s , respectively) of apples using a newly developed spatially '/> Prediction of Apple Internal Quality Using Spectral Absorption and Scattering Properties
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Prediction of Apple Internal Quality Using Spectral Absorption and Scattering Properties

机译:利用光谱吸收和散射特性预测苹果内部质量

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摘要

The objective of this research was to measure the absorption and reduced scattering coefficients ( µ a and µ ' s , respectively) of apples using a newly developed spatially resolved hyperspectral imaging technique and relate them to fruit firmness and soluble solids content (SSC). Spatially resolved hyperspectral scattering images were acquired for 600 'Golden Delicious' apples, and values for µ a and µ ' s were determined using an inverse algorithm to fit the spectral scattering profiles with a diffusion theory model over the wavelengths of 500-1000 nm. The absorption spectra were characterized by two predominant peaks around 675 nm and 970 nm due to the presence of chlorophylls and water in the fruit, respectively. Values of µ ' s for most apples decreased with the increasing wavelength. Both µ a and µ ' s were correlated to fruit firmness and SSC, but higher correlations were obtained with µ a than with µ ' s . The combined data of µ a and µ ' s gave better predictions of fruit firmness and SSC with values for the correlation coefficient (r) of 0.857 and 0.754, respectively. In comparison, a simpler method of calculating relative mean spectra from the hyperspectral scattering profiles gave comparable firmness predictions (r = 0.844) and better SSC predictions (r = 0.864). The spatially resolved technique provides an efficient means for measuring the optical properties of fruit, and it is also useful for assessing fruit quality attributes
机译:这项研究的目的是使用一种新开发的空间分辨高光谱成像技术来测量苹果的吸收系数和减少的散射系数(分别为µ a 和µ' s )。将它们与水果硬度和可溶性固形物含量(SSC)相关联。获取了600个“金冠”苹果的空间分辨高光谱散射图像,并使用逆算法确定µ a 和µ' s 的值以拟合光谱散射曲线在500-1000 nm波长范围内具有扩散理论模型。由于水果中分别存在叶绿素和水,吸收光谱的特征是在675 nm和970 nm附近有两个主要峰。大多数苹果的µ' s 值随波长增加而减小。 μ a 和μ' s 都与果实硬度和SSC相关,但是与<μ'相比,μ a 的相关性更高。 > s 。 µ a 和µ' s 的组合数据可以更好地预测水果的硬度和SSC,相关系数(r)的值分别为0.857和0.754。相比之下,从高光谱散射曲线计算相对平均光谱的更简单方法给出了可比的硬度预测(r = 0.844)和更好的SSC预测(r = 0.864)。空间分辨技术为测量水果的光学特性提供了一种有效的方法,并且对于评估水果的品质属性也很有用。

著录项

  • 来源
    《Transactions of the ASABE》 |2009年第2期|p.499-507|共9页
  • 作者

    J. Qin; R. Lu; Y. Peng;

  • 作者单位

    Jianwei Qin, ASABE Student Member, Post-Doctoral Research Associate, Department of Agricultural and Biological Engineering, University of Florida, Gainesville, Florida (former Graduate Student, Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, Michigan);

    Renfu Lu, ASABE Member Engineer, Supervisory Agricultural Engineer, USDA-ARS Sugarbeet and Bean Research Unit, Michigan State University, East Lansing, Michigan;

    and Yankun Peng, ASABE Member Engineer, Professor, College of Engineering, China Agricultural University, Beijing, China (former Visiting Assistant Professor, Michigan State University, East Lansing, Michigan). Corresponding author: Renfu Lu, USDA-ARS Sugarbeet and Bean Research Unit, 224 Farrall Hall, Michigan State University, East Lansing, MI 48824;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Apple; Firmness; Fruit; Hyperspectral imaging; Quality; Soluble solids; Spectroscopy;

    机译:苹果;牢固度;水果;高光谱成像;质量;可溶性固体;光谱学;

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