TY - JOUR
T1 - Application of NIR spectroscopy and multivariate analysis for Non-destructive evaluation of apple moisture content during ultrasonic drying
AU - Malvandi, Amir
AU - Feng, Hao
AU - Kamruzzaman, Mohammed
N1 - Funding Information:
This study was supported by Agriculture and Food Research Initiative (AFRI) awards no. 2018-67017-27913 from the USDA National Institute of Food and Agriculture (NIFA) and by DOE AMO award no. DE-EE0009125. The corresponding author acknowledges the funding from the USDA-NIFA, Hatch project ILLU-741-334.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2022/3/15
Y1 - 2022/3/15
N2 - Direct-contact ultrasonic drying is a novel approach to dehydrate fruits and vegetables to reduce microbial growth and post-harvest loss while preserving nutrients and the quality of the final product. Moisture content is a critical component for food behavior during drying, and its accurate evaluation in real-time is essential for food quality control. This study conveys the potential implementation of portable near-infrared spectroscopy (NIRS) combined with multivariate analysis for real-time assessment of moisture content in apple slices during direct-contact ultrasonic drying. Partial least squares regression (PLSR) and Gaussian process regression (GPR) models were developed, and their performances for different pre-treatments methods and data partitioning algorithms were evaluated with both internal cross-validation and an external dataset. Three wavelengths were selected by SPA (1359, 1517, and 1594 nm) which were then used to introduce a closed-form equation for moisture content prediction with R2p = 0.99 and RMSEP = 3.32%. The results revealed that portable NIRS combined with multivariate analysis is quite promising for monitoring and evaluating the moisture content during ultrasonic drying.
AB - Direct-contact ultrasonic drying is a novel approach to dehydrate fruits and vegetables to reduce microbial growth and post-harvest loss while preserving nutrients and the quality of the final product. Moisture content is a critical component for food behavior during drying, and its accurate evaluation in real-time is essential for food quality control. This study conveys the potential implementation of portable near-infrared spectroscopy (NIRS) combined with multivariate analysis for real-time assessment of moisture content in apple slices during direct-contact ultrasonic drying. Partial least squares regression (PLSR) and Gaussian process regression (GPR) models were developed, and their performances for different pre-treatments methods and data partitioning algorithms were evaluated with both internal cross-validation and an external dataset. Three wavelengths were selected by SPA (1359, 1517, and 1594 nm) which were then used to introduce a closed-form equation for moisture content prediction with R2p = 0.99 and RMSEP = 3.32%. The results revealed that portable NIRS combined with multivariate analysis is quite promising for monitoring and evaluating the moisture content during ultrasonic drying.
KW - Mems-based NIRS
KW - Moisture content
KW - Multivariate analysis
KW - Non-destructive measurement
KW - Ultrasonic drying
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U2 - 10.1016/j.saa.2021.120733
DO - 10.1016/j.saa.2021.120733
M3 - Article
C2 - 34920303
AN - SCOPUS:85121117752
SN - 1386-1425
VL - 269
JO - Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
JF - Spectrochimica Acta - Part A: Molecular and Biomolecular Spectroscopy
M1 - 120733
ER -