کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5767243 | 1628384 | 2017 | 38 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discrimination of gluten-free oats from contaminants using near infrared hyperspectral imaging technique
ترجمه فارسی عنوان
جداسازی جو از گلوتن از آلاینده ها با استفاده از تکنیک تصویربرداری فوق العاده مادون قرمز
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
دانش تغذیه
چکیده انگلیسی
Oat is considered as a good addition to the gluten-free diet, but it is a challenge to keep the oats segregated from other gluten-rich grains, such as wheat, barley, and rye. Therefore, oat-processing industry demands better detection tools for identifying and screening oat grain. The research goal of this study was to investigate the potential of near infrared (NIR) hyperspectral imaging for non-destructive and accurate discrimination of oats from barley, wheat, and rye. A procedure was developed to classify six grains (oat, dehulled oat, barley, dehulled barley, wheat and rye) using NIR hyperspectral imaging in the wavelength range of 900-1700Â nm coupled with multivariate data analysis. The reflectance spectra were analyzed using Principal Component Analysis (unsupervised) and Partial Least Squares Discriminant Analysis (supervised) classification models to discriminate single oat kernels. Good results of dehulled oats grain prediction (99%) were achieved using only few selected key wavelengths (1069, 1126, 1189, 1243, and 1413Â nm). Our results establish that NIR hyperspectral imaging has potential for application in on-line oat grain quality control and inspection at the different stages of industrial processing.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Food Control - Volume 80, October 2017, Pages 197-203
Journal: Food Control - Volume 80, October 2017, Pages 197-203
نویسندگان
Chyngyz Erkinbaev, Kelly Henderson, Jitendra Paliwal,