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1.
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   

2.
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   

3.
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   

4.
INTRODUCTION Soluble solids content (SSC) is a major charac- teristic used for assessing citrus fruit quality. Near-infrared spectroscopy (NIRS) has been used as a rapid and nondestructive technique for determining the soluble solids content of fruit. Kawano et al.(1992) measured sugar content of peaches in the wavelength region of 680~1235 nm. Their experiments indicated good correlation between the NIR spectra and the sugar content (r=0.97, SEP=0.05 °Brix). Slaughter (1995) devel…  相似文献   

5.
INTRODUCTION The bands of near-infrared (NIR) spectra have low absorptivities, which allow in situ analysis of chemical and biological materials with no or little sample preparation. Therefore, as one of the most important nondestructive analytical techniques, NIR spectroscopy is being extensively applied in the fields of agriculture, industry, biotechnology and medicine (Siesler et al., 2002; Scarff et al., 2006; Ward et al., 2006). Recently, with instrumental developments such as Fou…  相似文献   

6.
Corn steep liquor(CSL) is an important raw material that has high nutritional value and serves as a nitrogen source.Biotin in CSL is especially of great importance to fermentation.In order to develop a fast,versatile,cheap,and environmentally safe analytical method for quantifying vitamins B2(VB2),B3(VB3),B6(VB6) and B7(VB7) in CSL,the near-infrared spectroscopy(NIR) measurements of 66 samples(22 batches) of CSL were analyzed by partial least-square regression(PLSR).Multivariate models developed in the NIR regions showed good predictive abilities for VB2,VB3,VB6 and VB7.Results confirmed the probability of the multivariate spectroscopic approach as a replacement for expensive and time-consuming conventional chemical methods.  相似文献   

7.
Near-infrared (NIR) spectroscopy combined with chemometrics techniques was used to classify the pure bayberry juice and the one adulterated with 10% (w/w) and 20% (w/w) water. Principal component analysis (PCA) was applied to reduce the dimensions of spectral data, give information regarding a potential capability of separation of objects, and provide principal component (PC) scores for radial basis function neural networks (RBFNN). RBFNN was used to detect bayberry juice adulterant. Multiplicative scatter correction (MSC) and standard normal variate (SNV) transformation were used to preprocess spectra. The results demonstrate that PC-RBFNN with optimum parameters can separate pure bayberry juice samples from water-adulterated bayberry at a recognition rate of 97.62%, but cannot clearly detect water levels in the adulterated bayberry juice. We conclude that NIR technology can be successfully applied to detect water-adulterated bayberry juice.  相似文献   

8.
The use of visible-near infrared (NIR) spectroscopy was explored as a tool to discriminate two new tomato plant varieties in China (Zheza205 and Zheza207).In this study,82 top-canopy leaves of Zheza205 and 86 top-canopy leaves of Zheza207 were measured in visible-NIR reflectance mode.Discriminant models were developed using principal component analysis (PCA),discriminant analysis (DA),and discriminant partial least squares (DPLS) regression methods.After outliers detection,the samples were randomly split into two sets,one used as a calibration set (n=82) and the remaining samples as a validation set (n=82).When predicting the variety of the samples in validation set,the classification correctness of the DPLS model after optimizing spectral pretreatment was up to 93%.The DPLS model with raw spectra after multiplicative scatter correction and Savitzky-Golay filter smoothing pretreatments had the best satisfactory calibration and prediction abilities (correlation coefficient of calibration (Rc)=0.920,root mean square errors of calibration=0.196,and root mean square errors of prediction=0.216).The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.  相似文献   

9.
We have developed a set of chemometric methods to address two critical issues in quality control of a precious traditional Chinese medicine (TCM), Dong’e Ejiao (DEEJ). Based on near infrared (NIR) spectra of multiple samples, the genuine manufacturer of DEEJ, e.g. Dong’e Ejiao Co., Ltd., was accurately identified among 21 suppliers by the fingerprint method using Hotelling T2, distance to Model X (DModX), and similarity match value (SMV) as discriminate criteria. Soft independent modeling of the class analogy algorithm led to a misjudgment ratio of 6.2%, suggesting that the fingerprint method is more suitable for manufacturer identification. For another important feature related to clinical efficacy of DEEJ, storage time, the partial least squares-discriminant analysis (PLS-DA) method was applied with a satisfactory misjudgment ratio (15.6%) and individual prediction error around 1 year. Our results demonstrate that NIR spectra comprehensively reflect the essential quality information of DEEJ, and with the aid of proper chemometric algorithms, it is able to identify genuine manufacturer and determine accurate storage time. The overall results indicate the promising potential of NIR spectroscopy as an effective quality control tool for DEEJ and other precious TCM products.  相似文献   

10.
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   

11.
To compare mid-infrared(MIR)and near-infrared(NIR)spectroscopies for the determination of the fat and protein contents in milk,the same sample sets with varying concentrations of fat and protein were measured in the MIR range of 3 200-700 cm-1 and NIR range of 9 000-4 000 cm-1.The spectral features in the two regions were analyzed.The MIR spectra of milk were characteristic due to the MIR inherent molecular specificity,whereas the NIR spectra were relatively characterless due to the NIR low selectivity.Partial least squares(PLS)regression models for fat and protein were developed by using both MIR and NIR spectra.MIR data with no pretreatment gave better results than NIR data.The square correlation coefficient(R2)and the root mean square error of prediction(RMSEP)were 0.98 and 0.10 g/dL for fat and 0.97 and 0.11 g/dL for protein.With NIR techniques,satisfactory results were not obtained with raw data.However,NIR data after pretreatment gave similarly good results to the ones using MIR method.This paper indicates that either of the MIR and NIR spectral methods is reliable for the determination of the fat and protein contents.  相似文献   

12.
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   

13.
An efficient reflux extraction of polyethylene wax (PEW) in soil is presented, followed by molecular structure characterization methods to explore its degradation mechanism. To more realistically simulate the actual degradation of PE film powders in soil, low density PE (M=5 000) powders, being used as simulated PEW residue sample, were uniformly mixed with soil and then recovered by reflux extraction with decahydronaphthalen (decalin) at 90 ℃ for 60 min. The average recovery of PEW from fortified soils was 96.5% with the developed reflux extraction procedure. The recovered PEW residue samples were characterized by infrared spectroscopy (IR), element analysis (EA), X-ray fluorescence (XFR), and high-temperature gel permeation chromatography (GPC). The results from spectra analysis show that there were no significant changes in molecular structures and molecular mass distribution of PEW samples after the reflux extraction, which demonslrate the reliability of this method. These results also indicate that the reflux extraction procedure and analytical methods of characterization could serve as a novel measurement technique to evaluate the degradation of low-density PE powders in soil over time.  相似文献   

14.
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   

15.
In near-infrared (NIR) analysis of plant extracts, excessive background often exists in near-infrared spectra. The detection of active constituents is difficult because of excessive background, and correction of this problem remains difficult. In this work, the orthogonal signal correction (OSC) method was used to correct excessive background. The method was also compared with several classical background correction methods, such as offset correction, multiplicative scatter correction (MSC), standard normal variate (SNV) transformation, de-trending (DT), first derivative, second derivative and wavelet methods. A simulated dataset and a real NIR spectral dataset were used to test the efficiency of different background correction methods. The results showed that OSC is the only effective method for correcting excessive background.  相似文献   

16.
目的:采用偏最小二乘法结合近红外漫反射光谱,建立阿昔洛韦片的快速无损含量测定模型.方法:以阿昔洛韦片为分析对象,用光纤探头测定近红外漫反射光谱.对光谱进行不同预处理方法建模并进行比较,多元校正模型为偏最小二乘法.结果:在11995.5~4246.7cm-1波长范围内采用一阶导数结合矢量归一化对光谱进行预处理,结果最优.定量模型的浓度范围为27%~53%.预示集平均回收率为98.69%,RSD为4.60%,RMSEP为0.0526.结论:近红外漫反射光谱法快速,简便,无损,能够用于阿昔洛韦片含量测定.  相似文献   

17.
以重楼根茎粉末为原料,加热回流提取粗皂苷后,用近红外在线检测AB-8大孔吸附树脂除杂和洗脱分离的全过程,并以近红外光谱判别变量为表征手段,将分离过程分为四个阶段。分别对每个阶段收集的洗脱液进行比色和水解,通过离线的紫外光谱和高效液相色谱分析,结果显示,用70%的乙醇对大孔吸附树脂中除杂以后的重楼总皂苷进行洗脱,基本能将重楼总皂苷分为几类有效组分群。  相似文献   

18.
19.
研究了钛铁试剂分光光度法测定土壤中铁的方法,探讨了方法的最佳条件。结果表明,以钛铁试剂为显色剂,可于560nm处测定土壤中铁的含量,铁含量在0-3mg/L范围内服从比尔定律,线性回归方程为Y=0.0889x,相关系数1=0.9984,表观摩尔吸光系数为K560=5.12×10^4L·mol^-1·cm^-1。该方法简便,选择性好,灵敏度高。此法用于土壤中铁的测定,结果与磺基水杨酸法相符。样品标准加入回收率分别为95.6%~99.9%,相对标准偏差为0.34%-0.53%(n=6)。  相似文献   

20.
Visible and near infrared spectroscopy is a non-destructive, green, and rapid technology that can be utilized to estimate the components of interest without conditioning it, as compared with classical analytical methods. The objective of this paper is to compare the performance of artificial neural network (ANN) (a nonlinear model) and principal component regression (PCR) (a linear model) based on visible and shortwave near infrared (VIS-SWNIR) (400–1000 nm) spectra in the non-destructive soluble solids content measurement of an apple. First, we used multiplicative scattering correction to pre-process the spectral data. Second, PCR was applied to estimate the optimal number of input variables. Third, the input variables with an optimal amount were used as the inputs of both multiple linear regression and ANN models. The initial weights and the number of hidden neurons were adjusted to optimize the performance of ANN. Findings suggest that the predictive performance of ANN with two hidden neurons outperforms that of PCR.  相似文献   

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