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Recent Developments in Hyperspectral Imaging for Assessment of Food Quality and Safety

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2014 Apr 25
PMID 24759119
Citations 42
Authors
Affiliations
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Abstract

Hyperspectral imaging which combines imaging and spectroscopic technology is rapidly gaining ground as a non-destructive, real-time detection tool for food quality and safety assessment. Hyperspectral imaging could be used to simultaneously obtain large amounts of spatial and spectral information on the objects being studied. This paper provides a comprehensive review on the recent development of hyperspectral imaging applications in food and food products. The potential and future work of hyperspectral imaging for food quality and safety control is also discussed.

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References
1.
Feng Y, Sun D . Determination of total viable count (TVC) in chicken breast fillets by near-infrared hyperspectral imaging and spectroscopic transforms. Talanta. 2013; 105:244-9. DOI: 10.1016/j.talanta.2012.11.042. View

2.
Kong W, Zhang C, Liu F, Nie P, He Y . Rice seed cultivar identification using near-infrared hyperspectral imaging and multivariate data analysis. Sensors (Basel). 2013; 13(7):8916-27. PMC: 3758629. DOI: 10.3390/s130708916. View

3.
Lu J, Tan J, Shatadal P, Gerrard D . Evaluation of pork color by using computer vision. Meat Sci. 2011; 56(1):57-60. DOI: 10.1016/s0309-1740(00)00020-6. View

4.
Feng Y, ElMasry G, Sun D, Scannell A, Walsh D, Morcy N . Near-infrared hyperspectral imaging and partial least squares regression for rapid and reagentless determination of Enterobacteriaceae on chicken fillets. Food Chem. 2013; 138(2-3):1829-36. DOI: 10.1016/j.foodchem.2012.11.040. View

5.
Bauriegel E, Giebel A, Herppich W . Hyperspectral and chlorophyll fluorescence imaging to analyse the impact of Fusarium culmorum on the photosynthetic integrity of infected wheat ears. Sensors (Basel). 2011; 11(4):3765-79. PMC: 3231352. DOI: 10.3390/s110403765. View