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...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.展开更多
A kind of lead-free dielectric materials,such as the bismuth layered perovskite-type structure of Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04),was prepared by the conventional solid-state method at 800C and sintered at...A kind of lead-free dielectric materials,such as the bismuth layered perovskite-type structure of Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04),was prepared by the conventional solid-state method at 800C and sintered at 1100C.The variation of structure and electrical properties with different Bi concentration was studied.All the Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04)samples exhibited a single structured phase.SEM could be a better approach to present the microstructure of Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04)ceramics.It could be found that the grain size of Bi4.02Ti3O12.03 sintered at 1100C was smaller than that of others among the five samples through grain size mechanics.Through impedance spectra analysis,we knew,when the Bi content was fixed,that the dielectric constant and the loss values increased with the decrease of frequency.The Curie temperature of the five samples was about 670C.In particular,while at the frequency of 100 kHz,the lowest loss was 0.001 when Bi content was 3.98.The Bi4.02Ti3O12.03 ceramics with the minimum grain size had highest dielectric constant and the relatively low loss.Due to its high Curie temperature,high permittivity and low loss,the Bi_(4)Ti_(3)O_(12)(BIT)ceramics have a broad application prospect in high density memory,generator,sensor,ferroelectric tunnel junctions and so on.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.31501228)the Yangling Demonstration Zone Science and Technology Plan Project(Grant No.2016NY-31).
文摘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.
基金funding provided by the National Natural Science Foundation of China(Grant No.51202063).
文摘A kind of lead-free dielectric materials,such as the bismuth layered perovskite-type structure of Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04),was prepared by the conventional solid-state method at 800C and sintered at 1100C.The variation of structure and electrical properties with different Bi concentration was studied.All the Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04)samples exhibited a single structured phase.SEM could be a better approach to present the microstructure of Bi4-xTi3O12-1.5x(x=0.04,0.02,0,-0.02,-0.04)ceramics.It could be found that the grain size of Bi4.02Ti3O12.03 sintered at 1100C was smaller than that of others among the five samples through grain size mechanics.Through impedance spectra analysis,we knew,when the Bi content was fixed,that the dielectric constant and the loss values increased with the decrease of frequency.The Curie temperature of the five samples was about 670C.In particular,while at the frequency of 100 kHz,the lowest loss was 0.001 when Bi content was 3.98.The Bi4.02Ti3O12.03 ceramics with the minimum grain size had highest dielectric constant and the relatively low loss.Due to its high Curie temperature,high permittivity and low loss,the Bi_(4)Ti_(3)O_(12)(BIT)ceramics have a broad application prospect in high density memory,generator,sensor,ferroelectric tunnel junctions and so on.
