Abstract

Sugar “imaging” of fruit has previously been reported using NIR filters and relatively expensive (high signal-to-noise) charge-coupled device (CCD) instrumentation. In a bid to use lower cost CCD instrumentation (criterion of less than AU $5,000 total component costs), the signal-to-noise constraint on calibration model performance was investigated by artificially degrading spectra from a 15-bit AtoD system. A low cost 8-bit CCD camera was then used in conjunction with a filter wheel in a transmittance configuration employing three 50 W halogen lamps. Multiple linear regregression calibrations were developed based on absorbance data of five wavelengths (830, 850, 870, 905 and 930 nm) relevant to sugar and water. Calibration models for the sucrose concentration of solutions on a cellulose matrix were poor (R² = 0.4) when based on individual pixel data, but acceptable (R² = 0.98, RMSECV = 1.1) (n = 20, mean = 13.9% total soluble sugars (TSS), SD = 6.04) when based on an average of a 23 × 23 pixel block (i.e. 529 pixels). For a calibration based on melon tissue TSS, using spectral data averaged over groups of 529 pixels, results were poorer than expected (R² = 0.4, RMSEP = 1.74 (n = 163, mean = 9.45, SD = 2.07% TSS). Predicted TSS output for all pixel blocks from an image was used to generate a false colour image. We conclude that this application requires a higher level of signal-to-noise (for example, 10-bit, > 60 dB CCD).

© 2005 NIR Publications

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