具有重要意义。对比分析了脐橙漫透射、多点发射与接收及环形发射与接收漫反射光谱,其中,不同检测平台上,由于光程差的不同,大果光谱能量均比小果光谱能量要强,而环形发射与接收漫反射光谱能量要强于其他两种光谱,漫透射光谱能量最弱,波峰与波谷位置大致相同。分别建立不同检测方式下脐橙尺寸预测模型,其中,漫透射检测方式下尺寸预测模型的预测集相关系数为0.60,预测集均方根误差为3.95 mm,多点发射与接收漫反射检测方式下尺寸预测模型的预测集相关系数为0.97,预测集均方根误差为1.46 mm,环形发射与接收漫反射检测方式下小果预测模型的预测集相关系数为0.96,预测集均方根误差为1.73 mm。分别建立三种不同检测方式下大果、小果、混合果以及多元散射校正预处理的混合果糖度预测模型,小果的糖度预测模型精度均要高于大果和混合果,其中漫透射检测方式下小果预测模型的预测集相关系数为0.76,预测集均方根误差为0.81°Brix,多点发射与接收漫反射检测方式下小果预测模型的预测集相关系数为0.72,预测集均方根误差为0.97°Brix,环形发射与接收漫反射检测方式下小果预测模型的预测集相关系数为0.72,预测集均方根误差为0.93°Brix。经过多元散射校正预处理光谱后,近红外漫透射光谱的混合果模型精度要优于小果的模型,模型预测集相关系数为0.84,预测集均方根误差为0.64°Brix,而在两种漫反射检测方式中,多混合果模型精度反而降低。实验结果表明:在漫透射检测方式中,使用多元散射校正预处理光谱可以消除尺寸差异影响,在漫反射检测方式中,先进行尺寸分选,再进行糖度分选,也可以避免尺寸差异带来的影响。该研究为大宗水果快速在线分选提供了参考和理论支持。
Brix is one of the important indicators for evaluating the internal quality of navel orange.Due to the difference in the size of the fruit itself,the sugar content prediction model is poor in robustness and the prediction accuracy is not high.Therefore,eliminating the influence of fruit size effect is of great significance for improving the accuracy of fruit sorting model.The diffuse transmission,multi-point emission and reception,and circular emission and reception diffuse reflectance spectra of navel orange were compared and analyzed.Among different detection platforms,the spectral energy of the big fruit was stronger than that of the small fruit due to the difference of optical path difference,and the circular emission was obtained.The energy of the diffuse reflection spectrum is stronger than that of the other two spectra.The diffuse transmission spectrum energy is the weakest,and the peaks and troughs are roughly the same.The prediction model of orange navel size under different detection methods is established respectively.Among them,the prediction coefficient of the size prediction model under the diffuse transmission detection mode is 0.60,the root mean square error of the prediction set is 3.95 mm,and the size of the multi-point transmission and reception diffuse reflection detection mode.The prediction set correlation coefficient of the prediction model is 0.97.The prediction set RMS error is 1.46 mm,and the prediction set correlation coefficient of the small fruit prediction model under the ring emission and reception diffuse reflection detection mode is 0.96,and the prediction set RMS error is 1.73 mm.The mixed fructose prediction models of large fruit,small fruit,mixed fruit and multi-scattering correction pretreatment were established under three different detection methods.The precision of the sugar content prediction model of small fruit was higher than that of large fruit and mixed fruit,and diffuse transmission detection The correlation coefficient of the prediction set of the small fruit prediction model is 0.76,the root means square error of the prediction set is 0.81°Brix,and the correlation coefficient of the prediction set of the small fruit prediction model under the multi-point transmission and reception diffuse reflection detection mode is 0.72.The square root error is 0.97°Brix,and the prediction set correlation coefficient of the small fruit prediction model under the ring emission and reception diffuse reflection detection mode is 0.72,and the prediction set RMS error is 0.93°Brix.After multi-scattering correction pre-processing spectra,the hybrid fruit model of near-infrared diffuse transmission spectrum is better than the small fruit model.The correlation coefficient of the model prediction set is 0.84,and the root means square error of the prediction set is 0.64°Brix.In the diffuse reflection detection mode,the accuracy of the multi-mixed fruit model is reduced.The experimental results show that in the diffuse transmission detection method,the multi-scatter correction pre-processing spectrum can eliminate the effect of the size effect.In the diffuse reflection detection method,the size sorting is performed first,followed by the sugar separation,which can also avoid the size effect.This study provides reference and theoretical support for the rapid online sorting of bulk fruits.
作者
刘燕德
饶宇
孙旭东
姜小刚
徐海
李雄
王观田
徐佳
LIU Yan-de;RAO Yu;SUN Xun-dong;JIANG Xiao-gang;XU Hai;LI Xiong;WANG Guan-tian;XU Jia(School of Mechanical and Vehicle Engineering,East China Jiaotong University,Nanchang 330013,China)
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2020年第10期3241-3246,共6页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(31760344)
江西省杰出青年人才资助计划项目(20171BCB23060)
水果光电检测技术能力提升项目(S2016-90)资助。
关键词
脐橙
近红外
尺寸差异
无损检测
糖度
Navel orange
Near infrared
Size effect
Nondestructive testing
Sugar content