Discrimination of onion subjected to drought and normal watering mode based on fluorescence spectroscopic data

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dc.authorid0000-0003-0238-9606en_US
dc.authorid0000-0001-7549-0137en_US
dc.contributor.authorRopelewska, Ewa
dc.contributor.authorSlavova, Vanya
dc.contributor.authorSabancı, Kadir
dc.contributor.authorAslan, Muhammet Fatih
dc.contributor.authorCai, Xiang
dc.contributor.authorGenova, Stefka
dc.date.accessioned2022-04-11T08:28:03Z
dc.date.available2022-04-11T08:28:03Z
dc.date.issued2022en_US
dc.departmentKMÜ, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümüen_US
dc.descriptionWOS:000806136800005en_US
dc.description.abstractDrought stress can affect the yield and quality of cultivated plants. The deficit of water may result in the physiological and anatomical reactions at organ, tissue and cellular levels of the plant species. The objective of this study was to discriminate different onion samples with the use of innovative models based on fluorescence spectroscopic data using different classifiers. The onion growing under drought and normal watering conditions were compared. Additionally, the five different samples of onion including three varieties (Konkurent bql, Asenovgradska kaba, Trimoncium) and two lines (white, red) subjected to both the drought mode and normal watering mode were differentiated. The results were evaluated based on confusion matrices, average accuracies, and the values of TP (True Positive) Rate, FP (False Positive) Rate, Precision, F-Measure, ROC (Receiver Operating Characteristic) Area and PRC (Precision-Recall) Area. In the case of the discrimination of two classes: drought mode and normal watering mode, an average accuracy reached 100% for white line of onion for a model built using the Naive Bayes, Multilayer Perceptron, JRip and LMT classifiers and for red line of onion for all used classifiers (Naive Bayes, Multilayer Perceptron, IBk, Multi Class Classifier, JRip, LMT). The values of TP Rate, Precision, F-Measure, ROC Area and PRC Area were equal to 1.000, and FP Rate was 0.000. For onion samples subjected to drought, five classes including the Konkurent, Asenovgradska kaba, Trimoncium varieties and the white and red lines were discriminated with an average accuracy of up to 90% for the LMT classifier. The same classes of samples but subjected to normal watering were correctly distinguished in 84% for the Naive Bayes classifier.en_US
dc.identifier.citationRopelewska, E., Slavova, V., Sabanci, K., Fatih Aslan, M., Cai, X., & Genova, S. (2022). Discrimination of onion subjected to drought and normal watering mode based on fluorescence spectroscopic data. Computers and Electronics in Agriculture, 196 doi:10.1016/j.compag.2022.106916en_US
dc.identifier.doi10.1016/j.compag.2022.106916
dc.identifier.issn0168-1699
dc.identifier.scopus2-s2.0-85127283486
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.compag.2022.106916
dc.identifier.urihttps://hdl.handle.net/11492/6248
dc.identifier.volume196en_US
dc.identifier.wosWOS:000806136800005
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Sceince
dc.indekslendigikaynakScopus
dc.institutionauthorSabancı, Kadir
dc.institutionauthorAslan, Muhammet Fatih
dc.language.isoen
dc.publisherElsevier B.V.en_US
dc.relation.journalComputers and Electronics in Agricultureen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectClassification Metricsen_US
dc.subjectDrought Stressen_US
dc.subjectFluorescence Spectroscopyen_US
dc.subjectNormal Watering Conditionsen_US
dc.subjectOnion Varieties And Linesen_US
dc.titleDiscrimination of onion subjected to drought and normal watering mode based on fluorescence spectroscopic dataen_US
dc.typeArticle

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