Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts

Cereal grains and nuts are represented as the economic backbone of many developed and developing countries. Kernels of cereal grains and nuts are prone to mold infection under high relative humidity and suitable temperature conditions in the field as well as storage conditions. Health risks caused by molds and their molecular metabolite mycotoxins are, therefore, important topics to investigate. Strict regulations have been developed by international trade regulatory bodies for the detection of mold growth and mycotoxin contamination across the food chain starting from the harvest to storage and consumption. Molds and aflatoxins are not evenly distributed over the bulk of grains, thus appropriate sampling for detection and quantification is crucial. Existing reference methods for mold and mycotoxin detection are destructive in nature as well as involve skilled labor and hazardous chemicals. Also, these methods cannot be used for inline sorting of the infected kernels. Thus, analytical methods have been extensively researched to develop the one that is more practical to be used in commercial detection and sorting processes. Among various analytical techniques, optical imaging and spectroscopic techniques are attracting growers' attention for their potential of nondestructive and rapid inline identification and quantification of molds and mycotoxins in various food products. This review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging. Advance chemometric techniques to identify very low-level mold growth and mycotoxin contamination are also discussed. Benefits, limitations, and challenges of deploying these techniques in practice are also presented in this paper.

Detecting Biothreat Agents: From Current Diagnostics to Developing Sensor Technologies

Although a fundamental understanding of the pathogenicity of most biothreat agents has been elucidated and available treatments have increased substantially over the past decades, they still represent a significant public health threat in this age of (bio)terrorism, indiscriminate warfare, pollution, climate change, unchecked population growth, and globalization. The key step to almost all prevention, protection, prophylaxis, post-exposure treatment, and mitigation of any bioagent is early detection. Here, we review available methods for detecting bioagents including pathogenic bacteria and viruses along with their toxins. An introduction placing this subject in the historical context of previous naturally occurring outbreaks and efforts to weaponize selected agents is first provided along with definitions and relevant considerations. An overview of the detection technologies that find use in this endeavor along with how they provide data or transduce signal within a sensing configuration follows. Current "gold" standards for biothreat detection/diagnostics along with a listing of relevant FDA approved in vitro diagnostic devices is then discussed to provide an overview of the current state of the art. Given the 2014 outbreak of Ebola virus in Western Africa and the recent 2016 spread of Zika virus in the Americas, discussion of what constitutes a public health emergency and how new in vitro diagnostic devices are authorized for emergency use in the U.S. are also included. The majority of the Review is then subdivided around the sensing of bacterial, viral, and toxin biothreats with each including an overview of the major agents in that class, a detailed cross-section of different sensing methods in development based on assay format or analytical technique, and some discussion of related microfluidic lab-on-a-chip/point-of-care devices. Finally, an outlook is given on how this field will develop from the perspective of the biosensing technology itself and the new emerging threats they may face.

Fluorescence hyperspectral imaging technique for foreign substance detection on fresh-cut lettuce

BACKGROUND

Non-destructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed to detect worms on fresh-cut lettuce. The optimal wavebands for detecting the worms were investigated using the one-way ANOVA and correlation analyses.

RESULTS

The worm detection imaging algorithms, RSI-I(492-626)/492 , provided a prediction accuracy of 99.0%. The fluorescence HSI techniques indicated that the spectral images with a pixel size of 1 × 1 mm had the best classification accuracy for worms.

CONCLUSION

The overall results demonstrate that fluorescence HSI techniques have the potential to detect worms on fresh-cut lettuce. In the future, we will focus on developing a multi-spectral imaging system to detect foreign substances such as worms, slugs and earthworms on fresh-cut lettuce. © 2017 Society of Chemical Industry.