Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non-invasive hyperspectral imaging technique

Md Saleh, Rosalizan; Kulig, Boris; Arefi, Arman; Hensel, Oliver; Sturm, Barbara

dc.date.accessioned	2022-09-22T11:10:47Z
dc.date.available	2022-09-22T11:10:47Z
dc.date.issued	2022-02-04
dc.identifier	doi:10.17170/kobra-202209226880
dc.identifier.uri	http://hdl.handle.net/123456789/14158
dc.description.sponsorship	Gefördert im Rahmen des Projekts DEAL	ger
dc.language.iso	eng
dc.rights	Namensnennung 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	540
dc.subject.ddc	570
dc.title	Prediction of total carotenoids, color, and moisture content of carrot slices during hot air drying using non-invasive hyperspectral imaging technique	eng
dc.type	Aufsatz
dcterms.abstract	The objective of this paper was to evaluate the performance of Partial Least Square Regression (PLSR) model and to assess the statistical agreement between two different measurement techniques, that is, Vis–NIR hyperspectral imaging (HSI) and standard laboratory methods for quality evaluation of dried carrots throughout the hot-air drying process. Carrots at commercial maturity of 3.5 months after planting were harvested in two seasons (2017 and 2018) and dried in a convective hot air dryer at 50°C, 60°C, and 70°C. Quality measurements were examined at intervals of 30 minutes. PLSR was performed as a regression model to predict quality attributes in carrots, while Passing–Bablok and Deming regressions alongside Blant–Altman analysis were applied as method comparisons. Excellent prediction performance for moisture content was observed with high R²ₜ and R²ᵥ at 0.92 and 0.90 with values of RMSEₜ and RMSEᵥ at 8.15% and 8.16%. Satisfactory prediction accuracies were observed for total carotenoids (R²ᵥ = 0.64 and RMSEᵥ = 32.62) μg/g, L* (R²ᵥ = 0.68 and RMSEᵥ = 32.62), a* (R²ᵥ = 0.69 and RMSEᵥ = 1.18), and b* (R²ᵥ = 0.60 and RMSEᵥ = 1.45). Selected wavelengths for total carotenoids, moisture content, L, a, and b* based on the highest score of VIP loadings were 531, 973, 531, 531, and 680 nm, respectively. An adequate agreement of Blant–Altman analysis between the two methods within the upper and lower limits of 95% confidence interval (CI) were obtained for total carotenoids from 95.68 μg/g to 82.34 μg/g, moisture content (25.18% to 22.93%), L* (2.88 to −3.30), a* (4.15 to 3.43), and b* (4.53 to −3.11) with mean differences at 6.67, 1.12, −0.21, 0.36, and 0.71, respectively. Good correlation coefficients (r) were also observed at 0.89, 0.91, 0.78, and 0.83 for moisture content, L, a, and b* with a moderate correlation of total carotenoids at 0.69. The results indicate the potential feasibility of using non-invasive measurement of quality attributes using hyperspectral imaging during the drying of carrots. // Novelty impact statement: Non-invasive measurement using hyperspectral imaging for quality determination in carrots during convective drying demonstrated promising results. / Multivariate analysis of Partial Least Square Regression showed a good modeling performance for quality prediction in dried carrots. / A good statistical agreements between non-invasive quality measurements using hyperspectral imaging and standard laboratory analysis were achieved by comparative analysis using Blant–Altman plot, Deming, and Passing–Bablok regression.	eng
dcterms.accessRights	open access
dcterms.creator	Md Saleh, Rosalizan
dcterms.creator	Kulig, Boris
dcterms.creator	Arefi, Arman
dcterms.creator	Hensel, Oliver
dcterms.creator	Sturm, Barbara
dc.relation.doi	doi:10.1111/jfpp.16460
dc.subject.swd	Methode der partiellen kleinsten Quadrate	ger
dc.subject.swd	Karotte	ger
dc.subject.swd	Messung	ger
dc.subject.swd	Heißlufttrocknung	ger
dc.subject.swd	Pflanzeninhaltsstoff	ger
dc.type.version	publishedVersion
dcterms.source.identifier	eissn:1745-4549
dcterms.source.issue	Issue 9
dcterms.source.journal	Journal of Food Processing and Preservation	eng
dcterms.source.volume	Volume 46
kup.iskup	false
dcterms.source.articlenumber	e16460