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Chen X, Huang X, He S. 4D hyperspectral surface topography measurement system based on the Scheimpflug principle and hyperspectral imaging. APPLIED OPTICS 2023; 62:8855-8868. [PMID: 38038032 DOI: 10.1364/ao.501459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/30/2023] [Indexed: 12/02/2023]
Abstract
A four-dimensional (4D) hyperspectral surface topography measurement (HSTM) system that can acquire uniform inelastic signals [three-dimensional (3D) spatial data] and reflection/fluorescence spectra of an object is proposed. The key components of the system are a light-sheet profilometer based on the Scheimpflug principle and a hyperspectral imager. Based on the mapping relationships among the image coordinate systems of the two imaging subsystems and the coordinate system of the real space, the spectral data can be assigned to the corresponding 3D point cloud, forming a 4D model. The spectral resolution is better than 4 nm. 700 nm, 546 nm, and 436 nm are selected as the three primary colors of red, green, and blue to restore the color. The 4D hyperspectral surface reconstruction experiments of philodendron and chlorophytum have shown the good performance of the proposed HSTM system and the great application potential for plant phenotype and growth analysis in agriculture.
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Mao Y, Betters CH, Garske S, Randle J, Wong KC, Cairns IH, Evans BJ. A Customisable Data Acquisition System for Open-Source Hyperspectral Imaging. SENSORS (BASEL, SWITZERLAND) 2023; 23:8622. [PMID: 37896715 PMCID: PMC10611323 DOI: 10.3390/s23208622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/17/2023] [Accepted: 10/17/2023] [Indexed: 10/29/2023]
Abstract
Hyperspectral imagers, or imaging spectrometers, are used in many remote sensing environmental studies in fields such as agriculture, forestry, geology, and hydrology. In recent years, compact hyperspectral imagers were developed using commercial-off-the-shelf components, but there are not yet any off-the-shelf data acquisition systems on the market to deploy them. The lack of a self-contained data acquisition system with navigation sensors is a challenge that needs to be overcome to successfully deploy these sensors on remote platforms such as drones and aircraft. Our work is the first successful attempt to deploy an entirely open-source system that is able to collect hyperspectral and navigation data concurrently for direct georeferencing. In this paper, we describe a low-cost, lightweight, and deployable data acquisition device for the open-source hyperspectral imager (OpenHSI). We utilised commercial-off-the-shelf hardware and open-source software to create a compact data acquisition device that can be easily transported and deployed. The device includes a microcontroller and a custom-designed PCB board to interface with ancillary sensors and a Raspberry Pi 4B/NVIDIA Jetson. We demonstrated our data acquisition system on a Matrice M600 drone at a beach in Sydney, Australia, collecting timestamped hyperspectral, navigation, and orientation data in parallel. Using the navigation and orientation data, the hyperspectral data were georeferenced. While the entire system including the pushbroom hyperspectral imager and housing weighed 735 g, it was designed to be easy to assemble and modify. This low-cost, customisable, deployable data acquisition system provides a cost-effective solution for the remote sensing of hyperspectral data for everyone.
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Affiliation(s)
- Yiwei Mao
- School of Physics, The University of Sydney, Sydney, NSW 2006, Australia; (Y.M.); (C.H.B.)
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
| | - Christopher H. Betters
- School of Physics, The University of Sydney, Sydney, NSW 2006, Australia; (Y.M.); (C.H.B.)
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
| | - Samuel Garske
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
| | - Jeremy Randle
- Australian Centre for Field Robotics, The University of Sydney, Sydney, NSW 2006, Australia;
| | - K. C. Wong
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
| | - Iver H. Cairns
- School of Physics, The University of Sydney, Sydney, NSW 2006, Australia; (Y.M.); (C.H.B.)
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
| | - Bradley J. Evans
- ARC Training Centre for CubeSats UAVs and Their Applications, The University of Sydney, Sydney, NSW 2006, Australia; (S.G.); (K.C.W.); (B.J.E.)
- School of Environment and Rural Science, University of New England, Armidale, NSW 2351, Australia
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Dong K, Guan Y, Wang Q, Huang Y, An F, Zeng Q, Luo Z, Huang Q. Non-destructive prediction of yak meat freshness indicator by hyperspectral techniques in the oxidation process. Food Chem X 2022; 17:100541. [PMID: 36845518 PMCID: PMC9943752 DOI: 10.1016/j.fochx.2022.100541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/06/2022] [Accepted: 12/09/2022] [Indexed: 12/23/2022] Open
Abstract
This study examined the potential of hyperspectral techniques for the rapid detection of characteristic indicators of yak meat freshness during the oxidation of yak meat. TVB-N values were determined by significance analysis as the characteristic index of yak meat freshness. Reflectance spectral information of yak meat samples (400-1000 nm) was collected by hyperspectral technology. The raw spectral information was processed by 5 methods and then principal component regression (PCR), support vector machine regression (SVR) and partial least squares regression (PLSR) were used to build regression models. The results indicated that the full-wavelength based on PCR, SVR, and PLSR models were shown greater performance in the prediction of TVB-N content. In order to improve the computational efficiency of the model, 9 and 11 characteristic wavelengths were selected from 128 wavelengths by successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS), respectively. The CARS-PLSR model exhibited excellent predictive power and model stability.
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Affiliation(s)
- Kai Dong
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China,Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition of Ministry of Education, College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Yufang Guan
- The Food Processing Research Institute of Guizhou Province, Guizhou Academy of Agricultural Sciences/Potato Engineering Research Center of Guizhou Province/Guizhou Key Laboratory of Agricultural Biotechnology, Guiyang 550006, Guizhou, China
| | - Qia Wang
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China,Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition of Ministry of Education, College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Yonghui Huang
- The Food Processing Research Institute of Guizhou Province, Guizhou Academy of Agricultural Sciences/Potato Engineering Research Center of Guizhou Province/Guizhou Key Laboratory of Agricultural Biotechnology, Guiyang 550006, Guizhou, China
| | - Fengping An
- Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition of Ministry of Education, College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China
| | - Qibing Zeng
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China,Corresponding authors at: Guizhou Medical University, Gui 'an New District, Guizhou Province 550025, China.
| | - Zhang Luo
- College of Food Science, Tibet Agriculture and Animal Husbandry University, Linzhi, Tibet Autonomous Region 860000, China,Corresponding authors at: Guizhou Medical University, Gui 'an New District, Guizhou Province 550025, China.
| | - Qun Huang
- The Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, School of Public Health, Guizhou Medical University, Guiyang 550025, China,Engineering Research Centre of Fujian-Taiwan Special Marine Food Processing and Nutrition of Ministry of Education, College of Food Science, Fujian Agriculture and Forestry University, Fuzhou, Fujian 350002, China,Institute for Egg Science and Technology, School of Food and Biological Engineering, Chengdu University, Chengdu 610106, China,Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education & Key Laboratory of Medical Molecular Biology of Guizhou Province, Guizhou Medical University, Guiyang 550004, Guizhou, China,Corresponding authors at: Guizhou Medical University, Gui 'an New District, Guizhou Province 550025, China.
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Evaluation of pH in Sausages Stuffed in a Modified Casing with Orange Extracts by Hyperspectral Imaging Coupled with Response Surface Methodology. Foods 2022; 11:foods11182797. [PMID: 36140925 PMCID: PMC9497902 DOI: 10.3390/foods11182797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/04/2022] [Accepted: 09/08/2022] [Indexed: 11/16/2022] Open
Abstract
The pH values of sausages stuffed in natural hog casings with different modifications (soy lecithin, soy oil, orange extracts (OE) from waste orange peels, lactic acid in slush salt, and treatment time) after 16-day 4 °C storage were evaluated for the first time by hyperspectral imaging (350−1100 nm) coupled with response surface methodology (RSM). A partial least squares regression (PLSR) model was developed to relate the spectra to the pH of sausages. Spectral pretreatment, including first derivative, second derivative, multiplicative scatter correction (MSC), standard normal variate (SNV), normalization, and normalization, with different combinations was employed to improve model performance. RSM showed that only soy lecithin and OE interactively affected the pH of sausages (p < 0.05). The pH value decreased when the casing was treated with a higher concentration of soy lecithin with 0.26% OE. As the first and second derivatives are commonly used to eliminate the baseline shift, the PLSR model derived from absorbance pretreated by the first derivative in the full wavelengths showed a calibration coefficient of determination (R2) of 0.73 with a root mean square error of calibration of 0.4283. Twelve feature wavelengths were selected with a comparable R2 value compared with the full wavelengths. The prediction map enables the visualization of the pH evolution of sausages stuffed in the modified casings added with OE.
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Luo J, Forsberg E, Fu S, Xing Y, Liao J, Jiang J, Zheng Y, He S. 4D dual-mode staring hyperspectral-depth imager for simultaneous spectral sensing and surface shape measurement. OPTICS EXPRESS 2022; 30:24804-24821. [PMID: 36237025 DOI: 10.1364/oe.460412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 06/13/2022] [Indexed: 06/16/2023]
Abstract
A 4D dual-mode staring hyperspectral-depth imager (DSHI), which acquire reflectance spectra, fluorescence spectra, and 3D structural information by combining a staring hyperspectral scanner and a binocular line laser stereo vision system, is introduced. A 405 nm laser line generated by a focal laser line generation module is used for both fluorescence excitation and binocular stereo matching of the irradiated line region. Under the configuration, the two kinds of hyperspectral data collected by the hyperspectral scanner can be merged into the corresponding points in the 3D model, forming a dual-mode 4D model. The DSHI shows excellent performance with spectral resolution of 3 nm, depth accuracy of 26.2 µm. Sample experiments on a fluorescent figurine, real and plastic sunflowers and a clam are presented to demonstrate system's with potential within a broad range of applications such as, e.g., digital documentation, plant phenotyping, and biological analysis.
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Agricultural Potentials of Molecular Spectroscopy and Advances for Food Authentication: An Overview. Processes (Basel) 2022. [DOI: 10.3390/pr10020214] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Meat, fish, coffee, tea, mushroom, and spices are foods that have been acknowledged for their nutritional benefits but are also reportedly targets of fraud and tampering due to their economic value. Conventional methods often take precedence for monitoring these foods, but rapid advanced instruments employing molecular spectroscopic techniques are gradually claiming dominance due to their numerous advantages such as low cost, little to no sample preparation, and, above all, their ability to fingerprint and detect a deviation from quality. This review aims to provide a detailed overview of common molecular spectroscopic techniques and their use for agricultural and food quality management. Using multiple databases including ScienceDirect, Scopus, Web of Science, and Google Scholar, 171 research publications including research articles, review papers, and book chapters were thoroughly reviewed and discussed to highlight new trends, accomplishments, challenges, and benefits of using molecular spectroscopic methods for studying food matrices. It was observed that Near infrared spectroscopy (NIRS), Infrared spectroscopy (IR), Hyperspectral imaging (his), and Nuclear magnetic resonance spectroscopy (NMR) stand out in particular for the identification of geographical origin, compositional analysis, authentication, and the detection of adulteration of meat, fish, coffee, tea, mushroom, and spices; however, the potential of UV/Vis, 1H-NMR, and Raman spectroscopy (RS) for similar purposes is not negligible. The methods rely heavily on preprocessing and chemometric methods, but their reliance on conventional reference data which can sometimes be unreliable, for quantitative analysis, is perhaps one of their dominant challenges. Nonetheless, the emergence of handheld versions of these techniques is an area that is continuously being explored for digitalized remote analysis.
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Leighton PL, Segura JD, Lam SD, Marcoux M, Wei X, Lopez-Campos OD, Soladoye P, Dugan ME, Juarez M, PRIETO NURIA. Prediction of carcass composition and meat and fat quality using sensing technologies: A review. MEAT AND MUSCLE BIOLOGY 2021. [DOI: 10.22175/mmb.12951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
Consumer demand for high-quality healthy food is increasing, thus meat processors require the means toassess these rapidly, accurately, and inexpensively. Traditional methods forquality assessments are time-consuming, expensive, invasive, and have potentialto negatively impact the environment. Consequently, emphasis has been put onfinding non-destructive, fast, and accurate technologies for productcomposition and quality evaluation. Research in this area is advancing rapidlythrough recent developments in the areas of portability, accuracy, and machinelearning. The present review, therefore, critically evaluates and summarizes developmentsof popular non-invasive technologies (i.e., from imaging to spectroscopicsensing technologies) for estimating beef, pork, and lamb composition andquality, which will hopefully assist in the implementation of thesetechnologies for rapid evaluation/real-timegrading of livestock products in the nearfuture.
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Khaled AY, Parrish CA, Adedeji A. Emerging nondestructive approaches for meat quality and safety evaluation-A review. Compr Rev Food Sci Food Saf 2021; 20:3438-3463. [PMID: 34151512 DOI: 10.1111/1541-4337.12781] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 03/29/2021] [Accepted: 05/11/2021] [Indexed: 11/28/2022]
Abstract
Meat is one of the most consumed agro-products because it contains proteins, minerals, and essential vitamins, all of which play critical roles in the human diet and health. Meat is a perishable food product because of its high moisture content, and as such there are concerns about its quality, stability, and safety. There are two widely used methods for monitoring meat quality attributes: subjective sensory evaluation and chemical/instrumentation tests. However, these methods are labor-intensive, time-consuming, and destructive. To overcome the shortfalls of these conventional approaches, several researchers have developed fast and nondestructive techniques. Recently, electronic nose (e-nose), computer vision (CV), spectroscopy, hyperspectral imaging (HSI), and multispectral imaging (MSI) technologies have been explored as nondestructive methods in meat quality and safety evaluation. However, most of the studies on the application of these novel technologies are still in the preliminary stages and are carried out in isolation, often without comprehensive information on the most suitable approach. This lack of cohesive information on the strength and shortcomings of each technique could impact their application and commercialization for the detection of important meat attributes such as pH, marbling, or microbial spoilage. Here, we provide a comprehensive review of recent nondestructive technologies (e-nose, CV, spectroscopy, HSI, and MSI), as well as their applications and limitations in the detection and evaluation of meat quality and safety issues, such as contamination, adulteration, and quality classification. A discussion is also included on the challenges and future outlooks of the respective technologies and their various applications.
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Affiliation(s)
- Alfadhl Y Khaled
- Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, Kentucky, USA
| | - Chadwick A Parrish
- Department of Electrical and Computer Engineering, University of Kentucky, Lexington, Kentucky, USA
| | - Akinbode Adedeji
- Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, Kentucky, USA
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Chen X, Jiang Y, Yao Q, Ji J, Evans J, He S. Inelastic hyperspectral Scheimpflug lidar for microalgae classification and quantification. APPLIED OPTICS 2021; 60:4778-4786. [PMID: 34143042 DOI: 10.1364/ao.424900] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 05/12/2021] [Indexed: 06/12/2023]
Abstract
An inelastic hyperspectral Scheimpflug lidar system was developed for microalgae classification and quantification. The correction for the refraction at the air-glass-water interface was established, making our system suitable for aquatic environments. The fluorescence spectrum of microalgae was extracted by principal component analysis, and seven species of microalgae from different phyla have been classified. It was verified that when the cell density of Phaeocystis globosa was in the range of ${{1}}{{{0}}^4}\sim{{1}}{{{0}}^6}\;{\rm{cell}}\;{\rm{m}}{{\rm{L}}^{- 1}}$, the cell density had a linear relationship with the fluorescence intensity. The experimental results show our system can identify and quantify microalgae, with application prospects for microalgae monitoring in the field environment and early warning of red tides or algal blooms.
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10
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Luo L, Li S, Yao X, He S. Rotational hyperspectral scanner and related image reconstruction algorithm. Sci Rep 2021; 11:3296. [PMID: 33558585 PMCID: PMC7870810 DOI: 10.1038/s41598-021-82819-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 01/25/2021] [Indexed: 12/25/2022] Open
Abstract
We design and implement a compact and lightweight hyperspectral scanner. Based on this, a novel rotational hyperspectral scanner was demonstrated. Different from translational scanning, rotational scanning is a moveless and stable scanning method. We also designed a relevant image algorithm to reconstruct the image from an angular recorded hyperspectral data cube. The algorithm works well even with uncertain radial and tangential offset, which is caused by mechanical misalignment. The system shown a spectral resolution of 5 nm after calibration. Finally, spatial accuracy and spectral precision were discussed, based on some additional experiments.
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Affiliation(s)
- Longqiang Luo
- College of Optical Science and Engineering, Zhejiang University, 866 Yuhangtang Rd, Hangzhou, 310058, China
| | - Shuo Li
- College of Optical Science and Engineering, Zhejiang University, 866 Yuhangtang Rd, Hangzhou, 310058, China.,Ningbo Research Institute, Zhejiang University, Ningbo, 315100, China
| | - Xinli Yao
- College of Optical Science and Engineering, Zhejiang University, 866 Yuhangtang Rd, Hangzhou, 310058, China
| | - Sailing He
- College of Optical Science and Engineering, Zhejiang University, 866 Yuhangtang Rd, Hangzhou, 310058, China. .,Ningbo Research Institute, Zhejiang University, Ningbo, 315100, China. .,Department of Electromagnetic Engineering, School of Electrical Engineering, KTH Royal Institute of Technology, 100 44, Stockholm, Sweden.
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Antequera T, Caballero D, Grassi S, Uttaro B, Perez-Palacios T. Evaluation of fresh meat quality by Hyperspectral Imaging (HSI), Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI): A review. Meat Sci 2021; 172:108340. [DOI: 10.1016/j.meatsci.2020.108340] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 09/23/2020] [Accepted: 10/09/2020] [Indexed: 12/31/2022]
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Amani H, Badak-Kerti K, Mousavi Khaneghah A. Current progress in the utilization of smartphone-based imaging for quality assessment of food products: a review. Crit Rev Food Sci Nutr 2020; 62:3631-3643. [PMID: 33377398 DOI: 10.1080/10408398.2020.1867820] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The cell phone has been merely used for image acquisition and transmission in the last decades. Owing to the recent technological progress, its new generation, i.e., the smartphone, draws remarkable attention to food quality assessment with versatile applications. Smartphones possess high-resolution cameras, enabling them to be used instead of digital cameras in the computer vision system. Furthermore, their programmability and portability have recently encouraged researchers to introduce smartphone-based image processing in food analytical studies. This promising approach has advantages such as high sensing capability, being user friendly, and cost-effective over the conventional method, and therefore might be considered an emerging nondestructive technique for quality control purposes. However, there is a great effort to tackle implementation, calibration, as well as industrialization issues. In this context, this review aims to highlight the most recent studies of smartphone-based imaging systems in various food systems such as dairy, meat, fruit, and vegetables. Besides, the existing challenges and future trends for applying smartphones in food quality control are discussed. Although moving the computer vision systems toward a portable tool like a smartphone improves its versatility, more research works are needed to resolve its set-up weakness and limitations.
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Affiliation(s)
- Hanieh Amani
- Department of Grain and Industrial Plant Processing, Szent István University, Budapest, Hungary
| | - Katalin Badak-Kerti
- Department of Grain and Industrial Plant Processing, Szent István University, Budapest, Hungary
| | - Amin Mousavi Khaneghah
- Department of Food Science, University of Campinas (UNICAMP), Campinas, São Paulo, Brazil
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Xu Z, Jiang Y, Ji J, Forsberg E, Li Y, He S. Classification, identification, and growth stage estimation of microalgae based on transmission hyperspectral microscopic imaging and machine learning. OPTICS EXPRESS 2020; 28:30686-30700. [PMID: 33115064 DOI: 10.1364/oe.406036] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
A transmission hyperspectral microscopic imager (THMI) that utilizes machine learning algorithms for hyperspectral detection of microalgae is presented. The THMI system has excellent performance with spatial and spectral resolutions of 4 µm and 3 nm, respectively. We performed hyperspectral imaging (HSI) of three species of microalgae to verify their absorption characteristics. Transmission spectra were analyzed using principal component analysis (PCA) and peak ratio algorithms for dimensionality reduction and feature extraction, and a support vector machine (SVM) model was used for classification. The average accuracy, sensitivity and specificity to distinguish one species from the other two species were found to be 94.4%, 94.4% and 97.2%, respectively. A species identification experiment for a group of mixed microalgae in solution demonstrates the usability of the classification method. Using a random forest (RF) model, the growth stage in a phaeocystis growth cycle cultivated under laboratory conditions was predicted with an accuracy of 98.1%, indicating the feasibility to evaluate the growth state of microalgae through their transmission spectra. Experimental results show that the THMI system has the capability for classification, identification and growth stage estimation of microalgae, with strong potential for in-situ marine environmental monitoring and early warning detection applications.
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14
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Xu Z, Forsberg E, Guo Y, Cai F, He S. Light-Sheet Microscopy for Surface Topography Measurements and Quantitative Analysis. SENSORS 2020; 20:s20102842. [PMID: 32429437 PMCID: PMC7288151 DOI: 10.3390/s20102842] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 05/06/2020] [Accepted: 05/13/2020] [Indexed: 12/13/2022]
Abstract
A novel light-sheet microscopy (LSM) system that uses the laser triangulation method to quantitatively calculate and analyze the surface topography of opaque samples is discussed. A spatial resolution of at least 10 μm in z-direction, 10 μm in x-direction and 25 μm in y-direction with a large field-of-view (FOV) is achieved. A set of sample measurements that verify the system′s functionality in various applications are presented. The system has a simple mechanical structure, such that the spatial resolution is easily improved by replacement of the objective, and a linear calibration formula, which enables convenient system calibration. As implemented, the system has strong potential for, e.g., industrial sample line inspections, however, since the method utilizes reflected/scattered light, it also has the potential for three-dimensional analysis of translucent and layered structures.
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Affiliation(s)
- Zhanpeng Xu
- Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Zhejiang Provincial Key Laboratory for Sensing Technologies, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China; (Z.X.); (E.F.); (Y.G.)
| | - Erik Forsberg
- Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Zhejiang Provincial Key Laboratory for Sensing Technologies, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China; (Z.X.); (E.F.); (Y.G.)
| | - Yang Guo
- Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Zhejiang Provincial Key Laboratory for Sensing Technologies, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China; (Z.X.); (E.F.); (Y.G.)
| | - Fuhong Cai
- School of Biomedical Engineering, Hainan University, Haikou 570228, China;
| | - Sailing He
- Centre for Optical and Electromagnetic Research, National Engineering Research Center for Optical Instruments, Zhejiang Provincial Key Laboratory for Sensing Technologies, College of Optical Science and Engineering, Zhejiang University, Hangzhou 310058, China; (Z.X.); (E.F.); (Y.G.)
- Correspondence: ; Tel.: +86-571-8820-6525
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15
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Yao X, Li S, He S. DUAL-MODE HYPERSPECTRAL BIO-IMAGER WITH A CONJUGATED CAMERA FOR QUICK OBJECT-SELECTION AND FOCUSING. ACTA ACUST UNITED AC 2020. [DOI: 10.2528/pier20080308] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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16
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Park MY, Ryu YC, Kim CN, Ko KB, Kim JM. Evaluation of Myosin Heavy Chain Isoforms in Biopsied Longissimus Thoracis Muscle for Estimation of Meat Quality Traits in Live Pigs. Animals (Basel) 2019; 10:ani10010009. [PMID: 31861524 PMCID: PMC7022759 DOI: 10.3390/ani10010009] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 11/28/2019] [Accepted: 12/11/2019] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Pork quality has become an important parameter in the industry. Traditional pork quality was assessed postmortem. It is considered that the determination of meat quality in live pigs is beneficial in order to obtain better pork quality and to reduce cost in production. In the present study, myosin heavy chain (MHC) isoforms in both of the pre- and postmortem longissimus thoracis muscle were evaluated as novel parameters for meat quality estimation in pork by correlation and clustering analysis. MHC isoforms in live pigs could be applied in a practical and useful method to predict meat quality in pork. Abstract Estimating meat quality prior to slaughter will be beneficial for the rapid identification of specific traits or poor quality pork compared to a conventional assessment at postmortem. In this study, we identified and quantified myosin heavy chain (MHC) isoforms from a biopsied longissimus thoracis muscle of pigs, and determined their correlation with postmortem muscle fiber characteristics and meat quality. MHC slow and fast isoforms proportions from biopsied samples correlated with postmortem percentage of type I and type IIB muscle fibers, respectively (p < 0.05). The percentage of the biopsied MHC slow isoform showed a positive correlation with pH at 45 min postmortem, and negative correlations with filter-paper fluid uptake and drip loss in pork (p < 0.05). Furthermore, clustering the pigs into three groups based on the biopsied MHC isoform proportions was not only significantly associated with muscle fiber number and proportions of muscle fiber area, but also correlated with pH at 45 min postmortem and the National Pork Producers Council color score (p < 0.05). Collectively, our findings indicate that the biopsied MHC isoforms serve as parameter for estimating meat quality, with the association between the higher proportion of MHC slow isoforms and pH at 45 min postmortem in particular being indicative of better pork quality.
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Affiliation(s)
- Min Young Park
- Department of Animal Science and Technology, College of Biotechnology and Natural Resources, Chung-Ang University, Ansung-si Gyeonggi-do 17546, Korea;
| | - Youn-Chul Ryu
- Division of Biotechnology, SARI, Jeju National University, Jeju-do 63243, Korea; (Y.-C.R.); (C.-N.K.); (K.-B.K.)
| | - Chung-Nam Kim
- Division of Biotechnology, SARI, Jeju National University, Jeju-do 63243, Korea; (Y.-C.R.); (C.-N.K.); (K.-B.K.)
| | - Kyung-Bo Ko
- Division of Biotechnology, SARI, Jeju National University, Jeju-do 63243, Korea; (Y.-C.R.); (C.-N.K.); (K.-B.K.)
| | - Jun-Mo Kim
- Department of Animal Science and Technology, College of Biotechnology and Natural Resources, Chung-Ang University, Ansung-si Gyeonggi-do 17546, Korea;
- Correspondence: ; Tel.: +82-31-670-3053
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