A Preliminary Study on Whether the Soluble Solid Content and Acidity of Oranges Predicted by Near Infrared Spectroscopy Meet the Sensory Degustation

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AbstractInternal qualities of fruit, such as soluble solid content (SSC) and acidity, were mostly used to reflect people's sensory preference. Those indexes have been noninvasively measured by near infrared (NIR) spectroscopy over the past years. However, limited attentions have been given on whether the result of NIR spectroscopy detection can meet the sensory requirement of the consumers. In this research, NIR measurement and the sensory test were carried out on oranges to assay the answer. Multivariate analyses with several pretreatments were comparatively employed to calibrate a robust model on the basis of NIR spectra. The optimal partial least squares model was obtained with root mean square error of prediction of 0.613 for SSC, and 0.17 for acidity. The sensory test was investigated by well‐trained panelists to explore the sensory threshold, which had a root mean square error of deviation of 0.771 for SSC, as well as 0.203 for acidity. Results showed that the noninvasive method of NIR usage was acceptable with fewer root mean square error of prediction value than sensory threshold. This preliminary study revealed that an accurate and fast method by NIR spectrometer coupled with proper chemometric on oranges could meet the requirement of sensory taste.Practical ApplicationsOver the last decades, internal qualities of fruit have been noninvasively detected by NIR spectroscopy, but limited attentions have been given on whether the result of NIR detection can meet the sensory requirement of the consumers. A noninvasive NIR determination method should be deserving of its purpose that can at least meet the sensory taste. In this work, we examined whether the result of NIR application can meet the sensory taste for oranges. The sensory threshold was analyzed and compared with the proposed NIR model, which was simple and robust. It is of great importance to choose a proper NIR model resulting in not only covering the sensory degustation, but also low‐cost and fast detection in the practical implementation. This research will be a good reference for screening and grading of food control or process.