Abstract
In order to create a calibration model with temperature compensation, the calibration method using the partial least squares regression based on the combined spectra measured at some different temperatures is promising. However, the method is time-consuming since it requires spectra acquisition at different temperatures. In addition, the sample quality may change during the period for the different temperature adjustment of samples. The spectra of the target fruit species of peaches, pears, and persimmons were measured at 25℃ using the interactance method. Spectra for 20℃ and 30℃ were created artificially using temperature-difference second derivative spectra from the 25℃-second derivative spectra. Then, the possibility of temperature-difference second derivative spectra of fruit(s) to create the correct 20℃ and 30℃ artificial second derivative spectra was evaluated. The temperature-difference second derivative spectra created from each target fruit species could be useful for each target fruit species while the common temperature-difference second derivative spectra created from the three target fruit species were useful for not only each target fruit species but also the other fruit species of apples. The calibration model for apples developed using the common temperature-difference second derivative spectra showed low standard error of performance and bias of 0.45°Brix and 0.09°Brix, respectively. The model could be applied well to the prediction sets of apples at 20℃, 25℃, and 30℃ with non-significant biases.
© 2017 The Author(s)
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