Detection of sprout-damaged wheat using thermal imaging

Applied Engineering in Agriculture

Volumn 26, Issue 6, 2010, Pages 999-1004

  Vadivambal, R ^a   Chelladurai, V ^a   Jayas, D S ^a,b   White, N D G ^a  

^a AGRICULTURE AND AGRI FOOD CANADA   (Canada)

^b UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Artificial neural network; Sprout damage; Statistical classification; Thermal imaging; Wheat

Indexed keywords

ARTIFICIAL NEURAL NETWORK; SPROUT DAMAGE; STATISTICAL CLASSIFICATION; THERMAL IMAGING; WHEAT;

DISCRIMINANT ANALYSIS; GRAIN (AGRICULTURAL PRODUCT); INFRARED IMAGING;

NEURAL NETWORKS;

TRITICUM AESTIVUM;

EID: 78650396553     PISSN: 08838542     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (35)

1. AACC. 2000. Approved Methods of the American Association of Cereal Chemists. Method 5681B. 10th ed. St. Paul, Minn.: AACC.
2. Bailey, C. H., and A. M. Gurjar. 1920. Respiration of cereal plants and grains: II. Respiration of sprouted wheat. J. Biological Chem. 44(1): 5-7.
3. Baranowski, P., W. Mazurek, and R. T. Walczak. 2003. The use of thermography for presowing evaluation of seed germination capacity. Acta Hort. 604(2): 459-494.
4. Barnard, A., C. S. Van Deventer, and H. Maartens. 2005. Comparison between methods for estimating sprout damage in wheat. South African J. Plant and Soil 22(1): 44-48.
5. CGC. 2008. Procedures for the falling number test. Winnipeg, Manitoba, Canada: Canadian Grain Commission. Available at: www.grainscanada.gc.ca/wheat- ble/method-methode/fnt-dic-eng.htm. Accessed 22 August 2010.
6. Czuchajowska, Z., and Y. Pomeranz. 1993. Estimation of preharvest sprouting in wheat and barley by near-infrared reflectance spectroscopy. Pre-harvest Sprouting in Cereals, 409-416. M. K. Walker-Simmons, and J. L. Ried, eds. St. Paul, Minn.: AACC.
7. Danno, A., M. Miyazato, and E. Ishiguro. 1980. Quality evaluation of agricultural products by infrared imaging method: Maturity evaluation of fruits and vegetables. Memoirs Faculty Agric., Kagoshima University 16: 157-164.
8. Danno, A., M. Miyazato, and E. Ishiguro. 1977. Quality evaluation of agricultural products by infrared imaging method: Grading of fruits for bruise and other surface defects. Memoirs Faculty Agric., Kagoshima University 14: 123-138.
9. Derera, N. F. 1990. A perspective of sprouting research. Proc. of the 5th Intl. Symposium on Preharvest Sprouting in Cereals. K. Ringlund, E. Mosleth, and D. J. Mares, eds. Boulder, Colo.: Westview Press.
10. Friedman, J. H. 1989. Regularized discriminant analysis. J. American Statistical Assoc. 84(405): 165-175.
11. Gonzalez, R. C., and R. E. Woods. 2002. Digital Image Processing. 2nd ed. Upper Saddle River, N.J.: Prentice Hall. Huang
12. G., and E. Varriano-Marston. 1980. α-amylase activity and preharvest sprouting damage in Kansas hard white wheat. J. Agric. Food Che. 28(3): 509-512.
13. Jayas, D. S., J. Paliwal, and N. S. Visen. 2000. Multilayer neural networks for image analysis of agricultural products. J. Agric. Eng. Res. 77(2): 119-128.
14. Jensen, S. A., L. Munck, and J. E. Kruger. 1984. A rapid fluorescence method for assessment of preharvest sprouting of cereal grains. J. Cereal Sci. 2(3): 187-201.
15. Koeltzow, D. E., and A. C. Johnson. 1992. Comparison of sprout damage analysis techniques. Pre-harvest Sprouting in Cereals, 391-399. M. K. Walker-Simmons, and J. L. Ried, eds. St. Paul, Minn.: AACC.
16. Kruger, J. E. 1994. Enzymes of sprouted wheat and their possible technological significance. Wheat Production, Properties and Quality. W. Bushuk, and V. F. Rasper, eds. Glasgow, London: Blackie Academic and Professional.
17. Mahesh, S., A. Manickavasagan, D. S. Jayas, J. Paliwal, and N. D. G. White. 2008. Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes. Biosystems Eng. 101(1): 50-57.
18. Majumdar, S., and D. S. Jayas. 2000. Classification of cereal grains using machine vision: IV. Combined morphology, color and texture models. Trans. ASAE 43(6): 1689-1694.
19. Manickavasagan, A., D. S. Jayas, and N. D. G. White. 2008. Thermal imaging to detect infestation by Cryptolestes ferrugineus inside wheat kernels. J. Stored Prod. Res. 44(2): 186-192.
20. Manickavasagan, A., D. S. Jayas, and N. D. G. White. 2006. Non-uniformity of surface temperatures of grain after microwave treatment in an industrial microwave dryer. Drying Tech. 24(12): 1559-1567.
21. Mansour, K. 1992. Sprout damage in wheat and its effect on wheat flour products. Pre-harvest Sprouting in Cereals, 8-9. M. K. Walker-Simmons, and J. L. Ried, eds. St. Paul, Minn.: AACC.
22. MATLAB. 2009. Available at: www.mathworks.com/access/ helpdesk/help/toolbox/images/graythresh.html. Accessed 15 February 2010.
23. Meinlschmidt, P., and V. Margner. 2003. Thermographic techniques and adopted algorithms for automatic detection of foreign bodies in food. Proc. of Thermosense XXV, 168-177. Bellingham, Wash.: The International Society for Optical Engineering.
24. Mohan, A. 2008. Pre-harvest sprouting in cereals: A global scenario. Current Sci. 94(6): 704-705.
25. Naes, T., T. Isaksson, T. Fearn, and T. Davies. 2002. A user friendly guide to multivariate calibration and classification, Chichester, West Sussex: NIR Publications.
26. Neethirajan, S., D. S. Jayas, and N. D. G. White. 2007. Detection of sprouted wheat kernels using soft X-ray image analysis. J. Food Eng. 81(3): 509-513.
27. Shashikumar, K., J. L. Hazelton, G. H. Ryu, and C. E. Walker. 1993. Predicting sprout damage by near-infrared reflectance analysis. Cereal Foods World 38(5): 364-366.
28. Singh, C. B., D. S. Jayas, J. Paliwal, and N. D. G. White. 2009 Detection of sprout and midge-damaged wheat kernels using near-infrared hyperspectral imaging. Cereal Chem. 86(3): 256-260.
29. Sivakumar, S. S. 2006. Potential applications of hyperspectral imaging for the determination of total soluble solids, water content and firmness in mango. M.Sc thesis. Montreal, Quebec: McGill University, Department of Bioresource Engineering.
30. Sorells, M. E., A. H. Paterson, and P. L. Finney. 1989. Milling and baking quality of soft white wheat genotypes subjected to preharvest sprouting. Cereal Chem. 66(5): 407-410.
31. Tahir, A. R., S. Neethirajan, D. S. Jayas, M. A. Shahin, S. J. Symons, and N. D. G. White. 2007. Evaluation of the effect of moisture content on cereal grains by digital image analysis. Food Res. Inter. 40(9): 1140-1145.
32. Wahl, T. I., and D. O'Rourke. 1994. The economics of sprout damage in wheat. Agribusiness 10(1): 27-41.
33. Vadivambal, R., and D. S. Jayas. 2010. Application of thermal imaging in agriculture and food industry. Food and Bioprocess Tech. DOI: 10.1007/s11947-010-0333-5.
34. Varith, J., G. M. Hyde, A. L. Baritelle, J. K. Fellman, and T. Sattabongkot. 2003. Non-contact bruise detection in apples by thermal imaging. Innovative Food Sci. Emerging Tech. 4(2): 211-218.
35. Visen, N. S., D. S. Jayas, J. Paliwal, and N. D. G. White. 2004. Comparison of two neural network architectures for classification of singulated cereal grains. Can. Biosystems Eng. 46: 3.7-3.14.