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1.
Near-infrared (NIR) transmittance spectroscopy combined with least-squares support vector machine (LS-SVM) was investigated to study the quality change of tomato juice during the storage. A total of 100 tomato juice samples were used. The spectrum of each tomato juice was collected twice: the first measurement was taken when the tomato juice was fresh and had not undergone any changes, and the second measurement was taken after a month. Principal component analysis (PCA) was used to examine a potential capability of separating juice before and after the storage. The soluble solid content (SSC) and pH of the juice samples were determined. The results show that changes in certain compounds between tomato juice before and after the storage period were obvious. An excellent precision was achieved by LS-SVM model compared with discriminant partial least-squares (DPLS), soft independent modeling of class analogy (SIMCA), and discriminant analysis (DA) models, with 100% of a total accuracy. It can be found that N1R spectroscopy coupled with LS-SVM, DPLS, SIMCA, and DA can be used to control the quality change of tomato juice during the storage.  相似文献   

2.
Application of NIR spectroscopy for firmness evaluation of peaches   总被引：1，自引：0，他引：1  
The use of near infrared (NIR) spectroscopy was proved to be a useful tool for quality analysis of fruits. A bifurcated fiber type NIR spectrometer, with a detection range of 800～2500 nm by lnGaAs detector, was used to evaluate the firmness of peaches. Anisotropy of NIR spectra and firmness of peaches in relation to detecting positions of different parts (including three latitudes and three longitudes) were investigated. Both spectra absorbency and firmness of peach were influenced by longitudes (i,ii, iii) and latitudes (A, B, C). For modeling, two thirds of the samples were used as the calibration set and the remaining one third were used as the validation or prediction set. Partial least square regression (PLSR) models for different longitude and latitude spectra and for the whole fruit show that collecting several NIR spectra from different longitudes and latitudes of a fruit for NIR calibration modeling can improve the modeling performance. In addition, proper spectra pretreatments like scattering correction or derivative also can enhance the modeling performance. The best results obtained in this study were from the holistic model with multiplicative scattering correction (MSC) pretreatment, with correlation coefficient of cross-validation rcv=0.864, root mean square error of cross-validation RMSECV=6.71 N, correlation coefficient of calibration r=0.948, root mean square error of cali-bration RMSEC=4.21 N and root mean square error of prediction RMSEP=5.42 N. The results of this study are useful for further research and application that when applying NIR spectroscopy for objectives with anisotropic differences, spectra and quality indices are necessarily measured from several parts of each object to improve the modeling performance.  相似文献   

3.
基于近红外光谱结合化学模式识别中的偏最小二乘法研究了一种快速、简单和低成本检测STR基因型的方法．选择STR基因座D5S818中的总串数相差较大的10—10、11—11与13—13基因型作为研究对象,将这三个基因型样本进行标准的PCR扩增并采集PCR产物的近红外光谱,以每一基因型的任意三分之二样本作为校正集,剩余三分之一作为预测集样本,探索了基于近红外光谱进行基因分型的可能性,结果发现该三类模型能够得到正确的判别,没有误判,预测集预测率达到100％．成功实现了基于近红外光谱对STR基因型的快速、简单和低成本检测．  相似文献   

4.
A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.  相似文献   

5.
Near infrared reflectance （N1R） spectroscopy is as a rapid, convenient and simple nondestructive technique useful for quantifying several soil properties. This method was used to estimate nitrogen （N） and organic matter （OM） content in a soil of Zhejiang Province, Hangzhou County. A total of 125 soil samples were taken from the field. Ninety-five samples spectra were used during the calibration and cross validation stage. Thirty samples spectra were used to predict N and OM concentration. NIR spectra of these samples were correlated using partial least square regression. The regression coefficients between measured and predicted values of N and OM was 0.92 and 0.93, and SEP （standard error of prediction） were 3.28 and 0.06, respectively, which showed that NIR method had potential to accurately predict these constituents in this soil. The results showed that NIR spectroscopy could be a good tool for precision farming application.  相似文献   

6.
INTRODUCTION Consumers’ acceptance of fresh or processedapples is the ultimate goal of apple breeders, foodscientists and supermarket managers. Internal qualityassessment has focused on two major objectives:removal of fruit with internal defects and taste selec-tion. Three major parameters including sugar content,acidity and firmness have to be taken into account todetermine the internal quality and the taste of an apple.Near infrared spectroscopy has been used to measureseveral properti…  相似文献   

7.
目的：采用近红外漫反射光谱法对安乃近片的含量进行定量分析。方法：从某药业公司抽得安乃近片16批,在市场上购得该厂生产的安乃近片10批,经实验室检验含量是否合格。将这26批样品经内部交叉验证建立预测模型,从样品中自动选取55%为验证集,进行外部验证。结果：通过近红外测得的值跟实验室测得的值接近。结论：安乃近片用近红外漫反射光谱法预测含量,无损检测,比常规测量速度快且简便,用于药品检测及日常监管中具有可行性。  相似文献   

8.
This study evaluated the classification accuracy of a second grade oral reading fluency curriculum‐based measure (R‐CBM) in predicting third grade state test performance. It also compared the long‐term classification accuracy of local and publisher‐recommended R‐CBM cut scores. Participants were 266 students who were divided into a calibration sample (n = 170) and two cross‐validation samples (n = 46; n = 50), respectively. Using calibration sample data, local fall, winter, and spring R‐CBM cut scores for predicting students’ state test performance were developed using three methods: discriminant analysis (DA), logistic regression (LR), and receiver operating characteristic curve analysis (ROC). The classification accuracy of local and publisher‐recommended cut scores was evaluated across subsamples. Only DA and ROC produced cut scores that maintained adequate sensitivity (≥.70) across cohorts; however, LR and publisher‐recommended scores had higher levels of specificity and overall correct classification. Implications for developing local cut scores are discussed.  相似文献   

9.
The near infrared (NIR) spectroscopy technique has been applied in many fields because of its advantages of simple preparation,fast response,and non-destructiveness.We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content (SSC) and acidity (pH) of intact loquats.Two cultivars of loquats (Dahongpao and Jiajiaozhong) harvested from two orchards (Tangxi and Chun'an,Zhejiang,China) were used for the measurement of NIR spectra between 800 and 2500 nm.A total of 400 loquats (100 samples of each cultivar from each orchard) were used in this study.Relationships between NIR spectra and SSC and acidity of ioquats were evaluated using partial least square (PLS) method.Spectra preprocessing options included the first and second derivatives,multiple scatter correction (MSC),and the standard normal variate (SNV).Three separate spectral windows identified as full NIR (800-2500 nm),short NIR (800～1100 nm),and long NIR (1100～2500 nm) were studied in factorial combination with the preprocessing options.The models gave relatively good predictions of the SSC of loquats,with root mean square error of prediction (RMSEP) values of 1.21,1.00,0.965,and 1.16 °Brix for Tangxi-Dahongpao,Tangxi-Jiajiaozhong,Chun'an-Dahongpao,and Chun'an-Jiajiaozhong,respectively.The acidity prediction was not satisfactory,with the RMSEP of 0.382,0.194,0.388,and 0.361 for the above four loquats,respectively.The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.  相似文献   

10.
Yuan  Shijin  Pan  Yong  Xia  Yan  Zhang  Yan  Chen  Jiangnan  Zheng  Wei  Xu  Xiaoping  Xie  Xinyou  Zhang  Jun 《Journal of Zhejiang University. Science. B》2021,22(4):318-329
With the number of cases of coronavirus disease-2019(COVID-19) increasing rapidly, the World Health Organization(WHO) has recommended that patients with mild or moderate symptoms could be released from quarantine without nucleic acid retesting, and self-isolate in the community. This may pose a potential virus transmission risk. We aimed to develop a nomogram to predict the duration of viral shedding for individual COVID-19 patients. This retrospective multicentric study enrolled 135 patients as a training cohort and 102 patients as a validation cohort. Significant factors associated with the duration of viral shedding were identified by multivariate Cox modeling in the training cohort and combined to develop a nomogram to predict the probability of viral shedding at 9, 13, 17, and 21 d after admission. The nomogram was validated in the validation cohort and evaluated by concordance index(C-index), area under the curve(AUC), and calibration curve. A higher absolute lymphocyte count(P=0.001) and lymphocyte-to-monocyte ratio(P=0.013) were correlated with a shorter duration of viral shedding, while a longer activated partial thromboplastin time(P=0.007) prolonged the viral shedding duration. The C-indices of the nomogram were 0.732(95% confidence interval(CI): 0.685-0.777) in the training cohort and 0.703(95% CI: 0.642-0.764) in the validation cohort. The AUC showed a good discriminative ability(training cohort: 0.879, 0.762, 0.738, and 0.715 for 9, 13, 17, and 21 d; validation cohort: 0.855, 0.758, 0.728, and 0.706 for 9, 13, 17, and 21 d), and calibration curves were consistent between outcomes and predictions in both cohorts. A predictive nomogram for viral shedding duration based on three easily accessible factors was developed to help estimate appropriate self-isolation time for patients with mild or moderate symptoms, and to control virus transmission.  相似文献   

11.
INTRODUCTION Image quality in nuclear medicine tomography is critically dependent on the activity undergone by the patient. The optimal activity is the smallest amount of activity which preserves diagnostic accuracy. Nev- ertheless, the optimum depends on the gamma camera used for imaging, the size of the patient and the im- aging application (Mattsson et al., 1998). To optimize, one has to study how diagnostic accuracy depends on the activity undergone for each particular study, taking i…  相似文献   

12.
INTRODUCTION Determination of fruit and vegetable quality is very important for both producers and processors. Watermelon as a delicious fruit has been widely ac-cepted in the world and its internal quality is impor-tant for consumers and merchants. The current fa-vorite way for checking a watermelon is to sense sound or vibration by slapping or rapping it. It is time consuming, tedious, and subject to error. Several studies on assessing the quality of watermelon based on its acoustic o…  相似文献   

13.
Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera. In this paper, we propose a fast and stable linear discriminant approach based on Gaussian Single Model （GSM） and Markov Random Field （MRF）, The performance of GSM is analyzed first, and then two main improvements corresponding to the drawbacks of GSM are proposed： the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF. Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.  相似文献   

14.
Attribute reduction is necessary in decision making system. Selecting right attribute reduction method is more important. This paper studies the reduction effects of principal components analysis （PCA） and system reconstruction analysis , SRA） on coronary heart disease data. The data set contains 1723 records, and 71 attributes in each record. PCA and SRA are used to reduce attributes number （less than 71 ） in the data set. And then decision tree algorithms. C4.5, classification and regression tree （ CART）, and chi-square automatic interaction detector （ CHAID ）, are adopted to analyze the raw data and attribute reduced data. The parameters of decision tree algorithms, including internal node number, maximum tree depth, leaves number, and correction rate are analyzed. The result indicates that. PCA and SRA data can complete attribute reduction work. and the decision-making rate on the reduced data is quicker than that on the raw data： the reduction effect of PCA is better than that of SRA. while the attribute assertion of SRA is better than that of PCA. PCA and SRA methods exhibit good performance in selecting and reducing attributes.  相似文献   

15.
Using log data of 823 university students collected in two settings: their online learning setting and daily life setting (using campus ID cards for consumption purposes and book-borrowing in the university library), this study created indicators for online learning behavior, early-rising behavior, book-borrowing behavior and learning performance prediction. Five machine learning models were employed to analyze learning performance prediction, with the additional use of Boosting and Bagging to improve the accuracy of the prediction model. The predictability of the proposed model was also compared with that of both the Artificial Neural Network model and the Deep Neural Network model. At the same time, a classification rule set was established by combining decision tree and rule model, and a learning behavior diagnosis model combining decision tree and deep neural network was constructed. Findings showed that multi-scenario behavior performance indicators had strong predictive capabilities while the Deep Neural Network model had the highest prediction accuracy (82%) but was most time-consuming. The model based on the rule set is highly accurate, readable and operable and may be conducive to making accurate teaching interventions and resource recommendations.  相似文献   

16.
二维最大散度差鉴别准则和二维Fisher鉴别准则抽取的特征具有很强的相关性.本文在此基础上,通过对传统的基于向量的典型相关分析方法进行分析改进,提出了一种新的直接基于图像二维鉴别特征矩阵融合的二维典型相关分析方法,并将其应用于人脸识别的特征融合过程中.较基于向量的典型相关分析,该方法计算过程中构造的协方差矩阵维数大幅度减小.这在一定程度上避免了人脸识别中存在的"高维小样本问题",另一方面也使算法的速度明显提高.  相似文献   

17.
To establish a financial early-warning model with high accuracy of discrimination and achieve the aim of long-term prediction, principal component analysis (PCA), Fisher discriminant, together with grey forecasting models are used at the same time. 110 A-share companies listed on the Shanghai and Shenzhen stock exchange are selected as research samples. And 10 extractive factors with 89.746% of all the original information are determined by applying PCA, which obtains the goal of dimension reduction without information loss. Based on the index system, the early-warning model is constructed according to the Fisher rules. And then the GM(1,1) is adopted to predict financial ratios in 2004, according to 40 testing samples from 2000 to 2003. Finally, two different methods, a self-validated and a forecasting-validated, are used to test the validity of the financial crisis warning model. The empirical results show that the model has better predictability and feasibility, and GM(1,1) contributes to the ability to make long-term predictions.  相似文献   

18.
二维最大散度差线性鉴别分析方法不仅有效地避免了在人脸识别中传统的Fisher线性鉴别分析通常存在的“小样本问题”,而且使其特征抽取的速度有了大幅度的提高．本文通过引入著名的“核技巧”,将二维最大散度差线性鉴别分析扩展到非线性空间,提出了一种新的二维核最大散度差鉴别分析方法．该方法不仅抽取了图像中更加有效的非线性鉴别特征,使正确识别率显著提高,而且为二维非线性鉴别分析提供了一个统一的构架．最后在AR标准人脸库中的实验结果验证了本文算法的有效性．  相似文献   

19.
Endophytic flora plays a vital role in the colonization and survival of host plants, especially in harsh environments, such as arid regions. This flora may, however, contain pathogenic species responsible for various troublesome host diseases. The present study is aimed at investigating the diversity of both cultivable and non-cultivable endophytic fungal floras in the internal tissues (roots and leaves) of Tunisian date palm trees (Phoenix dactylifera). Accordingly, 13 isolates from both root and leaf samples, exhibiting distinct colony morphology, were selected from potato dextrose agar (PDA) medium and identified by a sequence match search wherein their 18S–28S internal transcribed spacer (ITS) sequences were compared to those available in public databases. These findings revealed that the cultivable root and leaf isolates fell into two groups, namely Nectriaceae and Pleosporaceae. Additionally, total DNA from palm roots and leaves was further extracted and ITS fragments were amplified. Restriction fragment length polymorphism (RFLP) analysis of the ITS from 200 fungal clones (leaves: 100; roots: 100) using HaeIII restriction enzyme revealed 13 distinct patterns that were further sequenced and led to the identification of Alternaria, Cladosporium, Davidiella (Cladosporium teleomorph), Pythium, Curvularia, and uncharacterized fungal endophytes. Both approaches confirmed that while the roots were predominantly colonized by Fusaria (members of the Nectriaceae family), the leaves were essentially colonized by Alternaria (members of the Pleosporaceae family). Overall, the findings of the present study constitute, to the authors’ knowledge, the first extensive report on the diversity of endophytic fungal flora associated with date palm trees (P. dactylifera).  相似文献   

20.
本文主要采用两种降维的方法和k-近邻法(KNN)有监督分类的方法来对基因芯片(微阵列)数据进行分析。PCA,PLS是一种提取海量的数据有效特征的有效方法,可以获得与原来基因芯片数据更为接近的成分的提取特征的效果。比较PCA降维方法和PLS降维方法对KNN统计判别分类的效果。  相似文献   

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