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1

Roberto de Alvarenga Junior, Benedito, and Renato Lajarim Carneiro. "Chemometrics Approaches in Forced Degradation Studies of Pharmaceutical Drugs." Molecules 24, no. 20 (October 22, 2019): 3804. http://dx.doi.org/10.3390/molecules24203804.

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Анотація:
Chemometrics is the chemistry field responsible for planning and extracting the maximum of information of experiments from chemical data using mathematical tools (linear algebra, statistics, and so on). Active pharmaceutical ingredients (APIs) can form impurities when exposed to excipients or environmental variables such as light, high temperatures, acidic or basic conditions, humidity, and oxidative environment. By considering that these impurities can affect the safety and efficacy of the drug product, it is necessary to know how these impurities are yielded and to establish the pathway of their formation. In this context, forced degradation studies of pharmaceutical drugs have been used for the characterization of physicochemical stability of APIs. These studies are also essential in the validation of analytical methodologies, in order to prove the selectivity of methods for the API and its impurities and to create strategies to avoid the formation of degradation products. This review aims to demonstrate how forced degradation studies have been actually performed and the applications of chemometric tools in related studies. Some papers are going to be discussed to exemplify the chemometric applications in forced degradation studies.
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2

Sohn, Soo-In, Subramani Pandian, Young-Ju Oh, John-Lewis Zinia Zaukuu, Yong-Ho Lee, and Eun-Kyoung Shin. "Discrimination of Brassica juncea Varieties Using Visible Near-Infrared (Vis-NIR) Spectroscopy and Chemometrics Methods." International Journal of Molecular Sciences 23, no. 21 (October 24, 2022): 12809. http://dx.doi.org/10.3390/ijms232112809.

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Brown mustard (Brassica juncea (L.) is an important oilseed crop that is mostly used to produce edible oils, industrial oils, modified lipids and biofuels in subtropical nations. Due to its higher level of commercial use, the species has a huge array of varieties/cultivars. The purpose of this study is to evaluate the use of visible near-infrared (Vis-NIR) spectroscopy in combination with multiple chemometric approaches for distinguishing four B. juncea varieties in Korea. The spectra from the leaves of four different growth stages of four B. juncea varieties were measured in the Vis-NIR range of 325–1075 nm with a stepping of 1.5 nm in reflectance mode. For effective discrimination, the spectral data were preprocessed using three distinct approaches, and eight different chemometric analyses were utilized. After the detection of outliers, the samples were split into two groups, one serving as a calibration set and the other as a validation set. When numerous preprocessing and chemometric approaches were applied for discriminating, the combination of standard normal variate and deep learning had the highest classification accuracy in all the growth stages achieved up to 100%. Similarly, few other chemometrics also yielded 100% classification accuracy, namely, support vector machine, generalized linear model, and the random forest. Of all the chemometric preprocessing methods, Savitzky–Golay filter smoothing provided the best and most convincing discrimination. The findings imply that chemometric methods combined with handheld Vis-NIR spectroscopy can be utilized as an efficient tool for differentiating B. juncea varieties in the field in all the growth stages.
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3

Singh, Inderbir, Prateek Juneja, Birender Kaur, and Pradeep Kumar. "Pharmaceutical Applications of Chemometric Techniques." ISRN Analytical Chemistry 2013 (October 30, 2013): 1–13. http://dx.doi.org/10.1155/2013/795178.

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Анотація:
Chemometrics involves application of various statistical methods for drawing vital information from various manufacturing-related processes. Multiway chemometric models like parallel factor analysis (PARAFAC), Tucker-3, N-partial least square (N-PLS), and bilinear models like principle component regression (PCR) and partial least squares (PLS) have been discussed in the paper. Chemometric approaches can be used to analyze the data obtained from various instruments including near infrared (NIR), attenuated total reflectance Fourier transform infrared (ATR-FTIR), high-performance liquid chromatography (HPLC), and terahertz pulse spectroscopy. The technique has been used in the quality assurance and quality control of pharmaceutical solid dosage forms. Moreover, application of chemometric methods in the evaluation of properties of pharmaceutical powders and tablet parametric tests has also been discussed in the review. It has been suggested as a useful method for the real-time in-process testing and is a valuable process analytical tool.
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4

Boyd, J. C. "Perspectives on the use of chemometrics in laboratory medicine." Clinical Chemistry 32, no. 9 (September 1, 1986): 1726–33. http://dx.doi.org/10.1093/clinchem/32.9.1726.

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Abstract Today's automated laboratory instruments are capable of generating prodigious volumes of high-quality measurements. Increasingly, the powerful mathematical and statistical methods of chemometrics are being called upon to help reduce these measurements to useful information. Chemometric methods have been important in automating various data-intensive functions of the clinical laboratory, including analysis of cellular images, identification of bacteria and fungi on the basis of their metabolic and chemical properties, and identification of drugs and toxic substances from their mass spectra. These methods also appear promising in aiding both the selection and interpretation of laboratory tests for diagnosis, monitoring, and prognosis. In spite of the demonstrated potential of these methods, significant problems remain to be solved in the areas of measurement standardization, data-base collection, and user familiarity with these approaches before chemometric methods can be used most fully by the clinical laboratory.
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5

Meade, A. D., H. J. Byrne, and F. M. Lyng. "Spectroscopic and chemometric approaches to radiobiological analyses." Mutation Research/Reviews in Mutation Research 704, no. 1-3 (April 2010): 108–14. http://dx.doi.org/10.1016/j.mrrev.2010.01.010.

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6

Sauzier, Georgina, Wilhelm van Bronswijk, and Simon W. Lewis. "Chemometrics in forensic science: approaches and applications." Analyst 146, no. 8 (2021): 2415–48. http://dx.doi.org/10.1039/d1an00082a.

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7

Dinç, Erdal, A. Hakan Aktaş, and Özgür Üstündağ. "New Liquid Chromatographic-Chemometric Approach for the Determination of Sunset Yellow and Tartrazine in Commercial Preparation." Journal of AOAC INTERNATIONAL 88, no. 6 (September 1, 2005): 1748–55. http://dx.doi.org/10.1093/jaoac/88.6.1748.

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Анотація:
Abstract A new liquid chromatographic (LC)-chemometric approach was developed for the determination of sunset yellow (SUN) and tartrazine (TAR) in commercial preparations. This approach uses LC and chemometric calibration methods, i.e., classical least-squares (CLS), principal component regression (PCR), and partial–least squares (PLS), simultaneously. The combined LC-chemometric approaches, denoted as LC-CLS, LC-PCR, and LC-PLS, are based on photodiode array (PDA) detection at multiple wavelengths. Optimum chromatographic separation of SUN and TAR with allura red as the internal standard (IS) was obtained by using a Waters Symmetry® C18 column, 5 μm, 4.6 × 250 mm, and 0.2 M acetate buffer (pH 5)–acetonitrile–methanol–bidistilled water (55 + 20 + 15 + 10, v/v) as the mobile phase at a flow rate of 1.9 mL/min. The LC data sets consisting of the ratios of analyte peak areas to the IS peak area were obtained by using PDA detection at 5 wavelengths (465, 470, 475, 480, and 485 nm). LC-chemometric calibrations for SUN and TAR were separately constructed by using the relationship between the peak-area ratio and the training sets for each colorant. LC-chemometric approaches were tested for different synthetic mixtures containing SUN and TAR in the presence of the IS. These LC-chemometric calibrations were applied to a commercial preparation of the 2 colorants. The experimental results of the LC-chemometric approaches were compared with those obtained by a developed classical LC method using single-wavelength detection.
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8

Ranaweera, Ranaweera K. R., Dimitra L. Capone, Susan E. P. Bastian, Daniel Cozzolino, and David W. Jeffery. "A Review of Wine Authentication Using Spectroscopic Approaches in Combination with Chemometrics." Molecules 26, no. 14 (July 17, 2021): 4334. http://dx.doi.org/10.3390/molecules26144334.

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Анотація:
In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.
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9

Stöckel, S., S. Meisel, M. Elschner, P. Rösch, and J. Popp. "Identification ofBacillus anthracisvia Raman Spectroscopy and Chemometric Approaches." Analytical Chemistry 84, no. 22 (November 6, 2012): 9873–80. http://dx.doi.org/10.1021/ac302250t.

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10

Silva, Carolina S., Maria Fernanda Pimentel, José Manuel Amigo, Carmen García-Ruiz, and Fernando Ortega-Ojeda. "Chemometric approaches for document dating: Handling paper variability." Analytica Chimica Acta 1031 (November 2018): 28–37. http://dx.doi.org/10.1016/j.aca.2018.06.031.

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11

Yehia, Ali M., Heba T. Elbalkiny, Safa’a M. Riad, and Yasser S. Elsaharty. "Application of Chemometrics for Spectral Resolving and Determination of Three Analgesics in Water Samples." Journal of AOAC INTERNATIONAL 103, no. 1 (January 1, 2020): 257–64. http://dx.doi.org/10.5740/jaoacint.19-0140.

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Анотація:
Abstract Background: Chemometrics is a discipline that allows the spectral resolution of drugs in a complicated matrix (e.g., environmental water samples) as an alternative to chromatographic methods. Objective: Three analgesics were traced in wastewater samples with simple and cost-effective multivariate approaches using spectrophotometric data. Methods and Results: Four chemometric approaches were applied for the simultaneous determination of diclofenac, paracetamol, and ibuprofen. Partial least squares (PLS), principal component regression (PCR), artificial neural networks (ANN), and multivariate curve resolution (MCR)–alternating least squares (ALS) were selected. The presented methods were compared and validated for their qualitative and quantitative analyses. Moreover, statistical comparison between the results obtained by the proposed methods and the official methods showed no significant differences. Conclusions: The proposed multivariate calibrations were accurate and specific for quantitative analysis of the studied components. MCR-ALS is the only method that has the capacity for both the quantitative and qualitative analysis of the studied drugs. Highlights: Four chemometric approaches were used for analysis of severally overlapped ternary mixture of three analgesics. The analytical performance of PCR, PLS, MCR-ALS, and ANN was compared and validated in terms of root mean square error of calibration (RMSEC), SE of prediction, and recoveries. ANN gave the highest predicted concentrations with the lowest RMSEC and root mean square error of prediction. MCR-ALS has the capacity for both qualitative and quantitative measurement. The methods have been effectively applied for real samples and compared to official methods.
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12

Etezadi, Haniyeh, S. Maryam Sajjadi, and Aziz Maleki. "Crucial successes in drug delivery systems using multivariate chemometric approaches: challenges and opportunities." New Journal of Chemistry 43, no. 13 (2019): 5077–87. http://dx.doi.org/10.1039/c8nj06272b.

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13

Zappi, Alessandro, Valentina Marassi, Stefano Giordani, Nicholas Kassouf, Barbara Roda, Andrea Zattoni, Pierluigi Reschiglian, and Dora Melucci. "Extracting Information and Enhancing the Quality of Separation Data: A Review on Chemometrics-Assisted Analysis of Volatile, Soluble and Colloidal Samples." Chemosensors 11, no. 1 (January 4, 2023): 45. http://dx.doi.org/10.3390/chemosensors11010045.

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Анотація:
Instrument automation, technological advancements and improved computational power made separation science an extremely data-rich approach, requiring the use of statistical and data analysis tools that are able to optimize processes and combine multiple outputs. The use of chemometrics is growing, greatly improving the ability to extract meaningful information. Separation–multidetection generates multidimensional data, whose elaboration should not be left to the discretion of the operator. However, some applications or techniques still suffer from the lack of method optimization through DoE and downstream multivariate analysis, limiting their potential. This review aims at summarizing how chemometrics can assist analytical chemists in terms of data elaboration and method design, focusing on what can be achieved by applying chemometric approaches to separation science. Recent applications of chemometrics in separation analyses, in particular in gas, liquid and size-exclusion chromatography, together with field flow fractionation, will be detailed to visualize the state of the art of separation chemometrics, encompassing volatile, soluble and solid (colloidal) analytes. The samples considered will range from food chemistry and environmental chemistry to bio/pharmaceutical science.
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14

Yang, Liming, and Qun Sun. "Comparison of chemometric approaches for near-infrared spectroscopic data." Analytical Methods 8, no. 8 (2016): 1914–23. http://dx.doi.org/10.1039/c5ay01304f.

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15

Del Bonis-O’Donnell, Jackson Travis, Rebecca L. Pinals, Sanghwa Jeong, Ami Thakrar, Russ D. Wolfinger, and Markita P. Landry. "Chemometric Approaches for Developing Infrared Nanosensors To Image Anthracyclines." Biochemistry 58, no. 1 (November 27, 2018): 54–64. http://dx.doi.org/10.1021/acs.biochem.8b00926.

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16

Stalikas, Constantine, Yiannis Fiamegos, Vasilios Sakkas, and Triantafyllos Albanis. "Developments on chemometric approaches to optimize and evaluate microextraction." Journal of Chromatography A 1216, no. 2 (January 2009): 175–89. http://dx.doi.org/10.1016/j.chroma.2008.11.060.

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17

Ebrahimi, Pouneh, and Sadegh Salmanpour. "Topical Quercetin Nanoemulsions: Optimization of Preparation Using Chemometric Approaches." Pharmaceutical Chemistry Journal 48, no. 6 (September 2014): 402–7. http://dx.doi.org/10.1007/s11094-014-1120-9.

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18

Ziyatdinova, G. K., A. A. Saveliev, G. A. Evtugyn, and H. C. Budnikov. "Simultaneous voltammetric determination of phenolic antioxidants with chemometric approaches." Electrochimica Acta 137 (August 2014): 114–20. http://dx.doi.org/10.1016/j.electacta.2014.06.009.

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19

Truzzi, Eleonora, Caterina Durante, Davide Bertelli, Benedetta Catellani, Samuele Pellacani, and Stefania Benvenuti. "Rapid Classification and Recognition Method of the Species and Chemotypes of Essential Oils by ATR-FTIR Spectroscopy Coupled with Chemometrics." Molecules 27, no. 17 (August 31, 2022): 5618. http://dx.doi.org/10.3390/molecules27175618.

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Анотація:
In the present work, the applicability of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric tools in recognizing essential oils (EOs) for routine control, was evaluated. EOs belonging to Mentha, Cymbopogon, and Lavandula families and to S. rosmarinus and T. vulgaris species were analyzed, and the performance of several untargeted approaches, based on the synergistic combination of ATR-FTIR and Partial Least Squares Discriminant Analysis (PLS-DA), was tested to classify the species and chemotypes. Different spectra pre-processing methods were employed, and the robustness of the built models was tested by means of a Receiver Operating Characteristic (ROC) curve and random permutations test. The application of these approaches revealed fruitful results in terms of sensitivity and specificity, highlighting the potentiality of ATR-FTIR and chemometrics techniques to be used as a sensitive, cost-effective, and rapid tool to differentiate EO samples according to their species and chemotype.
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20

Booth, David, David Zhu, David Baker, and James Hamburg. "Recent Chemometric Approaches to the Detection of Nuclear Material Losses." Current Analytical Chemistry 1, no. 2 (June 1, 2005): 181–86. http://dx.doi.org/10.2174/1573411054021538.

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21

Dörfer, Thomas, Thomas Bocklitz, Nicolae Tarcea, Michael Schmitt, and Jürgen Popp. "Checking and Improving Calibration of Raman Spectra using Chemometric Approaches." Zeitschrift für Physikalische Chemie 225, no. 6-7 (July 2011): 753–64. http://dx.doi.org/10.1524/zpch.2011.0077.

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22

Dinç, Erdal, and Dumitru Baleanu. "Ultra-Performance Liquid Chromatography for the Multicomponent Analysis of a Ternary Mixture Containing Thiamine, Pyridoxine, and Lidocaine in Ampules." Journal of AOAC INTERNATIONAL 95, no. 3 (May 1, 2012): 903–12. http://dx.doi.org/10.5740/jaoacint.11-199.

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Анотація:
Abstract New chemometric approaches based on the application of partial least squares (PLS) and principal component regression (PCR) algorithms with fractional wavelet transform (FWT) and continuous wavelet transform (CWT) are proposed for the spectrophotometric multicomponent determination of thiamine hydrochloride (B1), pyridoxine hydrochloride (B6), and lidocaine hydrochloride (LID) in ampules without any separation step. In this study PLS and PCR techniques were applied to the raw spectral data, FWT-coefficients, and FWT-CWT-coefficients. These calibration models were labeled as Raw-PLS and Raw-PCR, FWT-PLS and FWT-PCR, and FWT-CWT-PLS and FWT-CWT-PCR, respectively. A new ultra-performance liquid chromatographic (UPLC) method was developed for the comparison of the results obtained by applying the chemometric calibration methods. Chromatographic separation and determination of B1, B6, and LID in ampules were performed on an Acquity UPLC® BEH C18 column (50 × 2.1 mm id, 1.7 μm particle size) using gradient elution with a mobile phase consisting of methanol and 0.01 M HCl at a constant flow rate of 0.6 mL/min. These combined chemometric calibrations and UPLC were validated by analyzing various ternary mixtures, B1, B6, and LID. The proposed chemometric approaches (signal processing-multivariate calibrations) and UPLC method were applied to the quantitative multicomponent analysis of marketed ampules containing the vitamins B1 and B6 with LID.
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23

Tse, Poki, Jenifer Shafer, Samuel A. Bryan, Gilbert L. Nelson, and Amanda M. Lines. "Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet–Visible Spectra." Applied Spectroscopy 76, no. 2 (October 26, 2021): 173–83. http://dx.doi.org/10.1177/00037028211053852.

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Анотація:
Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV–Vis absorbance of neodymium (Nd3+) in the presence of interferents, erbium (Er3+) and copper (Cu2+) under conditions simulating the liquid–liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. The selected chemometric model, partial least squares regression, accurately quantifies Nd3+ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.
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24

Tse, Poki, Jenifer Shafer, Samuel A. Bryan, Gilbert L. Nelson, and Amanda M. Lines. "Measuring Nd(III) Solution Concentration in the Presence of Interfering Er(III) and Cu(II) Ions: A Partial Least Squares Analysis of Ultraviolet–Visible Spectra." Applied Spectroscopy 76, no. 2 (October 26, 2021): 173–83. http://dx.doi.org/10.1177/00037028211053852.

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Анотація:
Optical spectroscopy is a powerful characterization tool with applications ranging from fundamental studies to real-time process monitoring. However, it can be difficult to apply to complex samples that contain interfering analytes which are common in processing streams. Multivariate (chemometric) analysis has been examined for providing selectivity and accuracy to the analysis of optical spectra and expanding its potential applications. Here we will discuss chemometric modeling with an in-depth comparison to more simplistic analysis approaches and outline how chemometric modeling works while exploring the limits on modeling accuracy. Understanding the limitations of the chemometric model can provide better analytical assessment regarding the accuracy and precision of the analytical result. This will be explored in the context of UV–Vis absorbance of neodymium (Nd3+) in the presence of interferents, erbium (Er3+) and copper (Cu2+) under conditions simulating the liquid–liquid extraction approach used to recycle plutonium (Pu) and uranium (U) in used nuclear fuel worldwide. The selected chemometric model, partial least squares regression, accurately quantifies Nd3+ with a low percentage error in the presence of interfering analytes and even under conditions that the training set does not describe.
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25

Pennisi, Francesco, Alessandro Giraudo, Nicola Cavallini, Giovanna Esposito, Gabriele Merlo, Francesco Geobaldo, Pier Luigi Acutis, Marzia Pezzolato, Francesco Savorani, and Elena Bozzetta. "Differentiation between Fresh and Thawed Cephalopods Using NIR Spectroscopy and Multivariate Data Analysis." Foods 10, no. 3 (March 3, 2021): 528. http://dx.doi.org/10.3390/foods10030528.

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Анотація:
The sale of frozen–thawed fish and fish products, labeled as fresh, is currently one of the most common and insidious commercial food frauds. For this reason, the demand of reliable tools to identify the storage conditions is increasing. The present study was performed on two species, commonly sold in large-scale distribution: Cuttlefish (Sepia officinalis) and musky octopus (Eledone spp.). Fifty fresh cephalopod specimens were analyzed at refrigeration temperature (2 ± 2 °C), then frozen at −20 °C for 10 days and finally thawed and analyzed again. The performance of three near-infrared (NIR) instruments in identifying storage conditions were compared: The benchtop NIR Multi Purpose Analyzer (MPA) by Bruker, the portable MicroNIR by VIAVI and the handheld NIR SCiO by Consumer Physics. All collected spectra were processed and analyzed with chemometric methods. The SCiO data were also analyzed using the analytical tools available in the online application provided by the manufacturer to evaluate its performance. NIR spectroscopy, coupled with chemometrics, allowed discriminating between fresh and thawed samples with high accuracy: Cuttlefish between 82.3–94.1%, musky octopus between 91.2–97.1%, global model between 86.8–95.6%. Results show how food frauds could be detected directly in the marketplace, through small, ultra-fast and simplified handheld devices, whereas official control laboratories could use benchtop analytical instruments, coupled with chemometric approaches, to develop accurate and validated methods, suitable for regulatory purposes.
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26

Navarro-Reig, Meritxell, Elena Ortiz-Villanueva, Romà Tauler, and Joaquim Jaumot. "Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches." Metabolites 7, no. 4 (October 24, 2017): 54. http://dx.doi.org/10.3390/metabo7040054.

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27

Gong, Fan, Bo‐Tang Wang, Foo‐Tim Chau, and Yi‐Zeng Liang. "Data Preprocessing for Chromatographic Fingerprint of Herbal Medicine with Chemometric Approaches." Analytical Letters 38, no. 14 (November 2005): 2475–92. http://dx.doi.org/10.1080/00032710500318338.

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28

Nunes, Cleiton A., and Mário C. Guerreiro. "Chemometric approaches on glycerol oxidation with H2O2 over supported gold nanoparticles." Journal of Molecular Catalysis A: Chemical 370 (April 2013): 145–51. http://dx.doi.org/10.1016/j.molcata.2013.01.006.

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29

Ebrahimi, Pouneh. "Erratum to: Topical Quercetin Nanoemulsions: Optimization of Preparation Using Chemometric Approaches." Pharmaceutical Chemistry Journal 48, no. 10 (January 2015): 696. http://dx.doi.org/10.1007/s11094-015-1173-4.

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30

Rudniev, V., E. Simakova-Yefremian, V. Khosha, and V. Ostropilets. "Chemometric Approaches In Analysis Of Vegetable Oils As A Way To Improve An Efficiency Of Forensic Examination." Methods and Objects of Chemical Analysis 14, no. 4 (2019): 192–99. http://dx.doi.org/10.17721/moca.2019.192-199.

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Анотація:
The approach to forensic examination performance through accelerated classification and identification research of vegetable oils is demonstrated. It includes derivatization of the original objects, analysis of obtained methyl esters mixture using GC-MS technique and applying of chemometric tools for gathering preliminary data. Subsequent processing of obtained chromatograms using principal component analysis for grouping of objects simplifies further detailed examination. An analysis of hidden correlations between variables and influence of the initial data on the first to third major components formation is provided. Using values of content of only 5 most widespread fat acids leads to satisfied visual pattern for prior recognition of oil samples. Applying of various split ratios is recommended at different stages of gas-chromatographic analysis. Split ratio 1 : 50 is recommended for gathering of data treated by chemometric methods and 1 : 2 is useful for determination of minor components presence as specific features.
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31

Cavallini, Nicola, Francesco Savorani, Rasmus Bro, and Marina Cocchi. "A Metabolomic Approach to Beer Characterization." Molecules 26, no. 5 (March 8, 2021): 1472. http://dx.doi.org/10.3390/molecules26051472.

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The consumers’ interest towards beer consumption has been on the rise during the past decade: new approaches and ingredients get tested, expanding the traditional recipe for brewing beer. As a consequence, the field of “beeromics” has also been constantly growing, as well as the demand for quick and exhaustive analytical methods. In this study, we propose a combination of nuclear magnetic resonance (NMR) spectroscopy and chemometrics to characterize beer. 1H-NMR spectra were collected and then analyzed using chemometric tools. An interval-based approach was applied to extract chemical features from the spectra to build a dataset of resolved relative concentrations. One aim of this work was to compare the results obtained using the full spectrum and the resolved approach: with a reasonable amount of time needed to obtain the resolved dataset, we show that the resolved information is comparable with the full spectrum information, but interpretability is greatly improved.
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32

Nedyalkova, Miroslava, and Vasil Simeonov. "Multivariate Chemometrics as a Strategy to Predict the Allergenic Nature of Food Proteins." Symmetry 12, no. 10 (September 29, 2020): 1616. http://dx.doi.org/10.3390/sym12101616.

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The purpose of the present study is to develop a simple method for the classification of food proteins with respect to their allerginicity. The methods applied to solve the problem are well-known multivariate statistical approaches (hierarchical and non-hierarchical cluster analysis, two-way clustering, principal components and factor analysis) being a substantial part of modern exploratory data analysis (chemometrics). The methods were applied to a data set consisting of 18 food proteins (allergenic and non-allergenic). The results obtained convincingly showed that a successful separation of the two types of food proteins could be easily achieved with the selection of simple and accessible physicochemical and structural descriptors. The results from the present study could be of significant importance for distinguishing allergenic from non-allergenic food proteins without engaging complicated software methods and resources. The present study corresponds entirely to the concept of the journal and of the Special issue for searching of advanced chemometric strategies in solving structural problems of biomolecules.
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33

Abdelazim, Ahmed H., and Mohammed Shahin. "Different chemometric assisted approaches for spectrophotometric quantitative analysis of lesinurad and allopurinol." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 251 (April 2021): 119421. http://dx.doi.org/10.1016/j.saa.2020.119421.

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34

Karlberg, Bo, and Ralf Torgrip. "Increasing the scope and power of flow-injection analysis through chemometric approaches." Analytica Chimica Acta 500, no. 1-2 (December 2003): 299–306. http://dx.doi.org/10.1016/s0003-2670(03)00562-2.

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35

Medina, Sonia, Rosa Perestrelo, Pedro Silva, Jorge A. M. Pereira, and José S. Câmara. "Current trends and recent advances on food authenticity technologies and chemometric approaches." Trends in Food Science & Technology 85 (March 2019): 163–76. http://dx.doi.org/10.1016/j.tifs.2019.01.017.

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36

dos Santos Freitas, Deisy, and Glaucia Braz Alcantara. "Metabolic Study of Dioecy in Mauritia flexuosa : NMR-based and Chemometric Approaches." Phytochemical Analysis 29, no. 3 (January 21, 2018): 316–24. http://dx.doi.org/10.1002/pca.2745.

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37

Vighi, M., P. Gramatica, F. Consolaro, and R. Todeschini. "QSAR and Chemometric Approaches for Setting Water Quality Objectives for Dangerous Chemicals." Ecotoxicology and Environmental Safety 49, no. 3 (July 2001): 206–20. http://dx.doi.org/10.1006/eesa.2001.2064.

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38

Spanos, Th, V. Simeonov, S. Tsakovski, and D. Thiokas. "Chemometric study of soil analysis data." Open Chemistry 2, no. 2 (June 1, 2004): 402–16. http://dx.doi.org/10.2478/bf02475582.

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AbstractThe present paper deals with chemometric interpretation of soil analysis data collected from 31 sampling sites in the region of Kavala and Drama, Northern Greece. The determination of 16 different chemical and physicochemical characteristics is principally needed for prognosis of the land treatment and fertilizing. The study carried out indicates that the application of multivariate statistical approaches could reveal new and specific information about sampling sites. It has been found that they could be divided into four general patterns: pattern 1 contains dominantly inorganic and alkaline soil samples from semi-mountainous regions in close proximity to the seacoast; pattern 2 indicates the same soil sample type and regional location as pattern 1 but is far from the coastal line; pattern 3 includes samples from sites from the plains with organic and alkaline soils with close proximity to the coast; pattern 4 resembles pattern 3 as soil type but involves samples from sites far from the shore. Further, six latent factors were identified, conditionally named “structural”, “acidic”, “nutritional”, “salt”, “microcomponents” and “organic”. Finally, an apportioning procedure was carried out to find the source contributions in the measured analytical values. In this way the routine estimation of the soil quality could be improved.
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39

Conrad, Anna, Caterina Villari, Patrick Sherwood, and Pierluigi (Enrico) Bonello. "Phenotyping Austrian Pine for Resistance Using Fourier-Transform Infrared Spectroscopy." Arboriculture & Urban Forestry 46, no. 4 (July 1, 2020): 276–86. http://dx.doi.org/10.48044/jauf.2020.020.

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Austrian pine (Pinus nigra) is a valuable component of the urban landscape in the Midwestern USA. In this area, it is impacted by the fungal pathogen Diplodia sapinea, which causes a tip blight and canker on infected trees. While the disease can be managed through the application of fungicides and/or by preventing environmental conditions that are favorable for the pathogen, these practices only temporarily alleviate the problem. A more sustainable solution is to use resistant trees. The objective of this study was to evaluate whether Fourier-transform infrared (FT-IR) spectroscopy combined with chemometric analysis can distinguish between trees that vary in susceptibility to D. sapinea. Trees were phenotyped for resistance to D. sapinea by artificially inoculating shoots and measuring ensuing lesions seven days following inoculation. Then, three different chemometric approaches, including a type of machine learning called support vector machine (SVM), were used to evaluate whether or not trees that varied in susceptibility could be distinguished. Trees that varied in susceptibility could be discriminated based on FT-IR spectra collected prior to pathogen infection using the three chemometric approaches: soft independent modeling of class analogy, partial least squares regression, and SVM. While further validation of the predictive models is needed, the results suggest that the approach may be useful as a tool for screening and breeding Austrian pine for resistance to D. sapinea. Furthermore, this approach may have wide applicability in other tree/plant pathosystems of concern and economic value to the nursery and ornamental industries.
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40

Patel, Kalpana, Priyanka Shah, Purvi Shah, and Tejal Gandhi. "UV-spectrophotometry-assisted chemometric methods for simultaneous determination of ambroxol hydrochloride and doxofylline in pharmaceutical formulation." Journal of Chemical Metrology 14, no. 2 (December 1, 2020): 106–13. http://dx.doi.org/10.25135/jcm.47.20.05.1638.

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Two methods, ratio spectra derivative method and partial least squares regression (PLS) were developed for the simultaneous estimation of ambroxol hydrochloride and doxofylline in combined dosage form. In the first method, ratio spectra derivative method, analytical signals were measured at the wavelengths corresponding to either maximums or minimums for both drugs in the first derivative spectra of the ratio spectra obtained by dividing the standard spectrum of one of two drugs in water. Partial least squares regression (PLS) was used for data analysis of and the parameters of the chemometry procedures were optimized. In this study, the simultaneous determination of ambroxol hydrochloride and doxofylline in pharmaceuticals by chemometric approaches using UV spectrophotometry has been reported. Spectra of ABH and DOX were recorded at several concentrations within their linear ranges between 2-12 μg/mL and 15-40 μg/mL respectively and applied to pharmaceutical formulation, tablet, with no interference with excipients as indicated by the results of the recovery study. The proposed methods are simple, rapid and can be easily used in the quality control of drugs as alternative analytical tools.
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41

Maltsev, Artem S., Nailya N. Umarova, Galina V. Pashkova, Maria M. Mukhamedova, Dmitriy L. Shergin, Vitaly V. Panchuk, Dmitry O. Kirsanov, and Elena I. Demonterova. "Combination of Total-Reflection X-Ray Fluorescence Method and Chemometric Techniques for Praovenance Study of Archaeological Ceramics." Molecules 28, no. 3 (January 21, 2023): 1099. http://dx.doi.org/10.3390/molecules28031099.

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The provenance study of archaeological materials is an important step in understanding the cultural and economic life of ancient human communities. One of the most popular approaches in provenance studies is to obtain the chemical composition of material and process it with chemometric methods. In this paper, we describe a combination of the total-reflection X-ray fluorescence (TXRF) method and chemometric techniques (PCA, k-means cluster analysis, and SVM) to study Neolithic ceramic samples from eastern Siberia (Baikal region). A database of ceramic samples was created and included 10 elements/indicators for classification by geographical origin and ornamentation type. This study shows that PCA cannot be used as the primary method for provenance purposes, but can show some patterns in the data. SVM and k-means cluster analysis classified most of the ceramic samples by archaeological site and type with high accuracy. The application of chemometric techniques also showed the similarity of some samples found at sites located close to each other. A database created and processed by SVM or k-means cluster analysis methods can be supplemented with new samples and automatically classified.
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42

Gupta, Shikha, Nikita Basant, and Kunwar Pal Singh. "Identifying high energy molecules and predicting their detonation potency using chemometric modelling approaches." Combustion Theory and Modelling 19, no. 4 (May 22, 2015): 451–64. http://dx.doi.org/10.1080/13647830.2015.1043747.

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43

Saurina, Javier. "Flow-injection analysis for multi-component determinations of drugs based on chemometric approaches." TrAC Trends in Analytical Chemistry 29, no. 9 (October 2010): 1027–37. http://dx.doi.org/10.1016/j.trac.2010.05.012.

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44

Versari, Andrea, V. Felipe Laurie, Arianna Ricci, Luca Laghi, and Giuseppina P. Parpinello. "Progress in authentication, typification and traceability of grapes and wines by chemometric approaches." Food Research International 60 (June 2014): 2–18. http://dx.doi.org/10.1016/j.foodres.2014.02.007.

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45

Pages, Guilhem, Corinne Delaurent, Roger Phan-Tan-Luu, and Michelle Sergent. "Different chemometric approaches to optimize the assay of St. John's Wort active ingredients." Chemometrics and Intelligent Laboratory Systems 86, no. 2 (April 2007): 159–67. http://dx.doi.org/10.1016/j.chemolab.2006.06.006.

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46

Sigman, Michael E., and Mary R. Williams. "Assessing evidentiary value in fire debris analysis by chemometric and likelihood ratio approaches." Forensic Science International 264 (July 2016): 113–21. http://dx.doi.org/10.1016/j.forsciint.2016.03.051.

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47

Singh, Kunwar P., Shikha Gupta, and Premanjali Rai. "Investigating hydrochemistry of groundwater in Indo-Gangetic alluvial plain using multivariate chemometric approaches." Environmental Science and Pollution Research 21, no. 9 (January 25, 2014): 6001–15. http://dx.doi.org/10.1007/s11356-014-2517-4.

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48

Küçükboyacı, Nurgün, Ayşegül Güvenç, Erdal Dinç, Nezaket Adıgüzel, and Barış Bani. "New HPLC-chemometric approaches to the analysis of isoflavones in Trifolium lucanicum Gasp." Journal of Separation Science 33, no. 17-18 (August 30, 2010): 2558–67. http://dx.doi.org/10.1002/jssc.201000273.

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49

Biancolillo, Alessandra, Federico Marini, Cyril Ruckebusch, and Raffaele Vitale. "Chemometric Strategies for Spectroscopy-Based Food Authentication." Applied Sciences 10, no. 18 (September 18, 2020): 6544. http://dx.doi.org/10.3390/app10186544.

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In the last decades, spectroscopic techniques have played an increasingly crucial role in analytical chemistry, due to the numerous advantages they offer. Several of these techniques (e.g., Near-InfraRed—NIR—or Fourier Transform InfraRed—FT-IR—spectroscopy) are considered particularly valuable because, by means of suitable equipment, they enable a fast and non-destructive sample characterization. This aspect, together with the possibility of easily developing devices for on- and in-line applications, has recently favored the diffusion of such approaches especially in the context of foodstuff quality control. Nevertheless, the complex nature of the signal yielded by spectroscopy instrumentation (regardless of the spectral range investigated) inevitably calls for the use of multivariate chemometric strategies for its accurate assessment and interpretation. This review aims at providing a comprehensive overview of some of the chemometric tools most commonly exploited for spectroscopy-based foodstuff analysis and authentication. More in detail, three different scenarios will be surveyed here: data exploration, calibration and classification. The main methodologies suited to addressing each one of these different tasks will be outlined and examples illustrating their use will be provided alongside their description.
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50

Pandey, Vandana. "Comparative Study of Depuration Rate Prediction against Mussel (Elliptio complanata) using Different Chemometric Approaches." Trends in Sciences 19, no. 10 (May 1, 2022): 3976. http://dx.doi.org/10.48048/tis.2022.3976.

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Different chemometric approaches were applied to a heterogeneous dataset of persistent organic pollutants(POPs), which included polybrominated diphenyl ethers(PBDEs), polychlorinated biphenyls(PCBs) and polycyclic aromatic hydrocarbons(PAHs) with associated depuration rate constant in Mussel (Elliptio complanata), to develop robust quantitative structure-activity relationship(QSAR) models. These models were further validated for statistical significance and predictive ability by internal and external validation. Out of various methods available, genetic algorithm and principal component analysis (PCA) approaches were used to identify relevant molecular descriptors from a large descriptor pool that exhibited a strong correlation with the depuration rate constant values of the diverse dataset. Then, multiple linear regression(MLR) and artificial neural network (ANN) methods were applied to the selected descriptors to create good predictive models. Statistical comparison of 3 hybrid approaches namely, GA-MLR, GA-ANN and PCA-ANN have shown that the genetic algorithm coupled with ANN model is superior to the other 2 models (R2train= 0.961, R2test= 0.947, mapetest= 7.939 and rmsetest=0.128). The applicability domain of the selected models was analyzed using the Euclidean distance and leverage approach signifies that all test set compounds fall within the applicability domain of the developed regression-based models. HIGHLIGHTS Evaluation of toxicokinetic parameters in aquatic ecosystem from the molecular structure satisfies the growing demand of theoretical methods for sustainable chemistry Three different chemometric approaches namely GA-MLR, GA-ANN and PCA-ANN are applied to establish quantitative-structure-activity relationships for the prediction of depuration rate constant values (logkd) of a dataset containing POPs in mussel Elliptio complanata OECD guidelines are used to evaluate and validate the presented models
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