High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods

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dc.authoridFrancis, David/0000-0003-2016-1357
dc.authoridRodriguez-Saona, Luis/0000-0002-6615-1296
dc.contributor.authorAkpolat, Hacer
dc.contributor.authorBarineau, Mark
dc.contributor.authorJackson, Keith A.
dc.contributor.authorAkpolat, Mehmet Z.
dc.contributor.authorFrancis, David M.
dc.contributor.authorChen, Yu-Ju
dc.contributor.authorRodriguez-Saona, Luis E.
dc.date.accessioned2024-10-04T18:51:04Z
dc.date.available2024-10-04T18:51:04Z
dc.date.issued2020
dc.departmentBayburt Üniversitesien_US
dc.description.abstractOur objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-trans-lycopene and beta-carotene levels were measured with a UV-visible spectrophotometer, and prediction models were developed using PLSR and ANN. Regression models developed with Raman spectra provided excellent prediction performance by ANN (r(pre)= 0.9, SEP = 1.1 mg/100 g) and PLSR (r(pre)= 0.87, SEP = 2.4 mg/100 g) for non-invasive determination of all-trans-lycopene in fruits. Although the number of samples were limited for beta-carotene quantification, PLSR modeling showed promising results (r(cv)= 0.99, SECV = 0.28 mg/100 g). Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with novel profiles and for separating orange varieties with distinct carotenoids (high in beta-carotene and high incis-lycopene).en_US
dc.description.sponsorshipLipman Family Farms (Naples, FL, USA)en_US
dc.description.sponsorshipThis work was financially supported by Lipman Family Farms (Naples, FL, USA), and samples were provided by Lipman Family Farms (Naples, FL, USA) and Ohio State University Tomato Breeding and Genetics program.en_US
dc.identifier.doi10.3390/s20133723
dc.identifier.issn1424-8220
dc.identifier.issue13en_US
dc.identifier.pmid32635217en_US
dc.identifier.scopus2-s2.0-85087456212en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.3390/s20133723
dc.identifier.urihttp://hdl.handle.net/20.500.12403/3368
dc.identifier.volume20en_US
dc.identifier.wosWOS:000553193500001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherMdpien_US
dc.relation.ispartofSensorsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjecttomato carotenoidsen_US
dc.subjecthandheld Raman spectroscopyen_US
dc.subjectchemometricsen_US
dc.subjectartificial neural networksen_US
dc.titleHigh-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methodsen_US
dc.typeArticleen_US

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