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Xia Y, Liu W, Meng J, Hu J, Liu W, Kang J, Luo B, Zhang H, Tang W. Principles, developments, and applications of spatially resolved spectroscopy in agriculture: a review. FRONTIERS IN PLANT SCIENCE 2024; 14:1324881. [PMID: 38269139 PMCID: PMC10805836 DOI: 10.3389/fpls.2023.1324881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 12/19/2023] [Indexed: 01/26/2024]
Abstract
Agriculture is the primary source of human survival, which provides the most basic living and survival conditions for human beings. As living standards continue to improve, people are also paying more attention to the quality and safety of agricultural products. Therefore, the detection of agricultural product quality is very necessary. In the past decades, the spectroscopy technique has been widely used because of its excellent results in agricultural quality detection. However, traditional spectral inspection methods cannot accurately describe the internal information of agricultural products. With the continuous research and development of optical properties, it has been found that the internal quality of an object can be better reflected by separating the properties of light, such as its absorption and scattering properties. In recent years, spatially resolved spectroscopy has been increasingly used in the field of agricultural product inspection due to its simple compositional structure, low-value cost, ease of operation, efficient detection speed, and outstanding ability to obtain information about agricultural products at different depths. It can also separate optical properties based on the transmission equation of optics, which allows for more accurate detection of the internal quality of agricultural products. This review focuses on the principles of spatially resolved spectroscopy, detection equipment, analytical methods, and specific applications in agricultural quality detection. Additionally, the optical properties methods and direct analysis methods of spatially resolved spectroscopy analysis methods are also reported in this paper.
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Affiliation(s)
- Yu Xia
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
| | - Wenxi Liu
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
- Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Jingwu Meng
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
| | - Jinghao Hu
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
| | - Wenbo Liu
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
| | - Jie Kang
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
| | - Bin Luo
- Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Han Zhang
- Intelligent Equipment Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing, China
| | - Wei Tang
- School of Electrical and Control Engineering, Shaanxi University of Science & Technology, Xi’an, Shaanxi, China
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Si W, Xiong J, Huang Y, Jiang X, Hu D. Quality Assessment of Fruits and Vegetables Based on Spatially Resolved Spectroscopy: A Review. Foods 2022; 11:foods11091198. [PMID: 35563921 PMCID: PMC9104625 DOI: 10.3390/foods11091198] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/11/2022] [Accepted: 04/19/2022] [Indexed: 01/15/2023] Open
Abstract
Damage occurs easily and is difficult to find inside fruits and vegetables during transportation or storage, which not only brings losses to fruit and vegetable distributors, but also reduces the satisfaction of consumers. Spatially resolved spectroscopy (SRS) is able to detect the quality attributes of fruits and vegetables at different depths, which is of great significance to the quality classification and defect detection of horticultural products. This paper is aimed at reviewing the applications of spatially resolved spectroscopy for measuring the quality attributes of fruits and vegetables in detail. The principle of light transfer in biological tissues, diffusion approximation theory and methodologies are introduced, and different configuration designs for spatially resolved spectroscopy are compared and analyzed. Besides, spatially resolved spectroscopy applications based on two aspects for assessing the quality of fruits and vegetables are summarized. Finally, the problems encountered in previous studies are discussed, and future development trends are presented. It can be concluded that spatially resolved spectroscopy demonstrates great application potential in the field of fruit and vegetable quality attribute evaluation. However, due to the limitation of equipment configurations and data processing speed, the application of spatially resolved spectroscopy in real-time online detection is still a challenge.
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Affiliation(s)
- Wan Si
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China; (W.S.); (J.X.); (X.J.)
| | - Jie Xiong
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China; (W.S.); (J.X.); (X.J.)
| | - Yuping Huang
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China; (W.S.); (J.X.); (X.J.)
- Correspondence:
| | - Xuesong Jiang
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China; (W.S.); (J.X.); (X.J.)
| | - Dong Hu
- College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China;
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Assessment of Tomato Maturity in Different Layers by Spatially Resolved Spectroscopy. SENSORS 2020; 20:s20247229. [PMID: 33348611 PMCID: PMC7766491 DOI: 10.3390/s20247229] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 12/11/2020] [Accepted: 12/15/2020] [Indexed: 11/17/2022]
Abstract
Tomato maturity is important to determine the fruit shelf life and eating quality. The objective of this research was to evaluate tomato maturity in different layers by using a newly developed spatially resolved spectroscopic system over the spectral region of 550-1650 nm. Thirty spatially resolved spectra were obtained for 600 tomatoes, 100 for each of the six maturity stages (i.e., green, breaker, turning, pink, light red, and red). Support vector machine discriminant analysis (SVMDA) models were first developed for each of individual spatially resolved (SR) spectra to compare the classification results of two sides. The mean spectra of two sides with the same source-detector distances were employed to determine the model performance of different layers. SR combination by averaging all the SR spectra was also subject to comparison with the classification model performance. The results showed large source-detector distances would be helpful for evaluating tomato maturity, and the mean_SR 15 obtained excellent classification results with the total classification accuracy of 98.3%. Moreover, the classification results were distinct for two sides of the probe, which demonstrated even if in the same source-detector distances, the classification results were influenced by the measurement location due to the heterogeneity for tomato. The mean of all SR spectra could only improve the classification results based on the first three mean_SR spectra, but could not obtain the accuracy as good as the following mean_SR spectra. This study demonstrated that spatially resolved spectroscopy has potential for assessing tomato maturity in different layers.
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Identification of Apple Varieties Using a Multichannel Hyperspectral Imaging System. SENSORS 2020; 20:s20185120. [PMID: 32911790 PMCID: PMC7571201 DOI: 10.3390/s20185120] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 09/03/2020] [Accepted: 09/07/2020] [Indexed: 12/17/2022]
Abstract
This paper reports the nondestructive detection of apple varieties using a multichannel hyperspectral imaging system consisting of an illumination fiber and 30 detection fibers arranged at source–detector distances of 1.5–36 mm over the spectral range of 550–1650 nm. Spatially resolved (SR) spectra were obtained for 1500 apples, 500 each of three varieties from the same orchard to avoid environmental and geographical influences. Partial least squares discriminant analysis (PLSDA) models were developed for single SR spectra and spectral combinations to compare their performance of variety detection. To evaluate the effect of spectral range on variety detection, three types of spectra (i.e., visible region: 550–780 nm, near-infrared region: 780–1650 nm, full region: 550–1650 nm) were analyzed and compared. The results showed that the single SR spectra presented a different accuracy for apple variety classification, and the optimal SR spectra varied with spectral types. Spectral combinations had better accuracies for variety detection with best overall classifications of 99.4% for both spectral ranges in the NIR and full regions; however, the spectral combination could not improve the results over the optimal single SR spectra in the visible region. Moreover, the recognition of golden delicious (GD) was better than those of the other two varieties, with the best classification accuracy of 100% for three types of spectra. Overall, the multichannel hyperspectral imaging system provides more spatial-spectral information for the apples, and the results demonstrate that the technique gave excellent classifications, which suggests that the multichannel hyperspectral imaging system has potential for apple variety detection.
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Assessment of tomato soluble solids content and pH by spatially-resolved and conventional Vis/NIR spectroscopy. J FOOD ENG 2018. [DOI: 10.1016/j.jfoodeng.2018.05.008] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Holman BWB, Hopkins DL. A comparison of the Nix Colour Sensor Pro™ and HunterLab MiniScan™ colorimetric instruments when assessing aged beef colour stability over 72 h display. Meat Sci 2018; 147:162-165. [PMID: 30253262 DOI: 10.1016/j.meatsci.2018.09.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 09/12/2018] [Accepted: 09/12/2018] [Indexed: 10/28/2022]
Abstract
We compared the capacity for the Nix Colour Sensor Pro™ (NIX) and HunterLab MiniScan™ (HUNTER) to detect colour variation using aged (0, 3 and 5 weeks) and then displayed (0, 1, 2 and 3 d) beef M. longissimus lumborum samples (n = 8). NIX L* and hue values were found to be respectively higher and lower than for the HUNTER. No significant interactions between instrument and display or ageing periods were identified for a* - unlike for b* and chroma where NIX measures were observed to be lower than those from the HUNTER. Both instruments identified ageing and display period effects on colorimetric traits. Based on these results, the NIX cannot be considered comparable to the HUNTER when measuring beef colour - albeit captured similar colorimetric trends over display and ageing periods which suggest its independent usefulness to beef colour assessment.
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Affiliation(s)
- Benjamin W B Holman
- Centre for Red Meat and Sheep Development, NSW Department of Primary Industries, Cowra, NSW 2794, Australia
| | - David L Hopkins
- Centre for Red Meat and Sheep Development, NSW Department of Primary Industries, Cowra, NSW 2794, Australia.
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Van Beers R, Kokawa M, Aernouts B, Watté R, De Smet S, Saeys W. Evolution of the bulk optical properties of bovine muscles during wet aging. Meat Sci 2018; 136:50-58. [DOI: 10.1016/j.meatsci.2017.10.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Revised: 09/18/2017] [Accepted: 10/16/2017] [Indexed: 11/26/2022]
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Van Beers R, Aernouts B, Reis MM, Saeys W. Anisotropic light propagation in bovine muscle tissue depends on the initial fiber orientation, muscle type and wavelength. OPTICS EXPRESS 2017; 25:22082-22095. [PMID: 29041497 DOI: 10.1364/oe.25.022082] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 08/22/2017] [Indexed: 06/07/2023]
Abstract
The effects of fiber orientation on vis/NIR light propagation were studied in three bovine muscles: biceps brachii, brachialis and soleus. Broadband light was focused onto the sample and the diffuse reflectance spot was captured using a hyperspectral camera (470-1620 nm), after which rhombuses were fitted to equi-intensity points. In samples with fibers running parallel to the measurement surface, the rhombus' major axis was oriented perpendicular to the fiber direction close to the point of illumination. However, at larger distances from the illumination spot, the major axis orientation aligned with the fiber direction. This phenomenon was found to be muscle dependent. Furthermore, the rhombus orientation was highly dependent on the sample positioning underneath the camera, especially when the muscle fibers ran parallel to the measurement surface. The bias parameter, indicating the deviation from a circular shape, was higher for samples with the fibers running parallel to the measurement surface. Moreover, clear effects of wavelength and distance from the illumination point on this parameter were observed. These results show the importance of fiber orientation when considering optical techniques for measurements on anisotropic, fibrous tissues. Moreover, the prediction of muscle fiber orientation seemed feasible, which can be of interest to the meat industry.
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Nguyen Do Trong N, Rizzolo A, Herremans E, Vanoli M, Cortellino G, Erkinbaev C, Tsuta M, Spinelli L, Contini D, Torricelli A, Verboven P, De Baerdemaeker J, Nicolaï B, Saeys W. Reprint of "Optical properties–microstructure–texture relationships of dried apple slices: Spatially resolved diffuse reflectance spectroscopy as a novel technique for analysis and process control". INNOV FOOD SCI EMERG 2014. [DOI: 10.1016/j.ifset.2014.07.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Tao F, Peng Y. A method for nondestructive prediction of pork meat quality and safety attributes by hyperspectral imaging technique. J FOOD ENG 2014. [DOI: 10.1016/j.jfoodeng.2013.11.006] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Optical properties–microstructure–texture relationships of dried apple slices: Spatially resolved diffuse reflectance spectroscopy as a novel technique for analysis and process control. INNOV FOOD SCI EMERG 2014. [DOI: 10.1016/j.ifset.2013.09.014] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Herremans E, Bongaers E, Estrade P, Gondek E, Hertog M, Jakubczyk E, Nguyen Do Trong N, Rizzolo A, Saeys W, Spinelli L, Torricelli A, Vanoli M, Verboven P, Nicolaï B. Microstructure–texture relationships of aerated sugar gels: Novel measurement techniques for analysis and control. INNOV FOOD SCI EMERG 2013. [DOI: 10.1016/j.ifset.2013.02.003] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Wu J, Peng Y, Li Y, Wang W, Chen J, Dhakal S. Prediction of beef quality attributes using VIS/NIR hyperspectral scattering imaging technique. J FOOD ENG 2012. [DOI: 10.1016/j.jfoodeng.2011.10.004] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Tao F, Peng Y, Li Y, Chao K, Dhakal S. Simultaneous determination of tenderness and Escherichia coli contamination of pork using hyperspectral scattering technique. Meat Sci 2012; 90:851-7. [DOI: 10.1016/j.meatsci.2011.11.028] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2010] [Revised: 10/07/2011] [Accepted: 11/14/2011] [Indexed: 11/27/2022]
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Ranasinghesagara J, Nath T, Wells S, Weaver A, Gerrard D, Yao G. Imaging optical diffuse reflectance in beef muscles for tenderness prediction. Meat Sci 2010; 84:413-21. [DOI: 10.1016/j.meatsci.2009.09.010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2009] [Revised: 09/11/2009] [Accepted: 09/17/2009] [Indexed: 11/29/2022]
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