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Hyperspectral imaging for evaluating impact damage to mango according to changes in quality attributes

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Version 1 2018-11-27, 10:40
journal contribution
posted on 2024-06-18, 11:38 authored by D Xu, H Wang, H Ji, X Zhang, Yanan WangYanan Wang, Z Zhang, H Zheng
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.

History

Journal

Sensors (Switzerland)

Volume

18

Article number

ARTN 3920

Pagination

1 - 14

Location

Switzerland

Open access

  • Yes

ISSN

1424-8220

eISSN

1424-8220

Language

English

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2018, the authors

Issue

11

Publisher

MDPI