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Cheng C, Chen H, Chen X, Lu M. A Simultaneous Calibration and Detection Strategy for Electrochemical Sensing with High Accuracy in Complex Water. ACS Sens 2024. [PMID: 39078137 DOI: 10.1021/acssensors.4c00759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
The electrochemical sensors loaded with nanomaterials have exhibited a great sensitivity. Nonetheless, the field detection for complex waterbodies can be affected by cross-sensitivity, environmental conditions such as temperature and pH value, as well as the relatively low reproducibility and stability of nanomaterials. In this paper, a simultaneous calibration and detection (SCD) strategy is proposed to introduce a simultaneous and precise calibration during field electrochemical detection, which is composed of a linear regression algorithm and a compact electrochemical sensor containing a series of identical sensing cells. This design can significantly mitigate cross-sensitivity in complex water and the inconsistency of sensing materials. Applied in the NO2- detection for practical waterbodies, the SCD strategy has exhibited a relative error of no more than 9.6% for the measurement compared to the results obtained by the standard Griess method and higher accuracy than the normal electrochemical method. The SCD strategy is independent of sensing materials, indicating that it can be widely applied to various detections by just switching the corresponding sensing material.
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Affiliation(s)
- Chu Cheng
- Pen-Tung Sah Research Institute of Micro-Nano Science & Technology, Xiamen University, Xiamen 361005, China
| | - Hongyu Chen
- Pen-Tung Sah Research Institute of Micro-Nano Science & Technology, Xiamen University, Xiamen 361005, China
| | - Xinyi Chen
- Pen-Tung Sah Research Institute of Micro-Nano Science & Technology, Xiamen University, Xiamen 361005, China
| | - Miao Lu
- Pen-Tung Sah Research Institute of Micro-Nano Science & Technology, Xiamen University, Xiamen 361005, China
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2
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Islam MA, Hossain MS, Hasnat S, Shuvo MH, Akter S, Maria MA, Tahcin A, Hossain MA, Hoque MN. In-silico study unveils potential phytocompounds in Andrographis paniculata against E6 protein of the high-risk HPV-16 subtype for cervical cancer therapy. Sci Rep 2024; 14:17182. [PMID: 39060289 PMCID: PMC11282209 DOI: 10.1038/s41598-024-65112-2] [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: 04/06/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Despite therapeutic advancements, cervical cancer caused by high-risk subtypes of the human papillomavirus (HPV) remains a leading cause of cancer-related deaths among women worldwide. This study aimed to discover potential drug candidates from the Asian medicinal plant Andrographis paniculata, demonstrating efficacy against the E6 protein of high-risk HPV-16 subtype through an in-silico computational approach. The 3D structures of 32 compounds (selected from 42) derived from A. paniculata, exhibiting higher binding affinity, were obtained from the PubChem database. These structures underwent subsequent analysis and screening based on criteria including binding energy, molecular docking, drug likeness and toxicity prediction using computational techniques. Considering the spectrometry, pharmacokinetic properties, docking results, drug likeliness, and toxicological effects, five compounds-stigmasterol, 1H-Indole-3-carboxylic acid, 5-methoxy-, methyl ester (AP7), andrographolide, apigenin and wogonin-were selected as the potential inhibitors against the E6 protein of HPV-16. We also performed 200 ns molecular dynamics simulations of the compounds to analyze their stability and interactions as protein-ligand complexes using imiquimod (CID-57469) as a control. Screened compounds showed favorable characteristics, including stable root mean square deviation values, minimal root mean square fluctuations and consistent radius of gyration values. Intermolecular interactions, such as hydrogen bonds and hydrophobic contacts, were sustained throughout the simulations. The compounds displayed potential affinity, as indicated by negative binding free energy values. Overall, findings of this study suggest that the selected compounds have the potential to act as inhibitors against the E6 protein of HPV-16, offering promising prospects for the treatment and management of CC.
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Affiliation(s)
- Md Aminul Islam
- Advanced Molecular Lab, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, 2310, Bangladesh.
| | - Md Shohel Hossain
- Department of Pharmacy, Jahangirnagar University, Savar, Dhaka, Bangladesh
| | - Soharth Hasnat
- Molecular Biology and Bioinformatics Laboratory, Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh
| | - Mahmudul Hasan Shuvo
- Department of Biochemistry and Molecular Biology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Shilpy Akter
- Department of Pharmacy, Comilla University, Shalmanpur, Bangladesh
| | - Mustary Anjum Maria
- Department of Biochemistry and Molecular Biology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Anika Tahcin
- Department of Biochemistry and Molecular Biology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh
| | - Md Arju Hossain
- Department of Microbiology, Primeasia University, Dhaka, 1213, Bangladesh
| | - M Nazmul Hoque
- Molecular Biology and Bioinformatics Laboratory, Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh.
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3
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Liu J, Yu T, Wang X, Liu X, Wu L, Liu H, Zhao Y, Zhou G, Yu W, Hu B. On-line measurement of COD and nitrate in water against stochastic background interference based on ultraviolet-visible spectroscopy and physics-informed multi-task learning. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2024; 323:124857. [PMID: 39067362 DOI: 10.1016/j.saa.2024.124857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 07/04/2024] [Accepted: 07/19/2024] [Indexed: 07/30/2024]
Abstract
Traditional ultraviolet-visible spectroscopic quantitative analytical methods face challenges in simultaneous and long-term accurate measurement of chemical oxygen demand (COD) and nitrate due to spectral overlap and the interference from stochastic background caused by turbidity and chromaticity in water. Addressing these limitations, a compact dual optical path spectrum detection sensor is introduced, and a novel ultraviolet-visible spectroscopic quantitative analysis model based on physics-informed multi-task learning (PI-MTL) is designed. Incorporating a physics-informed block, the PI-MTL model integrates pre-existing physical knowledge for enhanced feature extraction specific to each task. A multi-task loss wrapper strategy is also employed, facilitating comprehensive loss evaluation and adaptation to stochastic backgrounds. This novel approach significantly outperforms conventional models in COD and nitrate measurement under stochastic background interference, achieving impressive prediction R2 values of 0.941 for COD and 0.9575 for nitrate, while reducing root mean squared error (RMSE) by 60.89 % for COD and 77.3 % for nitrate in comparison to the conventional chemometric model partial least squares regression (PLSR), and by 30.59 % and 65.96 %, respectively, in comparison to a benchmark convolutional neural network (CNN) model. The promising results emphasize its potential as a spectroscopic instrument designed for online multi-parameter water quality monitoring against stochastic background interference, enabling long-term accurate measurement of COD and nitrate levels.
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Affiliation(s)
- Jiacheng Liu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Mechanical Engineering, National University of Singapore, 117575, Singapore
| | - Tao Yu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
| | - Xueji Wang
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China
| | - Xiao Liu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China
| | - Lichao Wu
- Radboud University, Nijmegen, 6525XZ, The Netherlands
| | - Hong Liu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China
| | - Yubo Zhao
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guangya Zhou
- Department of Mechanical Engineering, National University of Singapore, 117575, Singapore
| | - Weixing Yu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China
| | - Bingliang Hu
- Key Laboratory of Spectral Imaging Technology, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
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4
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Zhang L, Huang Z, Zhang X. Quantitative analysis of spectral data based on stochastic configuration networks. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2024; 16:4794-4806. [PMID: 38961818 DOI: 10.1039/d4ay00656a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
In quantitative analysis of spectral data, traditional linear models have fewer parameters and faster computation speed. However, when encountering nonlinear problems, their predictive accuracy tends to be lower. Nonlinear models provide higher computational accuracy in such situations but may suffer from drawbacks such as slow convergence speed and susceptibility to get stuck in local optima. Taking into account the advantages of these two algorithms, this paper introduces the single-hidden layer feedforward neural network named stochastic configuration networks (SCNs) into chemometrics analysis. Firstly, the model termination parameters, that is, the error tolerance and the allowed maximum number of hidden nodes are analyzed. Secondly, times of random configuration are discussed and analyzed, and then the appropriate number is determined by considering the efficiency and stability comprehensively. Finally, predictions made by the SCN are tested on two public datasets. The performance of the SCN is then compared with that of other techniques, including principal component regression (PCR), partial least squares (PLS), back propagation neural network (BPNN), and extreme learning machine (ELM). Experimental results show that the SCN has good stability, high prediction accuracy and efficiency, making it suitable for quantitative analysis of spectral data.
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Affiliation(s)
- Lixin Zhang
- School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing 210014, Jiangsu 210014, China.
- College of Information Engineering, Tarim University, Alar, Xinjiang 843300, China
- Key Laboratory of Tarim Oasis Agriculture, Tarim University, Ministry of Education, China
| | - Zhensheng Huang
- School of Mathematics and Statistics, Nanjing University of Science and Technology, Nanjing 210014, Jiangsu 210014, China.
| | - Xiao Zhang
- College of Information Engineering, Tarim University, Alar, Xinjiang 843300, China
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5
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Yu Y, Jia H, Gao F, Zhu H, Zhang L, Wang J. Spectral fusion-based machine learning classifiers for discriminating membrane breakage in multiple scenarios. WATER RESEARCH 2024; 257:121714. [PMID: 38723357 DOI: 10.1016/j.watres.2024.121714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 04/26/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024]
Abstract
Membrane breakage can lead to filtration failure, which allows harmful substances to enter the effluent, posing potential hazards to human health and the environment. This study is an innovative combination of fluorescence and ultraviolet-visible (UV-Vis) spectroscopy to identify membrane breakage. It aims to unravel more comprehensive information, improve detection sensitivity and selectivity, and enable real-time monitoring capabilities. Fluorescence and UV-Vis data are extracted through variance partitioning analysis (VPA) and integrated through a decision tree algorithm to form a superior system with enhanced discrimination capabilities. VPA improves discrimination efficiency by extracting key information from spectral data and eliminating redundancy. The decision tree algorithm, on the other hand, can process large amounts of data simultaneously. In addition, the method has a wide range of applications and can be used in various scenarios accurately. The scenarios include domestic sewage, micropollutant water, aquaculture wastewater, and secondary treated sewage. The experimental results validate the application of machine learning classifiers in membrane breakage detection with an accuracy rate of 96.8 % to 97.4 %.
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Affiliation(s)
- Yang Yu
- State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Hui Jia
- State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Fei Gao
- State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Haifeng Zhu
- State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
| | - Lei Zhang
- Shenyang Academy of Environmental Sciences, Shenyang 110167, China
| | - Jie Wang
- State Key Laboratory of Separation Membranes and Membrane Processes, Tiangong University, Tianjin 300387, China; School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China; Hebei Industrial Technology Research Institute of Membranes, Cangzhou Institute of Tiangong University, Cangzhou 061000, China.
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6
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Xiao Y, Zhang X, Liu J, Li H, Jiang J, Li Y, Diao S. Prediction of cyanidin 3-rutinoside content in Michelia crassipes based on near-infrared spectroscopic techniques. FRONTIERS IN PLANT SCIENCE 2024; 15:1346192. [PMID: 38766470 PMCID: PMC11099265 DOI: 10.3389/fpls.2024.1346192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 04/17/2024] [Indexed: 05/22/2024]
Abstract
Currently the determination of cyanidin 3-rutinoside content in plant petals usually requires chemical assays or high performance liquid chromatography (HPLC), which are time-consuming and laborious. In this study, we aimed to develop a low-cost, high-throughput method to predict cyanidin 3-rutinoside content, and developed a cyanidin 3-rutinoside prediction model using near-infrared (NIR) spectroscopy combined with partial least squares regression (PLSR). We collected spectral data from Michelia crassipes (Magnoliaceae) tepals and used five different preprocessing methods and four variable selection algorithms to calibrate the PLSR model to determine the best prediction model. The results showed that (1) the PLSR model built by combining the blockScale (BS) preprocessing method and the Significance multivariate correlation (sMC) algorithm performed the best; (2) The model has a reliable prediction ability, with a coefficient of determination (R2) of 0.72, a root mean square error (RMSE) of 1.04%, and a residual prediction deviation (RPD) of 2.06. The model can be effectively used to predict the cyanidin 3-rutinoside content of the perianth slices of M. crassipes, providing an efficient method for the rapid determination of cyanidin 3-rutinoside content.
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Affiliation(s)
- Yuguang Xiao
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
| | - Xiaoshu Zhang
- School of Civil Engineering and Architecture, Xinxiang University, Xinxiang, China
| | - Jun Liu
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
| | - He Li
- Research Institute of Landscape Plants, Guizhou Academy of Forestry, Guiyang, China
| | - Jingmin Jiang
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
| | - Yanjie Li
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
| | - Shu Diao
- Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
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Hou S, Zhang Y, Yuan D, Feng X, Zhang Y. Determination of seawater COD spectra using double-loop contraction and sorted frog optimization. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2024; 89:1613-1629. [PMID: 38619893 DOI: 10.2166/wst.2024.101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 02/02/2024] [Indexed: 04/17/2024]
Abstract
This study develops a novel double-loop contraction and C value sorting selection-based shrinkage frog-leaping algorithm (double-contractive cognitive random field [DC-CRF]) to mitigate the interference of complex salts and ions in seawater on the ultraviolet-visible (UV-Vis) absorbance spectra for chemical oxygen demand (COD) quantification. The key innovations of DC-CRF are introducing variable importance evaluation via C value to guide wavelength selection and accelerate convergence; a double-loop structure integrating random frog (RF) leaping and contraction attenuation to dynamically balance convergence speed and efficiency. Utilizing seawater samples from Jiaozhou Bay, DC-CRF-partial least squares regression (PLSR) reduced the input variables by 97.5% after 1,600 iterations relative to full-spectrum PLSR, RF-PLSR, and CRF-PLSR. It achieved a test R2 of 0.943 and root mean square error of 1.603, markedly improving prediction accuracy and efficiency. This work demonstrates the efficacy of DC-CRF-PLSR in enhancing UV-Vis spectroscopy for rapid COD analysis in intricate seawater matrices, providing an efficient solution for optimizing seawater spectra.
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Affiliation(s)
- Shiwei Hou
- Qilu University of Technology (Shandong Academy of Sciences), Institute of Oceanographic Instrumentation, Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, No 37 Miaoling Road, 266061 Qingdao, China
| | - Yingying Zhang
- Qilu University of Technology (Shandong Academy of Sciences), Institute of Oceanographic Instrumentation, Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, No 37 Miaoling Road, 266061 Qingdao, China E-mail:
| | - Da Yuan
- Qilu University of Technology (Shandong Academy of Sciences), Institute of Oceanographic Instrumentation, Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, No 37 Miaoling Road, 266061 Qingdao, China
| | - Xiandong Feng
- Qilu University of Technology (Shandong Academy of Sciences), Institute of Oceanographic Instrumentation, Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, No 37 Miaoling Road, 266061 Qingdao, China
| | - Ying Zhang
- Qilu University of Technology (Shandong Academy of Sciences), Institute of Oceanographic Instrumentation, Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology, National Engineering and Technological Research Center of Marine Monitoring Equipment, No 37 Miaoling Road, 266061 Qingdao, China
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8
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Li Q, Wu S, Liu Q, Chen S, Chen F. Spectrophotometric determination of COD based on synergistic photocatalysis redox reaction using titanium dioxide nanoparticles and phosphomolybdic heteropoly acid. Talanta 2024; 268:125327. [PMID: 37898033 DOI: 10.1016/j.talanta.2023.125327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 10/16/2023] [Accepted: 10/19/2023] [Indexed: 10/30/2023]
Abstract
Chemical oxygen demand (COD) is one of the important indicators to measure the degree of organic pollution in water. In this work, a rapid spectrophotometric method for detection of COD was achieved based on the oxidation of organics in water by photogenerated holes or free radicals and the reduction of phosphomolybdic heteropolyacid by photogenerated electrons by using TiO2 nanoparticles as a photocatalyst. Taking potassium hydrogen phthalate as the COD standard, under the optimal conditions, the absorbance of reduced phosphomolybdic heteropoly acid was linear with COD in the range of 0.50-100 mg L -1. The detection limit for was COD detection was 0.171 mg L -1. The proposed methods was used for the determination of COD in real water samples, and the results were in general agreement with the national standard method. Compared with the direct photo initiated reduction of phosphomolybdic heteropoly acid without TiO2 nanoparticles, the photocatalytic reaction has better stability and higher efficiency.
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Affiliation(s)
- Qian Li
- Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, 430074, Wuhan, China; Key Laboratory of Material Chemistry for Energy Conversion and Storage (HUST), Ministry of Education, 430074, Wuhan, China; School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China
| | - Shu Wu
- Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, 430074, Wuhan, China; Key Laboratory of Material Chemistry for Energy Conversion and Storage (HUST), Ministry of Education, 430074, Wuhan, China; School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China
| | - Qing Liu
- Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, 430074, Wuhan, China; Key Laboratory of Material Chemistry for Energy Conversion and Storage (HUST), Ministry of Education, 430074, Wuhan, China; School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China
| | - Si Chen
- Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, 430074, Wuhan, China; Key Laboratory of Material Chemistry for Energy Conversion and Storage (HUST), Ministry of Education, 430074, Wuhan, China; School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China
| | - Fang Chen
- Hubei Key Laboratory of Bioinorganic Chemistry & Materia Medica, 430074, Wuhan, China; Key Laboratory of Material Chemistry for Energy Conversion and Storage (HUST), Ministry of Education, 430074, Wuhan, China; School of Chemistry and Chemical Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China.
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Goblirsch T, Mayer T, Penzel S, Rudolph M, Borsdorf H. In Situ Water Quality Monitoring Using an Optical Multiparameter Sensor Probe. SENSORS (BASEL, SWITZERLAND) 2023; 23:9545. [PMID: 38067918 PMCID: PMC10708653 DOI: 10.3390/s23239545] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 03/25/2024]
Abstract
Optical methods such as ultraviolet/visible (UV/Vis) and fluorescence spectroscopy are well-established analytical techniques for in situ water quality monitoring. A broad range of bio-logical and chemical contaminants in different concentration ranges can be detected using these methods. The availability of results in real time allows a quick response to water quality changes. The measuring devices are configured as portable multi-parameter probes. However, their specification and data processing typically cannot be changed by users, or only with difficulties. Therefore, we developed a submersible sensor probe, which combines UV/Vis and fluorescence spectroscopy together with a flexible data processing platform. Due to its modular design in the hardware and software, the sensing system can be modified to the specific application. The dimension of the waterproof enclosure with a diameter of 100 mm permits also its application in groundwater monitoring wells. As a light source for fluorescence spectroscopy, we constructed an LED array that can be equipped with four different LEDs. A miniaturized deuterium-tungsten light source (200-1100 nm) was used for UV/Vis spectroscopy. A miniaturized spectrometer with a spectral range between 225 and 1000 nm permits the detection of complete spectra for both methods.
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Affiliation(s)
- Tobias Goblirsch
- UFZ Helmholtz Centre for Environmental Research, Department Monitoring and Exploration Technologies, Permoserstraße 15, 04318 Leipzig, Germany; (T.M.); (H.B.)
| | - Thomas Mayer
- UFZ Helmholtz Centre for Environmental Research, Department Monitoring and Exploration Technologies, Permoserstraße 15, 04318 Leipzig, Germany; (T.M.); (H.B.)
| | - Stefanie Penzel
- Faculty of Engineering, Leipzig University of Applied Sciences (HTWK Leipzig), Karl-Liebknecht-Straße 134, 04277 Leipzig, Germany; (S.P.); (M.R.)
| | - Mathias Rudolph
- Faculty of Engineering, Leipzig University of Applied Sciences (HTWK Leipzig), Karl-Liebknecht-Straße 134, 04277 Leipzig, Germany; (S.P.); (M.R.)
| | - Helko Borsdorf
- UFZ Helmholtz Centre for Environmental Research, Department Monitoring and Exploration Technologies, Permoserstraße 15, 04318 Leipzig, Germany; (T.M.); (H.B.)
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10
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Tan Z, Liu R, Liu J. BR-Net: Band reweighted network for quantitative analysis of rapeseed protein spectroscopy. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 299:122828. [PMID: 37192577 DOI: 10.1016/j.saa.2023.122828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 04/14/2023] [Accepted: 05/05/2023] [Indexed: 05/18/2023]
Abstract
Compared with the complexity of chemical methods, near-infrared spectroscopy (NIRS) is widely used in the detection of protein content because of its advantages of being fast and non-destructive. Aiming to tackle the problem that the raw near-infrared spectroscopy contains many redundant wavelengths, which affects the accuracy of quantitative prediction and requires expertise to process, we propose an end-to-end network: Band Reweighted Network (BR-Net) that automates wavelength reweighted and quantitative prediction of protein content in rapeseed. Unlike extracting part of wavelengths by the traditional wavelength selection methods, BR-Net retains all spectral wavelengths and assigns different weights to the wavelengths to express the correlation with the corresponding concentration, which enables wavelength selection without ignoring the information contained in the less relevant wavelengths. We compare BR-Net with traditional selection methods such as SPA, LARS, CARS, and UVE to verify its efficiency and robustness, finding that the R2 of the training set and test set are 0.9797 and 0.9215, the RMSEC and RMSEP are 0.4053 and 0.8501, respectively, and the RPD is 3.5686, which prove BR-Net outperforms all the traditional methods. The network described here is universally applicable to a variety of NIR quantitative analyses.
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Affiliation(s)
- Zhenglin Tan
- Department of Cuisine and Nutrition, Hubei University of Economics, Wuhan 430205, China; Hubei Chu Cuisine Research Institute, Wuhan 430205, China
| | - Ruirui Liu
- Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, China
| | - Jun Liu
- Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan 430205, China; School of Computer Science & Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
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Bieroza M, Acharya S, Benisch J, ter Borg RN, Hallberg L, Negri C, Pruitt A, Pucher M, Saavedra F, Staniszewska K, van’t Veen SGM, Vincent A, Winter C, Basu NB, Jarvie HP, Kirchner JW. Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:4701-4719. [PMID: 36912874 PMCID: PMC10061935 DOI: 10.1021/acs.est.2c07798] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 03/03/2023] [Accepted: 03/03/2023] [Indexed: 06/18/2023]
Abstract
High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.
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Affiliation(s)
- Magdalena Bieroza
- Department
of Soil and Environment, SLU, Box 7014, Uppsala 750
07 Sweden
| | - Suman Acharya
- Department
of Environment and Genetics, School of Agriculture, Biomedicine and
Environment, La Trobe University, Albury/Wodonga Campus, Victoria 3690, Australia
| | - Jakob Benisch
- Institute
for Urban Water Management, TU Dresden, Bergstrasse 66, Dresden 01068, Germany
| | | | - Lukas Hallberg
- Department
of Soil and Environment, SLU, Box 7014, Uppsala 750
07 Sweden
| | - Camilla Negri
- Environment
Research Centre, Teagasc, Johnstown Castle, Wexford Y35 Y521, Ireland
- The
James
Hutton Institute, Craigiebuckler, Aberdeen AB15 8QH, United Kingdom
- School
of
Archaeology, Geography and Environmental Science, University of Reading, Whiteknights, Reading RG6 6AB, United Kingdom
| | - Abagael Pruitt
- Department
of Biological Sciences, University of Notre
Dame, Notre
Dame, Indiana 46556, United States
| | - Matthias Pucher
- Institute
of Hydrobiology and Aquatic Ecosystem Management, Vienna University of Natural Resources and Life Sciences, Gregor Mendel Straße 33, Vienna 1180, Austria
| | - Felipe Saavedra
- Department
for Catchment Hydrology, Helmholtz Centre
for Environmental Research - UFZ, Theodor-Lieser-Straße 4, Halle (Saale) 06120, Germany
| | - Kasia Staniszewska
- Department
of Earth and Atmospheric Sciences, University
of Alberta, Edmonton, Alberta T6G 2E3, Canada
| | - Sofie G. M. van’t Veen
- Department
of Ecoscience, Aarhus University, Aarhus 8000, Denmark
- Envidan
A/S, Silkeborg 8600, Denmark
| | - Anna Vincent
- Department
of Biological Sciences, University of Notre
Dame, Notre
Dame, Indiana 46556, United States
| | - Carolin Winter
- Environmental
Hydrological Systems, University of Freiburg, Friedrichstraße 39, Freiburg 79098, Germany
- Department
of Hydrogeology, Helmholtz Centre for Environmental
Research - UFZ, Permoserstr.
15, Leipzig 04318, Germany
| | - Nandita B. Basu
- Department
of Civil and Environmental Engineering and Department of Earth and
Environmental Sciences, and Water Institute, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - Helen P. Jarvie
- Water Institute
and Department of Geography and Environmental Management, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada
| | - James W. Kirchner
- Department
of Environmental System Sciences, ETH Zurich, Zurich CH-8092, Switzerland
- Swiss
Federal Research Institute WSL, Birmensdorf CH-8903, Switzerland
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12
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Chu CH, Lin YX, Liu CK, Lai MC. Development of Innovative Online Modularized Device for Turbidity Monitoring. SENSORS (BASEL, SWITZERLAND) 2023; 23:3073. [PMID: 36991784 PMCID: PMC10051103 DOI: 10.3390/s23063073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/07/2023] [Accepted: 03/09/2023] [Indexed: 06/19/2023]
Abstract
Given progress in water-quality analytical technology and the emergence of the Internet of Things (IoT) in recent years, compact and durable automated water-quality monitoring devices have substantial market potential. Due to susceptibility to the influence of interfering substances, which lowers measurement accuracy, existing automated online monitoring devices for turbidity, a key indicator of a natural water body, feature a single light source and are thus insufficient for more complicated water-quality measurement. The newly developed modularized water-quality monitoring device boasts dual light sources (VIS/NIR), capable of measuring the intensity of scattering, transmission, and reference light at the same time. Coupled with a water-quality prediction model, it can attain a good estimate for continuing monitoring of tap water (<2 NTU, error < 0.16 NTU, relative error < 19.6%) and environmental water samples (<400 NTU, error < 3.86 NTU, relative error < 2.3%). This indicates the optical module can both monitor water quality in low turbidity and provide water-treatment information alerts in high turbidity, thereby materializing automated water-quality monitoring.
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Affiliation(s)
- Chen-Hua Chu
- Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan
| | - Yu-Xuan Lin
- Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan
| | - Chun-Kuo Liu
- Center for Measurement Standards, Industrial Technology Research Institute, Hsinchu 310, Taiwan
| | - Mei-Chun Lai
- Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Hsinchu 310, Taiwan
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13
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Dixon B, Sui C, Briley A, Hsu PC, Howell C. Continuous, Nondestructive Detection of Microorganism Growth at Buried Interfaces with Vascularized Polymers. ACS APPLIED BIO MATERIALS 2023; 6:519-528. [PMID: 36633595 DOI: 10.1021/acsabm.2c00837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Evaluating surface bacterial growth at buried interfaces can be problematic due to the difficulties associated with obtaining samples. In this work, we present a new method to detect signals from microorganisms at buried interfaces that is nondestructive and can be conducted continuously. Inspired by vascular systems in nature that permit chemical communication between the surface and underlying tissues of an organism, we created a system in which an inert carrier fluid could be introduced into an empty vascular network embedded in a polymer matrix. When a microorganism layer was grown on top, small molecules produced by the growth process would diffuse down into the carrier fluid, which could then be collected and analyzed. We used this system to nondestructively detect signals from a surface layer of Escherichia coli using conductivity, ultraviolet-visible (UV-vis) absorbance spectroscopy, and high-performance liquid chromatography (HPLC) for organic acids, methods that ranged in sensitivity, time-to-result, and cost. Carrier fluid from sample vascularized polymers with surface bacterial growth recorded significantly higher values in both conductivity and absorbance at 350 nm compared to controls with no bacteria after 24 h. HPLC analysis showed three clear peaks that varied between the samples with bacteria and the controls without. Tests tracking the change in signals over 48 h showed clear trends that matched the bacterial growth curves, demonstrating the system's ability to monitor changes over time. A 2D finite element model of the system closely matched the experimental results, confirming the predictability of the system. Finally, tests using clinically relevant Staphylococcus aureus and Pseudomonas aeruginosa yielded differences in conductivity, absorbance, and HPLC peak areas unique to each species. This work lays the foundation for the use of vascularized polymers as an adaptive system for the continuous, nondestructive detection of surface microorganisms at buried interfaces in both industry and medicine.
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Affiliation(s)
- Brandon Dixon
- Department of Chemical and Biomedical Engineering, University of Maine, Orono, Maine04469, United States
| | - Chenxi Sui
- Thomas Lord Department of Mechanical Engineering and Material Science, Duke University, Durham, North Carolina27708, United States
| | - Anna Briley
- Department of Chemical and Biomedical Engineering, University of Maine, Orono, Maine04469, United States
| | - Po-Chun Hsu
- Thomas Lord Department of Mechanical Engineering and Material Science, Duke University, Durham, North Carolina27708, United States.,Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois60637, United States
| | - Caitlin Howell
- Department of Chemical and Biomedical Engineering, University of Maine, Orono, Maine04469, United States.,Graduate School of Biomedical Science and Engineering, University of Maine, Orono, Maine04469, United States
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14
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Li L, Liang T, Qiu S, Zhang Y, Qu J, Liu T, Ma F. A rapid and simplified method for evaluating the performance of fungi-algae pellets: A hierarchical analysis model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 860:160442. [PMID: 36435261 DOI: 10.1016/j.scitotenv.2022.160442] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/08/2022] [Accepted: 11/19/2022] [Indexed: 06/16/2023]
Abstract
Microbial pellets technology has undergone extensive research recently and has increasingly matured, showing significant promise. However, the performance of microbial pellets cannot be predicted quickly by the current evaluating methods because they are complicated to operate, take a long time, and pose a risk to the environment. In this study, a representative microbial pellet, fungi-algae pellet, was selected as the research object. Eight evaluation parameters and four evaluation indices were chosen to construct the performance evaluation system of the fungal-algal pellets using the analytic hierarchy process (AHP) and weighting method. Combining the correlation analysis and expert opinion, we found that among the eight parameters selected, the adsorption saturation rate of mycelial pellets on algae had the most significant influence weight on the performance of fungi-algae pellet, followed by algal culture time and fungal incubation time. This research proposes and validates the Performance Evaluation Value (PEV) of fungi-algae pellet and its calculation method. We also discuss the effectiveness of this new evaluation system in saving time, cost, and emission reductions. The results of this paper enable the rapid evaluation of fungi-algae pellets and promote the better development of fungi-algae pellets technology and even other multi-microbial symbiotic pellet technologies.
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Affiliation(s)
- Lixin Li
- School of Environment and Chemical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China.
| | - Taojie Liang
- School of Environment and Chemical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China; School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou 510006, China
| | - Shan Qiu
- State Key Lab of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Yanlong Zhang
- Department of Environmental Science and Engineering, Nankai University Binhai College, Tianjin 300270, China
| | - Jiwei Qu
- School of Environment and Chemical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China
| | - Tiantian Liu
- School of Environment and Chemical Engineering, Heilongjiang University of Science and Technology, Harbin 150022, China
| | - Fang Ma
- State Key Lab of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China
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15
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Tian L, Song X, Liu T, Li A, Ning Y, Hua X, Dong D, Liang D. A combined UV-visible with fluorescence detection method based on an unlabeled aptamer and AuNPs for the sensitive detection of acetamiprid. NEW J CHEM 2023. [DOI: 10.1039/d3nj00399j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
Abstract
A simple spectral method with a wider detection range is proposed for the detection of acetamiprid.
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Affiliation(s)
- Liran Tian
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Xiangwei Song
- School of Life Sciences, Changchun Normal University, Changchun 130031, P. R. China
| | - Tianjiao Liu
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Anfeng Li
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Yang Ning
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Xiuyi Hua
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Deming Dong
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
| | - Dapeng Liang
- Key Laboratory of Groundwater Resources and Environment of Ministry of Education, College of New Energy and Environment, Jilin University, Changchun, 130012, P. R. China
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16
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Xia M, Yang R, Yin G, Chen X, Chen J, Zhao N. A method based on a one-dimensional convolutional neural network for UV-vis spectrometric quantification of nitrate and COD in water under random turbidity disturbance scenario. RSC Adv 2022; 13:516-526. [PMID: 36605648 PMCID: PMC9773182 DOI: 10.1039/d2ra06952k] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
This paper proposed a novel spectrometric quantification method for nitrate and COD concentration in water using a double-channel 1-D convolution neural network for relatively long UV-vis absorption spectra data (2600 points). To improve the model's ability to resist turbidity disturbance, a new dataset augmentation method was applied and the absorption spectra of nitrate and COD under different turbidity disturbances were successfully simulated. Compared to the PLSR model, the value of RRMSEP for the CNN model was reduced from 6.1% to 1.4% in nitrate solution and 4.5% to 1.3% in COD solution. Compared to the PLSR model, the regression accuracy of the CNN model was increased from 56% to 93% in nitrate solution and 68% to 91% in COD solution. The test on the actual solution under different turbidity disturbances shows that the 1D-CNN model had a bias rate of less than 2% in both nitrate and COD solutions, while the worst bias rate in the PLSR method was 15%.
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Affiliation(s)
- Meng Xia
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China,University of Science and Technology of ChinaHefei 230026China
| | - Ruifang Yang
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China
| | - Gaofang Yin
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China
| | - Xiaowei Chen
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China
| | - Jingsong Chen
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China,University of Science and Technology of ChinaHefei 230026China
| | - Nanjing Zhao
- Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences350 Shushanhu RoadHefei 230031China,Institutes of Physical Science and Information Technology, Anhui UniversityHefei 230601China
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17
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Detection Limits of Antibiotics in Wastewater by Real-Time UV–VIS Spectrometry at Different Optical Path Length. Processes (Basel) 2022. [DOI: 10.3390/pr10122614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Real-time monitoring of antibiotics in hospital and pharmaceutical wastewater using ultraviolet–visible (UV–Vis) spectroscopy is considered a promising method. Although gas chromatography–mass spectrometry (GC–MS) and other methods can detect antibiotics with quite low limits of detection (LOD), they possess various limitations. UV–Vis spectroscopy combined with chemometric methods is a promising choice for monitoring antibiotics. In this study, two immersed in situ UV–Vis sensors were used to explore the relationship between absorption spectra and antibiotics and study the influence of the optical path length on the LOD. The LODs of sensor 2 using a 10 cm optical path is up to 300 times lower than that of sensor 1 using a 0.5 mm optical path. Moreover, multiple antibiotics in the wastewater were investigated in real-time manner. The absorption spectra of 70 groups of wastewater samples containing different concentrations of tetracycline, ofloxacin, and chloramphenicol were measured. The results indicate that the nine wavelengths selected by interval partial least squares (iPLS) after the second derivative pretreatment have better predictability for ofloxacin and the six wavelengths selected by competitive adaptive reweighted sampling (CARS) after the first derivative. The multi-fold cross-validation results indicate that the model has a good predictive ability.
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18
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Robust off-grid analyser for autonomous remote in-situ monitoring of nitrate and nitrite in water. TALANTA OPEN 2022. [DOI: 10.1016/j.talo.2022.100173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
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19
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Almaviva S, Artuso F, Giardina I, Lai A, Pasquo A. Fast Detection of Different Water Contaminants by Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22218338. [PMID: 36366036 PMCID: PMC9655218 DOI: 10.3390/s22218338] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 10/20/2022] [Accepted: 10/25/2022] [Indexed: 05/14/2023]
Abstract
Fast monitoring of water quality is a fundamental part of environmental management and protection, in particular, the possibility of qualitatively and quantitatively determining its contamination at levels that are dangerous for human health, fauna and flora. Among the techniques currently available, Raman spectroscopy and its variant, Surface-Enhanced Raman Spectroscopy (SERS), have several advantages, including no need for sample preparation, quick and easy operation and the ability to operate on the field. This article describes the application of the Raman and SERS technique to liquid samples contaminated with different classes of substances, including nitrates, phosphates, pesticides and their metabolites. The technique was also used for the detection of the air pollutant polycyclic aromatic hydrocarbons and, in particular, benzo(a)pyrene, considered as a reference for the carcinogenicity of the whole class of these compounds. To pre-concentrate the analytes, we applied a methodology based on the well-known coffee-ring effect, which ensures preconcentration of the analytes without any pretreatment of the sample, providing a versatile approach for fast and in-situ detection of water pollutants. The obtained results allowed us to reveal these analytes at low concentrations, close to or lower than their regulatory limits.
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20
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Guo S, Du J, Yan F, Wang Z, Wang J. Fabrication of anti-fouling polyamide nanofiltration membrane by incorporating streptomycin as a novel co-monomer. Chin J Chem Eng 2022. [DOI: 10.1016/j.cjche.2022.07.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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21
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Pandiselvam R, Kaavya R, Martinez Monteagudo SI, Divya V, Jain S, Khanashyam AC, Kothakota A, Prasath VA, Ramesh SV, Sruthi NU, Kumar M, Manikantan MR, Kumar CA, Khaneghah AM, Cozzolino D. Contemporary Developments and Emerging Trends in the Application of Spectroscopy Techniques: A Particular Reference to Coconut ( Cocos nucifera L.). Molecules 2022; 27:molecules27103250. [PMID: 35630725 PMCID: PMC9147692 DOI: 10.3390/molecules27103250] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/07/2022] [Accepted: 05/16/2022] [Indexed: 12/26/2022] Open
Abstract
The number of food frauds in coconut-based products is increasing due to higher consumer demands for these products. Rising health consciousness, public awareness and increased concerns about food safety and quality have made authorities and various other certifying agencies focus more on the authentication of coconut products. As the conventional techniques for determining the quality attributes of coconut are destructive and time-consuming, non-destructive testing methods which are accurate, rapid, and easy to perform with no detrimental sampling methods are currently gaining importance. Spectroscopic methods such as nuclear magnetic resonance (NMR), infrared (IR)spectroscopy, mid-infrared (MIR)spectroscopy, near-infrared (NIR) spectroscopy, ultraviolet-visible (UV-VIS) spectroscopy, fluorescence spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and Raman spectroscopy (RS) are gaining in importance for determining the oxidative stability of coconut oil, the adulteration of oils, and the detection of harmful additives, pathogens, and toxins in coconut products and are also employed in deducing the interactions in food constituents, and microbial contaminations. The objective of this review is to provide a comprehensive analysis on the various spectroscopic techniques along with different chemometric approaches for the successful authentication and quality determination of coconut products. The manuscript was prepared by analyzing and compiling the articles that were collected from various databases such as PubMed, Google Scholar, Scopus and ScienceDirect. The spectroscopic techniques in combination with chemometrics were shown to be successful in the authentication of coconut products. RS and NMR spectroscopy techniques proved their utility and accuracy in assessing the changes in coconut oil’s chemical and viscosity profile. FTIR spectroscopy was successfully utilized to analyze the oxidation levels and determine the authenticity of coconut oils. An FT-NIR-based analysis of various coconut samples confirmed the acceptable levels of accuracy in prediction. These non-destructive methods of spectroscopy offer a broad spectrum of applications in food processing industries to detect adulterants. Moreover, the combined chemometrics and spectroscopy detection method is a versatile and accurate measurement for adulterant identification.
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Affiliation(s)
- Ravi Pandiselvam
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR-Central Plantation Crops Research Institute, Kasaragod 671124, Kerala, India;
- Correspondence: or (R.P.); (R.K.); (M.R.M.); (A.M.K.); (D.C.)
| | - Rathnakumar Kaavya
- Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007, USA;
- Correspondence: or (R.P.); (R.K.); (M.R.M.); (A.M.K.); (D.C.)
| | - Sergio I. Martinez Monteagudo
- Dairy and Food Science Department, South Dakota State University, Brookings, SD 57007, USA;
- Department of Family and Consumer Sciences, New Mexico State University, Las Cruces, NM 88003, USA
- Chemical & Materials Engineering Department, New Mexico State University, Las Cruces, NM 88003, USA
| | - V. Divya
- School of BioSciences and Technology, VIT University, Vellore 632014, Tamil Nadu, India;
| | - Surangna Jain
- Department of Biotechnology, Mahidol University, Bangkok 12120, Thailand;
| | | | - Anjineyulu Kothakota
- Agro-Processing & Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Trivandrum 695019, Kerala, India;
| | - V. Arun Prasath
- Department of Food Process Engineering, NIT, Rourkela 769008, Odisha, India;
| | - S. V. Ramesh
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR-Central Plantation Crops Research Institute, Kasaragod 671124, Kerala, India;
| | - N. U. Sruthi
- Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur 721302, West Bengal, India;
| | - Manoj Kumar
- Chemical and Biochemical Processing Division, ICAR-Central Institute for Research on Cotton Technology, Mumbai 400019, Maharashtra, India;
| | - M. R. Manikantan
- Physiology, Biochemistry and Post-Harvest Technology Division, ICAR-Central Plantation Crops Research Institute, Kasaragod 671124, Kerala, India;
- Correspondence: or (R.P.); (R.K.); (M.R.M.); (A.M.K.); (D.C.)
| | - Chinnaraja Ashok Kumar
- Department of Food Safety and Quality Assurance, College of Food and Dairy Technology, Chennai 600051, Tamil Nadu, India;
| | - Amin Mousavi Khaneghah
- Department of Food Science and Nutrition, Faculty of Food Engineering, University of Campinas (UNICAMP), Campinas 13083-875, SP, Brazil
- Department of Fruit and Vegetable Product Technology, Prof. Wacław Dąbrowski Institute of Agricultural and Food Biotechnology, 02-532 Warsaw, Poland
- Correspondence: or (R.P.); (R.K.); (M.R.M.); (A.M.K.); (D.C.)
| | - Daniel Cozzolino
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Brisbane 4072, Australia
- Correspondence: or (R.P.); (R.K.); (M.R.M.); (A.M.K.); (D.C.)
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22
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Tirado-Kulieva VA, Hernández-Martínez E, Suomela JP. Non-destructive assessment of vitamin C in foods: a review of the main findings and limitations of vibrational spectroscopic techniques. Eur Food Res Technol 2022. [DOI: 10.1007/s00217-022-04023-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
AbstractThe constant increase in the demand for safe and high-quality food has generated the need to develop efficient methods to evaluate food composition, vitamin C being one of the main quality indicators. However, its heterogeneity and susceptibility to degradation makes the analysis of vitamin C difficult by conventional techniques, but as a result of technological advances, vibrational spectroscopy techniques have been developed that are more efficient, economical, fast, and non-destructive. This review focuses on main findings on the evaluation of vitamin C in foods by using vibrational spectroscopic techniques. First, the fundamentals of ultraviolet–visible, infrared and Raman spectroscopy are detailed. Also, chemometric methods, whose use is essential for a correct processing and evaluation of the spectral information, are described. The use and importance of vibrational spectroscopy in the evaluation of vitamin C through qualitative characterization and quantitative analysis is reported. Finally, some limitations of the techniques and potential solutions are described, as well as future trends related to the utilization of vibrational spectroscopic techniques.
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23
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Shi Z, Chow CWK, Fabris R, Liu J, Jin B. Applications of Online UV-Vis Spectrophotometer for Drinking Water Quality Monitoring and Process Control: A Review. SENSORS 2022; 22:s22082987. [PMID: 35458971 PMCID: PMC9024714 DOI: 10.3390/s22082987] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 03/22/2022] [Accepted: 04/07/2022] [Indexed: 01/27/2023]
Abstract
Water quality monitoring is an essential component of water quality management for water utilities for managing the drinking water supply. Online UV-Vis spectrophotometers are becoming popular choices for online water quality monitoring and process control, as they are reagent free, do not require sample pre-treatments and can provide continuous measurements. The advantages of the online UV-Vis sensors are that they can capture events and allow quicker responses to water quality changes compared to conventional water quality monitoring. This review summarizes the applications of online UV-Vis spectrophotometers for drinking water quality management in the last two decades. Water quality measurements can be performed directly using the built-in generic algorithms of the online UV-Vis instruments, including absorbance at 254 nm (UV254), colour, dissolved organic carbon (DOC), total organic carbon (TOC), turbidity and nitrate. To enhance the usability of this technique by providing a higher level of operations intelligence, the UV-Vis spectra combined with chemometrics approach offers simplicity, flexibility and applicability. The use of anomaly detection and an early warning was also discussed for drinking water quality monitoring at the source or in the distribution system. As most of the online UV-Vis instruments studies in the drinking water field were conducted at the laboratory- and pilot-scale, future work is needed for industrial-scale evaluation with ab appropriate validation methodology. Issues and potential solutions associated with online instruments for water quality monitoring have been provided. Current technique development outcomes indicate that future research and development work is needed for the integration of early warnings and real-time water treatment process control systems using the online UV-Vis spectrophotometers as part of the water quality management system.
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Affiliation(s)
- Zhining Shi
- School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia; (Z.S.); (B.J.)
| | - Christopher W. K. Chow
- Sustainable Infrastructure and Resource Management, UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
- Future Industries Institute, University of South Australia, Mawson Lakes, SA 5095, Australia
- Correspondence:
| | - Rolando Fabris
- South Australia Water Corporation, Adelaide, SA 5000, Australia;
| | - Jixue Liu
- UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia;
| | - Bo Jin
- School of Chemical Engineering and Advanced Materials, The University of Adelaide, Adelaide, SA 5005, Australia; (Z.S.); (B.J.)
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24
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Abstract
Nitrogen species present in the atmosphere, soil, and water play a vital role in ecosystem stability. Reactive nitrogen gases are key air quality indicators and are responsible for atmospheric ozone layer depletion. Soil nitrogen species are one of the primary macronutrients for plant growth. Species of nitrogen in water are essential indicators of water quality, and they play an important role in aquatic environment monitoring. Anthropogenic activities have highly impacted the natural balance of the nitrogen species. Therefore, it is critical to monitor nitrogen concentrations in different environments continuously. Various methods have been explored to measure the concentration of nitrogen species in the air, soil, and water. Here, we review the recent advancements in optical and electrochemical sensing methods for measuring nitrogen concentration in the air, soil, and water. We have discussed the advantages and disadvantages of the existing methods and the future prospects. This will serve as a reference for researchers working with environment pollution and precision agriculture.
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25
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Ovung A, Mavani A, Ghosh A, Chatterjee S, Das A, Suresh Kumar G, Ray D, Aswal VK, Bhattacharyya J. Heme Protein Binding of Sulfonamide Compounds: A Correlation Study by Spectroscopic, Calorimetric, and Computational Methods. ACS OMEGA 2022; 7:4932-4944. [PMID: 35187312 PMCID: PMC8851458 DOI: 10.1021/acsomega.1c05554] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 01/24/2022] [Indexed: 05/16/2023]
Abstract
Protein-ligand interaction studies are useful to determine the molecular mechanism of the binding phenomenon, leading to the establishment of the structure-function relationship. Here, we report the binding of well-known antibiotic sulfonamide drugs (sulfamethazine, SMZ; and sulfadiazine, SDZ) with heme protein myoglobin (Mb) using spectroscopic, calorimetric, ζ potential, and computational methods. Formation of a 1:1 complex between the ligand and Mb through well-defined equilibrium was observed. The binding constants obtained between Mb and SMZ/SDZ drugs were on the order of 104 M-1. SMZ with two additional methyl (-CH3) substitutions has higher affinity than SDZ. Upon drug binding, a notable loss in the helicity (via circular dichroism) and perturbation of the three-dimensional (3D) protein structure (via infrared and synchronous fluorescence experiments) were observed. The binding also indicated the dominance of non-polyelectrolytic forces between the amino acid residues of the protein and the drugs. The ligand-protein binding distance signified high probability of energy transfer between them. Destabilization of the protein structure upon binding was evident from differential scanning calorimetry results and ζ potential analyses. Molecular docking presented the best probable binding sites of the drugs inside protein pockets. Thus, the present study explores the potential binding characteristics of two sulfonamide drugs (with different substitutions) with myoglobin, correlating the structural and energetic aspects.
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Affiliation(s)
- Aben Ovung
- Department
of Chemistry, National Institute of Technology
Nagaland, Chumukedima, Dimapur 797103, India
| | - A. Mavani
- Department
of Chemistry, National Institute of Technology
Nagaland, Chumukedima, Dimapur 797103, India
| | - Ambarnil Ghosh
- UCD
Conway Institute of Biomolecular & Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland
| | - Sabyasachi Chatterjee
- Biophysical
Chemistry Laboratory, CSIR—Indian
Institute of Chemical Biology, 4, Raja S.C. Mullick Road, Kolkata 700032, India
| | - Abhi Das
- Biophysical
Chemistry Laboratory, CSIR—Indian
Institute of Chemical Biology, 4, Raja S.C. Mullick Road, Kolkata 700032, India
| | - Gopinatha Suresh Kumar
- Biophysical
Chemistry Laboratory, CSIR—Indian
Institute of Chemical Biology, 4, Raja S.C. Mullick Road, Kolkata 700032, India
| | - Debes Ray
- Solid
State Physics Division, Bhabha Atomic Research
Centre, Mumbai 400085, India
| | - Vinod K. Aswal
- Solid
State Physics Division, Bhabha Atomic Research
Centre, Mumbai 400085, India
| | - Jhimli Bhattacharyya
- Department
of Chemistry, National Institute of Technology
Nagaland, Chumukedima, Dimapur 797103, India
- ,
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26
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Kong YJ, Hou GZ, Gong ZN, Zhao FT, Han LJ. Fluorescence detection of malachite green and cations (Cr 3+, Fe 3+ and Cu 2+) by a europium-based coordination polymer. RSC Adv 2022; 12:8435-8442. [PMID: 35424814 PMCID: PMC8984937 DOI: 10.1039/d2ra00077f] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/09/2022] [Indexed: 12/17/2022] Open
Abstract
A europium-based CP fluorescent sensor was synthesized and exhibited excellent recognition ability for malachite green (MG) and metal cations (Cr3+, Fe3+ and Cu2+).
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Affiliation(s)
- Ya-Jie Kong
- School of Chemistry, Chemical Engineering and Materials, Jining University, Qufu, Shandong, 273155, P. R. China
| | - Guo-Zheng Hou
- School of Chemistry, Chemical Engineering and Materials, Jining University, Qufu, Shandong, 273155, P. R. China
| | - Zhao-Ning Gong
- School of Chemistry, Chemical Engineering and Materials, Jining University, Qufu, Shandong, 273155, P. R. China
| | - Feng-Tan Zhao
- School of Chemistry, Chemical Engineering and Materials, Jining University, Qufu, Shandong, 273155, P. R. China
| | - Li-Juan Han
- School of Chemistry, Chemical Engineering and Materials, Jining University, Qufu, Shandong, 273155, P. R. China
- State Key Laboratory of Coordination Chemistry, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing 210023, P. R. China
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27
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Yuan Z, Hou G, Han L. A Terbium‐Based MOF as fluorescent probe for the detection of Malachite Green, Fe
3+
and MnO
4
−. Z Anorg Allg Chem 2021. [DOI: 10.1002/zaac.202100301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Zhuang‐Dong Yuan
- School of Chemistry Chemical Engineering and Materials Jining University Qufu 273155 P. R. China
| | - Guo‐Zheng Hou
- School of Chemistry Chemical Engineering and Materials Jining University Qufu 273155 P. R. China
| | - Li‐Juan Han
- School of Chemistry Chemical Engineering and Materials Jining University Qufu 273155 P. R. China
- State Key Laboratory of Coordination Chemistry School of Chemistry and Chemical Engineering Nanjing University Nanjing 210023 P. R. China
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28
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Issarangkura Na Ayutthaya P, Yeerum C, Kesonkan K, Kiwfo K, Grudpan K, Teshima N, Murakami H, Vongboot M. Lead Assays with Smartphone Detection Using a Monolithic Rod with 4-(2-Pyridylazo) Resorcinol. Molecules 2021; 26:5720. [PMID: 34577191 PMCID: PMC8466971 DOI: 10.3390/molecules26185720] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 09/16/2021] [Accepted: 09/18/2021] [Indexed: 11/16/2022] Open
Abstract
A monolithic rod of polyurethane foam-[4-(2-pyridylazo) resorcinol] (PUF-PAR) as a simple chemical sensor for lead assays with smartphone detection and image processing was developed. With readily available simple apparatus such as a plastic cup and a stirrer rod, the monolithic PUF rod was synthesized in a glass tube. The monolithic PUF-PAR rod could be directly loaded by standard/sample solution without sample preparation. A one-shot image in G/B value from a profile plot in ImageJ for a sample with triplicate results via a single standard calibration approach was obtained. A linear single standard calibration was: [G/B value] = -0.038[µg Pb2+] + 2.827, R2 = 0.95 for 10-30 µg Pb2+ with a limit of quantitation (LOQ) of 33 µg L-1. The precision was lower than 15% RSD. The proposed method was tested by an assay for Pb2+ contents in drinking water samples from Bangkok. The results obtained by the proposed method agree with those of ICP-OES and with 100-120% recovery, demonstrating that the method is useful for screening on-site water monitoring.
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Affiliation(s)
- Piyanat Issarangkura Na Ayutthaya
- Department of Chemistry, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (P.I.N.A.); (C.Y.); (K.K.)
| | - Chonnipa Yeerum
- Department of Chemistry, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (P.I.N.A.); (C.Y.); (K.K.)
| | - Kullapon Kesonkan
- Department of Chemistry, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (P.I.N.A.); (C.Y.); (K.K.)
| | - Kanokwan Kiwfo
- Center of Excellence for Innovation in Analytical Science and Technology and Department of Chemistry, Faculty of Sciences, Chiang Mai University, Chiang Mai 50200, Thailand;
| | - Kate Grudpan
- Center of Excellence for Innovation in Analytical Science and Technology and Department of Chemistry, Faculty of Sciences, Chiang Mai University, Chiang Mai 50200, Thailand;
| | - Norio Teshima
- Department of Applied Chemistry, Aichi Institute of Technology, 1247 Yachigusa, Yakusa-cho, Toyota 470-0392, Japan; (N.T.); (H.M.)
| | - Hiroya Murakami
- Department of Applied Chemistry, Aichi Institute of Technology, 1247 Yachigusa, Yakusa-cho, Toyota 470-0392, Japan; (N.T.); (H.M.)
| | - Monnapat Vongboot
- Department of Chemistry, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok 10140, Thailand; (P.I.N.A.); (C.Y.); (K.K.)
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29
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Antony A, Mitra J. Refractive index-assisted UV/Vis spectrophotometry to overcome spectral interference by impurities. Anal Chim Acta 2021; 1149:238186. [PMID: 33551061 DOI: 10.1016/j.aca.2020.12.061] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 12/02/2020] [Accepted: 12/27/2020] [Indexed: 10/22/2022]
Abstract
A major challenge hindering the application of techniques like UV/Vis spectrophotometry in determining concentration is spectral interference from contaminants. Since molar absorptivities vary significantly, even minuscule amounts of specific contaminants may cause relatively large errors in UV/Vis spectrophotometry based quantification. Current methods to deal with this are slow, cost-intensive, or ineffective for unknown interferents. We propose constrained refractometry as an expedient technique to aid UV/Vis spectrophotometry, avoiding large errors due to spectral interference. Based on a modified Lorentz Lorenz equation, the technique helps not only in detecting and reducing error from unknown contaminants but also in identifying the significant impurity. Experimental results show a significant reduction of error in concentration determination even for multiple unknown interfering contaminants.
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Affiliation(s)
- Airin Antony
- School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM), Thiruvananthapuram, 695551, Kerala, India.
| | - J Mitra
- School of Physics, Indian Institute of Science Education and Research Thiruvananthapuram (IISER TVM), Thiruvananthapuram, 695551, Kerala, India.
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30
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Zhang Y, Luan Q, Jiang J, Li Y. Prediction and Utilization of Malondialdehyde in Exotic Pine Under Drought Stress Using Near-Infrared Spectroscopy. FRONTIERS IN PLANT SCIENCE 2021; 12:735275. [PMID: 34733301 PMCID: PMC8558207 DOI: 10.3389/fpls.2021.735275] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/17/2021] [Indexed: 05/10/2023]
Abstract
Drought is a major abiotic stress that adversely affects the growth and productivity of plants. Malondialdehyde (MDA), a substance produced by membrane lipids in response to reactive oxygen species (ROS), can be used as a drought indicator to evaluate the degree of plasma membrane damage and the ability of plants to drought stress tolerance. Still measuring MDA is usually a labor- and time-consuming task. In this study, near-infrared (NIR) spectroscopy combined with partial least squares (PLS) was used to obtain rapid and high-throughput measurements of MDA, and the application of this technique to plant drought stress experiments was also investigated. Two exotic conifer tree species, namely, slash pine (Pinus elliottii) and loblolly pine (Pinus taeda), were used as plant material exposed to drought stress; different types of spectral preprocessing methods and important feature-selection algorithms were applied to the PLS model to calibrate it and obtain the best MDA-predicting model. The results show that the best PLS model is established via the combined treatment of detrended variable-significant multivariate correlation algorithm (DET-sMC), where latent variables (LVs) were 6. This model has a respectable predictive capability, with a correlation coefficient (R 2) of 0.66, a root mean square error (RMSE) of 2.28%, and a residual prediction deviation (RPD) of 1.51, and it was successfully implemented in drought stress experiments as a reliable and non-destructive method to detect the MDA content in real time.
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