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 spectr...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.展开更多
For several years, near-infrared spectroscopy (NIRS) has become an analytical technique of great interest for the pharmaceutical industry, particularly for the non-destructive analysis of dosage forms. The goal of thi...For several years, near-infrared spectroscopy (NIRS) has become an analytical technique of great interest for the pharmaceutical industry, particularly for the non-destructive analysis of dosage forms. The goal of this study is to show the capacity of this new technique to assay the active ingredient in low-dosage tablets. NIR spectroscopy is a rapid, non-destructive technique and does not need any sample preparation. A prediction model was built by using a partial least square regression fit method. The NIR assay was performed by transmission. The results obtained by NIR spectroscopy were compared with the conventional HPLC method for Montelukast tablets produced by Sigma pharmaceutical corp. The study showed that Montelukast tablets can be individually analyzed by NIR with high accuracy. It was shown that the variability of this new tech- nique is less important than that of the conventional method which is the HPLC with UV detection.展开更多
Herbal medicines are popular natural medicines that have been used for decades.The use of alternative medicines continues to expand rapidly across the world.The World Health Organization suggests that quality assessme...Herbal medicines are popular natural medicines that have been used for decades.The use of alternative medicines continues to expand rapidly across the world.The World Health Organization suggests that quality assessment of natural medicines is essential for any therapeutic or health care applications,as their therapeutic potential varies between different geographic origins,plant species,and varieties.Classification of herbal medicines based on a limited number of secondary metabolites is not an ideal approach.Their quality should be considered based on a complete metabolic profile,as their pharmacological activity is not due to a few specific secondary metabolites but rather a larger group of bioactive compounds.A holistic and integrative approach using rapid and nondestructive analytical strategies for the screening of herbal medicines is required for robust characterization.In this study,a rapid and effective quality assessment system for geographical traceability,species,and variety-specific authenticity of the widely used natural medicines turmeric,Ocimum,and Withania somnifera was investigated using Fourier transform near-infrared(FT-NIR)spectroscopy-based metabolic fingerprinting.Four different geographical origins of turmeric,five different Ocimum species,and three different varieties of roots and leaves of Withania somnifera were studied with the aid of machine learning approaches.Extremely good discrimination(R^(2)>0.98,Q^(2)>0.97,and accuracy=1.0)with sensitivity and specificity of 100%was achieved using this metabolic fingerprinting strategy.Our study demonstrated that FT-NIR-based rapid metabolic fingerprinting can be used as a robust analytical method to authenticate several important medicinal herbs.展开更多
乳制品的质量安全问题受到广泛的关注。为快速、准确判定乳制品污染源,利用傅里叶变换近红外光谱技术采集被阪崎肠杆菌、金葡萄球菌、大肠杆菌三种致病菌污染的牛奶样品的近红外透射光谱(NP),使用一阶求导(FD),标准正态变量变换(SNV),...乳制品的质量安全问题受到广泛的关注。为快速、准确判定乳制品污染源,利用傅里叶变换近红外光谱技术采集被阪崎肠杆菌、金葡萄球菌、大肠杆菌三种致病菌污染的牛奶样品的近红外透射光谱(NP),使用一阶求导(FD),标准正态变量变换(SNV),多元散射校正(MSC)对光谱进行预处理,结合偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)对三种细菌判别的可行性进行探究。研究表明,利用FD与SNV预处理方法得到PLS-DA模型判别结果均比NP差,而利用MSC预处理后准确率与NP一致达到了100%,且预测集相关系数(Rp)比NP高,预测均方根误差(RMSEP)更小,表明模型在经过MSC预处理后预测性能更理想。阐明利用FT-NIR技术结合化学计量学方法经过合适预处理方法后能有效用于乳制品中微生物类别的鉴别。展开更多
Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describ...Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) re- gression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 °Brix.展开更多
The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared(FT-NIR)Spee-trometer.Samples of milled:parboile...The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared(FT-NIR)Spee-trometer.Samples of milled:parboiled rioe,white rioe,new Jasmine rice(harvested in 2012)and aged Jasmine rice(harvested in 2006 or during the period 2007-2011)were used in this study.The eating quality of the cooked rioe,ie,adhesiveness,hardness,dryness,whiteness and aroma,were evaluated by trained sensory panelists.FT-NIR spectroscopy models for predicting the eating quality of cooked rioe were established using the partial least squares regression.Among the eating quality,the stickiness model indicated its highest prediction ability(ie,R2a=0.71;.RMSEP=0.65;Bias=0.00;RPD=1.87)and SEP/SD of 2.In addition,it was clear that the water content did not affect the eating quality of cooked rice,rather the main chemical com-ponent implicated was starch.展开更多
Objectives:Storage studies were carried out in wheat grains with different moisture contents,level of infestation,and storage days.Material and Methods:Wheat grain samples were infested with Rhyzopertha dominica and s...Objectives:Storage studies were carried out in wheat grains with different moisture contents,level of infestation,and storage days.Material and Methods:Wheat grain samples were infested with Rhyzopertha dominica and stored for up to 90 days under ambient conditions.Every 45 days,samples of wheat were collected and evaluated for protein,fat,ash,1000 kernel weight,and hardness.Results:The physicochemical parameters,namely,protein,1000 kernel weight,and hardness decreased while fat and ash content increased with the storage.Methodology for identification of infested samples was developed in Fourier transform near infrared(FT-NIR)and near infrared(NIR)using infested wheat and control samples.The linear regression plots for different quality parameters gave an R2 value of 82.04%and 97.15%via FT-NIR and 81.61%and 98.07%via NIR.The RMSEP values by NIR were in the range of 0.03 to 0.7,whereas the RMSECV values of FT-NIR were in the range of 0.03 to 1.2.Conclusions:Both the models performed well for the cross validation studies;hence,they can be used in future for the rapid assessment of storage quality of wheat grains.展开更多
基金Project (No. 30270763) supported by the National Natural Science Foundation of China
文摘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.
文摘For several years, near-infrared spectroscopy (NIRS) has become an analytical technique of great interest for the pharmaceutical industry, particularly for the non-destructive analysis of dosage forms. The goal of this study is to show the capacity of this new technique to assay the active ingredient in low-dosage tablets. NIR spectroscopy is a rapid, non-destructive technique and does not need any sample preparation. A prediction model was built by using a partial least square regression fit method. The NIR assay was performed by transmission. The results obtained by NIR spectroscopy were compared with the conventional HPLC method for Montelukast tablets produced by Sigma pharmaceutical corp. The study showed that Montelukast tablets can be individually analyzed by NIR with high accuracy. It was shown that the variability of this new tech- nique is less important than that of the conventional method which is the HPLC with UV detection.
基金Department of Science and Technology-SERB-SRG research grant(Grant No.:SRG/2021/000750-G)and Department of Biotechnology for Ramalingaswami grant(Grant No.:BT/RLF/Re-entry/21/2020)Director,Prabodh Kumar Trivedi,of CSIR-CIMAP for providing infrastructure,facility,and funding support from CSIR,India(Grant Nos.:FC2020-23/NMITLI/TLP0001&TLP0002)We acknowledge Dr.Ritu Trivedi(CSIR-CDRI Lucknow,India)for support and Dr.Abolie Girme and Dr.Lal Hingorani(Pharmanza herbal Pvt.Ltd,India)for providing Withania somnifera samples.We acknowledge Dr.Neerja Tiwari for FT-NIR access,Ms.Manju Yadav and Ms.Namita Gupta for HPLC access,and Ms.Anju Yadav for GC-MS access.Authors would like to thank Aroma mission HCP-0007,India for funding support.Prof.Christopher T.Elliott would like to thank Bualuang ASEAN Chair Professor Fund,UK and Queen's University Belfast Fund,UK.
文摘Herbal medicines are popular natural medicines that have been used for decades.The use of alternative medicines continues to expand rapidly across the world.The World Health Organization suggests that quality assessment of natural medicines is essential for any therapeutic or health care applications,as their therapeutic potential varies between different geographic origins,plant species,and varieties.Classification of herbal medicines based on a limited number of secondary metabolites is not an ideal approach.Their quality should be considered based on a complete metabolic profile,as their pharmacological activity is not due to a few specific secondary metabolites but rather a larger group of bioactive compounds.A holistic and integrative approach using rapid and nondestructive analytical strategies for the screening of herbal medicines is required for robust characterization.In this study,a rapid and effective quality assessment system for geographical traceability,species,and variety-specific authenticity of the widely used natural medicines turmeric,Ocimum,and Withania somnifera was investigated using Fourier transform near-infrared(FT-NIR)spectroscopy-based metabolic fingerprinting.Four different geographical origins of turmeric,five different Ocimum species,and three different varieties of roots and leaves of Withania somnifera were studied with the aid of machine learning approaches.Extremely good discrimination(R^(2)>0.98,Q^(2)>0.97,and accuracy=1.0)with sensitivity and specificity of 100%was achieved using this metabolic fingerprinting strategy.Our study demonstrated that FT-NIR-based rapid metabolic fingerprinting can be used as a robust analytical method to authenticate several important medicinal herbs.
文摘乳制品的质量安全问题受到广泛的关注。为快速、准确判定乳制品污染源,利用傅里叶变换近红外光谱技术采集被阪崎肠杆菌、金葡萄球菌、大肠杆菌三种致病菌污染的牛奶样品的近红外透射光谱(NP),使用一阶求导(FD),标准正态变量变换(SNV),多元散射校正(MSC)对光谱进行预处理,结合偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA)对三种细菌判别的可行性进行探究。研究表明,利用FD与SNV预处理方法得到PLS-DA模型判别结果均比NP差,而利用MSC预处理后准确率与NP一致达到了100%,且预测集相关系数(Rp)比NP高,预测均方根误差(RMSEP)更小,表明模型在经过MSC预处理后预测性能更理想。阐明利用FT-NIR技术结合化学计量学方法经过合适预处理方法后能有效用于乳制品中微生物类别的鉴别。
基金Project supported by New Century Excellent Talents in University(No. NCET-04-0524), and the Research Fund for the Doctoral Pro-gram of Higher Education (No. 20030335060) of China
文摘Nondestructive method of measuring soluble solids content (SSC) of citrus fruits was developed using Fourier transform near infrared reflectance (FT-NIR) measurements collected through optics fiber. The models describing the relationship between SSC and the NIR spectra of citrus fruits were developed and evaluated. Different spectra correction algorithms (standard normal variate (SNV), multiplicative signal correction (MSC)) were used in this study. The relationship between laboratory SSC and FT-NIR spectra of citrus fruits was analyzed via principle component regression (PCR) and partial least squares (PLS) re- gression method. Models based on the different spectral ranges were compared in this research. The first derivative and second derivative were applied to all spectra to reduce the effects of sample size, light scattering, instrument noise, etc. Different baseline correction methods were applied to improve the spectral data quality. Among them the second derivative method after baseline correction produced best noise removing capability and yielded optimal calibration models. A total of 170 NIR spectra were acquired; 135 NIR spectra were used to develop the calibration model; the remaining spectra were used to validate the model. The developed PLS model describing the relationship between SSC and NIR reflectance spectra could predict SSC of 35 samples with correlation coefficient of 0.995 and RMSEP of 0.79 °Brix.
文摘The goal of this research was to study the relationship between the eating quality of cooked rice and near infrared spectra measured by a Fourier Transform near infrared(FT-NIR)Spee-trometer.Samples of milled:parboiled rioe,white rioe,new Jasmine rice(harvested in 2012)and aged Jasmine rice(harvested in 2006 or during the period 2007-2011)were used in this study.The eating quality of the cooked rioe,ie,adhesiveness,hardness,dryness,whiteness and aroma,were evaluated by trained sensory panelists.FT-NIR spectroscopy models for predicting the eating quality of cooked rioe were established using the partial least squares regression.Among the eating quality,the stickiness model indicated its highest prediction ability(ie,R2a=0.71;.RMSEP=0.65;Bias=0.00;RPD=1.87)and SEP/SD of 2.In addition,it was clear that the water content did not affect the eating quality of cooked rice,rather the main chemical com-ponent implicated was starch.
文摘Objectives:Storage studies were carried out in wheat grains with different moisture contents,level of infestation,and storage days.Material and Methods:Wheat grain samples were infested with Rhyzopertha dominica and stored for up to 90 days under ambient conditions.Every 45 days,samples of wheat were collected and evaluated for protein,fat,ash,1000 kernel weight,and hardness.Results:The physicochemical parameters,namely,protein,1000 kernel weight,and hardness decreased while fat and ash content increased with the storage.Methodology for identification of infested samples was developed in Fourier transform near infrared(FT-NIR)and near infrared(NIR)using infested wheat and control samples.The linear regression plots for different quality parameters gave an R2 value of 82.04%and 97.15%via FT-NIR and 81.61%and 98.07%via NIR.The RMSEP values by NIR were in the range of 0.03 to 0.7,whereas the RMSECV values of FT-NIR were in the range of 0.03 to 1.2.Conclusions:Both the models performed well for the cross validation studies;hence,they can be used in future for the rapid assessment of storage quality of wheat grains.
