Use of an NIR MEMS spectrophotometer and visible/NIR hyperspectral imaging systems to predict quality parameters of treated ground peppercorns. (September 2020)

• Record Type: Journal Article
• Authors: Esquerre, Carlos A.; Achata, Eva M.; García-Vaquero, Marco; Zhang, Zhihang; Tiwari, Brijesh K.; O'Donnell, Colm P.
• Is Part Of: Lebensmittel-Wissenschaft + Technologie =. Volume 131(2020)
• Publication Date: 2020-09
• Subjects: NIR MEMS -- Hyperspectral imaging -- Antioxidant capacity -- Total phenolic content -- Peppercorn; Food industry and trade -- Periodicals; Food -- Composition -- Periodicals; Microbiology -- Periodicals; Nutrition -- Periodicals; 664.005
• DOI: 10.1016/j.lwt.2020.109761
• Languages: English
• ISSNs: 0023-6438

Abstract

Abstract: The aim of this study was to investigate the potential of a micro-electromechanical NIR spectrophotometer (NIR-MEMS) and visible (Vis)/NIR hyperspectral imaging (HSI) systems to predict the moisture content, antioxidant capacity (DPPH, FRAP) and total phenolic content (TPC) of treated ground peppercorns. Partial least squares (PLS) models were developed using spectra from peppercorns treated with hot-air, microwave and cold plasma. The spectra were acquired using three spectroscopy systems: NIR-MEMS (1350–1650 nm), Vis-NIR HSI (450–950 nm) and NIR HSI (957–1664 nm). Very good predictions of TPC (RPD > 3.6) were achieved using NIR-MEMS. The performance of models developed using Vis-NIR HSI and NIR HSI were good or very good for DPPH (RPD > 3.0), FRAP (RPD >2.9) and TPC (RPD > 3.8). This study demonstrated the potential of NIR-MEMS and Vis-NIR/NIR HSI to predict the moisture content, antioxidant capacity and total phenolic content of peppercorns. The spectroscopy technologies investigated are suitable for use as in-line PAT tools to facilitate improved process control and understanding during peppercorn processing. Highlights: NIR MEMS and Vis/NIR hyperspectral imaging predict antioxidant capacity of peppercorns. NIR MEMS and Vis/NIR hyperspectral imaging predict total phenolic content of peppercorns. Band selection and spectral pre-treatments were key for robust prediction model development. NIR MEMS and hyperspectral imaging may be employed as in-line PAT tools in peppercorn processing.