[A dual-band algorithm to detect contaminants with low visibility on chicken carcass surface].

A novel dual-band algorithm for detecting contaminants with low visibility on chicken carcass surface based on hyperspectral image was proposed. Firstly, The 675 nm band image, in which the identity of the intensity within ROI (Region of Interest) is the best and the spectrum difference between ROI and the edge of the ROI is the biggest, was chosen from the hyperspectral data for binarization and the mask was extracted by using region growing on the biggest connected area. Then the "and" operation between the mask and the 400 nm band image with the largest discriminability of contaminants was carried out. The max ROI which can self adapt according to the position and shape of the chicken carcass was obtained. Finally, the labeling method was used to recognize if there are contaminations within the segmented ROI. The results showed that through the proposed method, the max ROIs which could self adapt to the position and shape of the chicken carcass were extracted and the average size of the ROI was bigger than 176% compared to that by existing methods. The average correct identification rate of contaminations such as blood, bile and feces was 81.6%.

Broiler stunned state detection based on an improved fast region-based convolutional neural network algorithm.

An improved fast region-based convolutional neural network (RCNN) algorithm is proposed to improve the accuracy and efficiency of recognizing broilers in a stunned state. The algorithm recognizes 3 stunned state conditions: insufficiently stunned, moderately stunned, and excessively stunned. Image samples of stunned broilers were collected from a slaughter line using an image acquisition platform. According to the format of PASCAL VOC (pattern analysis, statistical modeling, and computational learning visual object classes) dataset, a dataset for each broiler stunned state condition was obtained using an annotation tool to mark the chicken head and wing area in the original image. A rotation and flip data augmentation method was used to enhance the effectiveness of the datasets. Based on the principle of a residual network, a multi-layer residual module (MRM) was constructed to facilitate more detailed feature extraction. A model was then developed (entitled here Faster-RCNN+MRMnet) and used to detect broiler stunned state conditions. When applied to a reinforcing dataset containing 27,828 images of chickens in a stunned state, the identification accuracy of the model was 98.06%. This was significantly higher than both the established back propagation neural network model (90.11%) and another Faster-RCNN model (96.86%). The proposed algorithm can complete the inspection of the stunned state of more than 40,000 broilers per hour. The approach can be used for online inspection applications to increase efficiency, reduce labor and cost, and yield significant benefits for poultry processing plants.

Multiple headspace solid-phase microextraction after matrix modification for avoiding matrix effect in the determination of ethyl carbamate in bread.

This study presents the potential of multiple headspace solid-phase microextraction (multiple HS-SPME) for the quantification of analytes in solid samples. Multiple HS-SPME shares the same advantages as SPME. It also enables a complete recovery of the target compound and therefore the matrix effect, which commonly appears in SPME-based analysis, is avoided. A method based on multiple HS-SPME for the determination of the toxic contaminant ethyl carbamate (EC) in bread samples has been developed and validated, using gas chromatography with flame ionization detector. A novel polyethylene glycol/hydroxy-terminated silicone oil fiber was prepared for the first time and subsequently used instead of commercial ones because of its high extraction ability and good operational stability. An important problem still remained in multiple HS-SPME of EC in fresh bread samples. The adsorption of EC by water in the samples caused low transport of analyte to the headspace, which made multiple HS-SPME invalidated. Mixing with anhydrous sodium sulphate, the sensitivity of the method was improved and the problem was solved. The proposed method showed satisfactory linearity (0.15-1500 µg g(-1)), precision (1.6%, n=5) and limit of detection (0.041 µg g(-1)). Good recoveries, from 92.5 to 103.4%, were observed at three spiking levels. The method was applied to 14 bread samples. The multiple HS-SPME technique offers several advantages including reducing the manipulation time and cost, and avoiding analyte losses, especially in the analysis of a large number of samples in different matrices.

Multiple headspace solid-phase microextraction of ethyl carbamate from different alcoholic beverages employing drying agent based matrix modification.

Multiple headspace solid-phase microextraction (MHS-SPME) combined with gas chromatography-nitrogen phosphorus detector is proposed to determine the toxic contaminant ethyl carbamate (EC) in various alcoholic beverages after matrix modification. The remarkable feature of this method is that matrix effect, which commonly appears in SPME-based analysis, is avoided by determining the total amount of the analyte in the sample. To increase the sensitivity of the method, a novel polyethylene glycol/hydroxy-terminated silicone oil fiber was developed by sol-gel technique and applied for the analysis. Owing to the high polarity and hydrophilia of EC, an important problem still remains because the adsorption by sample matrix causes low transport of EC to the headspace and thus invalidates MHS-SPME for quantification. Mixing with anhydrous sodium sulphate, the sensitivity of the method can be improved. A Taguchi's L(16) (4(5)) orthogonal array design was employed to evaluate potentially significant factors and screen the optimum conditions for MHS-SPME of EC. Under the optimized conditions, limit of detection of 0.034 mg L(-1) was obtained. Relative standard deviation of replicate samples (n=6) was 2.19%. The proposed method was linear in the range of 0.04-100 mg L(-1), and the coefficient of determination was 0.9997. The method was used to determine EC in various alcoholic beverages. The concentrations obtained were compared with those obtained by standard addition method and no statistically significant differences were observed.

Development and application of an SPME/GC method for the determination of trace phthalates in beer using a calix[6]arene fiber.

A simple, low-cost and sensitive method for the determination of phthalate acid esters (PAEs) in beer has been developed based on solid-phase microextraction (SPME) followed by gas chromatography using a novel sol-gel calixarene-contained fiber. Generally speaking, matrix interference is one of the most important problems that researchers have to face when quantifying trace compounds in the complicated beer samples. In order to reproduce the influence of the matrix, synthetic beer solutions were popularly used, while they could not represent the real beer matrix absolutely. Owing to the good selectivity and high sensitivity of this new calixarene fiber, matrix interference from the beer samples was effectively avoided and low limits of detection (LODs) could be achieved. As a result, the SPME was performed in real beer matrices. Five experimental parameters including extraction temperature, extraction time, stirring speed, salt concentration and ultrasonic time were evaluated and optimized by means of a Taguchi's L25 (5(6)) orthogonal array experimental design. Under the optimized conditions, LODs of 0.003-3.429 microg L(-1) were obtained and the relative standard deviation values were < or =13.51% for all of the eight PAEs. The method was validated using standard addition methodology and recovery values were between 86.3% and 109.3%. The survey of three bottled beer samples showed that dibutyl-phthalate ester and bis(2-ethylhexyl)-phthalate ester (DEHP) were the main PAEs found in beer. The concentration of DEHP was as high as 5.24 microg L(-1). In order to investigate the source of phthalates contamination in beer, the composition of phthalates in the plasticized polyvinyl chloride (PVC) gaskets of the lids was analyzed. Results revealed that the high content of DEHP incorporated in PVC gaskets could be a potential source of PAEs in bottled beers during transportation and storage.