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Use of an NIR MEMS spectrophotometer and visible/NIR hyperspectral imaging systems to predict quality parameters of treated ground peppercorns
被引:18
作者:

Esquerre, Carlos A.
论文数: 0 引用数: 0
h-index: 0
机构:
Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland

Achata, Eva M.
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h-index: 0
机构:
Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland

Garcia-Vaquero, Marco
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h-index: 0
机构:
Univ Coll Dublin, Coll Hlth & Agr Sci, Sch Agr & Food Sci, Dublin D04V1 W8, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland

Zhang, Zhihang
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h-index: 0
机构:
TEAGASC, Food Res Ctr, Dept Food Chem & Technol, Dublin D15KN3K, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland

Tiwari, Brijesh K.
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h-index: 0
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TEAGASC, Food Res Ctr, Dept Food Chem & Technol, Dublin D15KN3K, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland

O'Donnell, Colm P.
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h-index: 0
机构:
Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland
机构:
[1] Univ Coll Dublin, Coll Engn & Architecture, Sch Biosyst & Food Engn, Dublin D04V1 W8, Ireland
[2] Univ Coll Dublin, Coll Hlth & Agr Sci, Sch Agr & Food Sci, Dublin D04V1 W8, Ireland
[3] TEAGASC, Food Res Ctr, Dept Food Chem & Technol, Dublin D15KN3K, Ireland
关键词:
NIR MEMS;
Hyperspectral imaging;
Antioxidant capacity;
Total phenolic content;
Peppercorn;
PROCESS ANALYTICAL TOOL;
BLACK;
IDENTIFICATION;
SPECTROSCOPY;
GREEN;
WHITE;
D O I:
10.1016/j.lwt.2020.109761
中图分类号:
TS2 [食品工业];
学科分类号:
0832 ;
摘要:
The aim of this study was to investigate the potential of a micro-electromechanical NIR spectrophotometer (NIRMEMS) 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 NIRMEMS 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.
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