Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Quantification of Total Soluble Solids and Titratable Acidity For Citrus Maturity Using Portable Vis-NIR Spectroradiometer

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Applied Engineering in Agriculture. 28(3): 735-743. (doi: 10.13031/2013.42420) @2012
Authors:   R. Ruslan, R. Ehsani, W. S. Lee
Keywords:   Citrus maturity, Vis-NIR spectroscopy, Principal component regression, Partial least squares regression

Soluble solids contents (SSC) and titratable acidity (TA) are the two major components in the citrus industry that have a direct impact on the crop value and the juice quality. It is crucial for growers to know the stage of maturity in-field before harvesting and to know the fruit quality for the juice processing in the processing plant. This study presents an application of a commercially available visible-near infrared (Vis-NIR) spectroradiometer for estimating SSC and TA of Hamlin and Valencia orange, and Thompson Red grapefruit. The Vis-NIR spectra of the juice were acquired using a portable spectroradiometer within the wavelength range of 350 to 2,500 nm in transmission mode. The absorbance spectra were compared to the values of SSC and TA as analyzed using a bench top refractrometer and chemical titration, respectively. Calibration models relating the Vis-NIR spectra of the juice to its SSC and TA were developed based on two different regression analyses: principal component regression (PCR) and partial least squares regression (PLS-R). Selected combinations of spectral preprocessing such as derivatives, mean centering, multiplicative signal correction, standard normal variate, and detrending were applied to evaluate the performance of the calibration models. Performance of five different models in predicting the SSC and TA using the Vis-NIR ranges were compared. The best R2 and root mean square error of prediction (RMSEP) for SSC were 0.91 and 0.47Brix developed by Valencia orange absorbance spectra (Model 5), respectively. Meanwhile, the combination of Hamlin and Valencia absorbance spectra (Model 2) predicted the maximum TA with an R2 of 0.73 and an RMSEP of 0.25%. The results concluded that portable Vis-NIR spectroradiometer-based technique can provide basic information on the levels of SSC and TA in-field as a preliminary analysis before harvesting.

(Download PDF)    (Export to EndNotes)