Quality Evaluation of Shelled and Unshelled Macadamia Nuts by Means of Near-Infrared Spectroscopy (NIR)

• Published in: Journal of food science Vol. 81; no. 7; pp. C1613 - C1621
• Main Authors: Canneddu, Giovanna, Júnior, Luis Carlos Cunha, de Almeida Teixeira, Gustavo Henrique
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01-07-2016; Wiley Subscription Services, Inc
• Subjects: acidity index; Acids - analysis; Animals; Artificial intelligence; Classification; Ecdytolopha aurantiana; Food Analysis - methods; Germination; Humans; Infrared imaging systems; Insecta; LDA; Leucopteara coffeella; Lipid Peroxidation; Macadamia; Macadamia integrifolia Maiden & Betche; Macadamia nuts; Mathematical models; Near infrared radiation; Nuts; Nuts - chemistry; Nuts - classification; Nuts - standards; PCA; peroxide value; Peroxides - analysis; PLS; PLS-DA; Quality; Quality assessment; Restaurants; Spectroscopy; Spectroscopy, Near-Infrared - methods; Spectrum analysis; Ecdytolopha aurantiana; Leucopteara coffeella; Macadamia integrifolia Maiden & Betche; peroxide value; PLS; LDA; PLS-DA; acidity index; PCA
• ISSN: 0022-1147; 1750-3841
• DOI: 10.1111/1750-3841.13343

The quality of shelled and unshelled macadamia nuts was assessed by means of Fourier transformed near‐infrared (FT‐NIR) spectroscopy. Shelled macadamia nuts were sorted as sound nuts; nuts infected by Ecdytolopha aurantiana and Leucopteara coffeella; and cracked nuts caused by germination. Unshelled nuts were sorted as intact nuts (<10% half nuts, 2014); half nuts (March, 2013; November, 2013); and crushed nuts (2014). Peroxide value (PV) and acidity index (AI) were determined according to AOAC. PCA‐LDA shelled macadamia nuts classification resulted in 93.2% accurate classification. PLS PV prediction model resulted in a square error of prediction (SEP) of 3.45 meq/kg, and a prediction coefficient determination value (Rp2) of 0.72. The AI PLS prediction model was better (SEP = 0.14%, Rp2 = 0.80). Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT‐NIR spectroscopy can be successfully used to predict PV and AI in unshelled macadamia nuts, though.
Practical Applications
Near‐infrared spectroscopy (FT‐NIR) was used to evaluate the quality of macadamia nuts, specially to access one of the major shelled macadamia nut defects (insect damage) and the onset of lipid oxidation in unshelled macadamia nuts. Although adequate classification was possible (93.2%), shelled nuts must not contain live insects, therefore the classification accuracy was not satisfactory. FT‐NIR spectroscopy can be successfully used to predict peroxide value (PV) and acidity index (AI) in unshelled macadamia nuts and can be used by the food industry in quality control processes.