检索结果-南通市图书馆

Journal of Integrative Agriculture 2024年第1期23卷 298-309页

作者： Phiraiwan Jermwongruttanachai Siwalak Pathaveerat Sirinad Noypitak Department of Agricultural Engineering Faculty of Engineering at Kamphaeng SaenKasetsart UniversityKamphaeng Saen CampusNakhon Pathom 73140Thailand

The adulteration concentration of palm kernel oil(PKO)in virgin coconut oil(VCO)was quantified using near-infrared(NIR)hyperspectral ***,some VCO is adulterated with lower-priced PKO to reduce production costs,which diminishes the quality of the *** study used NIR hyperspectral imaging in the wavelength region 900-1,650 nm to create a quantitative model for the detection of PKO contaminants(0-100%)in VCO and to develop predictive *** prediction equation for the adulteration of VCO with PKO was constructed using the partial least squares regression *** best predictive model was pre-processed using the standard normal variate method,and the coefficient of determination of prediction was 0.991,the root mean square error of prediction was 2.93%,and the residual prediction deviation was *** results showed that this model could be applied for quantifying the adulteration concentration of PKO in *** prediction adulteration concentration mapping of VCO with PKO was created from a calibration model that showed the color level according to the adulteration concentration in the range of 0-100%.NIR hyperspectral imaging could be clearly used to quantify the adulteration of VCO with a color level map that provides a quick,accurate,and non-destructive detection method.

关键词： virgin coconut oil adulteration contamination palm kernel oil hyperspectral imaging

Research on the detection of early caries based on hyperspectral imaging

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Journal of Innovative Optical Health Sciences 2023年第3期16卷 101-112页

作者： Cheng Wang Haoying Zhang Guangyun Lai Songzhu Hu Jun Wang Dawei Zhang Institute of Biomedical Optics and Optometry Key Laboratory of Medical Optical Technology and Instruments Ministry of Education University of Shanghai for Science&Technology 200093P.R.China Department of Paediatric Dentistry Ninth People's Hospital Shanghai Jiaotong University200011P.R.China Equipment Department Nantong Hospital of Traditional Chinese Medicine 226007 P.R.China Engineering Research Centre for Optical Instruments and Systems Ministry of Education Shanghai Key Laboratory of Modern Optical SystemsUniversity of Shanghai for Science&Technology200093P.R.China

Objective:We applied hyperspectral imaging(HSI)system to distinguish early caries from soundand pigmented *** will provide a theoretical basis and technical support,for research anddevelopment of an instrument that could be used for screening and detection of early ***:Eighteen extracted human teeth(molars and premolars),with varying degrees ofnatural pathology and no degree of decay involving dentin were *** system with awavelength range from 400 to 1000nm was used to obtain images of all 18 teeth containingsound,carious and pigmented *** compared the spectra of the wavebands at both 500 nmand 780 nm from the different tooth states,and the reflectance diference bet ween sound versuscarious lesions and sound versus pigmented areas,***:There was a slight diference in refectance bet ween carious areas and pigmented areas at500 nm.A substantial difference was additionally noted in refectance bet ween carious areas andpigmented areas at 780 ***:The results have shown that the interference of tooth surface pigment can be elim-inated in the near-infrared(NIR)waveband,and the caries can be effectively identifed from the pigmented ***,it could be used to detect carious areas of teeth in place of the traditionalvisual inspection method or white light *** significance:The NIR difused light signal enables the identification of early caries frompigment and other interference,providing a reasonable detection tool for early detection andearly treatment of teeth diseases.

关键词： hyperspectral imaging near-infrared light early dental caries spectral reflectance

Single stain hyperspectral imaging for accurate fungal pathogens identification and quantification

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2022年第7期15卷 6399-6406页

作者： Yongqiang Zhang Kunxing Liu Jingkun Yu Haifeng Chen Rui Fu Siqi Zhu Zhenqiang Chen Shuangpeng Wang Siyu Lu Green Catalysis Center and College of ChemistryZhengzhou UniversityZhengzhou 450001China Department of Optoelectronic Engineering Jinan UniversityGuangzhou 510632China Institute of Applied Physics and Materials Engineering University of MacaoTaipaMacao 999078China School of electronic information and electrical engineering Chongqing University of Arts and SciencesChongqing 402160China

The most widely used method of identification of microbial morphology and structure is microscopy,but it can be difficult to distinguish between pathogens with a similar *** fluorescent staining methods require a combination of a variety of fluorescent materials to meet this *** this study,unique concentration-dependent fluorescent carbon dots(CDs)were synthesized for the identification and quantification of *** emission wavelength of the CDs could be tuned spanning the full visible region by virtue of aggregation-induced narrowing of *** tunable emission wavelength of the specific concentration response to diverse microbes can be used to distinguish microorganisms with a similar appearance,even in a same genus.A hyperspectral microscopy system was demonstrated to distinguish Aspergillus flavus and *** based on the results *** identification accuracy of the two similar-looking pathogens can be close to 100%,and the relative proportions and spatial distributions can also be profiled from the mixture of the *** technique can provide a solution to the fast detection of microorganisms and is potentially applicable to a wide range of problems in areas such as healthcare,food preparation,biotechnology,and health emergency.

关键词： carbon dots concentration-dependent wavelength-tunable hyperspectral imaging pathogens rapid detection machinelearning

Detection of skin defects on loquat using hyperspectral imaging combining both band radio and improved three-phase level set segmentation method

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Food Quality and Safety 2023年第1期7卷 100-111页

作者： Zhaoyang Han Bin Li Qiu Wang Zhaoxiang Sun Yande Liu School of Mechatronics&Vehicle Engineering East China Jiaotong UniversityNational and Local Joint Engineering Research Center of Fruit Intelligent Photoelectric Detection Technology and EquipmentNanchangChina

Background and objectives Skin defects are one of the primary problems that occur in post-harvest grading and processing of *** defects lead to the loquat being easily destroyed during transportation and storage,which causes the risk of other loquats being infected,affecting the selling *** and Methods In this paper,a method combining band radio image with an improved three-phase level set segmentation algorithm(ITPLSSM)is proposed to achieve high accuracy,rapid,and non-destructive detection of skin defects of *** component analysis(PCA)was used to find the characteristic wavelength and PC images to distinguish four types of skin *** best band ratio image based on characteristic wavelength was *** The band ratio image(Q782/944)based on PC2 image is the best segmented *** on pseudo-color image enhancement,morphological processing,and local clustering criteria,the band ratio image(Q782/944)has better contrast between defective and normal areas in ***,the ITPLSSM was used to segment the processing band ratio image(Q782/944),with an accuracy of 95.28%.Conclusions The proposed ITPLSSM method is effective in distinguishing four types of skin ***,it also effectively segments images with intensity inhomogeneities.

关键词： Loquat skin defects hyperspectral imaging multispectral images band ratio improved three-phase level set segmentation.

Predicting the true density of commercial biomass pellets using near-infrared hyperspectral imaging

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Artificial Intelligence in Agriculture 2022年第1期6卷 266-275页

作者： Lakkana Pitak Khwantri Saengprachatanarug Kittipong Laloon Jetsada Posom Department of Agricultural Engineering Faculty of EngineeringKhon Kaen UniversityKhon Kaen 40002Thailand Center for Alternative Energy Research and Development Khon Kaen UniversityThailand

The use of biomass is increasing because it is a form of renewable energy that provides high heating *** measurements could be used to check the quality of biomass pellets during *** research aims to apply a near-infrared(NIR)hyperspectral imaging system for the evaluation of the true density of individual biomass pellets during the production ***-time measurement of the true density could be beneficial for the operation settings,such as the ratio of the binding agent to the raw material,the temperature of operation,the production rate,and the mixing *** true density could also be used for rough measurement of the bulk density,which is a necessary parameter in commercial ***,knowledge of the true density is required during production in order to maintain the pellet quality as well as operation conditions.A prediction model was developed using partial least squares(PLS)regression across different wavelengths selected using different spectral pre-treatment methods and variable selection *** model development,the performance of the models was *** best model for predicting the true density of individual pellets was developed with first-derivative spectra(D1)and variables selected by the genetic algorithm(GA)method,and the number of variables was reduced from 256 to 53 *** model gave R_(cal)^(2),R_(val)^(2),SEC,SEP,and RPD values of 0.88,0.89,0.08 g/cm^(3),0.07 g/cm^(3),and 3.04,*** optimal prediction model was applied to construct distribution maps of the true density of individual biomass pellets,with the level of the predicted values displayed in colour *** imaging technique could be used to check visually the true density of biomass pellets during the production process for warnings to quality control equipment.

关键词： True density hyperspectral imaging Biomass pellet Variable selection method

Differentiation of Wheat Diseases and Pests Based on hyperspectral imaging Technology with a Few Specific Bands

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Phyton-International Journal of Experimental Botany 2023年第2期92卷 611-628页

作者： Lin Yuan Jingcheng Zhang Quan Deng Yingying Dong Haolin Wang Xiankun Du School of Information Engineering Zhejiang University of Water Resources and Electric PowerHangzhou310018China School of Automation Hangzhou Dianzi UniversityHangzhou310018China Aerospace Information Research Institute Chinese Academy of SciencesBeijing100094China

hyperspectral imaging technique is known as a promising non-destructive way for detecting plants diseases and *** most previous studies,the utilization of the whole spectrum or a large number of bands as well as the complexity of model structure severely hampers the application of the technique in *** a detection system can be established with a few bands and a relatively simple logic,it would be of great significance for *** study established a method for identifying and discriminating three commonly occurring diseases and pests of wheat,i.e.,powdery mildew,yellow rust and aphid with a few specific *** a comprehensive spectral analysis,only three bands at 570,680 and 750 nm were selected.A novel vegetation index namely Ratio Triangular Vegetation Index(RTVI)was developed for detecting anomalous areas on ***,the Support Vector Machine(SVM)method was applied to construct the discrimination model based on the spectral ratio *** validating results suggested that the proposed method with only three spectral bands achieved a promising accuracy with the Overall Accuracy(OA)of 83%.With three bands from the hyperspectral imaging data,the three wheat diseases and pests were successfully detected and discriminated.A stepwise strategy including background removal,damage lesions recognition and stresses discrimination was *** present work can provide a basis for the design of low cost and smart instruments for disease and pest detection.

关键词： Winter wheat diseases pests hyperspectral imaging discriminant analysis

Identification of Early Peach Aphid Infestation Based on hyperspectral imaging Technology

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Beijing Institute of Technology 2023年第3期32卷 374-383页

作者： Yangyang Fan Wenjie Feng Zhengjun Qiu Shuai Wang Institute of Agricultural Information and Economics Shandong Academy of Agricultural SciencesJinan 250000China College of Biosystems Engineering and Food Science Zhejiang UniversityHangzhou 310000China

Peach aphid is a common pest and hard to *** study employs hyperspectral imaging technology to identify early damage in green cabbage caused by peach *** principal component transformation and multiple linear regression analysis,the correlation relation between spectral characteristics and infestation stage is ***,four characteristic wavelength selection methods are compared and optimal characteristic wavelengths subset is determined to be input for *** linear algorithm and two nonlinear modelling algorithms are ***,support vector machine(SVM)model based on the characteristic wavelengths selected by multi-cluster feature selection(MCFS)acquires the highest identification accuracy,which is 98.97%.These results indicate that hyperspectral imaging technology have the ability to identify early peach aphid infestation stages on green cabbages.

关键词： peach aphid hyperspectral imaging machine learning green cabbage

hyperspectral imaging and remote trace detection of cis-1,3,4,6-tetranitrooctahydroimidazo-[4,5 d]imidazole(BCHMX)compared with traditional explosives using laser induced fluorescence

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Defence Technology（防务技术） 2021年第5期17卷 1609-1616页

作者： Hany S.Ayoub Ashraf F.El-Sherif Ahmed Elbeih Department of Physics Faculty of ScienceCairo UniversityEgypt Laser Photonics Research Center Engineering Physics DepartmentMilitary Technical CollegeCairoEgypt Explosives Department Military Technical CollegeKobry ElkobbahCairoEgypt

cis-1,3,4,6-Tetranitrooctahydroimidazo-[4,5 d]imidazole(BCHMX)is an advanced energetic compound that expected to spread worldwide in the near ***,no approved remote detection methods were reported in current literature for this material,we performed hyper-spectral imaging and laser induced fluorescence(LIF)to a BCHMX sample under low laser fluence for determining the optimum laser wavelength used in any future BCHMX-LIF based remote detection *** this purpose,an experimental setup consisted of a sun spectrum lamp and hyper-spectral camera was built to illuminate and image white powder samples of BCHMX in comparison with the traditional explosives,HMX(1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane),RDX(1,3,5-trinitro-1,3,5-triazacyclohexane),PETN(2,2-Bis[(nitroxy)methyl]propane-1,3-diyldinitrate).The imaging reveals strong BCHMX sample absorption contrast among other samples at wavelength ranging from 400 to 410 *** light source was replaced by a 405 nm laser diode illuminator,a strong BCHMX sample LIF at the spectral range from 425 to 700 nm was observed under low laser fluence condition of 0.1 mJ/cm^(2).Finally,we demonstrated successfully the ability of the 405 nm LIF and the hyperspectral imaging technique to detect finger print traces of BCHMX on white cellulose fabric from a distance of 15 m and a detection limit of 1 mg/cm^(2).

关键词： hyperspectral imaging Remote trace detection BCHMX Laser induced fluorescence

Prediction of nitrogen and phosphorus contents in citrus leaves based on hyperspectral imaging

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

International Journal of Agricultural and Biological Engineering 2015年第2期8卷 80-88页

作者： Liu Yanli Lyu Qiang He Shaolan Yi Shilai Liu Xuefeng Xie Rangjin Zheng Yongqiang Deng Lie College of Horticulture and Landscape Southwest UniversityBeibeiChongqing 400715China Citrus Research Institute Southwest University-Chinese Academy of Agricultural SciencesBeibeiChongqing 400712China

The nutritional status of citrus leaves is very important to the determining of fertilization *** spectrum technique is a quick,un-injured method and is becoming widely used for plant nutrient *** possibility and method of using spectrum technique to estimate the nutrient of citrus leaf was explored in this study.A total amount of 135 leaves from the mature spring shoots of navel orange trees(*** Osbeck,“Newhall”)were collected and randomly grouped into two sets of samples:100 leaves for the calibration set and 35 leaves for the prediction *** hyperspectral images were scanned upper and lower side of each leaf and then the total nitrogen(N)and phosphorus(P)contents of each leaf were *** raw spectra data were extracted to generate average spectra curves,preprocessed with five different methods,and was used to build N and P content prediction *** performances of the five preprocessing methods,i.e.,Savitzky-Golay smoothing(SGS),standard normal variate(SNV),multiplicative scatter correction(MSC),first-derivative(1-Der)and second-derivative(2-Der),were tested with linear partial least squares(PLS)models and nonlinear least squares-support vector machine(LS-SVM)*** results showed that the SG-PLS and PLS were the best for the N predicting(Rp=0.9049,RMSEP=0.1041)and P(Rp=0.9235,RMSEP=0.0514)in citrus leaves,respectively;the hyperspectral image data from leaf‟s upper side predicting better for the contents of N and *** study suggested that the hyperspectral image data from the upper side of the citrus leaves are suitable for nondestructive estimation of nutrient content.

关键词： citrus leaves nitrogen phosphorus prediction hyperspectral imaging

Identification of seedling cabbages and weeds using hyperspectral imaging

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Agricultural and Biological Engineering 2015年第5期8卷 65-72,I0004页

作者： Deng Wei Yanbo Huang Zhao Chunjiang Wang Xiu Beijing Research Center of Intelligent Equipment for Agriculture Beijing Academy of Agriculture and Forestry ScienceBeijing 100097China United States Department of Agriculture Agricultural Research ServiceCrop Production Systems Research UnitStonevilleMississippiUSA National Research Center of Intelligent Equipment for Agriculture Beijing 100097China Key Laboratory of Agri-informatics Ministry of AgricultureBeijing 100097China Beijing Key Laboratory of Intelligent Equipment Technology for Agriculture Beijing 100097China

Target detection is one of research focuses for precision chemical *** study developed a method to identify seedling cabbages and weeds using hyperspectral *** processing the image data with ENVI software,after dimension reduction,noise reduction,de-correlation for high-dimensional data,and selection of the region of interest,the SAM(Spectral Angle Mapping)model was built for automatic identification of cabbages and *** the HSI(Hyper Spectral imaging)Analyzer,the training pixels were used to calculate the average spectrum as the standard *** parameters of the SAM model,which had the best classification results with 3-point smoothing,zero-order derivative,and 6-degrees spectral angle,was determined to achieve the accurate identification of the background,weeds,and *** comparison,the SAM model can completely separate the plants from the soil background but not perfect for weeds to be separated from the *** conclusion,the SAM classification model with the HSI analyzer could completely distinguish weeds from background and cabbages.

关键词： hyperspectral imaging weed identification cabbage seedlings