Abstract

A nondestructive method for measuring the soluble solids (SS) content of peaches [Prunus persica (L.) Batsch] was developed using near-infrared (NIR) spectrometry. NIR transmittance in the 800 to 1050 nm region was measured for four cultivars of peaches (`Blake', `Encore', `Red Haven', and `Winblo'), over a period of three seasons (1993 through 1995). Each fruit was scanned on both halves keeping the suture away from the incident light beam. Soluble solids contents of flesh samples taken from corresponding scanned areas were determined using a refractometer. Multiple linear regression models using two wavelengths were developed with second derivative spectral data and laboratory measurements of SS content. Multiple correlation coefficients (R) for individual cultivar calibrations within a single season ranged from 0.76 to 0.98 with standard error of calibration (SEC) values from 0.35% to 1.22%. Selected spectra and corresponding SS data in individual cultivar calibration data sets were combined to create season and cultivar calibration data sets to cover the entire range of SS contents within the season or within the cultivar. These combined calibrations resulted in R values of 0.92 to 0.97 with SEC values ranging from 0.37% to 0.79%. Simple correlations of validations (r) ranged from 0.20 to 0.94 and the standard error of prediction (SEP) ranged from 0.49% to 1.63% while the bias varied from -0.01% to -2.62%. Lower r values and higher SEP and bias values resulted when individual cultivar calibrations were used to predict SS levels in other cultivar validation data sets. Cultivar calibrations, season calibrations and the overall calibration predicted SS content of all validation data sets with a smaller bias and SEP and with higher r values. These results indicate that NIR spectrometry is suitable for rapid nondestructive determination of SS in peaches. Feasible applications of the method include packinghouse sorting of peaches for sweetness and parent and progeny fruit quality assessment in peach breeding programs. Using this technique fruit may be sorted into two or three sweetness classes. The technique may also potentially be extended to other fruit.

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