Advances in Spectroscopic and Chromatographic Techniques

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.7	4.5	2011	16.9 Days	CHF 2400
Catalysts catalysts	3.9	6.3	2011	14.3 Days	CHF 2700
Chemistry chemistry	2.1	2.5	2019	19.1 Days	CHF 1800
Foods foods	5.2	5.8	2012	13.1 Days	CHF 2900
Molecules molecules	4.6	6.7	1996	14.6 Days	CHF 2700
Separations separations	2.6	2.5	2014	13.6 Days	CHF 2600

20 pages, 1720 KiB

Open AccessArticle

Chemical Characterization of Red Wine Polymers and Their Interaction Affinity with Odorants

by Anna Maria Gabler, Annalena Ludwig, Florian Biener, Magdalena Waldner, Corinna Dawid and Oliver Frank

Foods 2024, 13(4), 526; https://doi.org/10.3390/foods13040526 - 08 Feb 2024

Viewed by 629

Abstract

In order to characterize red wine polymers with regard to their binding properties to aroma compounds (odorants), a qualitative and quantitative analysis of chemical degradation products after different chemical treatments (thiolytic, acidic, and alkaline depolymerization) of high -molecular-weight (HMW) fractions of red wine [...] Read more.

In order to characterize red wine polymers with regard to their binding properties to aroma compounds (odorants), a qualitative and quantitative analysis of chemical degradation products after different chemical treatments (thiolytic, acidic, and alkaline depolymerization) of high -molecular-weight (HMW) fractions of red wine was performed. Using ¹H NMR, LC-ToF-MS, LC-MS/MS, and HPIC revealed key structural features such as carbohydrates, organic acids, phenolic compounds, anthocyanins, anthocyanidins, amino acids, and flavan-3-ols responsible for odorant-polymer interactions. Further, NMR-based interaction studies of the selected aroma compounds 3-methylbutanol, cis-whisky lactone, 3-methylbutanoic acid, and 3-isobutyl-2-methoxypyrazine with HMW polymers after chemical treatment demonstrated a reduced interaction affinity of the polymer compared to the native HMW fractions, and further, the importance of aromatic compounds such as flavan-3-ols for the formation of odorant polymer interactions. In addition, these observations could be verified by human sensory experiments. For the first time, the combination of a compositional analysis of red wine polymers and NMR-based interaction studies with chemically treated HMW fractions enabled the direct analysis of the correlation of the polymer’s structure and its interaction affinity with key odorants in red wine. Full article

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18 pages, 4315 KiB

Open AccessArticle

Predictive Analysis of Linoleic Acid in Red Meat Employing Advanced Ensemble Models of Bayesian and CNN-Bi-LSTM Decision Layer Fusion Based Hyperspectral Imaging

by Xiuwei Yan, Sijia Liu, Songlei Wang, Jiarui Cui, Yongrui Wang, Yu Lv, Hui Li, Yingjie Feng, Ruiming Luo, Zhifeng Zhang and Lei Zhang

Foods 2024, 13(3), 424; https://doi.org/10.3390/foods13030424 - 28 Jan 2024

Viewed by 787

Abstract

Rapid non-destructive testing technologies are effectively used to analyze and evaluate the linoleic acid content while processing fresh meat products. In current study, hyperspectral imaging (HSI) technology was combined with deep learning optimization algorithm to model and analyze the linoleic acid content in [...] Read more.

Rapid non-destructive testing technologies are effectively used to analyze and evaluate the linoleic acid content while processing fresh meat products. In current study, hyperspectral imaging (HSI) technology was combined with deep learning optimization algorithm to model and analyze the linoleic acid content in 252 mixed red meat samples. A comparative study was conducted by experimenting mixed sample data preprocessing methods and feature wavelength extraction methods depending on the distribution of linoleic acid content. Initially, convolutional neural network Bi-directional long short-term memory (CNN-Bi-LSTM) model was constructed to reduce the loss of the fully connected layer extracted feature information and optimize the prediction effect. In addition, the prediction process of overfitting phenomenon in the CNN-Bi-LSTM model was also targeted. The Bayesian-CNN-Bi-LSTM (Bayes-CNN-Bi-LSTM) model was proposed to improve the linoleic acid prediction in red meat through iterative optimization of Gaussian process acceleration function. Results showed that best preprocessing effect was achieved by using the detrending algorithm, while 11 feature wavelengths extracted by variable combination population analysis (VCPA) method effectively contained characteristic group information of linoleic acid. The Bi-directional LSTM (Bi-LSTM) model combined with the feature extraction data set of VCPA method predicted 0.860 Rp² value of linoleic acid content in red meat. The CNN-Bi-LSTM model achieved an Rp² of 0.889, and the optimized Bayes-CNN-Bi-LSTM model was constructed to achieve the best prediction with an Rp² of 0.909. This study provided a reference for the rapid synchronous detection of mixed sample indicators, and a theoretical basis for the development of hyperspectral on-line detection equipment. Full article

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17 pages, 2077 KiB

Open AccessArticle

Moderate Signal Enhancement in Electrospray Ionization Mass Spectrometry by Focusing Electrospray Plume with a Dielectric Layer around the Mass Spectrometer’s Orifice

by Zi Qing Chua, Gurpur Rakesh D. Prabhu, Yi-Wun Wang, Chamarthi Maheswar Raju, Krzysztof Buchowiecki, Ochir Ochirov, Decibel P. Elpa and Pawel L. Urban

Molecules 2024, 29(2), 316; https://doi.org/10.3390/molecules29020316 - 08 Jan 2024

Viewed by 980

Abstract

Electrospray ionization (ESI) is among the commonly used atmospheric pressure ionization techniques in mass spectrometry (MS). One of the drawbacks of ESI is the formation of divergent plumes composed of polydisperse microdroplets, which lead to low transmission efficiency. Here, we propose a new [...] Read more.

Electrospray ionization (ESI) is among the commonly used atmospheric pressure ionization techniques in mass spectrometry (MS). One of the drawbacks of ESI is the formation of divergent plumes composed of polydisperse microdroplets, which lead to low transmission efficiency. Here, we propose a new method to potentially improve the transmission efficiency of ESI, which does not require additional electrical components and complex interface modification. A dielectric plate—made of ceramic—was used in place of a regular metallic sampling cone. Due to the charge accumulation on the dielectric surface, the dielectric layer around the MS orifice distorts the electric field, focusing the charged electrospray cloud towards the MS inlet. The concept was first verified using charge measurement on the dielectric material surface and computational simulation; then, online experiments were carried out to demonstrate the potential of this method in MS applications. In the online experiment, signal enhancements were observed for dielectric plates with different geometries, distances of the electrospray needle axis from the MS inlet, and various compounds. For example, in the case of acetaminophen (15 μM), the signal enhancement was up to 1.82 times (plate B) using the default distance of the electrospray needle axis from the MS inlet (d = 1.5 mm) and 12.18 times (plate C) using a longer distance (d = 7 mm). Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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17 pages, 5313 KiB

Open AccessReview

Pros and Cons of Separation, Fractionation and Cleanup for Enhancement of the Quantitative Analysis of Bitumen-Derived Organics in Process-Affected Waters—A Review

by Ralph Hindle, John Headley and Douglas G. Muench

Separations 2023, 10(12), 583; https://doi.org/10.3390/separations10120583 - 24 Nov 2023

Viewed by 1292

Abstract

Oil sands process-affected water (OSPW) contains a diverse mixture of inorganic and organic compounds. Naphthenic acids (NAs) are a subset of the organic naphthenic acid fraction compounds (NAFCs) and are a major contributor of toxicity to aquatic species. Thousands of unique chemical formulae [...] Read more.

Oil sands process-affected water (OSPW) contains a diverse mixture of inorganic and organic compounds. Naphthenic acids (NAs) are a subset of the organic naphthenic acid fraction compounds (NAFCs) and are a major contributor of toxicity to aquatic species. Thousands of unique chemical formulae are measured in OSPW by accurate mass spectrometry and high-resolution mass spectrometry (MS) analysis of NAFCs. As no commercial reference standard is available to cover the range of compounds present in NAFCs, quantitation may best be referred to as “semi-quantitative” and is based on the responses of one or more model compounds. Negative mode electrospray ionization (ESI-) is often used for NAFC measurement but is prone to ion suppression in complex matrices. This review discusses aspects of off-line sample preparation techniques and liquid chromatography (LC) separations to help reduce ion suppression effects and improve the comparability of both inter-laboratory and intra-laboratory results. Alternative approaches to the analytical parameters discussed include extraction solvents, salt content of samples, extraction pH, off-line sample cleanup, on-line LC chromatography, calibration standards, MS ionization modes, NAFC compound classes, MS mass resolution, and the use of internal standards. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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21 pages, 6462 KiB

Open AccessArticle

The Identification of Fritillaria Species Using Hyperspectral Imaging with Enhanced One-Dimensional Convolutional Neural Networks via Attention Mechanism

by Huiqiang Hu, Zhenyu Xu, Yunpeng Wei, Tingting Wang, Yuping Zhao, Huaxing Xu, Xiaobo Mao and Luqi Huang

Foods 2023, 12(22), 4153; https://doi.org/10.3390/foods12224153 - 16 Nov 2023

Viewed by 796

Abstract

Combining deep learning and hyperspectral imaging (HSI) has proven to be an effective approach in the quality control of medicinal and edible plants. Nonetheless, hyperspectral data contains redundant information and highly correlated characteristic bands, which can adversely impact sample identification. To address this [...] Read more.

Combining deep learning and hyperspectral imaging (HSI) has proven to be an effective approach in the quality control of medicinal and edible plants. Nonetheless, hyperspectral data contains redundant information and highly correlated characteristic bands, which can adversely impact sample identification. To address this issue, we proposed an enhanced one-dimensional convolutional neural network (1DCNN) with an attention mechanism. Given an intermediate feature map, two attention modules are constructed along two separate dimensions, channel and spectral, and then combined to enhance relevant features and to suppress irrelevant ones. Validated by Fritillaria datasets, the results demonstrate that an attention-enhanced 1DCNN model outperforms several machine learning algorithms and shows consistent improvements over a vanilla 1DCNN. Notably under VNIR and SWIR lenses, the model obtained 98.97% and 99.35% for binary classification between Fritillariae Cirrhosae Bulbus (FCB) and other non-FCB species, respectively. Additionally, it still achieved an extraordinary accuracy of 97.64% and 98.39% for eight-category classification among Fritillaria species. This study demonstrated the application of HSI with artificial intelligence can serve as a reliable, efficient, and non-destructive quality control method for authenticating Fritillaria species. Moreover, our findings also illustrated the great potential of the attention mechanism in enhancing the performance of the vanilla 1DCNN method, providing reference for other HSI-related quality controls of plants with medicinal and edible uses. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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13 pages, 2646 KiB

Open AccessArticle

Raman Spectrum of the Li₂SO₄-MgSO₄-H₂O System: Excess Spectrum and Hydration Shell Spectrum

by Haiwen Ge and Min Wang

Molecules 2023, 28(21), 7356; https://doi.org/10.3390/molecules28217356 - 31 Oct 2023

Viewed by 921

Abstract

Lithium, as a green energy metal used to promote world development, is an important raw material for lithium-ion, lithium–air, and lithium–sulfur batteries. It is challenging to directly extract lithium resources from brine with a high Mg/Li mass ratio. The microstructure study of salt [...] Read more.

Lithium, as a green energy metal used to promote world development, is an important raw material for lithium-ion, lithium–air, and lithium–sulfur batteries. It is challenging to directly extract lithium resources from brine with a high Mg/Li mass ratio. The microstructure study of salt solutions provides an important theoretical basis for the separation of lithium and magnesium. The changes in the hydrogen bond network structure and ion association of the Li₂SO₄ aqueous solution and Li₂SO₄-MgSO₄-H₂O mixed aqueous solution were studied by Raman spectroscopy. The SO₄²⁻ fully symmetric stretching vibration peak at 940~1020 cm⁻¹ and the O-H stretching vibration peak at 2800~3800 cm⁻¹ of the Li₂SO₄ aqueous solution at room temperature were studied by Raman spectroscopy and excess spectroscopy. According to the peak of the O-H stretching vibration spectrum, with an increase in the mass fraction of the Li₂SO₄ solution, the proportion of DAA-type and DDAA-type hydrogen bonds at low wavenumbers decreases gradually, while the proportion of DA-type hydrogen bonds at 3300 cm⁻¹ increases. When the mass fraction is greater than 6.00%, this proportion increases sharply. Although the spectra of hydrated water molecules and bulk water molecules are different, the spectra of the two water molecules seriously overlap. The spectrum of the anion hydration shell in a solution can be extracted via spectrum division. By analyzing the spectra of these hydration shells, the interaction between the solute and water molecules, the structure of the hydration shell and the number of water molecules are obtained. For the same ionic strength solution, different cationic salts have different hydration numbers of anions, indicating that there is a strong interaction between ions in a strong electrolytic solution, which will lead to ion aggregation and the formation of ion pairs. When the concentration of salt solution increases, the hydration number decreases rapidly, indicating that the degree of ion aggregation increases with increasing concentration. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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21 pages, 9577 KiB

Open AccessArticle

Study of Microstructural, Nutritional, and Biochemical Changes in Hulled and Hulless Barley during Storage Using X-ray and Infrared Techniques

by Navnath S. Indore, Digvir S. Jayas, Chithra Karunakaran, Jarvis Stobbs, Viorica F. Bondici, Miranda Vu, Kaiyang Tu and Omar Marinos

Foods 2023, 12(21), 3935; https://doi.org/10.3390/foods12213935 - 27 Oct 2023

Cited by 1 | Viewed by 1060

Abstract

Four varieties of barley (Esma, AC Metacalf, Tradition, and AB Cattlelac), representing four Canadian barley classes, were stored at 17% moisture content (mc) for 8 week. Stored barely was characterized using synchrotron X-ray phase contrast microcomputed tomography, synchrotron X-ray fluorescence imaging, and mid-infrared [...] Read more.

Four varieties of barley (Esma, AC Metacalf, Tradition, and AB Cattlelac), representing four Canadian barley classes, were stored at 17% moisture content (mc) for 8 week. Stored barely was characterized using synchrotron X-ray phase contrast microcomputed tomography, synchrotron X-ray fluorescence imaging, and mid-infrared spectroscopy at the Canadian Light Source, Saskatoon. The deterioration was observed in all the selected varieties of barley at the end of 8 week of storage. Changes due to spoilage over time were observed in the grain microstructure and its nutrient distribution and composition. This study underscores the critical importance of the initial condition of barley grain microstructure in determining its storage life, particularly under unfavorable conditions. The hulled barley varieties showed more deterioration in microstructure than the hulless varieties of barley, where a direct correlation between microstructural changes and alterations in nutritional content was found. All selected barley classes showed changes in the distribution of nutrients (Ca, Fe, K, Mn, Cu, and Zn), but the two-row AC Metcalf variety exhibited more substantial variations in their nutrient distribution (Zn and Mn) than the other three varieties during storage. The two-row class barley varieties showed more changes in biochemical components (protein, lipids, and carbohydrates) than the six-row class varieties. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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13 pages, 3599 KiB

Open AccessArticle

Silica-Based Stationary Phase with Surface Bound N-Acetyl-glucosamine for Hydrophilic Interaction Liquid Chromatography

by Vaithilingam Rajendiran and Ziad El Rassi

Molecules 2023, 28(20), 7099; https://doi.org/10.3390/molecules28207099 - 15 Oct 2023

Viewed by 886

Abstract

A hydrophilic silica-based stationary phase with surface bound N-acetylglucosamine (GlcNAc-silica) was prepared in house and characterized physically via Fourier transform infrared (FTIR) analysis and thermogravimetric analysis (TGA) and chromatographically over a wide range of mobile phase compositions. While both FTIR and TGA [...] Read more.

A hydrophilic silica-based stationary phase with surface bound N-acetylglucosamine (GlcNAc-silica) was prepared in house and characterized physically via Fourier transform infrared (FTIR) analysis and thermogravimetric analysis (TGA) and chromatographically over a wide range of mobile phase compositions. While both FTIR and TGA confirmed the attachment of the GlcNAc ligands to the silica surface, the chromatographic evaluation of GlcNAc-silica with polar and slightly polar standard solutes (e.g., sugars, nucleic acid fragments, phenolic, and benzoic acid derivatives) yielded the typical hydrophilic interaction liquid chromatography (HILIC) behaviors in the sense that retention increased with increases in solute polarity and the organic content (i.e., acetonitrile) of the hydro-organic mobile phase (i.e., ACN-rich mobile phase). Sugars derivatized with 1-naphthylamine (1-NA) and 2-aminoanthrcene (2-AA) such as xylose, glucose, and short chains maltooligosaccharides constituted the most polar species for HILIC retention evaluation, and in addition, the maltooligosaccharides offered a polar homologous series for gauging the hydrophilicity of GlcNAc-silica in analogy with alkylbenzene homologous series and other nonpolar homologues for evaluating the hydrophobicity of non-polar stationary phases. On the other hand, the benzoic acid and phenolic acid derivatives were the probe solutes for evaluating the HILIC retention dependence of ionizable solutes on the pH of the mobile phase. Similarly, the nucleobase and nucleoside weak basic solutes as well as some typical cyclic nucleotide acidic solutes allowed for the examination of the dependence of solute retention on the pH of the mobile as well as the polarity of the species. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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18 pages, 2726 KiB

Open AccessArticle

Research on the Effects of Drying Temperature for the Detection of Soil Nitrogen by Near-Infrared Spectroscopy

by Ling Zhou, Jiangjun Yao, Honggang Xu, Yahui Zhang and Pengcheng Nie

Molecules 2023, 28(18), 6507; https://doi.org/10.3390/molecules28186507 - 07 Sep 2023

Viewed by 771

Abstract

Nitrogen nitrates play a significant role in the soil’s nutrient cycle, and near-infrared spectroscopy can efficiently and accurately detect the content of nitrate–nitrogen in the soil. Accordingly, it can provide a scientific basis for soil improvement and agricultural productivity by deeply examining the [...] Read more.

Nitrogen nitrates play a significant role in the soil’s nutrient cycle, and near-infrared spectroscopy can efficiently and accurately detect the content of nitrate–nitrogen in the soil. Accordingly, it can provide a scientific basis for soil improvement and agricultural productivity by deeply examining the cycle and transformation pattern of nutrients in the soil. To investigate the impact of drying temperature on NIR soil nitrogen detection, soil samples with different N concentrations were dried at temperatures of 50 °C, 65 °C, 80 °C, and 95 °C, respectively. Additionally, soil samples naturally air-dried at room temperature (25 °C) were used as a control group. Different drying times were modified based on the drying temperature to completely eliminate the impact of moisture. Following data collection with an NIR spectrometer, the best preprocessing method was chosen to handle the raw data. Based on the feature bands chosen by the RFFS, CARS, and SPA methods, two linear models, PLSR and SVM, and a nonlinear ANN model were then established for analysis and comparison. It was found that the drying temperature had a great effect on the detection of soil nitrogen by near-infrared spectroscopy. In the meantime, the SPA-ANN model simultaneously yielded the best and most stable accuracy, with

R_{c}^{2}

= 0.998,

R_{p}^{2}

= 0.989, RMSEC = 0.178 g/kg, and RMSEP = 0.257 g/kg. The results showed that NIR spectroscopy had the least effect and the highest accuracy in detecting nitrogen at 80 °C soil drying temperature. This work provides a theoretical foundation for agricultural production in the future. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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17 pages, 3011 KiB

Open AccessArticle

A Novel Variable Selection Method Based on Binning-Normalized Mutual Information for Multivariate Calibration

by Liang Zhong, Ruiqi Huang, Lele Gao, Jianan Yue, Bing Zhao, Lei Nie, Lian Li, Aoli Wu, Kefan Zhang, Zhaoqing Meng, Guiyun Cao, Hui Zhang and Hengchang Zang

Molecules 2023, 28(15), 5672; https://doi.org/10.3390/molecules28155672 - 26 Jul 2023

Viewed by 948

Abstract

Variable (wavelength) selection is essential in the multivariate analysis of near-infrared spectra to improve model performance and provide a more straightforward interpretation. This paper proposed a new variable selection method named binning-normalized mutual information (B-NMI) based on information entropy theory. “Data binning” was [...] Read more.

Variable (wavelength) selection is essential in the multivariate analysis of near-infrared spectra to improve model performance and provide a more straightforward interpretation. This paper proposed a new variable selection method named binning-normalized mutual information (B-NMI) based on information entropy theory. “Data binning” was applied to reduce the effects of minor measurement errors and increase the features of near-infrared spectra. “Normalized mutual information” was employed to calculate the correlation between each wavelength and the reference values. The performance of B-NMI was evaluated by two experimental datasets (ideal ternary solvent mixture dataset, fluidized bed granulation dataset) and two public datasets (gasoline octane dataset, corn protein dataset). Compared with classic methods of backward and interval PLS (BIPLS), variable importance projection (VIP), correlation coefficient (CC), uninformative variables elimination (UVE), and competitive adaptive reweighted sampling (CARS), B-NMI not only selected the most featured wavelengths from the spectra of complex real-world samples but also improved the stability and robustness of variable selection results. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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15 pages, 1608 KiB

Open AccessArticle

Development of a Green Microwell Spectrofluorimetric Assay with High Analytical Throughput for the Determination of Selective Serotonin Reuptake Inhibitors in Pharmaceutical Dosage Forms and Plasma

by Nourah Z. Alzoman and Ibrahim A. Darwish

Molecules 2023, 28(13), 5221; https://doi.org/10.3390/molecules28135221 - 05 Jul 2023

Cited by 1 | Viewed by 877

Abstract

In this study, a new green microwell spectrofluorimetric assay (MW-SFA) with high throughput was developed and validated, for the first time, for the determination of three selective serotonin reuptake inhibitors (SSRIs) in pharmaceutical dosage forms and plasma. These SSRIs were fluoxetine (FLX), fluvoxamine [...] Read more.

In this study, a new green microwell spectrofluorimetric assay (MW-SFA) with high throughput was developed and validated, for the first time, for the determination of three selective serotonin reuptake inhibitors (SSRIs) in pharmaceutical dosage forms and plasma. These SSRIs were fluoxetine (FLX), fluvoxamine (FXM), and paroxetine (PXT), which are commonly prescribed drugs for depression treatment. The MW-SFA is based on the condensation reaction of SSRIs with 4-chloro-7-nitrobenzo-2-oxa-1,3-diazole (NBD-Cl) in alkaline media to form highly fluorescent derivatives. The MW-SFA procedures were conducted in 96-microwell white opaque assay plates with a flat bottom and the fluorescence signals were measured using a microplate reader at their maximum excitation and emission wavelengths. The calibration curves were generated with good correlation coefficients (0.9992–0.9995) between the relative fluorescence intensity (RFI) and the SSRI concentrations in the range of 35–800 ng/mL. The limits of detection were in the range of 11–25 ng/mL, and the precision and accuracy were satisfactory. The proposed MW-SFA was successfully applied to the analysis of the SSRIs in their pharmaceutical dosage forms. The statistical analysis for the comparison between the MW-SFA assay results and those of pharmacopeial assays showed no significant differences between the assays in terms of their accuracy and precision. The application of the proposed MW-SFA was extended to successfully analyze SSRIs in plasma samples. The greenness of the assay was confirmed using three different metric tools. The assay was characterized with high throughput properties, enabling the sensitive simultaneous analysis of many samples in a short time. This assay is valuable for rapid routine applications in pharmaceutical quality control units and clinical laboratories for the determination of SSRIs. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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17 pages, 2316 KiB

Open AccessArticle

Research on Online Nondestructive Detection Technology of Duck Egg Origin Based on Visible/Near-Infrared Spectroscopy

by Qingxu Li, Wanhuai Zhou, Qiaohua Wang and Dandan Fu

Foods 2023, 12(9), 1900; https://doi.org/10.3390/foods12091900 - 06 May 2023

Cited by 3 | Viewed by 1475

Abstract

As living standards rise, people have higher requirements for the quality of duck eggs. The quality of duck eggs is related to their origin. Thus, the origin traceability and identification of duck eggs are crucial for protecting the rights and interests of consumers [...] Read more.

As living standards rise, people have higher requirements for the quality of duck eggs. The quality of duck eggs is related to their origin. Thus, the origin traceability and identification of duck eggs are crucial for protecting the rights and interests of consumers and preserving food safety. As the world’s largest producer and consumer of duck eggs, China’s duck egg market suffers from a severe lack of duck egg traceability and rapid origin identification technology. As a result, a large number of duck eggs from other regions are sold as products from well-known brands, which seriously undermines the rights and interests of consumers and is not conducive to the sound development of the duck egg industry. To address the above issues, this study collected visible/near-infrared spectral data online from duck eggs of three distinct origins. To reduce noise in the spectral data, various pre-processing algorithms, including MSC, SNV, and SG, were employed to process the spectral data of duck eggs in the range of 400–1100 nm. Meanwhile, CARS and SPA were used to select feature variables that reflect the origin of duck eggs. Finally, classification models of duck egg origin were developed based on RF, SVM, and CNN, achieving the highest accuracy of 97.47%, 98.73%, and 100.00%, respectively. To promote the technology’s implementation in the duck egg industry, an online sorting device was built for duck eggs, which mainly consists of a mechanical drive device, spectral software, and a control system. The online detection performance of the machine was validated using 90 duck eggs, and the final detection accuracy of the RF, SVM, and CNN models was 90%, 91.11%, and 94.44%, with a detection speed of 0.1 s, 0.3 s, and 0.5 s, respectively. These results indicate that visible/near-infrared spectroscopy can be exploited to realize rapid online detection of the origin of duck eggs, and the methodologies used in this study can be immediately implemented in production practice. Full article

(This article belongs to the Topic Advances in Spectroscopic and Chromatographic Techniques)

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