Detection of Fecal Residue on Poultry Carcasses by Laser-Induced Fluorescence Imaging

Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review

Fluorescence spectroscopy, color imaging and multispectral imaging (MSI) have emerged as effective analytical methods for the non-destructive detection of quality attributes of various white meat products such as fish, shrimp, chicken, duck and goose. Based on machine learning and convolutional neural network, these techniques can not only be used to determine the freshness and category of white meat through imaging and analysis, but can also be used to detect various harmful substances in meat products to prevent stale and spoiled meat from entering the market and causing harm to consumer health and even the ecosystem. The development of quality inspection systems based on such techniques to measure and classify white meat quality parameters will help improve the productivity and economic efficiency of the meat industry, as well as the health of consumers. Herein, a comprehensive review and discussion of the literature on fluorescence spectroscopy, color imaging and MSI is presented. The principles of these three techniques, the quality analysis models selected and the research results of non-destructive determinations of white meat quality over the last decade or so are analyzed and summarized. The review is conducted in this highly practical research field in order to provide information for future research directions. The conclusions detail how these efficient and convenient imaging and analytical techniques can be used for non-destructive quality evaluation of white meat in the laboratory and in industry.

Multispectral Fluorescence Imaging Technique for On-Line Inspection of Fecal Residues on Poultry Carcasses

Rapid and reliable inspection of food is essential to ensure food safety, particularly in mass production and processing environments. Many studies have focused on spectral imaging for poultry inspection; however, no research has explored the use of multispectral fluorescence imaging (MFI) for on-line poultry inspection. In this study, the feasibility of MFI for on-line detection of fecal matter from the ceca, colon, duodenum, and small intestine of poultry carcasses was investigated for the first time. A multispectral line-scan fluorescence imaging system was integrated with a commercial poultry conveying system, and the images of chicken carcasses with fecal contaminants were scanned at processing line speeds of one, three, and five birds per second. To develop an optimal detection and classification algorithm to distinguish upper and lower feces-contaminated parts from skin, the principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) were first performed using the spectral data of the selected regions, and then applied in spatial domain to visualize the feces-contaminated area based on binary images. Our results demonstrated that for the spectral data analysis, both the PCA and PLS-DA can distinguish the high and low feces-contaminated area from normal skin; however, the PCA analysis based on selected band ratio images (F630 nm/F600 nm) exhibited better visualization and discrimination of feces-contaminated area, compared with the PLS-DA-based developed chemical images. A color image analysis using histogram equalization, sharpening, median filter, and threshold value (1) demonstrated 78% accuracy. Thus, the MFI system can be developed utilizing the two band ratios for on-line implementation for the effective detection of fecal contamination on chicken carcasses.

Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review

With improvement in people's living standards, many people nowadays pay more attention to quality and safety of meat. However, traditional methods for meat quality and safety detection and evaluation, such as manual inspection, mechanical methods, and chemical methods, are tedious, time-consuming, and destructive, which cannot meet the requirements of modern meat industry. Therefore, seeking out rapid, non-destructive, and accurate inspection techniques is important for the meat industry. In recent years, a number of novel and noninvasive imaging techniques, such as optical imaging, ultrasound imaging, tomographic imaging, thermal imaging, and odor imaging, have emerged and shown great potential in quality and safety assessment. In this paper, a detailed overview of advanced applications of these emerging imaging techniques for quality and safety assessment of different types of meat (pork, beef, lamb, chicken, and fish) is presented. In addition, advantages and disadvantages of each imaging technique are also summarized. Finally, future trends for these emerging imaging techniques are discussed, including integration of multiple imaging techniques, cost reduction, and developing powerful image-processing algorithms.

Optimal fluorescence waveband determination for detecting defective cherry tomatoes using a fluorescence excitation-emission matrix

A multi-spectral fluorescence imaging technique was used to detect defective cherry tomatoes. The fluorescence excitation and emission matrix was used to measure for defects, sound surface and stem areas to determine the optimal fluorescence excitation and emission wavelengths for discrimination. Two-way ANOVA revealed the optimal excitation wavelength for detecting defect areas was 410 nm. Principal component analysis (PCA) was applied to the fluorescence emission spectra of all regions at 410 nm excitation to determine the emission wavelengths for defect detection. The major emission wavelengths were 688 nm and 506 nm for the detection. Fluorescence images combined with the determined emission wavebands demonstrated the feasibility of detecting defective cherry tomatoes with >98% accuracy. Multi-spectral fluorescence imaging has potential utility in non-destructive quality sorting of cherry tomatoes.

The development of chlorophyll-based markers in poultry diets to aid detection of fluorescent fecal contamination

Incidents of foodborne illness associated with consuming undercooked or raw chicken are often linked to 2 causative pathogens: Campylobacter spp. or Salmonella spp. Numerous studies have shown that contamination of carcasses results when pathogens are transferred from the intestinal tract or fecal material on feet and feathers to the dressed carcass. Ultraviolet spectral imaging to detect surface fecal and ingesta contamination on poultry carcasses may provide a solution to aid detection. However, poultry diets do not provide sufficiently high levels of natural fluorophores for this system to be reliable. This study investigated the potential of chlorophyll-based feed additives to improve fluorescence of the feces and narrow the excitation and emission wavelengths to aid in the development of a simple visualization system. Twenty-four hens (Gallus gallus domesticus) were allocated at random to 1 of 4 treatments: control (C, no marker), Zn chlorophyllin, Mg chlorophyllin, or Fe chlorophyllin. All markers were incorporated into mash before pelleting at a rate of 1 g/kg of DM. The experiment consisted of two 4 × 4 Latin squares with each period consisting of 2 wk. Feces were collected and extracted in acetone:water (50:50; vol/vol) with fecal fluorescence emission spectra determined using a Jasco FP-6200 Spectrofluorometer with excitation at 382 nm. A main peak evolved at wavelength 670 nm with the total area under the peak used as fluorescence intensity. Following 7 d of marker supplementation, the 3 markers improved the fluorescence intensity by ×14.8, 12.8, and 6.9 for Fe, Mg, and Zn chlorophyllin, respectively, compared with the control. The addition of feces containing Mg chlorophyllin to chicken carcass increased detection of the feces compared with feces with no marker. Also, due to the plain background of chicken skin, a simple image at 675 nm with appropriate thresholds would allow detection of contaminated carcasses at the current slaughter line speed without the need of expensive hyperspectral imaging.

Quality and safety assessment of food and agricultural products by hyperspectral fluorescence imaging

Hyperspectral fluorescence imaging (HSFI) is potentially useful for assessing food and agricultural products, because it combines the merits of both hyperspectral imaging and fluorescence spectroscopy. This paper provides an introduction to HSFI: the principle and components of HSFI, calibration and image processing are described. In addition, recent advances in the application of HSFI to food and agricultural product assessment are reviewed, such as contaminant detection, constituent analysis and quality evaluation. Finally, current limitations and likely future development trends are discussed.