The purpose of this study is to compare the efficiency of calibration transfer procedures between three spectrometers involving two Ocean Optics Inc. spectrometers, namely, QE65000 and Jaz, and also, ASD FieldSpec 3 in measuring the pH of Sala mango by visible reflectance spectroscopy. This study evaluates the ability of these spectrometers in measuring the pH of Sala mango by applying similar calibration algorithms through direct calibration transfer. This visible reflectance spectroscopy technique defines a spectrometer as a master instrument and another spectrometer as a slave. The multiple linear regression (MLR) of calibration model generated using the QE65000 spectrometer is transferred to the Jaz spectrometer and vice versa for Set 1. The same technique is applied for Set 2 with QE65000 spectrometer is transferred to the FieldSpec3 spectrometer and vice versa. For Set 1, the result showed that the QE65000 spectrometer established a calibration model with higher accuracy than that of the Jaz spectrometer. In addition, the calibration model developed on Jaz spectrometer successfully predicted the pH of Sala mango, which was measured using QE65000 spectrometer, with a root means square error of prediction RMSEP = 0.092 pH and coefficients of determination R 2 = 0.892. Moreover, the best prediction result is obtained for Set 2 when the calibration model developed on QE65000 spectrometer is successfully transferred to FieldSpec 3 with R 2 = 0.839 and RMSEP = 0.16 pH.

This study presents an alternative approach for the nondestructive assessment of fruit quality parameters with the use of a simplified optical fiber red-green-blue system (OF-RGB). The optical sensor system presented in this work is designed to rapidly measure the firmness, acidity, and soluble solid content of an intact Sala mango on the basis of color properties. The system consists of three light-emitting diodes with peak emission at 635 (red), 525 (green), and 470 nm (blue), as well as a single photodetector capable of sensing visible light. The measurements were conducted using the reflectance technique. The analyses were conducted by comparing the results obtained through the proposed system with those measured using two commercial spectrometers, namely, QE65000 and FieldSpec 3. The developed RGB system showed satisfactory accuracy in the measurement of acidity (R 2 ¼ 0.795) and firmness (R 2 ¼ 0.761), but a relatively lower accuracy in the measurement of soluble solid content (R 2 ¼ 0.593) of intact mangoes. The results obtained through OF-RGB are comparable with those measured by QE65000 and FieldSpec 3. This system is a promising new technology with rapid response, easy operation, and low cost with potential applications in the nondestructive assessment of quality attributes.

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Color analysis is a critical approach used to analyze the quality properties of fruits, particularly in tracing the ripening stage through the peel color of the fruits. In this study, the color features of natural and untreated tropical fruit juice images (ie, B10 Averrhoa carambola L. and Sala mango) were correlated with the pH of the juice samples. The CIELAB color characteristics of the fruits showed that the mango juice had darker features than the carambola juice. The cause may be due to the higher soluble solid content and denser yellow and red pigments in the mango juice. For carambola juice, multiple linear regression (MLR) performed on red‐blue (RB) components generated the best prediction of pH with the highest coefficient of determination and lowest root mean square of error. For mango juice, MLR performed on normalized red‐green‐blue (RGB) components generated the best prediction of pH.

Fruits and vegetables are generally valued based on their visual appearance, particularly their color. Color is an important quality attribute that affects consumer acceptance and preference in the food industry. Human perception of color has been used as an indirect measure for classifying fruits in indices as fruits matured and ripened. This study was conducted to measure fruit quality by using visible optical fiber sensors that contains of RGB LEDs which are red, green and blue with peak wavelengths at 635 nm, 525 nm, and 470 nm, respectively. Moreover, this study aims to provide an innovative and low-cost approach for nondestructive fruit quality measurement. Multiple linear regressions was applied to develop calibration models for classifying fruits based on the index. Results showed that the proposed optical instruments can produce good and accurate measurements when evaluating the index. The highest coefficient of determination (R 2 = 0.879), was obtained by using a combination of red, green, and blue data sets at various ripeness indices. Meanwhile, the optical fiber of red system generated by the monochromatic wavelength exhibited better precision (R 2 = 0.795) compared with the other two wavelengths. In conclusion, the application of these systems leads to the rapid and efficient assessment of the quality measurement of mangoes.