IMPROVEMENT OF NIR TRANSMISSION MODE FOR INTERNAL QUALITY ASSESSMENT OF FRUIT USING DIFFERENT ORIENTATIONS

Abstract

ABSTRACTIn the last decade, visible and near‐infrared spectroscopy (including three modes reflectance, interactance and transmission) has increasingly been utilized in food industry. In this research, transmission mode was used to acquire spectra of kiwifruits, apples and oranges in the range of 400–1,000 nm, with an emphasis on the effect of fruit orientation on the spectra pattern. For soluble solids content and acidity (pH) to be predicted, various calibration models were developed, based on different combinations of preprocessing techniques. The best model for each characteristic was obtained by standard normal variate transformation in combination with median filter and first derivative. The correlation coefficients for soluble solids content and pH were 0.93 and 0.943, and the root mean square errors of prediction for them were 0.259°Brix and 0.076, respectively. The results indicate that the occurrence of peaks is uniquely the inherent of the fruit, independent of orientation. The transmission calibration model for the estimation of fruit constituents could be improved by using proper preprocessing techniques.PRACTICAL APPLICATIONSNear‐infrared spectroscopy (NIRS) for food quality assessment has its own advantages in comparison with other nondestructive techniques. The accuracy of NIR models is usually more than the other techniques. It is fast, easy to use and noninvasive. Moreover, there is no need for reagents, and minimal or no sample preparation is required. Because of these advantages, NIRS has been used in many fields including grains, beverages, dairy product, processed food, fruits and vegetables for determination of water, proteins, fats, carbohydrates, starch, amino acid, ash, soluble solid content, pH and so on. NIRS have shown promise as a fast, nondestructive and low‐running‐cost technique. It is also a nondestructive tool for the determination of organic component concentration. NIRS can be applied in different areas of food industry. This wide range of NIRS applications demands more gradual research to make it more efficient and practical.