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Analysis of hyperspectral scattering characteristics for predicting apple fruit firmness and soluble solids content

机译：预测苹果果实硬度和可溶性固形物含量的高光谱散射特性分析

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摘要

Spectral scattering is useful for assessing the firmness and soluble solids content (SSC) of apples because it provides an effective means for characterizing light scattering in the fruit. This research compared three methods for quantifying the spectral scattering profiles acquired from 'Golden Delicious' apples using a hyperspectral imaging system for the spectral region of 500-1000 run. The first method relied on a diffusion theory model to describe the scattering profiles, from which the absorption and reduced scattering coefficients were obtained. The second method utilized a four-parameter Lorentzian function, an empirical model, to describe the scattering profiles. And the third method was calculation of mean reflectance from the scattering profiles for a scattering distance of 10 mm. Calibration models were developed, using multi-linear regression (MLR) and partial least squares (PLS), relating function parameters for each scattering characterization method to the fruit firmness and SSC of 'Golden Delicious' apples. The diffusion theory model gave poorer prediction results for fruit firmness and SSC (the average values of r obtained with PLS were 0.837 and 0.664 respectively for the validation samples). Lorentzian function and mean reflectance performed better than the diffusion theory model; their average r values for PLS validations were 0.860 and 0.852 for firmness and 0.828 and 0.842 for SSC respectively. The mean reflectance method is recommended for firmness and SSC prediction because it is simple and much faster for characterizing spectral scattering profiles for apples.
机译：光谱散射可用于评估苹果的硬度和可溶性固形物含量（SSC），因为它提供了表征水果中光散射的有效手段。这项研究比较了使用高光谱成像系统对500-1000光谱范围内从“金冠”苹果获得的光谱散射曲线进行定量的三种方法。第一种方法依赖于扩散理论模型来描述散射轮廓，由此获得吸收系数和减小的散射系数。第二种方法利用经验参数四参数洛伦兹函数描述散射曲线。第三种方法是从散射轮廓计算10 mm散射距离的平均反射率。使用多线性回归（MLR）和偏最小二乘（PLS）开发了校准模型，并将每种散射表征方法的功能参数与“黄金美味”苹果的果实硬度和SSC相关联。扩散理论模型对水果硬度和SSC的预测结果较差（对于PLS验证样品，r的r平均值分别为0.837和0.664）。洛伦兹函数和平均反射率比扩散理论模型更好。他们的PLS验证的平均r值（硬度）分别为0.860和0.852，SSC的平均值为0.828和0.842。建议将平均反射率方法用于硬度和SSC预测，因为它用于表征苹果的光谱散射曲线非常简单且速度更快。

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