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

Xu, Duohua, Wang, Huaiwen, Ji, Hongwei, Zhang, Xiaochuan, Wang, Yanan, Zhang, Zhe and Zheng, Hongfei 2018, Hyperspectral imaging for evaluating impact damage to mango according to changes in quality attributes, Sensors, vol. 18, no. 11, pp. 1-14, doi: 10.3390/s18113920.

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Title Hyperspectral imaging for evaluating impact damage to mango according to changes in quality attributes
Author(s) Xu, Duohua
Wang, Huaiwen
Ji, Hongwei
Zhang, Xiaochuan
Wang, YananORCID iD for Wang, Yanan orcid.org/0000-0003-0324-6519
Zhang, Zhe
Zheng, Hongfei
Journal name Sensors
Volume number 18
Issue number 11
Article ID 3920
Start page 1
End page 14
Total pages 14
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2018-11
ISSN 1424-8220
Keyword(s) hyperspectral imaging
impact damage
mango
partial least squares regression
quality attributes
Mangifera indica Linn
science & technology
physical sciences
technology
chemistry, analytical
electrochemistry
instruments & instrumentation
chemistry
Summary 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.
Language eng
DOI 10.3390/s18113920
Field of Research 0301 Analytical Chemistry
0906 Electrical And Electronic Engineering
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2018, the authors
Persistent URL http://hdl.handle.net/10536/DRO/DU:30115734

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