Recent advancement in near infrared spectroscopy and hyperspectral imaging techniques for quality and safety assessment of agricultural and food products in the China Agricultural University

Abstract

Near infrared spectroscopy and hyperspectral imaging are fast-growing, rapid, powerful, and non-destructive optical technologies that can be used especially in quality and safety control of agro-food products. The Non-destructive Detecting Laboratory for Agricultural and Food Products in the College of Engineering, China Agricultural University in Beijing, China, has engaged in research on sensing and characterizing agro-food quality and safety attributes with the latest optical methods including near infrared spectroscopy and hyperspectral imaging for over five years. In this report, some of our latest research and developments through multidisciplinary international collaborations will be highlighted to demonstrate our contributions to this near infrared spectroscopy and hyperspectral imaging sensing area to improve non-destructive diagnosis and quality control of agricultural and food products.

Keywords

Near infrared spectroscopy hyperspectral imaging aflatoxin maize kernels poultry meat adulteration detection

Get full access to this article

View all access options for this article.

References

Teye

Huang

Afoakwa

. Review on the potential use of near infrared spectroscopy (NIRS) for the measurement of chemical residues in food. J Agr Food Chem 2013; 27: 29–35.

Gowen

O'Donnell

Cullen

et al.

Hyperspectral imaging – an emerging process analytical tool for food quality and safety control. Trends Food Sci Technol 2007; 18: 590–598.

Sun DW. Hyperspectral imaging for food quality analysis and control. Amsterdam: Elsevier, 2010.

Bryden

. Mycotoxin contamination of the feed supply chain: implications for animal productivity and feed security. Anim Feed Sci Technol 2012; 173: 134–158.

Wright

Greenemcdowelle

Zeringue

HJJ

et al.

Effects of volatile aldehydes from aspergillus-resistant varieties of corn on Aspergillus parasiticus growth and aflatoxin biosynthesis. Toxicon 2000; 38: 1215–1223.

Wang

Lawrence

et al.

Near-infrared hyperspectral imaging for detecting aflatoxin B₁ of maize kernels. Food Control 2015; 51: 347–355.

Wang

Lawrence

et al.

Feasibility of detecting aflatoxin B₁ in single maize kernels using hyperspectral imaging. J Food Eng 2015; 166: 182–192.

Wang

Heitschmidt

et al.

Identification of aflatoxin B₁ on maize kernel surfaces using hyperspectral imaging. Food Control 2014; 42: 78–86.

Wang

Heitschmidt

Windham

et al.

Feasibility of detecting aflatoxin B₁ on inoculated maize kernels surface using vis/NIR hyperspectral imaging. J Food Sci 2015; 80: 116–122.

10.

Jia

Yoon

Zhuang

et al.

Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging. J Food Eng 2017; 208: 57–65.

11.

Jiang

Yoon

Zhuang

et al.

Tenderness classification of fresh broiler breast fillets using visible and near-infrared hyperspectral imaging. Meat Sci 2018; 139: 82–90.

12.

Yang

Zhuang

Yoon

et al.

Rapid classification of intact chicken breast fillets by predicting principal component score of quality traits with visible/near-infrared spectroscopy. Food Chem 2018; 244: 184.

13.

Premanandh

. Horse meat scandal – a wake-up call for regulatory authorities. Food Control 2013; 34: 568–569.

14.

Lin

. A review of traditional and novel detection techniques for melamine and its analogues in foods and animal feed. Front Chem Eng China 2009; 3: 427–435.

15.

Chu

Wang

et al.

Identifying camellia oil adulteration with selected vegetable oils by characteristic near-infrared spectral regions. J Innov Opt Heal Sci 2018; 11: 1850006.

16.

Zhao

Wang

et al.

Evaluation of Near-infrared hyperspectral imaging for detection of peanut and walnut powders in whole wheat flour. Appl Sci 2018; 8: 1076.

17.

Park

. A new horizon for hyperspectral imaging: macro- and micro-scale measurements for food safety. NIR News 2013; 24: 12–14.