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Rapid Prediction of Moisture Content in Intact Green Coffee Beans Using Near Infrared Spectroscopy

dc.contributor.authorAdnan, Adnan
dc.contributor.authorHörsten, Dieter von
dc.contributor.authorPawelzik, Elke
dc.contributor.authorMörlein, Daniel
dc.date.accessioned2017-06-16T13:59:03Z
dc.date.available2017-06-16T13:59:03Z
dc.date.issued2017
dc.relation.ISSN2304-8158en
dc.identifier.urihttp://resolver.sub.uni-goettingen.de/purl?gs-1/14510
dc.description.abstractMoisture content (MC) is one of the most important quality parameters of green coffee beans. Therefore, its fast and reliable measurement is necessary. This study evaluated the feasibility of near infrared (NIR) spectroscopy and chemometrics for rapid and non-destructive prediction of MC in intact green coffee beans of both Coffea arabica (Arabica) and Coffea canephora (Robusta) species. Diffuse reflectance (log 1/R) spectra of intact beans were acquired using a bench top Fourier transform NIR instrument. MC was determined gravimetrically according to The International Organization for Standardization (ISO) 6673. Samples were split into subsets for calibration (n = 64) and independent validation (n = 44). A three-component partial least squares regression (PLSR) model using raw NIR spectra yielded a root mean square error of prediction (RMSEP) of 0.80% MC; a four component PLSR model using scatter corrected spectra yielded a RMSEP of 0.57% MC. A simplified PLS model using seven selected wavelengths (1155, 1212, 1340, 1409, 1724, 1908, and 2249 nm) yielded a similar accuracy (RMSEP: 0.77% MC) which opens the possibility of creating cheaper NIR instruments. In conclusion, NIR diffuse reflectance spectroscopy appears to be suitable for rapid and reliable MC prediction in intact green coffee; no separate model for Arabica and Robusta species is needed.en
dc.description.sponsorshipOpen-Access-Publikationsfonds 2017
dc.language.isoengen
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectquality; rapid methods; infrared spectroscopy; Coffea arabica (Arabica); Coffea canephora (Robusta); chemometricsen
dc.titleRapid Prediction of Moisture Content in Intact Green Coffee Beans Using Near Infrared Spectroscopyen
dc.typejournalArticle
dc.identifier.doi10.3390/foods6050038
dc.type.versionpublishedVersionen
dc.bibliographicCitation.volume6en
dc.bibliographicCitation.issue6en
dc.bibliographicCitation.firstPage38en
dc.type.subtypejournalArticle
dc.identifier.pmid28534842
dc.description.statuspeerRevieweden
dc.bibliographicCitation.journalFoodsen


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