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Visible and Near-Infrared Hyperspectral Imaging to Describe Properties of Conventionally and Organically Grown Carrots

Česonienė, Laima; Masaitis, Gediminas; Mozgeris, Gintautas; Gadal, Sébastien; Šileikienė, Daiva and Karklelienė, Rasa (2019) Visible and Near-Infrared Hyperspectral Imaging to Describe Properties of Conventionally and Organically Grown Carrots. Journal of Elementology, pp. 421-435.

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Document available online at: https://hal-amu.archives-ouvertes.fr/hal-01996397


Summary

This paper discusses the potential of visible and near-infrared hyperspectral imaging to describe properties of conventionally and organically grown carrots. 140 samples of four Lithuanian carrot cultivars were scanned using a VNIR400H hyperspectral camera, capable of covering the spectral range of 400-1000 nm with a sampling interval of 0.6 nm. Half of the samples were grown under organic farming conditions and the remainder under conventional conditions. Chemical and electro-chemical properties, i.e. nitrate content, acidity, reduction potential and electrical conductivity, were determined for the carrot root samples using conventional methods of chemical investigations. The ability to separate organically and conventionally grown samples on the basis of spectral data was examined by applying estimations of Jeffries-Matusita distances and linear discriminant analysis. Opportunities to predict the chemical and electro-chemical properties of samples applying the partial least squares regression and the spectral data as predictors were also investigated. The overall classification accuracy of samples of organically and conventionally grown carrot cultivars when applying linear discriminant analysis was in the range of 94.4-100% and the Jeffries-Matusita distances were in the range of 1.98-2.00. There was good prediction potential using the partial least squares regression for electrical conductivity (R 2 = 0.88) and reduction potential (R 2 = 0.81), better than moderate for nitrate content (R 2 = 0.77) and moderate for acidity (R 2 = 0.68) using hyperspectral reflectance data of carrot captured under laboratory conditions. Both the separation ability and prediction potential were higher if taking into account the cultivar.


EPrint Type:Journal paper
Keywords:Hyperspectral imaging (en), Organic and conventional farming (en), Chemical and electro-chemical properties (en), Carrots (en), Lithuania (en)
Subjects:"Organics" in general
Research affiliation: France > INRAe - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
ISSN:ISSN: 1644-2296
DOI:10.5601/jelem.2018.23.4.1724
Related Links:https://hal-amu.archives-ouvertes.fr/hal-01996397/document
Project ID:HAL-INRAe
Deposited By: PENVERN, Servane
ID Code:41325
Deposited On:12 Aug 2021 10:37
Last Modified:12 Aug 2021 10:37
Document Language:English

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