NDLI: Optimal Illumination-Detection Distance and Detector Size for Predicting Braeburn Apple Maturity from Vis/NIR Laser Reflectance Measurements

Content Provider	Springer Nature Link
Author	Van Beers, Robbe Aeruts, Ben León Gutiérrez, Lorenzo Erkinbaev, Chyngyz Rutten, Koen Schenk, Ann Nicolaï, Bart Saeys, Wouter
Copyright Year	2015
Abstract	The storage potential of apples highly depends on the maturity at harvest. Optical methods have been proposed to measure maturity in a fast, reliable and non-destructive way. However, the signal is often composed of photons with different penetration depths into the material. An attempt to separate these photons might result in more precise correlations with quality attributes, as these could relate to a specific layer/depth into the sample. Therefore, a Vis/NIR spatially resolved laser reflectance setup was used, combining a supercontinuum laser and a monochromator to illuminate samples with a monochrome focused beam in the 550–1000 nm wavelength range. A panchromatic camera was used to obtain diffuse reflectance profiles at each wavelength. In the period starting 50 days before until 11 days after commercial harvest, 320 Braeburn apples were measured. Partial least squares regression models were developed to relate apple maturity/quality to the diffuse reflectance spectra at different distances from the illumination point. The effect of detector size (spatial bandwidth) was also evaluated. A bandwidth of 0.82 mm in combination with a parameter specific illumination-detection distance, gave the best results. Using an internal test set, an R $^{2}$ of prediction of 0.98 and 0.93, and a ratio of prediction to performance (RPD) of 5.84 and 3.42, predicting, respectively, the Streif index and starch conversion values was obtained. The predictions of soluble solids content (SSC) (R $^{2}$ of 0.81; RPD of 2.04) and firmness (R $^{2}$ of 0.65; RPD of 1.66) were less accurate. Also, worse predictions were obtained using an external test set.
Starting Page	2123
Ending Page	2136
Page Count	14
File Format	PDF
ISSN	19355130
Journal	Food and Bioprocess Technology
Volume Number	8
Issue Number	10
e-ISSN	19355149
Language	English
Publisher	Springer US
Publisher Date	2015-07-23
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Hyperspectral Spatially resolved spectroscopy Laser reflectance Apple Maturity Streif index Food Science Chemistry/Food Science Agriculture Biotechnology
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Safety, Risk, Reliability and Quality Food Science Process Chemistry and Technology

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