Qualitative and quantitative analysis of Lanmaoa asiatica in different storage years based on FT-NIR combined with chemometrics

Yan, Ziyun; Liu, Honggao; Li, Jieqing; Wang, Yuanzhong

doi:10.1016/j.microc.2023.108580

Cited by 17 publications

(4 citation statements)

References 56 publications

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“…Near-infrared (NIR) spectroscopic analysis can reflect the overtone and combination frequency absorption information of hydrogen-containing functional groups in compounds . By combining chemometric algorithms, a rapid detection model can be established between the spectra and target properties, thus enabling the qualitative or quantitative analysis of samples. − NIR spectroscopy is highly efficient, rapid, and nondestructive and can simultaneously determine multiple components. It has been widely applied in various industries, such as chemical engineering, agriculture, and medicine. − In recent years, researchers have applied NIR spectroscopy to the characterization and quality detection of jet fuels.…”

Section: Introductionmentioning

confidence: 99%

“… 2 By combining chemometric algorithms, a rapid detection model can be established between the spectra and target properties, thus enabling the qualitative or quantitative analysis of samples. 2 − 4 NIR spectroscopy is highly efficient, rapid, and nondestructive and can simultaneously determine multiple components. It has been widely applied in various industries, such as chemical engineering, agriculture, and medicine.…”

Section: Introductionmentioning

confidence: 99%

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Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy

Li,

Zhang,

Zhang

et al. 2024

ACS Omega

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Jet fuel is the primary fuel used in the aviation industry, and its quality has a direct impact on the safety and operational efficiency of aircraft. The accurate quantitative detection and analysis of various physicochemical property indicators are important for improving and ensuring the quality of jet fuel in the domestic market. This study used near-infrared (NIR) spectroscopy to establish a suitable model for the simultaneous and rapid detection of multiple physicochemical properties in jet fuel. Using more than 40 different sources of jet fuel, a rapid detection model was established by optimizing the spectral processing methods. The measurement models were separately built using the partial least-squares (PLS) and orthogonal PLS algorithms, and the model parameters were optimized. The results show that after the Savitzky−Golay second derivative preprocessing, the PLS model built using the feature spectra selected by the uninformative variable elimination wavelength algorithm achieved the best measurement performance. Compared with the PLS model without preprocessing, the range of the resulting accuracy improvement was at least 15.01%. Under the optimal model parameters, the calibration set regression coefficient (R c 2 ) of the 11 jet fuel property index models ranged from 0.9102 to 0.9763, with the root-mean-square error of calibration values up to 0.8468 °C (for flash points). The regression coefficient (R p 2 ) of the validation set ranged from 0.8239 to 0.9557, with the root-mean-square error of prediction values up to 1.1354 °C (for flash points). The ratios of prediction to deviation (RPD) values were all in the range of 1.9−3.0, indicating high accuracy and reliability of the model. The rapid NIR analysis method established in this study enables the simultaneous and rapid detection of multiple physicochemical properties of jet fuel, thereby providing effective technical support for ensuring the quality of jet fuel in the market.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy

Li,

Zhang,

Zhang

et al. 2024

ACS Omega

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“…Chemical analysis is an important method for crop quality evaluation, and common methods include spectroscopic and chromatographic analysis. , Spectrometry is widely used in the characterization of comprehensive chemical information, classification and identification, and content prediction of agricultural products because of its rapidity, convenience and accuracy. , With the wide application of two-dimensional correlation spectroscopy (2DCOS), the ability of spectroscopy to characterize information has been strengthened, and it is capable of obtaining information on interactions within and between molecules, which is conducive to the comprehensive analysis and evaluation of chemical information . Gas chromatography–mass spectrometry (GC-MS) is capable of detecting important chemical components and their relative contents in A. tsao-ko , and in conjunction with spectroscopic and chemometric methods, it can be used to make a preliminary determination of chemical variability in different species of genus Amomum , and is commonly used for the characterization of metabolic phenotypes. , In addition, the use of network pharmacology to predict the medicinal and nutritional values of species based on the results of GC-MS is also an important way to evaluate the quality of crops …”

Section: Introductionmentioning

confidence: 99%

Analysis of Chemical Changes during Maturation of Amomum tsao-ko Based on GC-MS, FT-NIR, and FT-MIR

He,

Yang,

Wang

2024

ACS Omega

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Amomum tsao-ko Crevost et Lemaire (A. tsao-ko) is widely grown for its high nutritional and economic value. However, the lack of a scientific harvesting and quality control system has resulted in an uneven product quality. The present study was based on A. tsao-ko from four maturity stages from the same growing area, and its chemical trends and quality were evaluated using a combination of agronomic trait analysis, spectroscopy, chromatography, chemometrics, and network pharmacology. The results showed that A. tsao-ko was phenotypically dominant in October. Spectroscopy showed that the absorbance intensity at different maturity stages showed a trend of October > September > August > July. Further chemical differences between A. tsao-ko at different stages of maturity were found by chromatography to originate mainly from alcohol, aromatic, acids, esters, hydrocarbons, ketone, heterocyclic, and aldehydes. The network pharmacology results showed that the active ingredient for the treatment of obesity was present in A. tsao-ko and had high levels in A. tsao-ko in September and October. The results of this study provide a new idea for the comprehensive evaluation of A. tsao-ko and a theoretical basis for the harvesting and resource utilization of A. tsao-ko.

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“…As quick, non-destructive and trustworthy procedures for authentication analysis in the food sector, FTIR spectroscopy has arisen, particularly when paired with attenuated total reflectance (ATR) and chemometric software (Cárdenas-Escudero et al, 2023;Melucci et al, 2019;Mendes & Duarte, 2021;Palumbo et al, 2022;Rodriguez-Saona & Allendorf, 2011). Based on FTIR spectral features, this approach can distinguish between real and contaminated food qualitatively and quantitatively (Fajriati et al, 2021;Joshi et al, 2023;Li et al, 2021;Luan et al, 2023;Sousa et al, 2018;Yan et al, 2023). So, this study used FTIR combined with chemometric.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Gelatin on Soft Candy using a Combination of Fourier Transform Infrared Spectroscopy (FTIR) with Chemometrics for Halal Authentication

Salamah,

Jufri,

Susanti

et al. 2023

Indonesian Journal of Halal Research

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The main ingredients of soft candies are gelatin made from the skin/bones of cows and pigs, i.e. bovine and porcine gelatin. This research aims to analyze the present bovine and porcine gelatin in soft candy using a fast and low-cost method. The method used is a combination of FTIR and chemometrics. The reference candy samples were made with formulation porcine gelatin concentrations of 15, 30, 45, 60, 75, 90 and 100%. As a control, we used a bovine gelatin reference candy. All the candy samples were measured with FTIR in the reflection mode in the wavenumber range from 4000 to 500 cm-1. Data analysis was carried out using the chemometric method with the Minitab 18 application. PLS calibration results in y = 0, 99999x + 0.000396 indicate a good correlation. The value of R2 = 0.99999 and the RMSEC of 0.03%. Internal validation with R2 = 0.9999 and RMSECV = 3.69% and external validation with R2 = 0.9994 with RMSEP = 1.28%. The PCA results show different quadrant classifications of bovine and porcine gelatin. Also, there are similarities between the market candy quadrant, bovine gelatin, and porcine gelatin. The fast method and low cost involved simple sample preparation, which were developed to detect and classify the presence of bovine and porcine gelatin in soft candy using FTIR and chemometrics.

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Qualitative and quantitative analysis of Lanmaoa asiatica in different storage years based on FT-NIR combined with chemometrics

Cited by 17 publications

References 56 publications

Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy

Simultaneous Rapid Detection of Multiple Physicochemical Properties of Jet Fuel Using Near-Infrared Spectroscopy

Analysis of Chemical Changes during Maturation of Amomum tsao-ko Based on GC-MS, FT-NIR, and FT-MIR

Analysis of Gelatin on Soft Candy using a Combination of Fourier Transform Infrared Spectroscopy (FTIR) with Chemometrics for Halal Authentication

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