DSpace Repository

LOW COST AND LABORATORY SCALE NIR SPECTROSCOPY FOR QUALITY EVALUATION OF FRUITS AND VEGETABLES

Show simple item record

dc.contributor.author Kesilmis, Zehan
dc.contributor.author Vursavus, Kubilay K.
dc.date.accessioned 2019-11-21T08:31:31Z
dc.date.available 2019-11-21T08:31:31Z
dc.date.issued 2018
dc.identifier.citation Kesilmis, Z., & Vursavus, K. K. (2018). LOW COST AND LABORATORY SCALE NIR SPECTROSCOPY FOR QUALITY EVALUATION OF FRUITS AND VEGETABLES. Scientific Papers-Series B-Horticulture, 62, 165-168. tr_TR
dc.identifier.issn 2285-5653
dc.identifier.issn 2286-1580
dc.identifier.uri http://openaccess.adanabtu.edu.tr:8080/xmlui/handle/123456789/596
dc.identifier.uri http://horticulturejournal.usamv.ro/index.php/18-articles/articles-2018/544-low-cost-and-laboratory-scale-nir-spectroscopy-for-quality-evaluation-of-fruits-and-vegetables-544
dc.description WOS indeksli yayınlar koleksiyonu. / WOS indexed publications collection.
dc.description.abstract NIR spectroscopy has proved to be one of the efficient and easy tools to monitor the quality of agricultural products. NIR spectrometers are versatile devices to monitor the ripeness or quality parameters of the fruits. We demonstrate a low-cost spectrometer design that is produced with off the shelf components. In this work, the development, characterization and validation of a prototype is discussed. The proposed device has a dedicated user interface on the PC to plot and analyze spectral data. The performance of the proposed spectrometer is comparable to existing laboratory scale spectrometers in terms of stability and resolution. The spectral resolution and response range of the proposed spectrometer are 20 nm and 640-1050nm, respectively. Proposed device consists of MEMS based Hamamatsu spectrometer sensor (C11708MA), microcontroller (Arduino) and IR light source. Roles of the Arduino are generating essential control signals and sampling output of the C11708MA. These spectral response data have a huge advantage in generating data sets that may be useful in building machine learning based models. tr_TR
dc.language.iso en tr_TR
dc.publisher SCIENTIFIC PAPERS-SERIES B-HORTICULTURE / UNIV AGRICULTURAL SCIENCES & VETERINARY MEDICINE BUCHAREST tr_TR
dc.relation.ispartofseries 2018;Volume: 62
dc.subject fruit and vegetable quality spectrometer tr_TR
dc.subject near infrared spectroscopy
dc.subject non-destructive detection
dc.subject PREDICTION
dc.subject Plant Sciences
dc.title LOW COST AND LABORATORY SCALE NIR SPECTROSCOPY FOR QUALITY EVALUATION OF FRUITS AND VEGETABLES tr_TR
dc.type Article tr_TR


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Advanced Search

Browse

My Account