TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Steinbach, Julia
A1  - Golovko, Dmytro
A1  - Kandelbauer, Andreas
A1  - Rebner, Karsten
T1  - Real-time quantification of meat paste constituents displaying nonlinear blending behavior including salt using an in-line NIR MEMS sensor
JF  - ACS food science & technology
N2  - Rapid and robust quality monitoring of the composition of meat pastes is of fundamental importance in processing meat and sausage products. Here, an in-line near-infrared spectroscopy/micro-electro-mechanical-system-(MEMS)-based approach, combined with multivariate data analysis, was used for measuring the constituents fat, protein, water, and salt in meat pastes within a typical range of meat paste recipes. The meat pastes were spectroscopically characterized in-line with a novel process analyzer prototype. By integrating salt content in the calibration set, robust predictive PLSR models of high accuracy (R2 > 0.81) were obtained that take interfering matrix effects of the minor and NIR-inactive meat paste recipe component “salt” into account as well. The nonlinear blending behavior of salt concentration on the spectral features of meat pastes is discussed based on a designed mixture experiment with four systematically varied components.
KW  - in-line monitoring
KW  - NIR
KW  - design of experiments
KW  - DoE
KW  - MVA
KW  - meat pastes
KW  - constituents
Y1  - 2023
SN  - 2692-1944
SS  - 2692-1944
U6  - https://doi.org/10.1021/acsfoodscitech.3c00163
DO  - https://doi.org/10.1021/acsfoodscitech.3c00163
VL  - 3
IS  - 7
SP  - 1288
EP  - 1299
S1  - 12
PB  - American Chemical Society
CY  - Washington
ER  -