Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl Ri...Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters <em>d, p, m</em> and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEP<sub>V</sub>), relative root mean square error (R-SEP<sub>V</sub>) and correlation coefficients (R<sub>P, V</sub>) of prediction were 11.66 mg<span style="white-space:nowrap;">·</span>kg<sup>-1</sup>, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.展开更多
[Objective] To explore a method for the rapid determination of protein con- tent in grains of Panicum miliaceum L. [Method] The near infrared transmittance spec- troscopy （NITS） was used to build the mathematical mo...[Objective] To explore a method for the rapid determination of protein con- tent in grains of Panicum miliaceum L. [Method] The near infrared transmittance spec- troscopy （NITS） was used to build the mathematical models for the quantitative analy- sis of protein content in the grains. Four combinations of treatment that first derivative and second derivative were respectively combined with partial least squares （PLS） and modified partial least squares （MPLS） were set to compare their effects on the original transmission spectrum. [Result] The predicting effects of the 4 combinations were similar. The optimal combination was first derivative with MPLS, in which the average determination coefficient of validation （RSQ） was 0.880 6, correlation coeffi- cient of cross validation （1-VR） was 0.857 0, standard error of calibration （SEC） was 0.342 4, standard error of cross validation （SECV） was 0.375 1, and the standard er- ror of prediction （SEP） was 0.454. [Conclusion] The constructed NITS model is a rapid way for the determination of protein content in grains of P. miliaceum.展开更多
High-end wine brand is made through the use of high-quality grape variety and yeast strain, and through a unique process. Not only is it rich in nutrients, but also it has a unique taste and a fragrant scent. Brand id...High-end wine brand is made through the use of high-quality grape variety and yeast strain, and through a unique process. Not only is it rich in nutrients, but also it has a unique taste and a fragrant scent. Brand identification of wine is difficult and complex because of high similarity. In this paper, visible and near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was used to explore the feasibility of wine brand identification. Chilean Aoyo wine (2016 vintage) was selected as the identification brand (negative, 100 samples), and various other brands of wine were used as interference brands (positive, 373 samples). Samples of each type were randomly divided into the calibration, prediction and validation sets. For comparison, the PLS-DA models were established in three independent and two complex wavebands of visible (400 - 780 nm), short-NIR (780 - 1100 nm), long-NIR (1100 - 2498 nm), whole NIR (780 - 2498 nm) and whole scanning (400 - 2498 nm). In independent validation, the five models all achieved good discriminant effects. Among them, the visible region model achieved the best effect. The recognition-accuracy rates in validation of negative, positive and total samples achieved 100%, 95.6% and 97.5%, respectively. The results indicated the feasibility of wine brand identification with Vis-NIR spectroscopy.展开更多
The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spe...The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C<sub>5</sub>H<sub>10</sub>NNaO<sub>5</sub>) and caramel color (C<sub>6</sub>H<sub>8</sub>O<sub>3</sub>). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RAR<sub>V</sub>) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RAR<sub>V</sub> = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.展开更多
The characterization of these molecularly imprinted polymers is essential to understanding their binding dynamics and structural properties. Through the analysis of the current research, it is found that there are ove...The characterization of these molecularly imprinted polymers is essential to understanding their binding dynamics and structural properties. Through the analysis of the current research, it is found that there are overlaps in the methods used by scholars. The Langmuir equation is frequently applied to model the adsorption isotherms of MIPs, providing critical insight into the capacity and affinity of the binding sites. Infrared Spectroscopy (IR) plays a crucial role in identifying the functional groups involved in the imprinting process and confirming the successful formation of specific binding sites. UV-visible spectrophotometry is employed to monitor the absorption characteristics of the polymers, offering data on the interactions between the template molecules and the polymer matrix. Transmission Electron Microscopy (TEM) provides detailed visualization of the internal structure of MIPs at the nanoscale, revealing the morphology and size of the imprinted cavities. Thermogravimetric Analysis (TGA) assesses the thermal stability and composition of the polymers, identifying decomposition patterns that are indicative of the material’s robustness under different conditions. Finally, the Laser Particle Size Analyzer is used to measure the size distribution of the polymer particles, which is critical for determining the uniformity and efficiency of the imprinting process. The six characterization methods discussed in this paper provide a comprehensive understanding of MIP, and it is hoped that in the future, more optimized design solutions will emerge and their applications in various fields will be enhanced.展开更多
目的建立适用于抹茶品质的可见近红外(visible-nearinfrared,Vis-NIR)光谱快速无损检测模型以实现多种品质指标的定量分析。方法通过Vis-NIR获取抹茶样本的光谱数据,使用一阶导数(first derivative,1^(st))光谱预处理方法,最后采用自助...目的建立适用于抹茶品质的可见近红外(visible-nearinfrared,Vis-NIR)光谱快速无损检测模型以实现多种品质指标的定量分析。方法通过Vis-NIR获取抹茶样本的光谱数据,使用一阶导数(first derivative,1^(st))光谱预处理方法,最后采用自助软收缩法(bootstrapping soft shrinkage,BOSS)、迭代变量子集优化法(iterative variable subset optimization,IVSO)和竞争性自适应重加权采样法(competitive adaptive reweighted sampling,CARS)筛选光谱特征变量,构建抹茶品质指标的偏最小二乘(partial least square,PLS)预测模型,探究光谱信息与茶多酚、游离氨基酸、酚氨比、咖啡碱和可溶性糖之间的定量关系。结果构建的Vis-NIR的CARS-PLS预测模型在抹茶品质指标含量预测方面均获得了最佳结果,预测相关系数(correlation coefficient in the prediction set,Rp)分别为0.9227、0.8906、0.9243、0.9381和0.9522;预测均方根误差(root mean square error in the prediction set,RMSEP)分别为0.867、0.337、0.557、0.216和0.440。结论本研究采用的Vis-NIR光谱技术综合了可见光、短波近红外和长波近红外的优势,在快速无损预测多种抹茶品质指标方面具有良好应用潜力,为抹茶品质的快速无损高效检测提供理论依据和技术支撑。展开更多
文摘Using visible and near-infrared (Vis-NIR) spectroscopy combined with partial least squares (PLS) regression, the rapid reagent-free analysis model for chromium (Cr) content in tideland reclamation soil in the Pearl River Delta, China was established. Based on Savitzky-Golay (SG) smoothing and PLS regression, a multi-parameters optimization platform (SG-PLS) covering 264 modes was constructed to select the appropriately spectral preprocessing mode. The optimal SG-PLS model was determined according to the prediction effect. The selected optimal parameters <em>d, p, m</em> and LV were 2, 6, 23 and 8, respectively. Using the validation samples that were not involved in modeling, the root mean square error (SEP<sub>V</sub>), relative root mean square error (R-SEP<sub>V</sub>) and correlation coefficients (R<sub>P, V</sub>) of prediction were 11.66 mg<span style="white-space:nowrap;">·</span>kg<sup>-1</sup>, 10.7% and 0.722, respectively. The results indicated that the feasibility of using Vis-NIR spectroscopy combined with SG-PLS method to analyze soil Cr content. The constructed multi-parameters optimization platform with SG-PLS is expected to be applied to a wider field of analysis. The rapid detection method has important application values to large-scale agricultural production.
基金Supported by the National Key Technology R&D Program of China (2006BAD02B07)the National Mordern Agricultural Industry System of China(CARS-07-12.5-A12)~~
文摘[Objective] To explore a method for the rapid determination of protein con- tent in grains of Panicum miliaceum L. [Method] The near infrared transmittance spec- troscopy （NITS） was used to build the mathematical models for the quantitative analy- sis of protein content in the grains. Four combinations of treatment that first derivative and second derivative were respectively combined with partial least squares （PLS） and modified partial least squares （MPLS） were set to compare their effects on the original transmission spectrum. [Result] The predicting effects of the 4 combinations were similar. The optimal combination was first derivative with MPLS, in which the average determination coefficient of validation （RSQ） was 0.880 6, correlation coeffi- cient of cross validation （1-VR） was 0.857 0, standard error of calibration （SEC） was 0.342 4, standard error of cross validation （SECV） was 0.375 1, and the standard er- ror of prediction （SEP） was 0.454. [Conclusion] The constructed NITS model is a rapid way for the determination of protein content in grains of P. miliaceum.
文摘High-end wine brand is made through the use of high-quality grape variety and yeast strain, and through a unique process. Not only is it rich in nutrients, but also it has a unique taste and a fragrant scent. Brand identification of wine is difficult and complex because of high similarity. In this paper, visible and near-infrared (NIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA) was used to explore the feasibility of wine brand identification. Chilean Aoyo wine (2016 vintage) was selected as the identification brand (negative, 100 samples), and various other brands of wine were used as interference brands (positive, 373 samples). Samples of each type were randomly divided into the calibration, prediction and validation sets. For comparison, the PLS-DA models were established in three independent and two complex wavebands of visible (400 - 780 nm), short-NIR (780 - 1100 nm), long-NIR (1100 - 2498 nm), whole NIR (780 - 2498 nm) and whole scanning (400 - 2498 nm). In independent validation, the five models all achieved good discriminant effects. Among them, the visible region model achieved the best effect. The recognition-accuracy rates in validation of negative, positive and total samples achieved 100%, 95.6% and 97.5%, respectively. The results indicated the feasibility of wine brand identification with Vis-NIR spectroscopy.
文摘The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C<sub>5</sub>H<sub>10</sub>NNaO<sub>5</sub>) and caramel color (C<sub>6</sub>H<sub>8</sub>O<sub>3</sub>). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RAR<sub>V</sub>) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RAR<sub>V</sub> = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.
文摘The characterization of these molecularly imprinted polymers is essential to understanding their binding dynamics and structural properties. Through the analysis of the current research, it is found that there are overlaps in the methods used by scholars. The Langmuir equation is frequently applied to model the adsorption isotherms of MIPs, providing critical insight into the capacity and affinity of the binding sites. Infrared Spectroscopy (IR) plays a crucial role in identifying the functional groups involved in the imprinting process and confirming the successful formation of specific binding sites. UV-visible spectrophotometry is employed to monitor the absorption characteristics of the polymers, offering data on the interactions between the template molecules and the polymer matrix. Transmission Electron Microscopy (TEM) provides detailed visualization of the internal structure of MIPs at the nanoscale, revealing the morphology and size of the imprinted cavities. Thermogravimetric Analysis (TGA) assesses the thermal stability and composition of the polymers, identifying decomposition patterns that are indicative of the material’s robustness under different conditions. Finally, the Laser Particle Size Analyzer is used to measure the size distribution of the polymer particles, which is critical for determining the uniformity and efficiency of the imprinting process. The six characterization methods discussed in this paper provide a comprehensive understanding of MIP, and it is hoped that in the future, more optimized design solutions will emerge and their applications in various fields will be enhanced.
文摘目的建立适用于抹茶品质的可见近红外(visible-nearinfrared,Vis-NIR)光谱快速无损检测模型以实现多种品质指标的定量分析。方法通过Vis-NIR获取抹茶样本的光谱数据,使用一阶导数(first derivative,1^(st))光谱预处理方法,最后采用自助软收缩法(bootstrapping soft shrinkage,BOSS)、迭代变量子集优化法(iterative variable subset optimization,IVSO)和竞争性自适应重加权采样法(competitive adaptive reweighted sampling,CARS)筛选光谱特征变量,构建抹茶品质指标的偏最小二乘(partial least square,PLS)预测模型,探究光谱信息与茶多酚、游离氨基酸、酚氨比、咖啡碱和可溶性糖之间的定量关系。结果构建的Vis-NIR的CARS-PLS预测模型在抹茶品质指标含量预测方面均获得了最佳结果,预测相关系数(correlation coefficient in the prediction set,Rp)分别为0.9227、0.8906、0.9243、0.9381和0.9522;预测均方根误差(root mean square error in the prediction set,RMSEP)分别为0.867、0.337、0.557、0.216和0.440。结论本研究采用的Vis-NIR光谱技术综合了可见光、短波近红外和长波近红外的优势,在快速无损预测多种抹茶品质指标方面具有良好应用潜力,为抹茶品质的快速无损高效检测提供理论依据和技术支撑。
