Visible to SWIR hyperspectral imaging for produce safety and quality evaluation

Sensing and Instrumentation for Food Quality and Safety

Volumn 5, Issue 5, 2011, Pages 155-164

  Kim, Moon S ^a   Delwiche, Stephen R ^a   Chao, Kuanglin ^a   Garrido Varo, Ana ^b   Pérez Marín, Dolores ^b   Lefcourt, Alan M ^a   Chan, Diane E ^a  

^a AGRICULTURAL RESEARCH SERVICE   (United States)

^b UNIVERSITY OF CÓRDOBA   (Spain)

Author keywords

Hyperspectral imaging; InGaAs; Spectral calibration; SWIR; VNIR

Indexed keywords

HYPERSPECTRAL IMAGING; INGAAS; SPECTRAL CALIBRATION; SWIR; VNIR;

FOOD SAFETY; IMAGE PROCESSING; IMAGING SYSTEMS; SEMICONDUCTING INDIUM;

QUALITY CONTROL;

EID: 84862804965     PISSN: 19327587     EISSN: 19329954     Source Type: Journal    
DOI: 10.1007/s11694-012-9122-3     Document Type: Article

References (25)

1. M. S. Kim, Y. R. Chen, P. M. Mehl, Hyperspectral reflectance and fluorescence imaging system for food quality and safety. Trans. ASAE 44, 721-729 (2001).
2. A. A. Gowen, C. P. O'Donnell, P. J. Cullen, G. Downey, J. M. Frias, Hyperspectral imaging-an emerging process analytical tool for food quality and safety control. Trends Food Sci. Technol. 18, 590-598 (2007).
3. M. S. Kim, A. M. Lefcourt, Y. R. Chen, I. Kim, D. E. Chan, K. Chao, Multispectral detection of fecal contamination on apples based on hyperspectral imagery-part I: applications of visible and near-infrared reflectance imaging. Trans. ASAE 45, 2027-2037 (2002).
4. M. S. Kim, A. M. Lefcourt, Y. R. Chen, I. Kim, K. Chao, D. E. Chan, Multispectral detection of fecal contamination on apples based on hyperspectral imagery-part II: application of fluorescence imaging. Trans. ASAE 45, 2039-2047 (2002).
5. P. M. Mehl, K. Chao, M. S. Kim, Y. R. Chen, Detection of contamination on selected apple cultivars using reflectance hyperspectral and multispectral analysis. Appl. Eng. Agric. 18, 219-226 (2002).
6. R. Lu, Detection of bruises on apples using near-infrared hyperspectral imaging. Trans. ASAE 46(2), 523-530 (2003).
7. J. Xing, J. De Baerdemaeker, Bruise detection on 'Jonagold' apples using hyperspectral imaging. Postharvest Biol. Technol. 37, 152-162 (2005).
8. B. M. Nicolai, E. Lotze, A. Peirs, N. Scheerlinck, K. I. Theron, Non-destructive measurement of bitter pit in apple fruit using NIR hyperspectral imaging. Postharvest Biol. Technol. 40, 1-6 (2006).
9. X. Cheng, Y. R. Chen, Y. Tao, C. Y. Wang, M. S. Kim, A. M. Lefcourt, A novel integrated PCA and FLD method on hyperspectral image feature extraction for cucumber chilling damage inspection. Trans. ASAE 47, 1313-1320 (2004).
10. K. Lee, K. Kang, S. R. Delwiche, M. S. Kim, S. Noh, Correlation analysis of hyperspectral imagery for multispectral wavelength selection for detection of defects on apples. J. Sens. Instrum. Food Qual. Saf. 2, 90-96 (2008).
11. P. M. Mehl, Y. R. Chen, M. S. Kim, D. E. Chan, Development of hyperspectral imaging technique for the detection of apple surface defects and contaminations. J. Food Eng. 61, 67-81 (2004).
12. G. ElMasry, N. Wang, C. Vigneault, Detecting chilling injury in Red Delicious apple using hyperspectral imaging and neural networks. Postharvest Biol. Technol. 52, 1-8 (2009).
13. J. Xing, P. Jancsók, J. De Baerdemaeker, Stem-end/calyx identification on apples using contour analysis in multispectral images. Biosyst. Eng. 96, 231-237 (2007).
14. J. Qin, T. Burks, M. S. Kim, K. Chao, M. A. Ritenour, Citrus canker detection using hyperspectral reflectance imaging and PCA-based image classification method. J. Sens. Instrum. Food Qual. Saf. 2, 168-177 (2008).
15. A. A. Gowen, C. P. O'Donnell, M. Taghizadeh, E. Gaston, A. O'Gorman, Hyperspectral imaging for the investigation of quality deterioration in sliced mushroom (Agaricus bisporus) during storage. J. Sens. Instrum. Food Qual. Saf. 2, 133-143 (2008).
16. D. P. Ariana, R. F. Lu, D. E. Guyer, Near-infrared hyperspectral reflectance imaging for detection of bruises on pickling cucumbers. Comput. Electron. Agric. 53, 60-70 (2006).
17. Y. Liu, Y. R. Chen, C. Y. Wang, D. E. Chan, M. S. Kim, Development of hyperspectral imaging techniques for the detection of chilling injury in cucumbers; spectral and image analysis. Appl. Eng. Agric. 22, 101-111 (2006).
18. R. Lu, Y. Peng, Hyperspectral scattering for assessing peach fruit firmness. Biosyst. Eng. 93, 161-171 (2006).
19. F. Hahn, I. Lopez, G. Hernandez, Spectral detection and neural network discrimination of Rhizopus stolonifer spores on red tomatoes. Biosyst. Eng. 89, 93-99 (2004).
20. G. ElMasry, N. Wang, A. ElSayed, M. Ngadi, Hyperspectral imaging for nondestructive determination of some quality attributes for strawberry. J. Food Eng. 81, 98-107 (2007).
21. M. S. Kim, Y. R. Chen, B. Cho, A. M. Lefcourt, K. Chao, C. C. Yang, Hyperspectral reflectance and fluorescence line-scan imaging for online quality and safety inspection of apples. J. Sens. Instrum. Food Qual. Saf. 1, 151-159 (2007).
22. A. M. Vargas, M. S. Kim, Y. Tao, A. M. Lefcourt, Y. R. Chen, Y. Luo, Y. Song, Y. Buchanan, Detection of fecal contamination on cantaloupes using hyperspectral fluorescence imagery. J. Food Sci. 70, E471-E476 (2005).
23. S. R. Delwiche, M. S. Kim, Y. Dong, Fusarium damage assessment in wheat kernels by Vis/NIR hyperspectral imaging. J. Sens. Instrum. Food Qual. Saf. 5, 63-71 (2011).
24. V. Weidner, P. Barnes, K. Eckerle, A wavelength standard for the near infrared based on the reflectance of rare-earth oxides. J. Res. Natl. Bur. Stand. 91, 243-253 (1986).
25. M. S. Kim, K. Chao, D. Chan, W. Jun, A. Lefcourt, S. Delwiche, K. Lee, Line-scan hyperspectral imaging platform for food safety and quality evaluation: system characterization and enhancement. Trans. ASABE 54(2), 703-711 (2011).