2017
DOI: 10.1016/j.foodchem.2017.02.075
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A rapid and nondestructive method to determine the distribution map of protein, carbohydrate and sialic acid on Edible bird’s nest by hyper-spectral imaging and chemometrics

Abstract: A rapid and nondestructive method to determine the distribution map of protein, carbohydrate and sialic acid on Edible bird s nest by hyper-spectral imaging and chemometrics, Food Chemistry (2017), doi: http://dx.doi.org/10.1016/j.foodchem. 2017.02.075 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof b… Show more

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Cited by 41 publications
(16 citation statements)
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“…Relevant studies have reported that wavenumbers selection method can simply improve NIR models and increase reliability, which agrees with the results of the present study. 3739…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Relevant studies have reported that wavenumbers selection method can simply improve NIR models and increase reliability, which agrees with the results of the present study. 3739…”
Section: Resultsmentioning
confidence: 99%
“…Relevant studies have reported that wavenumbers selection method can simply improve NIR models and increase reliability, which agrees with the results of the present study. [37][38][39] Because agar medium contains a considerable high amount of water, bands in the water regions can be observed in Figure 3. The water content in agar medium may vary; therefore, estimating the effect of variations in water content was necessary in this study.…”
Section: Validation Of Calibration Modelsmentioning
confidence: 99%
“…The exposure time of the camera was 50 ms, and the speed of the conveyor was 0.9 mm/s. Detailed information regarding hyperspectral image collection is presented in our earlier study ( Shi et al, 2017 , Shi et al, 2018 ).…”
Section: Methodsmentioning
confidence: 99%
“…Hyperspectral technology has been widely used in the food field. In addition to the primary agricultural products and food mentioned above, this technology has also been applied to other kinds of food detection, such as nutriments (Shi et al., 2017) and cocoa beans (Caporaso, Whitworth, Fowler, & Fisk, 2018). Moreover, hyperspectral technology is first used to quantitatively predict the content of sucrose, caffeine, and triglycerides in single coffee bean (Caporaso, Whitworth, Grebby, & Fisk, 2018).…”
Section: Application Of Hyperspectral Technology In the Field Of Agrimentioning
confidence: 99%