Prediction of Sensory Texture of Cooked Potatoes using Uniaxial Compression, Near Infrared Spectroscopy and Low Field1H NMR Spectroscopy

The present work evaluated the ability of uniaxial compression, near-infrared reflectance (NIR) and low field pulsed 1H nuclear magnetic resonance (LF-NMR) in predicting the sensory texture quality of 24 samples of cooked potato by partial least squares regression (PLSR). The best predictions of the sensory texture profile were found for (1) LF-NMR measures (Carr-PurcellMeiboom-Gill relaxation) on raw potatoes and (2) uniaxial compression on cooked potatoes combined with the chemical measure dry matter and pectin methylesterase activity. Among the sensory variables, the root mean square error of prediction indicated springiness, firmness, moistness and chewiness to be better predicted than the geometrical variables reflection from surface, mealiness and graininess. Transverse relaxation times, determined according to biexponential fitting, resulted in a fast relaxing (T21of 100 ms) common water component for raw and cooked potatoes and a slower relaxing component with T22of 250 ms for cooked and 500 ms for raw potatoes. The only covariant NMR parameter was the amount of the slow relaxing component (T22) which correlates negatively to dry matter (r=-0.85) and to mealiness (r=-0.77), and positively to moistness (r=0.75). This study clearly demonstrates that LF-NMR (CPMG) relaxation on raw potato samples can be applied as an alternative rapid method for detecting sensory texture of cooked potatoes.