Detection of internal defect of apples by a multichannel Vis/NIR spectroscopic system

Authors: HUANG, YUPING - Nanjing Forestry University; Lu, Renfu; CHEN, KUNJIE - Nanjing Agricultural University

Submitted to: Postharvest Biology and Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/4/2019
Publication Date: 11/18/2019
Citation: Huang, Y., Lu, R., Chen, K. 2019. Detection of internal defect of apples by a multichannel Vis/NIR spectroscopic system. Postharvest Biology and Technology. 161:111065. https://doi.org/10.1016/j.postharvbio.2019.111065.
DOI: https://doi.org/10.1016/j.postharvbio.2019.111065

Interpretive Summary: Currently, visible and near-infrared (Vis/NIR) spectroscopic technique is commercially used for detecting internal defect in apples during postharvest sorting and grading. However, these commercial Vis/NIR systems still give high false detection rates, because they only provide single spectral measurements covering a limited area of each fruit. Internal defects such as internal browning, a common physiological disorder in apples, often occur in discrete, small regions in apple fruit, especially at the early stage of symptom development. In this research, a multichannel spectroscopic system in semi-transmittance mode was proposed for detecting internal browning in apples. The multichannel system enables simultaneous acquisition of six Vis/NIR spectra of 550-1,650 nm covering the 360-degree area of apple fruit, thus resulting in better, more complete assessment of whole fruit. The system was used to measure 430 ‘Honeycrisp’ apples in three orientations, 187 of which had various degrees of internal browning. Mathematical models for classification of good and defective fruit were then developed using the individual spectra as well as mean spectra from the six detection channels. Results showed that defect detection accuracy varied with detection channel and fruit orientation. The use of mean spectra of the six detection channels resulted in consistently better classification accuracies of 91.5%, 89.2%, and 93.1% for the three fruit orientations. Furthermore, compared with single-channel measurements, mean spectra gave significantly better detection results for mildly defective apples (i.e., with the internal browning area being less than 40%). The multichannel Vis/NIR spectroscopic system is thus advantageous for detection of internal defects, especially those localized ones, in apples.

Technical Abstract: This paper reports on nondestructive detection of internal defect in apples by using a noncontact multichannel spectroscopic system in semi-transmittance mode for the visible and near-infrared (Vis/NIR) range of 550-1,650 nm. The multichannel system consists of six optical fibers arranged in a 360-degree configuration for improved evaluation of each fruit. Spectra were acquired for 430 ‘Honeycrisp’ apples, 243 of which were good (defect free) and 187 internally defective. To assess the effect of fruit orientation on defect detection, each apple was measured in three orientations (i.e., the stem-end facing the light source (A), the calyx end facing the light source (B) and the stem-calyx axis being perpendicular to the light source(C)). Classification models based on partial least squares discriminant analysis (PLSDA) were established for spectra of each detection fiber and mean spectra of the six detection fibers, to compare their performance for internal defect detection. Results showed that classification results varied with detection fiber and fruit orientation. Mean spectra for each fruit orientation gave consistently better classifications, with the overall accuracies of 91.5%, 89.2% and 93.1% for orientations A, B and C, respectively. Moreover, the best PLSDA models had lower misclassification rates for good apples (4.3%) than for defective apples (10.0%). Furthermore, significantly better classification results for mildly defective apples were obtained when using mean spectra than using spectra of each detection fiber. The multichannel Vis/NIR spectroscopic system is thus advantageous for detection of internal defects, especially those localized ones, in apples.