...
首页> 外文期刊>Food analytical methods >Identification of Kiwifruits Treated with Exogenous Plant Growth Regulator Using Near-Infrared Hyperspectral Reflectance Imaging
【24h】

Identification of Kiwifruits Treated with Exogenous Plant Growth Regulator Using Near-Infrared Hyperspectral Reflectance Imaging

机译:利用近红外高光谱反射成像技术鉴定外源植物生长调节剂处理的猕猴桃

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The goal of this study was to explore the potential of using near-infrared (NIR) hyperspectral imaging in combination with multivariate analysis for the identification of kiwifruits treated with exogenous plant growth regulator (EPGR). One hundred twenty kiwifruits, variety 'Xixuan,' treated with EPGR and another 120 'Xixuan' kiwifruits without EPGR (named as normal ones) were used in the study. Hyperspectral images were acquired using a near-infrared hyperspectral imaging system in the spectral range of 865.11-1,711.71 nm. Based on the Kennard-Stone method, the samples were divided into two sets: 180 samples in calibration set and 60 samples in validation set. Standard normal variate transformation was used to preprocess obtained spectra. Principal component analysis (PCA) and successive projections algorithm (SPA) were used to select principal components and characteristic wavelengths. Partial least square (PLS) regression and support vector machine (SVM) modeling methods were used to establish models for identifying EPGR-treated kiwifruits and normal ones. The results indicated that average correct identification rates of all models were higher than 98.9 and 96.7 % for the calibration set and validation set, respectively. The identification performance of PLS was better than that of SVM, and the best model was PLS-SPA, whose average accuracy rate reached 100 % for the calibration set and 98.4 % for the validation set. The results demonstrated that NIR hyperspectral imaging technique can be used as a noninvasive method for distinguishing kiwifruits treated with EPGR from normal ones.
机译:这项研究的目的是探索使用近红外(NIR)高光谱成像技术与多变量分析相结合来鉴定用外源植物生长调节剂(EPGR)处理的奇异果的潜力。在研究中使用了120种经过EPGR处理的奇异果“ Xixuan”和另外120种未进行EPGR的“ Xixuan”奇异果(称为正常)。使用近红外高光谱成像系统在865.11-1,711.71 nm的光谱范围内获取高光谱图像。基于Kennard-Stone方法,将样本分为两组:校准集中的180个样本和验证集中的60个样本。使用标准正态变量转换对获得的光谱进行预处理。主成分分析(PCA)和连续投影算法(SPA)用于选择主成分和特征波长。使用偏最小二乘(PLS)回归和支持向量机(SVM)建模方法来建立用于识别EPGR处理的猕猴桃和正常猕猴桃的模型。结果表明,所有模型的校正集和验证集的平均正确识别率分别高于98.9%和96.7%。 PLS的识别性能优于SVM,最好的模型是PLS-SPA,其校正集的平均准确率达到100%,验证集的平均准确率达到98.4%。结果表明,NIR高光谱成像技术可作为一种非侵入性方法,将EPGR处理的猕猴桃与正常猕猴桃区分开。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号