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基于数字光处理技术的梨可溶性固形物含量的无损速测研究 被引量:2

Research on the rapid and non-destructive determination of soluble solid content of pears based on digital light procession
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摘要 目的为降低近红外光谱仪器制造成本,将近红外技术推广到农业生产一线,检验自主集成水果品质无损快速分析仪实验样机性能。方法以北京大兴产黄金梨、园黄梨为例,利用基于数字光处理技术内核的实验样机采集数据,采用偏最小二乘回归结合全交互验证算法分别建立黄金梨、园黄梨以及两种梨的可溶性固形物含量定量校正模型,并采用外部验证集对模型预测性能做进一步验证。结果黄金梨、园黄梨以及两种梨的可溶性固形物含量模型的测定系数R^2分别为0.6136、0.6576、0.5105,RMSEC分别为0.71、0.79、0.87:交互验证测定系数R^2_(CV)分别为0.5332、0.5076、0.4193,RMSECV分别为0.78、0.96、0.95;外部验证集相关系数r分别为0.7239、0.6825、0.6550,RMSEP分别为0.83、1.03、0.94。结论基于数字光处理技术内核自主集成的水果品质无损快速分析仪器在梨可溶性固形物含量的无损速测以及降低仪器制造成本方面具有一定的应用潜力。 Objective In order to decrease the manufacturing cost of the near-infrared (NIR) spectrometer to extend NIR technology to the frontline of agricultural production, and validate the autonomous integrating experimental prototype of the rapid and nondestructive analyzer for fruit quality. Methods Taking the Huangjin pear and Yuanhuang pear as the experimental objectives, based on the data collected by experimental prototype with the kernel of digital light procession (DLP) technology, the calibration models of soluble solid content (SSC) for Huangjin pear, Yuanhuang pear and the both, were developed by the partial least square (PLS) regression combined with full cross validation algorithm. Furthermore, the external validation sets were collected to validate the prediction performance of the models developed. Results For Huangjin pear, Yuanhuang pear and the both, the determination coefficients of calibration (RE) were 0.6136, 0.6576 and 0.5105 respectively; the RMSEC were 0.71, 0.79 and 0.87 respectively; the determination coefficients of full cross validation (R2cv) were 0.5332, 0.5076 and 0.4193 respectively; the RMSECV were 0.78, 0.96 and 0.95 respectively. Meanwhile, for the extemal validation set, the correlation coefficients (r) were 0.7239, 0.6835 and 0.6550 respectively; the RMSEP were 0.83, 1.03 and 0.94 respectively. Conclusion The autonomous integrating experimental prototype of the rapid and nondestructive analyzer for fruit quality based on DLP technology has certain application potential in the rapid and nondestructive determination of SSC for pears and the decreasement of the manufacturing cost of the instrument.
作者 王冬 王世芳 罗娜 朱业伟 韩平 卢娜 WANG Dong;WANG Shi-Fang;LUO Na;ZHU Ye-Wei;HAN Ping;LU Na(Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;Risk Assessment Laboratory for Agro-products (Beo'ing), Ministry of Agriculture, P. R. China, Beoing 100097, China;Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture, P. R. China, Beijing 100097, China;Beijing Great-Tech. Technology Development Co., Ltd., Beijing 100124, China)
出处 《食品安全质量检测学报》 CAS 2018年第11期2722-2727,共6页 Journal of Food Safety and Quality
基金 北京市农林科学院创新能力建设-高效节水农业专项研究(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)~~
关键词 数字光处理技术 近红外光谱 可溶性固形物含量 digital light procession near-infrared spectroscopy soluble solid content pear
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