Sensors (Nov 2018)

Hyperspectral Imaging for Evaluating Impact Damage to Mango According to Changes in Quality Attributes

  • Duohua Xu,
  • Huaiwen Wang,
  • Hongwei Ji,
  • Xiaochuan Zhang,
  • Yanan Wang,
  • Zhe Zhang,
  • Hongfei Zheng

DOI
https://doi.org/10.3390/s18113920
Journal volume & issue
Vol. 18, no. 11
p. 3920

Abstract

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Evaluation of impact damage to mango (Mangifera indica Linn) as a result of dropping from three different heights, namely, 0.5, 1.0 and 1.5 m, was conducted by hyperspectral imaging (HSI). Reflectance spectra in the 900⁻1700 nm region were used to develop prediction models for pulp firmness (PF), total soluble solids (TSS), titratable acidity (TA) and chroma (∆b*) by a partial least squares (PLS) regression algorithm. The results showed that the changes in the mangoes’ quality attributes, which were also reflected in the spectra, had a strong relationship with dropping height. The best predictive performance measured by coefficient of determination (R2) and root mean square errors of prediction (RMSEP) values were: 0.84 and 31.6 g for PF, 0.9 and 0.49 oBrix for TSS, 0.65 and 0.1% for TA, 0.94 and 0.96 for chroma, respectively. Classification of the degree of impact damage to mango achieved an accuracy of more than 77.8% according to ripening index (RPI). The results show the potential of HSI to evaluate impact damage to mango by combining with changes in quality attributes.

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