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Zou X, Wang Q, Chen Y, Wang J, Xu S, Zhu Z, Yan C, Shan P, Wang S, Fu Y. Fusion of convolutional neural network with XGBoost feature extraction for predicting multi-constituents in corn using near infrared spectroscopy. Food Chem 2025; 463:141053. [PMID: 39241414 DOI: 10.1016/j.foodchem.2024.141053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 07/31/2024] [Accepted: 08/21/2024] [Indexed: 09/09/2024]
Abstract
Near-infrared (NIR) spectroscopy has been widely utilized to predict multi-constituents of corn in agriculture. However, directly extracting constituent information from the NIR spectra is challenging due to many issues such as broad absorption band, overlapping and non-specific nature. To solve these problems and extract implicit features from the raw data of NIR spectra to improve performance of quantitative models, a one-dimensional shallow convolutional neural network (CNN) model based on an eXtreme Gradient Boosting (XGBoost) feature extraction method was proposed in this paper. The leaf node feature information in the XGBoost was encoded and reconstructed to obtain the implicit features of raw data in the NIR spectra. A two-parametric Swish (TSwish or TS) activation function was proposed to improve the performance of CNN, and the elastic net (EN) was also applied to avoid the overfitting problem of the CNN model. Performance of the developed XGBoost-CNN-TS-EN model was evaluated using two public NIR spectroscopy datasets of corn and soil, and the obtained determination coefficients (R2) for moisture, oil, protein, and starch of the corn on test set were 0.993, 0.991, 0.998, and 0.992, respectively, with that of the soil organic matter being 0.992. The XGBoost-CNN-TS-EN model exhibits superior stability, good prediction accuracy, and generalization ability, demonstrating its great potentials for quantitative analysis of multi-constituents in spectroscopic applications.
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Affiliation(s)
- Xin Zou
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Qiaoyun Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China.
| | - Yinji Chen
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Jilong Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Shunyuan Xu
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Ziheng Zhu
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Chongyue Yan
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Peng Shan
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Shuyu Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - YongQing Fu
- Faculty of Engineering & Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
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Han L, Wang H, Cai W, Shao X. Mechanism of Binding of Polyproline to Ice via Interfacial Water: An Experimental and Theoretical Study. J Phys Chem Lett 2023; 14:4127-4133. [PMID: 37129218 DOI: 10.1021/acs.jpclett.3c00577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The molecular mechanism underlying inhibition of ice growth by polyproline (PPro), a minimal antifreeze glycoprotein mimic, remains unclear. In this work, the change in the structure of water during the growth of ice in PPro solutions was investigated using a combination of near-infrared spectroscopy and molecular dynamics (MD) simulations. The results show that only high concentrations of PPro solutions can effectively inhibit ice growth, as indicated by the variation in the spectral intensity of ice with time. When PPro exhibits an antifreeze effect, the spectral intensity of hydrated water associated with PPro in a solution is weakened. The experiments and MD simulations reveal that the quantity of the interfacial water between the ice crystal and the hydrophobic groups of PPro progressively reaches a plateau. Most significantly, we present clear evidence that the stable existence of this interfacial water is critical for the antifreeze activity of PPro.
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Affiliation(s)
- Li Han
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Haipeng Wang
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, College of Chemistry, Nankai University, Tianjin 300071, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
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Han L, Sun Y, Wang Y, Fu H, Duan C, Wang M, Cai W, Shao X. Ultra-high resolution near-infrared spectrum by wavelet packet transform revealing the hydrogen bond interactions. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 289:122233. [PMID: 36525810 DOI: 10.1016/j.saa.2022.122233] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 12/02/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Resolution is always an obstacle to analyzing the fine structure of a spectrum. The problem is particularly serious in the analysis of the near-infrared (NIR) spectra of aqueous solutions, because the spectrum is generally composed of overlapping broad peaks making the understanding of the structures and the interactions notoriously difficult. In this work, wavelet packet transform (WPT) was adopted to enhance the resolution of the NIR spectra of aqueous mixtures. Due to the microscopic ability of WPT in both position and frequency, the fine details of a spectrum can be observed in the spectral components of different frequencies obtained by WPT decomposition. Ultra-high resolution spectrum can be obtained from the high-frequency component representing the spectral features. Spectral features of different hydrogen-bonded OH, as well as the OH in HOH and HOD, were identified from the high-resolution NIR spectra of water and heavy water mixtures and validated by the variation of the spectral intensity with the mole ratio of H2O and D2O. The high-resolution spectrum was further applied in analyzing the interaction of amine and water. The spectral features of the hydrogen bonding between CH/NH in tert-butylamine (TBA) and OH in water were observed. The structures of CH bonded to one water molecule, and the structures of NH connecting with one and two water molecules were identified.
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Affiliation(s)
- Li Han
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Yan Sun
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Yan Wang
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Haohao Fu
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Chaoshu Duan
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Mian Wang
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Tianjin Key Laboratory of Biosensing and Molecular Recognition, State Key Laboratory of Medicinal Chemical Biology, Nankai University, Tianjin 300071, China; Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China.
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Muncan J, Tsenkova R. Aquaphotomics—Exploring Water Molecular Systems in Nature. Molecules 2023; 28:molecules28062630. [PMID: 36985601 PMCID: PMC10059907 DOI: 10.3390/molecules28062630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 03/05/2023] [Indexed: 03/16/2023] Open
Abstract
Since its birth in 2005, when introduced by Prof [...]
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Wang M, Cai W, Shao X. Resolving Near-Infrared Spectra by Generalized Window Factor Analysis for Understanding Interactions in Aqueous Solution. ANAL LETT 2023. [DOI: 10.1080/00032719.2022.2162914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Mian Wang
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition; State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin, China
| | - Wensheng Cai
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition; State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin, China
| | - Xueguang Shao
- Research Center for Analytical Sciences, Frontiers Science Center for New Organic Matter, College of Chemistry, Nankai University, Tianjin Key Laboratory of Biosensing and Molecular Recognition; State Key Laboratory of Medicinal Chemical Biology, Tianjin, China
- Haihe Laboratory of Sustainable Chemical Transformations, Tianjin, China
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