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1.
Xia-ping Fu Jian-ping Li Ying Zhou Yi-bin Ying Li-juan Xie Xiao-ying Niu Zhan-ke Yan Hai-yan Yu 《Journal of Zhejiang University. Science. B》2009,10(2):120-125
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
2.
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
3.
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
4.
To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r^2) of 0.759,low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way. 相似文献
5.
INTRODUCTION Recently increasing demands from consumerhave been observed for premium quality fruit witbetter taste at a higher price. Three major parameters determine the internal quality and the tastof apples. These are hardness, sugar content antitratable acidity, which are still determined destructively. Near-infrared spectroscopy (NIRS) habeen used to nondestructively measure internquality in a wide range of fruits and vegetablesuch as onions (Birth et al., 1985), cantaloupe (… 相似文献
6.
To evaluate the potential of FT-NIR spectroscopy and the influence of the distance between the light source/detection probe and the fruit for measuring the sugar content (SC) of Fuji apples, diffuse reflectance spectra were measured in the spectral range from 12500 to 4000 cm(1 at 0 mm, 2 mm, 4 mm and 6 mm distances. Four calibration models at four distances were established between diffused reflectance spectra and sugar content by partial least squares (PLS) analysis. The correlation coefficients (R) of calibrations ranged from 0.982 to 0.997 with SEC values from 0.138 to 0.453 and the SECV values from 0.74 to 1.58. The best model of original spectra at 0 mm distance yielded high correlation determination of 0.918, a SEC of 0.092, and a SEP of 0.773. The results showed that different light/detection probe-fruit distances influence the apple reflective spectra and SC predictions. 相似文献
7.
偏最小二乘法用于阿昔洛韦片的近红外漫反射快速、无损含量测定 总被引：2，自引：0，他引：2
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
8.
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
9.
Hui-rong Xu Peng Yu Xia-ping Fu Yi-bin Ying 《Journal of Zhejiang University. Science. B》2009,10(2):126-132
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
10.
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
11.
Background correction in near-infrared spectra of plant extracts by orthogonal signal correction 总被引：1，自引：0，他引：1
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
12.
Measurement and analysis of soil nitrogen and organic matter content using near-infrared spectroscopy techniques 总被引：2，自引：0，他引：2
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
13.
基于光谱技术的苹果糖度快速无损检测研究 总被引：2，自引：0，他引：2
论文以＂红富士苹果＂为样品,研究可见/近红外光谱技术进行苹果糖度的无损检测方法。选取30个苹果,用漫反射方式获取苹果的光谱曲线,用WAY-2S数字阿贝折射仪测量苹果的糖度,对光谱曲线进行平滑和消除噪声预处理后,用偏最小二乘法（PLS）对糖度建立相应的光谱预测模型。结果表明,糖度的模型稳定性较好,相关系数r达到了0.869,说明可见/近红外光谱技术可以进行苹果糖度的检测。 相似文献
14.
To further develop the methods to remotely sense the biochemical content of plant canopies,we report the results of an experiment to estimate the concentrations of three biochemical variables of corn,i.e.,nitrogen (N),crude fat (EE) and crude fiber (CF) concentrations,by spectral reflectance and the first derivative reflectance at fresh leaf scale.The correlations between spectral reflectance and the first derivative transformation and three biochemical variables were analyzed,and a set of estimation models were established using curve-fitting analyses.Coefficient of determination (R2),root mean square error (RAISE) and relative error of prediction (PEP) of estimation models were calculated for the model quality evaluations,and the possible opti-mum estimation models of three biochemical variables were proposed,with R2 being 0.891,0.698 and 0.480 for the estimation models of N,EE and CF concentrations,respectively.The results also indicate that using the first derivative reflectance was better than using raw spectral reflectance for all three biochemical variables estimation,and that the first derivative reflectances at 759 nm,1954 nm and 2370 nm were most suitable to develop the estimation models of N,EE and CF concentrations,respectively.In addition,the high correlation coefficients of the theoretical and the measured biochemical parameters were obtained,especially for nitrogen (r=0.948). 相似文献
15.
Li-juan XIE Xing-qian YE Dong-hong LIU Yi-bin YING 《Journal of Zhejiang University. Science. B》2008,9(12):982-989
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
16.
YUAN Bo MURAYAMA Koichi 《浙江大学学报(A卷英文版)》2007,8(2):171-175
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
17.
针对基于Kubelka-Munk理论光谱反射比重建算法中获得浓度矩阵难的技术环节,提出了一种全新的光谱反射比的重建方法——基于比光谱-导数分光光度法的光谱反射比重建算法,并以获取二元混合颜料样本颜色信息为例,证明了此算法的可行性. 相似文献
18.
YANG Xiao-hua HUANG Jing-feng WANG Fu-min WANG Xiu-zhen YI Qiu-xiang WANG Yuan 《浙江大学学报(A卷英文版)》2006,7(12)
INTRODUCTION Great advance has been achieved in vegetation characterization with remote sensing techniques. Most spectral vegetation indices (VIs) are usually calculated as the combinations of red and near-in- frared (NIR) reflectance because the information contained in a single spectral band is insufficient for characterizing vegetation status as vegetation exhibits unique reflectance properties in these bands. These VIs can be generally grouped into ratio indices and orthogonal indic… 相似文献
19.
YANG Xiao-hua HUANG Jing-feng WANG Fu-min WANG Xiu-zhen YI Qiu-xiang WANG Yuan 《浙江大学学报(A卷英文版)》2006,7(12):2002-2006
There is increasing interest in using hyperspectral data for quantitative characterization of vegetation in spatial and temporal scopes. Many spectral indices are being developed to improve vegetation sensitivity by minimizing the background influence. The chlorophyll absorption continuum index （CACI） is such a measure to calculate the spectral continuum on which the analyses are based on the area of the troughs spanned by the spectral continuum, However, different values of CACI were obtained in this method because different positions of continuums were determined by different users. Furthermore, the sensitivity of CACI to agronomic parameters such as green leaf chlorophyll density （GLCD） has been reduced because the fixed positions of continuums are determined when the red edge shifted with the change in GLCD. A modified chlorophyll absorption continuum index （MCACI） is presented in this article. The red edge inflection point （REIP） replaces the maximum reflectance point （MRP） in near-infrared （NIR） shoulder on the CACI continuum. This MCACI has been proved to increase the sensitivity and predictive power of GLCD. 相似文献
20.
Refined empirical line method to calibrate IKONOS imagery 总被引：1，自引：0，他引：1
XU Jun-feng HUANG Jing-feng 《浙江大学学报(A卷英文版)》2006,7(4):641-646
INTRODUCTION To extract quantitative biophysical parameter such as leaf biomass and leaf chlorophyll concentra- tion from the remotely sensed imagery accurately, the effects of atmospheric scattering and absorption must be removed. Atmospheric effects add to or diminish true ground reflectance, if the atmospheric spectral features are not properly removed. A significant analytical bias could be introduced for data interpre- tation (Ben-Dor and Levin, 2000). Many approaches have been deve… 相似文献