王 冬,张鹤冬,朱业伟,汪 军,曹江娜,韩 平.基于LVF-NIR的樱桃可溶性固形物含量无损速测模型的建立与优化[J].食品安全质量检测学报,2020,11(3):854-859
基于LVF-NIR的樱桃可溶性固形物含量无损速测模型的建立与优化
Development and optimization of the rapid and non-destructive quantitative models of soluble solid content of cherry based on LVF-NIR spectrometer
投稿时间:2018-01-16  修订日期:2018-04-20
DOI:
中文关键词:  樱桃  可溶性固形物含量  线性渐变分光  定量校正模型
英文关键词:cherry  soluble solid content  linear variable filter  quantitative calibration model
基金项目:北京市农林科学院创新能力建设-高效节水农业专项研究项目(储备性研究课题)(KJCX20180409)、农业部农产品质量安全风险评估实验室(北京)开放课题(KFKT201702)、北京工商大学食品安全大数据技术北京市重点实验室开放课题(BUBD-2017KF-11)
作者单位
王 冬 北京农业质量标准与检测技术研究中心;农业部农产品质量安全风险评估实验室(北京);农业部(华北)都市农业重点实验室 
张鹤冬 北京农业质量标准与检测技术研究中心;北京工商大学食品安全大数据技术北京市重点实验室 
朱业伟 北京格致同德科技有限公司 
汪 军 北京格致同德科技有限公司 
曹江娜 北京格致同德科技有限公司 
韩 平 北京农业质量标准与检测技术研究中心;农业部农产品质量安全风险评估实验室(北京);农业部(华北)都市农业重点实验室 
AuthorInstitution
WANG Dong Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Sciences;Risk Assessment Laboratory for Agro-products (Beijing), Ministry of Agriculture, P. R. China;Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture, P. R. China 
ZHANG He-Dong Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Sciences;Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University 
ZHU Ye-Wei Beijing Great-Tech. Technology Development Co., Ltd 
WANG Jun Beijing Great-Tech. Technology Development Co., Ltd 
CAO Jiang-Na Beijing Great-Tech. Technology Development Co., Ltd 
HAN Ping Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Sciences;Risk Assessment Laboratory for Agro-products (Beijing), Ministry of Agriculture, P. R. China;Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture, P. R. China 
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中文摘要:
      目的 建立基于便携式近红外光谱仪的樱桃可溶性固形物含量无损快速定量检测模型, 从而实现樱桃品质的无损快速检测。方法 以北京通州产红灯樱桃、黄玉樱桃为研究对象, 采用便携式线性渐变分光近红外光谱仪采集光谱数据, 并采用折光仪测定其可溶性固形物含量; 采用偏最小二乘回归结合全交互验证算法将光谱数据与可溶性固形物含量测定值建立定量校正模型, 采用外部验证集对模型的预测性能做进一步测试。结果 红灯樱桃可溶性固形物含量模型的R2C、RMSEC、R2CV、RMSECV、RPD分别为0.9194、0.79、0.8920、0.92、3.54, 黄玉樱桃可溶性固形物含量模型的R2C、RMSEC、R2CV、RMSECV、RPD分别为0.8618、0.76、0.8246、0.86、2.70; 两种樱桃可溶性固形物含量合并模型的R2C、RMSEC、R2CV、RMSECV、RPD分别为0.9125、0.81、0.8946、0.89、3.38。结论 基于便携式线性渐变分光近红外光谱仪数据所建校正模型具有较好的准确度, 可满足樱桃可溶性固形物含量的无损快速检测需求。
英文摘要:
      Objective To determine the cherry quality rapidly and nondestructively, the calibration models of the soluble solid content (SSC) of cherries based on the linear variable filter (LVF) near-infrared (NIR) spectrometer were developed. Methods Taking the Hongdeng and Huangyu cherries from Tongzhou District, City of Beijing as the research objects, the portable LVF-NIR spectrometer were applied to collect the LVF-NIR spectra data. Meanwhile, the values of SSC was determined by the refractometer. Partial least square (PLS) regression combined with full cross validation algorithm were applied to develop the quantitative analysis models of SSC, with the external validation sets being predicted to validate the prediction ability of the models developed above. Results For Hongdeng cherry, the R2C, RMSEC, R2CV, RMSECV and RPD of the calibration model were 0.9194, 0.79, 0.8920, 0.92, 3.54, respectively; for Huangyu cherry, the R2C, RMSEC, R2CV, RMSECV and RPD of the calibration model were 0.8618, 0.76, 0.8246, 0.86, 2.70, respectively; furthermore, for the both cherries, the R2C, RMSEC, R2CV, RMSECV and RPD of the calibration model were 0.9125, 0.81, 0.8946, 0.89, 3.38, respectively. Conclusion The calibration models based on LVF-NIR spectrometer are of good accuracy, which can be able to satisfy the requirements of rapid and non-destructive determination of SSC of cherries.
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