Non-destructive determination of soluble solids content in intact apples using a self-made portable NIR diffuse reflectance instrument

文献类型： 外文期刊

第一作者： Yao, Ya-nan

作者： Yao, Ya-nan;Zhu, Jinfang;Huang, Fan;Li, Shuo;Ma, Kun;Zhu, Jinfang;Kuang, Liang;Wang, Xuejian

作者机构：

关键词： Non-destructive determination; Soluble solids content; Apple; NIR diffuse reflectance; Portable instrument

期刊名称：INFRARED PHYSICS & TECHNOLOGY （ 影响因子：3.3； 五年影响因子：3.2 ）

ISSN： 1350-4495

年卷期： 2023 年 132 卷

页码：

收录情况： SCI

摘要： The soluble solids content (SSC) is an important internal quality parameter of fruits that is monitored on the fruit market to meet different consumer demands. The aim of this study was to develop a self-made portable near -infrared (NIR) diffuse reflectance instrument to evaluate and monitor the SSC of intact apples. The visible and near-infrared (Vis-NIR) spectra of 118 'Fuji' apples were collected using a Vis-NIR diffuse reflectance spectro-scopic measurement system in the spectral range of 450-1100 nm. Savitzky-Golay convolution smoothing and first derivative methods were subsequently applied to eliminate noise interference and baseline shift. Successive projections algorithm (SPA) was performed to extract feature wavelengths from the pretreatment spectra, and the back-propagation artificial neural network (BP-ANN) and multivariate nonlinear regression (MNLR) models were employed to evaluate the predictive ability of the extracted and selected feature wavelengths for the SSC of apples. Seven wavelengths (881, 890, 901, 926, 941, 951, 978 nm) were selected as optimal feature wavelengths from the extracted feature wavelengths (18 wavelengths). The MNLR model (R2 = 0.953, RMSE = 0.391 %) exhibited a high prediction accuracy compared to the BP-ANN model (R2 = 0.865, RMSE = 0.754 %). Based on the results, NIR combined with the MNLR model could be applied in the self-made portable instrument to innovatively monitor the SSC of apples. Finally, a self-made portable NIR diffuse reflectance instrument was designed and developed, and the spectral information of 298 'Fuji' apples was collected using the instrument. According to the results, the MNLR model could well predict the SSC of apples (R2 = 0.871, RMSE = 0.687 %). The overall results also revealed that the developed portable NIR instrument is a promising device for rapid non-destructive monitoring of fruit SSC, thereby meeting the practical application requirement of postharvest commercial processing systems. This instrument could also be beneficial to customers, growers, and producers.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序