Use of Near-Infrared Spectroscopy and Chemometrics for the Nondestructive Identification of Concealed Damage in Raw Almonds (Prunus dulcis)

作者：Rogel Castillo Cristian; Boulton Roger; Opastpongkarn Arunwong; Huang Guangwei; Mitchell Alyson E

来源：Journal of Agricultural and Food Chemistry, 2016, 64(29): 5958-5962.

DOI：10.1021/acs.jafc.6b01828

• Prunus dulcis
• almond
• concealed damage
• near-infrared spectroscopy
• partial least squares regression
• discriminant analysis

Concealed damage (CD) is defined as a brown discoloration of the kernel interior (nutmeat) that appears only after moderate to high heat treatment (e.g., blanching, drying, roasting, etc.). Raw almonds with CD have no visible defects before heat treatment. Currently, there are no screening methods available for detecting CD in raw almonds. Herein, the feasibility of using near-infrared (NIR) spectroscopy between 1125 and 2153 nm for the detection of CD in almonds is demonstrated. Almond kernels with CD have less NIR absorbance in the region related with oil, protein, and carbohydrates. With the use of partial least squares discriminant analysis (PLS-DA) and selection of specific wavelengths, three classification models were developed. The calibration models have false-positive and false-negative error rates ranging between 12.4 and 16.1% and between 10.6 and 17.2%, respectively. The percent error rates ranged between 8.2 and 9.2%. Second-derivative preprocessing of the selected wavelength resulted in the most robust predictive model.

• 出版日期2016-7-27