Non-destructive techniques for the detection of fungal infection in cereal grains

Orina, Irene; Manley, Marena; Williams, Paul J.

doi:10.1016/j.foodres.2017.07.069

Cited by 54 publications

(28 citation statements)

References 135 publications

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“…Multiplicative scatter correction (MSC); normalized; standard normal variate (SNV); Savitzky-Golay 1st order (SVG-1) and 2nd order derivatives (SVG-2; Crichton et al, 2017) Successive projections algorithm (SPA); regression coefficient (Caporaso, Whitworth, Grebby, et al, 2018) Genetic synergy interval partial least square (GA-Si-PLS) algorithm (Ling et al, 2017) Autoscale (Sun et al, 2017) Competitive adaptive reweighted sampling (Tian et al, 2018) Partial least squares discrimination analysis (PLS-DA; Sun et al, 2017) De-trending (Caporaso, Whitworth, Grebby, et al, 2018) Weighted values (Qu et al, 2017) Partial least square regression (PLSR; Cheng et al, 2018) Principal component analysis (PCA;Munera et al, 2017) Linear and quadratic discriminant analysis (LDA and QDA) ；support vector machine (SVM; Munera et al, 2017) Genetic synergy interval partial least square (GA-Si-PLS) algorithm (Ling et al, 2017) Artificial neural network (ANN) ；multi-layer perceptron (MLP) neural networks (Orina et al, 2017) Two-wavelength combination method (Xie et al, 2018) East squares-support vector regression (LS-SVR;…”

Section: Modeling Methodsmentioning

confidence: 99%

Application of hyperspectral technology in detection of agricultural products and food: A Review

Zhu

Huang

et al. 2020

Food Science & Nutrition

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China is the third largest country with land area in the world and is also a big agricultural country. Every year, the total amount of agricultural products is in the forefront of the world. Although the output of all kinds of food has increased, a problem that cannot be ignored has aroused people's attention, that is, food safety. In particular, major food safety incidents in recent years, such as "red heart" duck eggs, "melamine" incident, and "lean meat powder" pork, once made China's food industry into a state of decline. The whole industrial chain from primary agricultural products to commodity was greatly affected. These problems not only appear in China, but also in other countries of the world. For example in 2005, the food standard agency of the UK found that salmon sold in

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Section: Modeling Methodsmentioning

confidence: 99%

Application of hyperspectral technology in detection of agricultural products and food: A Review

Zhu

Huang

et al. 2020

Food Science & Nutrition

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“…In thermal imaging, the radiation pattern of an object is transformed into visible images (Vadivambal & Jayas, ). The temperature and emissivity of objects affected the level of released radiation (Orina, Manley, & Williams, ). Thermal imaging systems typically consists of a camera, an optical system (focusing lens, collimating lenses, and filters), a detector array, signal processing, and an image‐processing system (Gowen, Tiwari, Cullen, McDonnell, & O'Donnell, ).…”

Section: Noninvasive Techniquesmentioning

confidence: 99%

Noninvasive techniques for detection of foreign bodies in food: A review

Khairi

Ibrahim

Yunus

et al. 2018

J Food Process Engineering

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Foreign body in food is a matter of concern in food industry as it determines the safety and quality of the product. This issue leads to anxiety as it is hazardous if it is accidentally being consumed. Therefore, foreign body detection is urgently needed. Noninvasive techniques are attractive as they can be used to evaluate without altering the originality of the food products in terms of ingredient and structure. With the growing interest in this subject, this article reviews the development of noninvasive techniques including X‐ray, thermal imaging, near‐infrared spectroscopy, hyperspectral imaging, ultrasonic, and terahertz. The principle and application of each technique are elaborated. The performances and limitations from previous studies in several types of food applications are analyzed. In addition, future trends and challenges encountered with these techniques are highlighted. It is envisaged that the information gathered in this article will be a valuable source of information for researchers working in this topic. Practical applications The existence of foreign bodies in food causes degradation of their quality and safety. The implementation of the noninvasive technique as a monitoring tool have received an encouraging response from the manufacturers which endeavors to maintain their credibility and reputation. This review serves to provide an up‐to‐date development on the noninvasive technique for detecting foreign bodies which is useful for academicians and researchers especially from the food processing industries.

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“…The most widely used methods to monitor mycotoxins are chromatographic and immunological methods, or are based on biosensors [ 9 , 10 , 11 , 12 , 13 ]. Immunological methods, such as ELISA, can detect most of the mycotoxins, but they are mainly used for screening.…”

Section: Introductionmentioning

confidence: 99%

“…Despite those limitations, much research has focused on using infrared spectroscopy to monitor and analyze fusariotoxins. Mycotoxins are small molecules (MW = 700 Da) [ 10 , 13 ]. These toxins are found at very low concentrations, mostly parts per million (ppm), and are toxic at very low levels [ 13 ].…”

Section: Introductionmentioning

confidence: 99%

Updated Overview of Infrared Spectroscopy Methods for Detecting Mycotoxins on Cereals (Corn, Wheat, and Barley)

Levasseur-Garcia

2018

Toxins

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Each year, mycotoxins cause economic losses of several billion US dollars worldwide. Consequently, methods must be developed, for producers and cereal manufacturers, to detect these toxins and to comply with regulations. Chromatographic reference methods are time consuming and costly. Thus, alternative methods such as infrared spectroscopy are being increasingly developed to provide simple, rapid, and nondestructive methods to detect mycotoxins. This article reviews research conducted over the last eight years into the use of near-infrared and mid-infrared spectroscopy to monitor mycotoxins in corn, wheat, and barley. More specifically, we focus on the Fusarium species and on the main fusariotoxins of deoxynivalenol, zearalenone, and fumonisin B1 and B2. Quantification models are insufficiently precise to satisfy the legal requirements. Sorting models with cutoff levels are the most promising applications.Keywords: NIR; MIR; mycotoxins; Fusarium; infrared spectroscopy Key Contribution: We have updated a review of the literature dealing with infrared spectroscopy and the detection of fusariotoxins in corn, wheat, and barley. The use of infrared spectroscopic tools to detect and quantify mycotoxins does not provide the requisite regulatory precision, nevertheless, these tools can be used for sorting cereals, be they in or out of risk groups.

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Non-destructive techniques for the detection of fungal infection in cereal grains

Cited by 54 publications

References 135 publications

Application of hyperspectral technology in detection of agricultural products and food: A Review

Application of hyperspectral technology in detection of agricultural products and food: A Review

Noninvasive techniques for detection of foreign bodies in food: A review

Updated Overview of Infrared Spectroscopy Methods for Detecting Mycotoxins on Cereals (Corn, Wheat, and Barley)

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