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Visible and Near-Infrared Hyperspectral Imaging to Describe Properties of Conventionally and Organically Grown Carrots
- Source :
- Journal of Elementology, Journal of Elementology, Polish Society for Magnesium Research and University of Warmia and Mazury in Olsztyn, 2019, 24 (2), pp.421-435. ⟨10.5601/jelem.2018.23.4.1724⟩, Journal of Elementology, 2019, 24 (2), pp.421-435. ⟨10.5601/jelem.2018.23.4.1724⟩
- Publication Year :
- 2019
- Publisher :
- HAL CCSD, 2019.
-
Abstract
- International audience; 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.
- Subjects :
- 0106 biological sciences
Materials science
Hyperspectral imaging
Health, Toxicology and Mutagenesis
Analytical chemistry
01 natural sciences
Inorganic Chemistry
Hyperspectral reflectance
chemistry.chemical_compound
Carrots
Nitrate
Partial least squares regression
[CHIM]Chemical Sciences
Cultivar
Near infrared hyperspectral imaging
Sampling interval
Organic and conventional farming
2. Zero hunger
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
Ecology
Lithuania
04 agricultural and veterinary sciences
Chemical and electro-chemical properties
Linear discriminant analysis
Pollution
chemistry
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
[SDV.AEN]Life Sciences [q-bio]/Food and Nutrition
010606 plant biology & botany
Subjects
Details
- Language :
- English
- ISSN :
- 16442296
- Database :
- OpenAIRE
- Journal :
- Journal of Elementology, Journal of Elementology, Polish Society for Magnesium Research and University of Warmia and Mazury in Olsztyn, 2019, 24 (2), pp.421-435. ⟨10.5601/jelem.2018.23.4.1724⟩, Journal of Elementology, 2019, 24 (2), pp.421-435. ⟨10.5601/jelem.2018.23.4.1724⟩
- Accession number :
- edsair.doi.dedup.....693d2c6f5afd4fd6abf1881b4243443a
- Full Text :
- https://doi.org/10.5601/jelem.2018.23.4.1724⟩