To develop near-infrared (NIR) reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders ...To develop near-infrared (NIR) reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere (IS) and fiberoptic probe (FOP) models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation (RMSECV) and the root mean square errors of prediction (RMSEP) of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.展开更多
[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, ...[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis (PCA). [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.展开更多
[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were cho...[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards (GB/T 21127-2007), and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination (RSQ) and cross-validation coefficient of determination (1-VR) were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.展开更多
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 ...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.展开更多
[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drou...[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat (GB/T 21127-2007). In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality (full spectrum analyzer) and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient (RSQ) and coeffi- cients of determination for cross validation (1-VR) in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.展开更多
Soil visible-near infrared diffuse reflectance spectroscopy(vis-NIR DRS)has become an important area of research in the fields of remote and proximal soil sensing.The technique is considered to be particularly useful ...Soil visible-near infrared diffuse reflectance spectroscopy(vis-NIR DRS)has become an important area of research in the fields of remote and proximal soil sensing.The technique is considered to be particularly useful for acquiring data for soil digital mapping,precision agriculture and soil survey.In this study,1581 soil samples were collected from 14 provinces in China,including Tibet,Xinjiang,Heilongjiang,and Hainan.The samples represent 16 soil groups of the Genetic Soil Classification of China.After air-drying and sieving,the diffuse reflectance spectra of the samples were measured under laboratory conditions in the range between 350 and 2500 nm using a portable vis-NIR spectrometer.All the soil spectra were smoothed using the Savitzky-Golay method with first derivatives before performing multivariate data analyses.The spectra were compressed using principal components analysis and the fuzzy k-means method was used to calculate the optimal soil spectral classification.The scores of the principal component analyses were classified into five clusters that describe the mineral and organic composition of the soils.The results on the classification of the spectra are comparable to the results of other similar research.Spectroscopic predictions of soil organic matter concentrations used a combination of the soil spectral classification with multivariate calibration using partial least squares regression(PLSR).This combination significantly improved the predictions of soil organic matter(R2=0.899;RPD=3.158)compared with using PLSR alone(R2=0.697;RPD=1.817).展开更多
Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared di...Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared diffuse reflectance spectroscopy (VNIR-DRS) provides a rapid and inexpensive tool to predict various soil properties simultaneously. This study evaluated the suitability of VNIR-DRS for predicting soil properties, including organic matter (OM), pH, and heavy metals (Cu, Pb, Zn, Cd, and Fe), using a total of 254 samples collected in soil profiles near a large copper smelter in China. Partial least square regression (PLSR) with cross-validation was used to relate soil property data to the reflectance spectral data by applying different preprocessing strategies. The performance of VNIR-DRS calibration models was evaluated using the coefficient of determination in cross-validation (R^2cv) and the ratio of standard deviation to the root mean standard error of cross-validation (SD/RMSEcv). The models provided fairly accurate predictions for OM and Fe (R2v 〉 0.80, SD/RMSEcv 〉 2.00), less accurate but acceptable for screening purposes for pH, Cu, Pb, and Cd (0.50 〈 Rcv 〈 0.80, 1.40 〈 SD/RMSEcv 〈 2.00), and poor accuracy for Zn (R2v 〈 0.50, SD/RMSEcv 〈 1.40). Because soil properties in conta- minated areas generally show large variation, a comparative large number of calibrating samples, which are variable enough and uniformly distributed, are necessary to create more accurate and robust VNIR-DRS calibration models. This study indicated that VNIR-DRS technique combined with continuously enriched soil spectral library could be a nondestructive alternative for soil environment monitoring.展开更多
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-ca...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 cor- rection 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 predic- tion=0.216). The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.展开更多
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 spectrosco...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 loquats 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 rim), 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.展开更多
基金National Key Technologies R&D Program Foundation of China (Grant No. 2006BAK04A11)
文摘To develop near-infrared (NIR) reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere (IS) and fiberoptic probe (FOP) models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation (RMSECV) and the root mean square errors of prediction (RMSEP) of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.
基金Supported by National Natural Science Foundation of China(81360623)~~
文摘[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis (PCA). [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.
基金Supported by National Wheat Industry System(CARS-E-2-36)Henan Wheat Industry System(S2010-10-02)National Science and Technology Support Plan(2011BAD35B-03)~~
文摘[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards (GB/T 21127-2007), and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination (RSQ) and cross-validation coefficient of determination (1-VR) were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.
基金Project supported by the National Natural Science Foundation of China (No. 30270773), and the Teaching and Research Award Pro-gram for Outstanding Young Teachers in Higher Education Institu-tions & the Specialized Research Fund for the Doctoral Program o
文摘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.
基金Supported by the Special Fund for the Industrial Technology System Construction of Modern Agriculture in Wheat(CARS-E-2-36)the Special Fund for Henan Industrial Technology System Construction of Modern Agriculture in Wheat(S2010-10-02)National Support Program for Science and Technology(2011BAD35B03)~~
文摘[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat (GB/T 21127-2007). In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality (full spectrum analyzer) and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient (RSQ) and coeffi- cients of determination for cross validation (1-VR) in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.
基金This project was funded in part by the National High Technology Research and Development Program (Grant No. 2013AA102301)the program for New Century Talents in University (Grant No. NCET-10-0694), and the National Natural Science Foundation of China (Grant No. 41271234)
文摘Soil visible-near infrared diffuse reflectance spectroscopy(vis-NIR DRS)has become an important area of research in the fields of remote and proximal soil sensing.The technique is considered to be particularly useful for acquiring data for soil digital mapping,precision agriculture and soil survey.In this study,1581 soil samples were collected from 14 provinces in China,including Tibet,Xinjiang,Heilongjiang,and Hainan.The samples represent 16 soil groups of the Genetic Soil Classification of China.After air-drying and sieving,the diffuse reflectance spectra of the samples were measured under laboratory conditions in the range between 350 and 2500 nm using a portable vis-NIR spectrometer.All the soil spectra were smoothed using the Savitzky-Golay method with first derivatives before performing multivariate data analyses.The spectra were compressed using principal components analysis and the fuzzy k-means method was used to calculate the optimal soil spectral classification.The scores of the principal component analyses were classified into five clusters that describe the mineral and organic composition of the soils.The results on the classification of the spectra are comparable to the results of other similar research.Spectroscopic predictions of soil organic matter concentrations used a combination of the soil spectral classification with multivariate calibration using partial least squares regression(PLSR).This combination significantly improved the predictions of soil organic matter(R2=0.899;RPD=3.158)compared with using PLSR alone(R2=0.697;RPD=1.817).
基金Supported by the National Natural Science Foundation of China (Nos. 40801081 and 40271104)the open fund from the Key Laboratory of Virtual Geographic Environment of the Ministry of Education,China (No. NS207002)
文摘Spatial and temporal monitoring of soil properties in smelting regions requires collection of a large number of sam- ples followed by laboratory cumbersome and time-consuming measurements. Visible and near-infrared diffuse reflectance spectroscopy (VNIR-DRS) provides a rapid and inexpensive tool to predict various soil properties simultaneously. This study evaluated the suitability of VNIR-DRS for predicting soil properties, including organic matter (OM), pH, and heavy metals (Cu, Pb, Zn, Cd, and Fe), using a total of 254 samples collected in soil profiles near a large copper smelter in China. Partial least square regression (PLSR) with cross-validation was used to relate soil property data to the reflectance spectral data by applying different preprocessing strategies. The performance of VNIR-DRS calibration models was evaluated using the coefficient of determination in cross-validation (R^2cv) and the ratio of standard deviation to the root mean standard error of cross-validation (SD/RMSEcv). The models provided fairly accurate predictions for OM and Fe (R2v 〉 0.80, SD/RMSEcv 〉 2.00), less accurate but acceptable for screening purposes for pH, Cu, Pb, and Cd (0.50 〈 Rcv 〈 0.80, 1.40 〈 SD/RMSEcv 〈 2.00), and poor accuracy for Zn (R2v 〈 0.50, SD/RMSEcv 〈 1.40). Because soil properties in conta- minated areas generally show large variation, a comparative large number of calibrating samples, which are variable enough and uniformly distributed, are necessary to create more accurate and robust VNIR-DRS calibration models. This study indicated that VNIR-DRS technique combined with continuously enriched soil spectral library could be a nondestructive alternative for soil environment monitoring.
基金Project (No.60405003) supported by the National Natural Science Foundation of China
文摘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 cor- rection 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 predic- tion=0.216). The results show that visible-NIR spectroscopy might be a suitable alternative tool to discriminate tomato plant varieties on-site.
基金Project supported by the National Natural Science Foundation of China(No.30825027)the National Key Technology R&D Program of China(No.2006BAD11A12)
文摘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 loquats 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 rim), 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.