Detection of Residual Yarn in Bobbin Based on Odd Partial Gabor Filter and Multi-Color Space Hierarchical Clustering

In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.

Detection of Atrazine Residue in Food Samples by a Monoclonal Antibody-based Enzyme-linked Immunosorbent Assay

Atrazine（AT,2-chloro-4-ethylamino-6-isopropyl-amino-s-triazine）has been detected in ground water in several areas of the United States for many years,as well as in China,wherein the growth rate of its gross

Determination of Residual Enrofloxacin in Fish Tissues by Terbium Ion-sensitized Fluorophotometry

In order to establish a new method for the determination of enrofloxacin, on the basis of the fluorescence characteristic of terbium-enrofloxacin complex, it was found that in a HAc-NaAc buffer solution with a pH value at 6.0, the terbiumenrofloxacin complex had a characteristic fluorescence peak of Tb3＋ at 545 nm （λex= 328 nm）, which could be used for the determination of enrofloxacin. A simple, rapid and sensitive fluorescence method for the determination of enrofloxacin was thus established, and an optimal reaction condition was selected. Under the optimal reaction condition, there was a good linear relation （r2=0.992 3） between concentration of enrofloxacin in the range of 1.0×10^-1.0×10^-6 g/ml and its fluorescence intensity at 545 nm, with a detection limit of 1.3×10^-9 g/ml; the recovery for enrofloxacin in tablets was 97.7% with a variation coefficient of 1.4%; and for enrofloxacin in fish tissues, the recovery was 79.0%-94.5% with a variation coefficient of 2.0%-7.8%.

Residual current compensation for single-phase grounding fault in coal mine power network

The way of neutral point to earth via full compensation arc suppression coil can solve the problem of residual current compensation in coal mine power network effectively. Based on the analysis on the grounding current detection results of Xieqiao coal mine, the conclusion that harmonic component of grounding current is dominated by higher harmonics with complex harmonic sources in coal mine power network system was obtained. The influences of harmonic source type and fault point position on harmonic voltage and harmonic current were analyzed theoretically. The influences of earthed fault feeder detection result and the estimation errors of parameters to earth on residual current compensation were analyzed. A new thought of residual current prediction and the selections of model method and control method were proposed on this basis. The simulation results prove that harmonic amplitudes of zero sequence voltage and zero sequence current are determined by harmonic source type as well as fault point position in coal mine power network, and also prove that zero sequence voltage detection can avoid the unstable problem of coal mine power network system caused by undercompensation of capacitive current. Finally, the experimental device of full compensation arc suppression coil is introduced.

A Device for Rapid Detection of Dithiocarbamate Pesticide Residues in Fruits

Based on the chemical properties of dithiocarbamate pesticides,a device for rapid detection was developed in the paper,and the experimental conditions were optimized. Dithiocarbamate residues in fruits were successfully detected using molecular absorption spectro-photometry,and the recovery rate was over 80%.The rapid detection method was simple to operate with low cost,and was conducive to application in basic level and enterprise laboratories.

Study on ELISA for detection of sulfamethazine residues

In this study, various factors of ELISA for detection of sulfamethazine residues were explored, the coating antigen was diluted to 1：400, the best coating condition was at 4℃ overnight, the working concentration of HRP-IgG enzyme conjugate was 1 ： 7 000. The pre-incubation time and incubation time was 30 min and 120 min, respectively, the substrate solution working time was 20 min. Two moL · L^-1 H2SO4 was used to stop the reaction and checked. A standard curve of direct competitive ELISA had been established to detect the sulfamethazine residues in milk. The detection limit of this method was 1.97 ng · mL^-1. The mean concentration of sulfamethazine required to inhibit 30% antibody was 7.1 ng · mL^-1. The linear range of the detection was 5-200 ng · mL^-1. The recovery ratio was between 73.20% and 91.16%. The CV% of within array and between arrays was less than 10%.

Highly selective NIR fluorescent probe for acetylcholinesterase and its application in pesticide residues detection

A series of near-infrared(NIR)fluorescent substrates(NDRO-1∼8)derived from fluorophore NDRH with different volumes of ester bond as the recognition group were designed and synthesized for the detection of acetylcholinesterase(AChE),among which NDRO-1 with the smallest acetate group displayed the highest activity toward AChE.The detection limit of NDRO-1 for sensing AChE was 0.32μg/mL,and K_(m )was 6.40μmol/L,indicating ultra-sensitivity and good affinity of NDRO-1 toward AChE.NDRO-1 was used to detect the inhibitory of four kinds of pesticides including methamidophos,dichlorvos,and the detection limit was lower than 50μg/L,which was further used in pesticide residues detection.

Immobilization of acetylcholinesterase on functionalized SBA-15 mesoporous molecular sieve for detection of organophosphorus and carbamate pesticide

The immobilization of acetylcholinesterase （ACHE） on amino functionalized SBA-15 mesoporous sieves （NH2-SBA-15） was explored for detection of organophosphorus and carhamate pesticides. Several methods have been studied and the ＂adsorption-crosslinking＂ is found to be the best one. Firstly, AChE and bovine serum albumin （BSA） were adsorbed in turn on the surface of NH2-SBA-15 by electrostatic adsorption, and then glutaraldehyde was added for cross-linking the amino group of AChE. The NH2-SBA- 15 showed around 95% immobilization efficiency and the specific activity of immobilized AChE （ACHE- NH2-SBA-15） reached 130% relative to free AChE under optimal immobilization conditions. It was found AChE-NH2-SBA-15 retained 94.0% and 82.8% of its initial activity after 60days at 4℃ and 25℃, respectively. It remained 55.0% of its initial activity after 6 times recycling. During the detection of pesticide, the AChE-NH2-SBA-15 showed wider linear range and much lower limit of detection compared with free ACHE. The current method showed good recovery （93.8%-109.3%） and low RSD （〈5%） for both standard solution and real vegetable samples of Carbaryl and Trichlorfon. It was believed that AChE-NH2- SBA- 15 could be exploited as a fast, sensitive and low-cost biocatalyst towards the detection of pesticides residues which could be stored at room temperature for a long time.

Fusion of machine vision technology and AlexNet-CNNs deep learning network for the detection of postharvest apple pesticide residues

Pesticide residue is an important factor that affects food safety.In order to achieve effective detection of pesticide residues in apples,a machine-vision-based segmentation algorithm and hyperspectral techniques were used to segment the foreground and background regions of the apple image.By calculating the roundness value and extracting the region with the highest roundness value in the connected region,a region of interest(ROI)maskwas created for the apple.Four pesticides(chlorpyrifos,carbendazimand two mixed pesticides)and an inactive control were used at the same concentration of 100 ppm(except for the control group),and the hyperspectral region of the corresponding sample image was extracted by obtaining the different types of pesticide residues in the ROI masks.To increase the diversity of the samples and to expand the dataset,Gaussianwhite noise with a varying signal-to-noise ratio was added to each of the hyperspectral images of the apple.The number of samples was increased from four types of 12 samples to four types of 72 samples,giving 4608 hyperspectral data images in each category.The structure and parameters of a convolutional neural network(CNN)were determined using theoretical analysis and experimental verification.All the extracted hyperspectral images of apples were normalized to 227×227×3 pixels as the input of the CNN network for pesticide residue detection.There were 18,432 sample data of four types for 72 samples.Of these,12,288 images were selected using a bootstrap sampling method as the training set,and 6144 as the test set,with no overlap.The test results showthatwhen the number of training epochswas 10,the accuracy of the test set detectionwas 99.09%,and the detection accuracy of the single-band average imagewas 95.35%.A comparison with traditional k-nearest neighbor(KNN)and support vectormachine classification algorithms showed that the detection accuracy for KNNwas 43.75%and the average time was 0.7645 s.These results demonstrate that our method is a small-sample,noncontact,fast,effective and low-cost technique that can provide effective pesticide residue detection in postharvest apples.