Predicting Marian Plum Fruit Quality without Environmental Condition Impact by Handheld VisibleNear-Infrared Spectroscopy - Jetsada Posom; Junjira Klaprachan; Kamonpan Rattanasopa; Panmanas Sirisomboon; Khwantri Saengprachatanarug; Seree Wongpichet (My University, 2020)
Handheld near-infrared spectroscopy was used to study the effect of integration time and wavelength selection on predicting marian plum quality including soluble solids content (SSC), the potential of hydrogen ion (pH), and titratable acidity (TA). For measurements representing actual conditions, the on-tree fruits were scanned under in-field conditions. The assumption was that the robust model might be achieved when the models were developed under actual conditions. The results of the main effect test show that the integration time did not statistically affect SSC, pH, and TA predictions (p-value > 0.05) and the wavelength range had a significant impact on prediction (p-value < 0.01). An integration time of 30 ms coupled with a wavelength range of 670-1000 nm was the optimal conditions for the SSC prediction, while an integration time of 20 ms with 670-1000 nm wavelength was optimal for pH and TA prediction because of the lowest root-mean-square error of cross-validation (RMSECV). The optimal models for SSC, pH, and TA could be improved using spectral pre-processing of multiplicative scatter correction. The effective models for SSC, pH, and TA improved and reported the coefficients of determination (r2) and root-mean-square errors of prediction (RMSEP) of 0.66 and 0.86 °Brix; 0.79 and 0.15; and 0.71 and 1.91%, respectively. The SSC, pH, and TA models could be applied for quality assurance. These models benefit the orchardist for on-tree measurement before harvesting.
Keywords: Root mean square; Titratable acid; Spectroscopy and Chemometric Analyses