FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4366503491> ?p ?o ?g. }

• W4366503491 endingPage "104692" @default.
• W4366503491 startingPage "104692" @default.
• W4366503491 abstract "Honey is a high-value product that proscribes adulteration. Authentication of pure honey is an imperative act that can disregard the adverse impacts brought by fraudsters on honey producers and consumers. A reliable method that can detect food adulteration that is nondestructive, rapid, and efficient can help maintain product authenticity. This study investigated the potential of a near-infrared hyperspectral imaging (NIR-HSI) system combined with supervised classification techniques for the classification of honey samples from different botanical origins that were adulterated with sugar cane syrup at 20 % and 40 % w/w. Reflectance and transflectance modes of measurement were used to obtain honey spectral images from 864.53 nm to 1700 nm. Supervised classification algorithms, namely, stepwise discriminant analysis (SDA), support vector machine (SVM), and k-nearest neighbors (kNN) were used for the classification based on whole spectral data and feature selected spectral data. The best classification model from reflectance mode was observed from SDA based on a leave-one-out cross-validation (LOOCV) method with a test accuracy of 95 %. For transflectance mode, the classification model developed from SDA based on a LOOCV method provided better test set accuracy of 100 %. The classification performance levels of the models developed from SVM and kNN were lower with the use of the whole wavelength region. Moreover, the classification performance levels of SVM and kNN using the selected features by the SDA greatly increased, however, they were not as good as from using SDA alone. The classifier maps created using SDA and predicting the averaged spectra of all pixels in the image with 10-discriminant functions for each mode of measurement displayed a two-dimensional image that had a distinct colour pertaining to a particular class that could easily discriminate one class from another." @default.
• W4366503491 created "2023-04-22" @default.
• W4366503491 creator A5007510376 @default.
• W4366503491 creator A5078777234 @default.
• W4366503491 creator A5080700317 @default.
• W4366503491 creator A5082367398 @default.
• W4366503491 date "2023-06-01" @default.
• W4366503491 modified "2023-09-25" @default.
• W4366503491 title "Improving the performance of the model developed from the classification of adulterated honey with different botanical origins based on near-Infrared hyperspectral imaging system and supervised classification algorithms" @default.
• W4366503491 cites W1120960026 @default.
• W4366503491 cites W1241026583 @default.
• W4366503491 cites W1965545172 @default.
• W4366503491 cites W1988975411 @default.
• W4366503491 cites W2008842627 @default.
• W4366503491 cites W2021754455 @default.
• W4366503491 cites W2031335397 @default.
• W4366503491 cites W2045423225 @default.
• W4366503491 cites W2156909104 @default.
• W4366503491 cites W2181985337 @default.
• W4366503491 cites W2344307348 @default.
• W4366503491 cites W2432436793 @default.
• W4366503491 cites W2487770199 @default.
• W4366503491 cites W2495250179 @default.
• W4366503491 cites W2507669320 @default.
• W4366503491 cites W2549074815 @default.
• W4366503491 cites W2589541741 @default.
• W4366503491 cites W2596459716 @default.
• W4366503491 cites W2751060678 @default.
• W4366503491 cites W2794828875 @default.
• W4366503491 cites W2795263948 @default.
• W4366503491 cites W2927442480 @default.
• W4366503491 cites W3004159173 @default.
• W4366503491 cites W3042063492 @default.
• W4366503491 cites W3045004532 @default.
• W4366503491 cites W4248083651 @default.
• W4366503491 doi "https://doi.org/10.1016/j.infrared.2023.104692" @default.
• W4366503491 hasPublicationYear "2023" @default.
• W4366503491 type Work @default.
• W4366503491 citedByCount "0" @default.
• W4366503491 crossrefType "journal-article" @default.
• W4366503491 hasAuthorship W4366503491A5007510376 @default.
• W4366503491 hasAuthorship W4366503491A5078777234 @default.
• W4366503491 hasAuthorship W4366503491A5080700317 @default.
• W4366503491 hasAuthorship W4366503491A5082367398 @default.
• W4366503491 hasConcept C12267149 @default.
• W4366503491 hasConcept C153180895 @default.
• W4366503491 hasConcept C154945302 @default.
• W4366503491 hasConcept C159078339 @default.
• W4366503491 hasConcept C33923547 @default.
• W4366503491 hasConcept C41008148 @default.
• W4366503491 hasConcept C69738355 @default.
• W4366503491 hasConcept C95623464 @default.
• W4366503491 hasConceptScore W4366503491C12267149 @default.
• W4366503491 hasConceptScore W4366503491C153180895 @default.
• W4366503491 hasConceptScore W4366503491C154945302 @default.
• W4366503491 hasConceptScore W4366503491C159078339 @default.
• W4366503491 hasConceptScore W4366503491C33923547 @default.
• W4366503491 hasConceptScore W4366503491C41008148 @default.
• W4366503491 hasConceptScore W4366503491C69738355 @default.
• W4366503491 hasConceptScore W4366503491C95623464 @default.
• W4366503491 hasLocation W43665034911 @default.
• W4366503491 hasOpenAccess W4366503491 @default.
• W4366503491 hasPrimaryLocation W43665034911 @default.
• W4366503491 hasRelatedWork W1809065030 @default.
• W4366503491 hasRelatedWork W1968332688 @default.
• W4366503491 hasRelatedWork W2028628118 @default.
• W4366503491 hasRelatedWork W2051197289 @default.
• W4366503491 hasRelatedWork W2146076056 @default.
• W4366503491 hasRelatedWork W2361282548 @default.
• W4366503491 hasRelatedWork W2380927352 @default.
• W4366503491 hasRelatedWork W3173596272 @default.
• W4366503491 hasRelatedWork W3184937839 @default.
• W4366503491 hasRelatedWork W2345184372 @default.
• W4366503491 hasVolume "131" @default.
• W4366503491 isParatext "false" @default.
• W4366503491 isRetracted "false" @default.
• W4366503491 workType "article" @default.