TY - JOUR
T1 - Sensory Assessment of Fish and Chicken Protein Hydrolysates. Evaluation of NMR Metabolomics Profiling as a New Prediction Tool
AU - Steinsholm, Silje
AU - Oterhals, Åge
AU - Underhaug, Jarl
AU - Måge, Ingrid
AU - Malmendal, Anders
AU - Aspevik, Tone
PY - 2020/3/2
Y1 - 2020/3/2
N2 - Nuclear magnetic resonance (NMR) metabolomics profiling was evaluated as a new tool in sensory assessment of protein hydrolysates. Hydrolysates were produced on the basis of different raw materials (cod, salmon, and chicken), enzymes (Food Pro PNL and Bromelain), and hydrolysis time (10 and 50 min). The influence of raw material and hydrolysis parameters on sensory attributes was determined by traditional descriptive sensory analysis and 1H NMR spectroscopy. The raw material had a major influence on the attribute intensity and metabolite variation, followed by enzyme and hydrolysis time. However, the formation of bitter taste was not affected by the raw material. Partial least-squares regression (PLSR) on 1H NMR and sensory data provided good models (Q2 = 0.55−0.89) for 11 of the 17 evaluated attributes, including bitterness. Significant metabolite−attribute associations were identified. The study confirms the potential prediction of the sensory properties of protein hydrolysates from cod, salmon, and chicken based on 1H NMR metabolomics profiling.
AB - Nuclear magnetic resonance (NMR) metabolomics profiling was evaluated as a new tool in sensory assessment of protein hydrolysates. Hydrolysates were produced on the basis of different raw materials (cod, salmon, and chicken), enzymes (Food Pro PNL and Bromelain), and hydrolysis time (10 and 50 min). The influence of raw material and hydrolysis parameters on sensory attributes was determined by traditional descriptive sensory analysis and 1H NMR spectroscopy. The raw material had a major influence on the attribute intensity and metabolite variation, followed by enzyme and hydrolysis time. However, the formation of bitter taste was not affected by the raw material. Partial least-squares regression (PLSR) on 1H NMR and sensory data provided good models (Q2 = 0.55−0.89) for 11 of the 17 evaluated attributes, including bitterness. Significant metabolite−attribute associations were identified. The study confirms the potential prediction of the sensory properties of protein hydrolysates from cod, salmon, and chicken based on 1H NMR metabolomics profiling.
U2 - 10.1021/acs.jafc.9b07828
DO - 10.1021/acs.jafc.9b07828
M3 - Journal article
SN - 0021-8561
VL - 68
SP - 3881
EP - 3890
JO - Journal of Agricultural and Food Chemistry
JF - Journal of Agricultural and Food Chemistry
IS - 12
ER -