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Predicting Apple Firmness and Soluble Solids Content Based on Hyperspectral Scattering Imaging Using Fourier Series Expansion
摘要： This article reports on using a Fourier series expansion method to extract features from hyperspectral scattering profiles for apple fruit firmness and soluble solids content (SSC) prediction. Hyperspectral scattering images of ‘Golden Delicious’ (GD), ‘Jonagold’ (JG), and ‘Delicious’ (RD) apples, harvested in 2009 and 2010, were acquired using an online hyperspectral imaging system over the wavelength region of 500 to 1000 nm. The moment method and Fourier series expansion method were used to analyze the scattering profiles of apples. The zeroth-first order moment (Z-FOM) spectra and Fourier coefficients were extracted from each apple, which were then used for developing fruit firmness and SSC prediction models using partial least squares (PLS) and least squares support vector machine (LSSVM). The PLS models based on the Fourier coefficients improved the standard errors of prediction (SEP) by 4.8% to 19.9% for firmness and by 2.4% to 13.5% for SSC, compared with the PLS models using the Z-FOM spectra. The LSSVM models for the prediction set of Fourier coefficients achieved better SEP results, with improvements of 4.4% to 11.3% for firmness and 2.8% to 16.5% for SSC over the LSSVM models for the Z-FOM spectra data and 3.7% to 12.6% for firmness and 5.4% to 8.6% for SSC over the PLS models for the Fourier coefficients. Experiments showed that Fourier series expansion provides a simple, fast, and effective means for improving hyperspectral scattering prediction of fruit internal quality when used with either PLS or LSSVM.
关键词： Partial least squares,Soluble solids content,Apples,Least squares support vector machine,Fourier series expansion,Hyperspectral scattering imaging,Firmness
更新于2025-09-23 15:22:29
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Non-destructive discrimination of avocado fruit ripeness using laser Doppler vibrometry
摘要： Consumers increasingly desire ready-to-eat avocado fruit, yet if supplies fall short of customer expectations, complaints follow, incurring considerable cost and waste. In the avocado sector, wastage due to destructive testing and inaccurate assessment of firmness is significant. The aim of this study was to evaluate whether non-destructive laser Doppler vibrometry (LDV) was capable of assessing avocado ripeness. Data were sourced from two trials using preclimacteric imported 'Hass' avocado fruit originating from Chile and Spain, ripened at 12 and 18 °C, respectively. Standard force-deformation measurements, and either single or simultaneous dual vibration time signals were recorded during shelf-life, and assessed against respiration and non-structural carbohydrate content. Resonant frequencies measured from fruit by means of LDV decreased two- to four-fold during ripening and this corresponded with a concomitant decrease in firmness (253 N e2 N). The capability of the LDV system to non-destructively discriminate between ripeness stages was demonstrated.
关键词： Quality control,Persea americana,Mannoheptulose,Impulse response,Firmness
更新于2025-09-23 15:19:57
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Use of steady-state imaging setup for assessing the internal optical properties of non-spherical apple samples
摘要： The aim of this paper was to retrieve the absorption (μa) and reduced scattering (μ's) coefficients of whole apples which exhibit a complex shape. The effect of the local boundary curvature on the retrieved optical properties was investigated by means of numerical simulations and measurements carried out at the wavelength of 633 nm. A first attempt was made by performing Monte Carlo simulations on an apple-like spheroid model covered with a thin skin layer of thickness 80 μm. Monte Carlo data were then analyzed to depict the changes of photon densities, diffusively reflected images and optical properties as a function of the light source location over the surface of such target. Second, spatially-resolved backscattered images were acquired from 207 ‘Royal Gala’, and the values of μa and μ's were retrieved using an inverse algorithm to fit the scattering profiles with a diffusion theory model, in a selected fitting range of 2.8–10 mm. The results confirm the theoretical prediction and show that the absorption coefficient μa may be overestimated, while the reduced scattering coefficient μ's is slowly changed when the measurements are performed on these apple species. Finally, experiments carried out on 200 apples still show that μ's is negatively correlated to the fruit firmness with a correlation coefficient (r) of 0.63. The spatially-resolved technique provides an efficient means for measuring the optical properties of fruits, and may be also useful for assessing the apple firmness.
关键词： Diffusion theory,Optical properties,Light propagation,Imaging system,Apple firmness
更新于2025-09-19 17:15:36
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Sugar Contents and Firmness of Apples Based on Multi-Spectral Imaging Technology
摘要： The paper proposed a prediction method of apple sugar content and firmness based on multi-spectral imaging. Firstly, four characteristic wavelengths (670, 750, 780 and 810 nm) were selected by correlation coefficient method. The gray images of samples at different wavelengths were collected by multi-spectral imaging system, then fitted with Lorenz function, modified Lorenz function, Gaussian function and polynomial function, respectively. It was found that the fitting effect of modified Lorenz function was best. Therefore, the experiment was performed by multiple linear regression and partial least square regression analysis of sugar content and firmness with the fitting parameters of modified Lorenz function. The result showed that the prediction of multiple linear regression model was better than partial least squares regression model. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and predicted standard deviation of sugar content were 0.8568, 0.6736, 0.8395 and 0.7068, respectively. The modeling correction correlation coefficient, calibration standard deviation, the prediction correlation coefficient and the predicted standard deviation of firmness were 0.8660, 0.3275, 0.8407 and 0.3555, respectively. The results also showed that this method was feasible for the prediction of apple sugar content and firmness.
关键词： Firmness,Multi-spectral imaging,Curve fitting,Apple,Multiple linear regression,Sugar content
更新于2025-09-04 15:30:14