| 摘要: |
| 【目的】应用近红外光谱漫反射技术在线检测脐橙内部的可溶性固形物含量(SSC)。【方法】以0.3 m/s的速度、400 W的光照强度获取脐橙（脐橙样品为97个，其中74个为校正集，23个样品为预测集）的漫反射光谱；对比不同光谱预处理方法（平滑、一阶微分、二阶微分等）对偏最小二乘回归（PLSR）所建预测模型性能的影响，建立PLSR、主成分回归（PCR）和多元线性回归（MLR）在线检测脐橙可溶性固形物含量的预测模型。【结果】在520～1 000 nm光谱范围，卷积平滑（S-G）能有效提高光谱的信噪比，改善模型预测精度；基于PLSR所建立的预测模型较PCR和MLR更为理想，其预测相关系数（RP）为0.90，预测均方根误差（RMSEP）为0.61。【结论】利用在线近红外光谱技术检测脐橙可溶性固形物含量是可行的。 |
| 关键词: 脐橙 近红外光谱 在线检测 可溶性固形物 |
| DOI： |
| 分类号: |
| 基金项目:国家“863”高技术研究发展计划项目(2012AA101906)；科技部农业科技成果转化项目(2011GB2C500008)；赣鄱英才555工程领军人才培养计划(2011-64)；江西省光电检测工程技术研究中心资助项目(赣科发财字［2012］155号)；江西省研究生创新专项资金项目(YC2013-S166) |
|
| Online detection of soluble solids in navel orange using near-infrared diffuse spectroscopy |
|
LIU Yan-de,ZHAI Jian-long
|
| Abstract: |
| 【Objective】The research focused on online detection of soluble solids content (SSC) in navel oranges using near-infrared spectroscopy.【Method】Navel oranges spectrum was collected using diffuse reflectance with movement speed of 0.3 m/s and light intensity of 400 W.A total of 97 navel oranges were measured in the experiment,among which 74 were within the calibration set and 23 were within validation set.Different pretreatment methods such as Savitzky Golay smooth,first derivative,second derivative and so on were compared.Different calibration models were developed based on partial least squares (PLSR),principal component regression (PCR),and multiple linear regression (MLR).【Result】In spectral range of 520-1 000 nm,the S-G smooth could increase S/N ratio and improve the performance of models.The best calibration model was based on PLSR method with the prediction correlation coefficients (RP) of 0.90 and the root mean square errors of prediction (RMSEP) of 0.61.【Conclusion】The established online detection of SSC in navel oranges is feasible. |
| Key words: navel orange near-infrared diffuse spectroscopy online detection soluble solids content |
