Non-destructive assessment of the oxidative stability of intact macadamia nuts during the drying process by near-infrared spectroscopy

• Autor(a) principal: Carvalho, Lívia C. [UNESP]
• Data de Publicação: 2019
• Outros Autores: Leite, Marcondes L., Morais, Camilo L.M., Lima, Kássio M.G., Teixeira, Gustavo H.A. [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1016/j.lwt.2018.12.056; http://hdl.handle.net/11449/188580
• topic: Acidity index; Macadamia integrifolia Maiden & Betche; Peroxide value; principal component analysis

We have developed a rapid non-destructive method to assess the oxidative stability of intact macadamia nuts using near-infrared spectroscopy (NIRS). Intact macadamia nuts of the cultivars HAES 344 ‘Kau’ HAES 660 ‘Keaau’ IAC 4–12 B, and IAC Campinas B were harvested and immediately oven-dried for 4 days at 30 °C, 2 days at 40 °C, and 1 day at 60 °C to achieve 1.5% kernel moisture content. At each drying step nuts were withdrawn and their moisture content, peroxide value (PV), and acidity index (AI) determined. The best partial least square model for PV prediction was obtained using the Savitzky-Golay (SG) second derivative resulting in a standard error of prediction (SEP) of 0.55 meq·kg −1 and a coefficient of determination (R 2 C ) of 0.57. The best AI prediction-model result was obtained using the SG second derivative (SEP = 0.14%, R 2 C = 0.29). Based on the maximum quality limits of 3 meq·kg −1 for PV and 0.5% for AI, the SEP values represented 18% and 28%, respectively. Therefore, the prediction method can be considered useful since the errors are lower than the quality limits. Thus, NIRS can be used to assess the oxidative stability of intact macadamia kernels.