[1]彭雅玲,邱雪,张海红,等.近红外光谱技术检测灵武长枣果肉硬度和贮藏时间[J].江苏农业学报,2019,(01):182-188.[doi:doi:10.3969/j.issn.1000-4440.2019.01.026]
　PENG Ya-ling,QIU Xue,ZHANG Hai-hong,et al.Near-infrared spectroscopy for the determination of hardness and storage time of jujube fruit[J].,2019,(01):182-188.[doi:doi:10.3969/j.issn.1000-4440.2019.01.026]
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近红外光谱技术检测灵武长枣果肉硬度和贮藏时间()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2019年01期
页码:
182-188
栏目:
加工贮藏·质量安全
出版日期:
2019-02-26

文章信息/Info

Title:
Near-infrared spectroscopy for the determination of hardness and storage time of jujube fruit
作者:
彭雅玲; 邱雪; 张海红; 吴宝婷; 朱韵昇
（宁夏大学农学院，宁夏银川750021）
Author(s):
PENG Ya-ling; QIU Xue; ZHANG Hai-hong; WU Bao-ting;  ZHU Yun-sheng
（College of Agronomy, Ningxia University, Yinchuan 750021, China）
关键词:
近红外光谱; 果肉硬度; 贮藏时间
Keywords:
near-infrared spectroscopy; flesh firmness; storage time
分类号:
S665.1
DOI:
doi:10.3969/j.issn.1000-4440.2019.01.026
文献标志码:
A
摘要:
利用近红外光谱（400～1 000 nm）系统采集140个灵武长枣样本的光谱信息，采用不同方法预处理原始光谱数据，优选出最佳预处理方法。分别建立竞争性自适应加权算法（CARS）和连续投影算法（SPA）提取特征变量的果肉硬度偏最小二乘回归（PLSR）预测模型，并利用原始光谱建立灵武长枣贮藏时间的偏最小二乘判别（PLS-DA）模型。结果表明，去趋势法（Detrend）为最优预处理方法；建立的Detrend-CARS-PLSR模型效果较好，果肉平均硬度校正集和预测集模型相关系数均为0.868；果肉最大硬度校正集和预测集模型相关系数分别为0.914、0.849。建立的贮藏时间PLS-DA判别模型的校正集判别准确率为98%，预测集判别准确率为99%。说明，采用近红外光谱技术对灵武长枣贮藏过程中长枣果肉硬度和贮藏时间的快速预测具有可行性。
Abstract:
Spectral information of 140 Lingwu long jujube samples was collected by using near-infrared spectroscopy (400-1 000 nm). Different methods were applied to preprocess the original spectrum, and the optimal pretreatment method was selected. The competitive adaptive reweighed sampling (CARS) and successive projections algorithm (SPA) were used to select characteristic wavelengths, and the partial least squares regression (PLSR) model was established based on characteristic wavelengths for predicting flesh firmness of Lingwu long jujube. The partial least squares discriminate analysis (PLS-DA) models of long jujube storage time were established based on full spectrum. The results indicated that the Detrend method was the optimal pretreatment method, the Detrend-CARS-PLSR model was the best, and correlation coefficients of average flesh firmness for calibration set and prediction set were 0.868 and 0.868, and correlation coefficients of maximum flesh firmness for calibration set and prediction set were 0.914 and 0.849, respectively. The PLS-DA discriminant model of storage time was established and the discrimination accuracy of calibration set and prediction set were 98% and 99%. In conclusion, it is feasible to predict flesh firmness and storage time of Lingwu long jujube based on near-infrared spectroscopy technique.

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备注/Memo

备注/Memo:
收稿日期：2018-05-02 基金项目：国家自然科学基金地区科学基金项目（31860422）；宁夏高校科学研究项目（NGY2016019） 作者简介：彭雅玲（1993-），女，甘肃白银人，硕士研究生，研究方向为农产品无损检测。（E-mail）m18341654254_2@163.com 通讯作者：张海红，（E-mail）nxdwjyxx@126.com
更新日期/Last Update: 2019-02-27