Predicting glycogen concentration in the foot muscle of abalone using near infrared reflectance spectroscopy (NIRS)

► Models based on Near Infrared Reflectance Spectroscopy (NIRS) were developed to allow the estimation of glycogen concentration in the muscle of live and shucked abalone. ► Models based on NIRS were developed to allow the quantitation of glycogen concentration in the dried abalone meat. ► Demonstration that NIRS could be applied as a tool for screening quality-associated components in abalone. Near infrared reflectance spectroscopy (NIRS) was used to predict glycogen concentrations in the foot muscle of cultured abalone. NIR spectra of live, shucked and freeze-dried abalones were modelled against chemically measured glycogen data (range: 0.77–40.9% of dry weight (DW)) using partial least squares (PLS) regression. The calibration models were then used to predict glycogen concentrations of test abalone samples and model robustness was assessed from coefficient of determination of the validation (R2val) and standard error of prediction (SEP) values. The model for freeze-dried abalone gave the best prediction (R2val 0.97, SEP=1.71), making it suitable for quantifying glycogen. Models for live and shucked abalones had R2val of 0.86 and 0.90, and SEP of 3.46 and 3.07 respectively, making them suitable for producing estimations of glycogen concentration. As glycogen is a taste-active component associated with palatability in abalone, this study demonstrated the potential of NIRS as a rapid method to monitor the factors associated with abalone quality.