Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/27/2009
Publication Date: 6/21/2009
Citation: Qin, J., Lu, R., Peng, Y. 2009. Prediction of Apple Internal Quality Using Spectral Absorption and Scattering Properties. Transactions of the ASABE. 52(2):499-507. Interpretive Summary: Light interactions with turbid or opaque biological materials involve both absorption and scattering. Absorption is primarily related to the chemical constituents of the material, whereas scattering is influenced by the density, cell structures and interfaces between cells. Thus measurement and separation of absorption and scattering properties of fruit can provide useful information about internal quality of apples. In this research, we measured spectral scattering profiles for 600 ‘Golden Delicious’ apples in the visible and near-infrared region between 500 and 1100 nm using a spatially resolved hyperspectral imaging technique recently developed in our lab. The absorption and scattering properties were extracted from the measured data. Statistical models were developed relating the measured optical properties to apple fruit firmness and soluble solids content (SSC). In addition, two simpler methods (i.e., the average value of scattering profiles at individual wavelengths and a modified Lorentzian function) were used to describe the spectral scattering profiles. Results showed that absorption was more useful than scattering in prediction of fruit firmness and SSC. Combination of the two optical properties provided better predictions of fruit firmness and SSC, with the correlation coefficient of 0.86 and 0.75, respectively. The prediction models using the two simpler methods (i.e., the mean spectra and the modified Lorentzian function) had better prediction results, with the correlation coefficient of 0.87 and 0.88 for firmness, and 0.89 and 0.86 for SSC, respectively. This research demonstrated that absorption and scattering properties are useful for predicting fruit quality. The research opened a new way for nondestructive quality sensing of horticultural and food products. Researchers now can use the method developed in this research to measure the optical properties of other food and agricultural products and use them to predict product quality attributes and quantify light interaction with food materials.
Technical Abstract: This paper reports on the measurement of the absorption and reduced scattering coefficients of apples via a new spatially-resolved hyperspectral imaging technique and their correlation with fruit firmness and soluble solids content (SSC). Spatially-resolved hyperspectral scattering profiles were acquired from 600 ‘Golden Delicious’ apples, and values for the absorption coefficient and reduced scattering coefficient were determined using an inverse algorithm to fit the diffusion theory model to the spectral scattering profiles for the spectral region of 500-1100 nm. There were two predominant peaks in the absorption spectra around 675 nm and 970 nm due to the presence of chlorophyll and water in the fruit, respectively. Spectra of the reduced scattering coefficient generally decreased with the increasing wavelength. Absorption coefficient was more useful than the reduced scattering coefficient in predicting fruit firmness and SSC. The combined data of absorption and reduced scattering coefficients had better predictions of fruit firmness with r = 0.86 and the standard error of prediction (SEP) of 6.05 N, and of the SSC with r = 0.75 and SEP = 0.90%. In addition, two simpler methods (i.e., the mean spectra and a modified Lorentzian distribution function) were used to describe the scattering profiles. The mean spectra and Lorentzian function resulted in better predictions of fruit firmness with r = 0.87 and 0.88, and of the SSC with r = 0.89 and 0.86, respectively. Spectral absorption and scattering properties are useful for evaluating internal quality attributes of horticultural products and especially for quantitative analysis of light propagation in individual fruit.