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Saleah SA, Kim S, Luna JA, Wijesinghe RE, Seong D, Han S, Kim J, Jeon M. Optical Coherence Tomography as a Non-Invasive Tool for Plant Material Characterization in Agriculture: A Review. SENSORS (BASEL, SWITZERLAND) 2023; 24:219. [PMID: 38203080 PMCID: PMC10781338 DOI: 10.3390/s24010219] [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: 12/03/2023] [Revised: 12/23/2023] [Accepted: 12/27/2023] [Indexed: 01/12/2024]
Abstract
Characterizing plant material is crucial in terms of early disease detection, pest control, physiological assessments, and growth monitoring, which are essential parameters to increase production in agriculture and prevent unnecessary economic losses. The conventional methods employed to assess the aforementioned parameters have several limitations, such as invasive inspection, complexity, high time consumption, and costly features. In recent years, optical coherence tomography (OCT), which is an ultra-high resolution, non-invasive, and real-time unique image-based approach has been widely utilized as a significant and potential tool for assessing plant materials in numerous aspects. The obtained OCT cross-sections and volumetrics, as well as the amplitude signals of plant materials, have the capability to reveal vital information in both axial and lateral directions owing to the high resolution of the imaging system. This review discusses recent technological trends and advanced applications of OCT, which have been potentially adapted for numerous agricultural applications, such as non-invasive disease screening, optical signals-based growth speed detection, the structural analysis of plant materials, and microbiological discoveries. Therefore, this review offers a comprehensive exploration of recent advanced OCT technological approaches for agricultural applications, which provides insights into their potential to incorporate OCT technology into numerous industries.
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Affiliation(s)
- Sm Abu Saleah
- ICT Convergence Research Center, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Shinheon Kim
- Institute of Biomedical Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
| | - Jannat Amrin Luna
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea; (J.A.L.)
| | - Ruchire Eranga Wijesinghe
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Sri Lanka Institute of Information Technology, Malabe 10115, Sri Lanka
| | - Daewoon Seong
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea; (J.A.L.)
| | - Sangyeob Han
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea; (J.A.L.)
| | - Jeehyun Kim
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea; (J.A.L.)
| | - Mansik Jeon
- School of Electronic and Electrical Engineering, College of IT Engineering, Kyungpook National University, 80, Daehak-ro, Buk-gu, Daegu 41566, Republic of Korea; (J.A.L.)
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Nturambirwe JFI, Hussein EA, Vaccari M, Thron C, Perold WJ, Opara UL. Feature Reduction for the Classification of Bruise Damage to Apple Fruit Using a Contactless FT-NIR Spectroscopy with Machine Learning. Foods 2023; 12:foods12010210. [PMID: 36613425 PMCID: PMC9818888 DOI: 10.3390/foods12010210] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/19/2022] [Accepted: 12/24/2022] [Indexed: 01/05/2023] Open
Abstract
Spectroscopy data are useful for modelling biological systems such as predicting quality parameters of horticultural products. However, using the wide spectrum of wavelengths is not practical in a production setting. Such data are of high dimensional nature and they tend to result in complex models that are not easily understood. Furthermore, collinearity between different wavelengths dictates that some of the data variables are redundant and may even contribute noise. The use of variable selection methods is one efficient way to obtain an optimal model, andthis was the aim of this work. Taking advantage of a non-contact spectrometer, near infrared spectral data in the range of 800-2500 nm were used to classify bruise damage in three apple cultivars, namely 'Golden Delicious', 'Granny Smith' and 'Royal Gala'. Six prominent machine learning classification algorithms were employed, and two variable selection methods were used to determine the most relevant wavelengths for the problem of distinguishing between bruised and non-bruised fruit. The selected wavelengths clustered around 900 nm, 1300 nm, 1500 nm and 1900 nm. The best results were achieved using linear regression and support vector machine based on up to 40 wavelengths: these methods reached precision values in the range of 0.79-0.86, which were all comparable (within error bars) to a classifier based on the entire range of frequencies. The results also provided an open-source based framework that is useful towards the development of multi-spectral applications such as rapid grading of apples based on mechanical damage, and it can also be emulated and applied for other types of defects on fresh produce.
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Affiliation(s)
| | - Eslam A. Hussein
- Inter-University Institute for Data Intensive Astronomy, Department of Physics and Astronomy, University of the Western Cape, Bellville 7535, South Africa
| | - Mattia Vaccari
- Eresearch Office, DVC Research and Innovation, University of the Western Cape, Private Bag X17, Bellville 7535, South Africa
- Inter-University Institute for Data Intensive Astronomy, Department of Physics and Astronomy, University of the Western Cape, Bellville 7535, South Africa
- Inter-University Institute for Data Intensive Astronomy, Department of Astronomy, University of Cape Town, Rondebosch 7701, South Africa
| | - Christopher Thron
- Department of Science and Mathematics, Texas A&M University-Central Texas, Killeen, TX 76549, USA
| | - Willem Jacobus Perold
- Department of Electrical and Electronic Engineering, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
| | - Umezuruike Linus Opara
- SARChI Postharvest Technology Research Laboratory, Africa Institute for Postharvest Technology, Faculty of AgriSciences, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
- UNESCO International Centre for Biotechnology, Nsukka 410001, Nigeria
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Yin H, Li B, Liu YD, Zhang F, Su CT, Ou-Yang AG. Detection of early bruises on loquat using hyperspectral imaging technology coupled with band ratio and improved Otsu method. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2022; 283:121775. [PMID: 36007346 DOI: 10.1016/j.saa.2022.121775] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 07/18/2022] [Accepted: 08/16/2022] [Indexed: 06/15/2023]
Abstract
The bruising is one of the major factors affecting the quality of loquat and the bruised areas of loquat are also prone to harbor bacteria and molds. Therefore, it is critical to detect early bruises of loquat. In this study, a method based on hyperspectral imaging technology coupled with band ratio and improved Otsu method was proposed to detect early bruises of loquat. Firstly, the principal component cluster analysis was used to analyze the three regions of Vis-NIR (397.5-1014.0 nm), Vis (397.5-780.0 nm), and NIR (780.0-1014.0 nm), respectively. It was found that the Vis-NIR and NIR spectral regions along PC1 could be used to effectively distinguish bruised tissues. Then, the key wavelength images corresponding to the two regions were selected according to the load curve, respectively, and two sets of PC images and band ratio images of them were established. After comparison, it was found that the band ratio image Q651.3 / 904.3 was the most suitable for subsequent analysis of detecting early bruises of loquat. Finally, in order to evaluate the segmentation effect of the improved Otsu method, the segmentation results of the global threshold and the Otsu method were compared with it, respectively, and it was found that the performance of the improved Otsu method was best. However, since the stem-end area and the bruised area have similar intensity features causing mis-segmentation, the stem-end area was removed by curvature-assisted Hough transform circle detection (CACD) algorithm. And all test set samples were used to evaluate the performance of the proposed method, and the overall accuracy of it was 96.0 %. The results show that the detection method proposed in this study has the potential to detect early bruises of loquat in online practical applications, and it provides a theoretical basis for hyperspectral imaging in the bruise detection of fruit.
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Affiliation(s)
- Hai Yin
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China
| | - Bin Li
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China
| | - Yan-de Liu
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China
| | - Feng Zhang
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China
| | - Cheng-Tao Su
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China
| | - Ai-Guo Ou-Yang
- Institute of Optical-electro-mechatronics Technology and Application, East China Jiao Tong University, National and local joint engineering research center of fruit intelligent photoelectric detection technology and equipment, Nanchang 330013, China.
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Lin M, Fawole OA, Saeys W, Wu D, Wang J, Opara UL, Nicolai B, Chen K. Mechanical damages and packaging methods along the fresh fruit supply chain: A review. Crit Rev Food Sci Nutr 2022; 63:10283-10302. [PMID: 35647708 DOI: 10.1080/10408398.2022.2078783] [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] [Indexed: 11/03/2022]
Abstract
Mechanical damage of fresh fruit occurs throughout the postharvest supply chain leading to poor consumer acceptance and marketability. In this review, the mechanisms of damage development are discussed first. Mathematical modeling provides advanced ways to describe and predict the deformation of fruit with arbitrary geometry, which is important to understand their mechanical responses to external forces. Also, the effects of damage at the cellular and molecular levels are discussed as this provides insight into fruit physiological responses to damage. Next, direct measurement methods for damage including manual evaluation, optical detection, magnetic resonance imaging, and X-ray computed tomography are examined, as well as indirect methods based on physiochemical indexes. Also, methods to measure fruit susceptibility to mechanical damage based on the bruise threshold and the amount of damage per unit of impact energy are reviewed. Further, commonly used external and interior packaging and their applications in reducing damage are summarized, and a recent biomimetic approach for designing novel lightweight packaging inspired by the fruit pericarp. Finally, future research directions are provided.HIGHLIGHTSMathematical modeling has been increasingly used to calculate damage to fruit.Cell and molecular mechanisms response to fruit damage is an under-explored area.Susceptibility measurement of different mechanical forces has received attention.Customized design of reusable and biodegradable packaging is a hot topic of research.
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Affiliation(s)
- Menghua Lin
- College of Agriculture & Biotechnology/Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou, P. R. China
| | - Olaniyi Amos Fawole
- Postharvest Research Laboratory, Department of Botany and Plant Biotechnology, University of Johannesburg, Johannesburg, South Africa
| | - Wouter Saeys
- BIOSYST-MeBioS, KU Leuven-University of Leuven, Leuven, Belgium
| | - Di Wu
- College of Agriculture & Biotechnology/Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou, P. R. China
- Zhejiang University Zhongyuan Institute, Zhengzhou, P. R. China
| | - Jun Wang
- Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology, Department of Packaging Engineering, Jiangnan University, Wuxi, P. R. China
| | - Umezuruike Linus Opara
- SARChI Postharvest Technology Research Laboratory, Africa Institute for Postharvest Technology, Faculty of AgriSciences, Stellenbosch University, Stellenbosch, South Africa
- UNESCO International Centre for Biotechnology, Nsukka, Enugu State, Nigeria
| | - Bart Nicolai
- BIOSYST-MeBioS, KU Leuven-University of Leuven, Leuven, Belgium
- Flanders Centre of Postharvest Technology, Leuven, Belgium
| | - Kunsong Chen
- College of Agriculture & Biotechnology/Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology/The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou, P. R. China
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Zhou Y, Wu Y, Chen Z. Early Detection of Mold-Contaminated Maize Kernels Based on Optical Coherence Tomography. FOOD ANAL METHOD 2022. [DOI: 10.1007/s12161-021-02205-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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6
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Zhou Y, Wang F, Zhou W, Wu Y. Feasibility study of detecting plum’s early mechanical injury based on optical coherence tomography and cell morphological parameters. J FOOD PROCESS PRES 2021. [DOI: 10.1111/jfpp.15664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Yang Zhou
- School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China
- Zhejiang Provincial Key Lab for Chem and Bio Processing Technology of Farm Product Zhejiang University of Science and Technology Hangzhou China
| | - Fenglin Wang
- School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China
- Zhejiang Provincial Key Lab for Chem and Bio Processing Technology of Farm Product Zhejiang University of Science and Technology Hangzhou China
| | - Wujie Zhou
- School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China
| | - Yuanfeng Wu
- Zhejiang Provincial Key Lab for Chem and Bio Processing Technology of Farm Product Zhejiang University of Science and Technology Hangzhou China
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He Y, Xiao Q, Bai X, Zhou L, Liu F, Zhang C. Recent progress of nondestructive techniques for fruits damage inspection: a review. Crit Rev Food Sci Nutr 2021; 62:5476-5494. [PMID: 33583246 DOI: 10.1080/10408398.2021.1885342] [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
In the process of growing, harvesting, and storage, fruits are vulnerable to mechanical damage, microbial infections, and other types of damage, which not only reduce the quality of fruits, increase the risk of fungal infections, in turn greatly affect food safety, but also sharply reduce economic benefits. Hence, it is essential to identify damaged fruits in time. Rapid and nondestructive detection of fruits damage is in great demand. In this paper, the latest research progresses on the detection of fruits damage by nondestructive techniques, including visible/near-infrared spectroscopy, chlorophyll fluorescence techniques, computer vision, multispectral and hyperspectral imaging, structured-illumination reflectance imaging, laser-induced backscattering imaging, optical coherence tomography, nuclear magnetic resonance and imaging, X-ray imaging, electronic nose, thermography, and acoustic methods, are summarized. We briefly introduce the principles of these techniques, summarize their applicability. The challenges and future trends are also proposed to provide beneficial reference for future researches and real-world applications.
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Affiliation(s)
- Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, China
| | - Qinlin Xiao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, China
| | - Xiulin Bai
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, China
| | - Lei Zhou
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, China
| | - Fei Liu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, China
| | - Chu Zhang
- School of Information Engineering, Huzhou University, Huzhou, China
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Khetani S, Kollath VO, Eastick E, Debert C, Sen A, Karan K, Sanati-Nezhad A. Single-step functionalization of poly-catecholamine nanofilms for ultra-sensitive immunosensing of ubiquitin carboxyl terminal hydrolase-L1 (UCHL-1) in spinal cord injury. Biosens Bioelectron 2019; 145:111715. [DOI: 10.1016/j.bios.2019.111715] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 09/17/2019] [Accepted: 09/17/2019] [Indexed: 02/06/2023]
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9
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Tang L, Yin D, Chen C, Yu D, Han W. Optimal Design of Plant Canopy Based on Light Interception: A Case Study With Loquat. FRONTIERS IN PLANT SCIENCE 2019; 10:364. [PMID: 30972094 PMCID: PMC6443822 DOI: 10.3389/fpls.2019.00364] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 03/08/2019] [Indexed: 05/10/2023]
Abstract
Canopy architecture determines the light distribution and light interception in the canopy. Reasonable shaping and pruning can optimize tree structure; maximize the utilization of land, space and light energy; and lay the foundation for achieving early fruiting, high yield, health and longevity. Due to the complexity of loquat canopy architecture and the multi-year period of tree growth, the variables needed for experiments in canopy type training are hardly accessible through field measurements. In this paper, we concentrated on exploring the relationship between branching angle and light interception using a three-dimensional (3D) canopy model in loquat (Eriobotrya japonica Lindl). First, detailed 3D models of loquat trees were built by integrating branch and organ models. Second, the morphological models of different loquat trees were constructed by interactive editing. Third, the 3D individual-tree modeling software LSTree integrated with the OpenGL shadow technique, a radiosity model and a modified rectangular hyperbola model was used to calculate the silhouette to total area ratio, the distribution of photosynthetically active radiation within canopies and the net photosynthetic rate, respectively. Finally, the influence of loquat tree organ organization on the light interception of the trees was analyzed with different parameters. If the single branch angle between the level 2 scaffold branch and trunk is approximately 15° and the angles among the level 2 scaffold branches range from 60 to 90°, then a better light distribution can be obtained. The results showed that the branching angle has a significant impact on light interception, which is useful for grower manipulation of trees, e.g., shoot bending (scaffold branch angle). Based on this conclusion, a reasonable tree structure was selected for intercepting light. This quantitative simulation and analytical method provides a new digital and visual method that can aid in the design of tree architecture.
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Affiliation(s)
- Liyu Tang
- Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
- National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou, China
| | - Dan Yin
- Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
- National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou, China
| | - Chongcheng Chen
- Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
- National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou, China
| | - Dayu Yu
- Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
- National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou, China
| | - Wei Han
- Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, China
- National Engineering Research Center of Geospatial Information Technology, Fuzhou University, Fuzhou, China
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