Abstract
Quality control is an important aspect of food production and processing providing foods of acceptable nutritional value, and safety of products. Several characteristics such as size, shape, density, maturity, moisture content, oil content, flavor, firmness, tenderness, color, defects, blemishes, etc., are routinely used in the quality control of agricultural and biological food products. Until recently, most analytical techniques used in quality control required isolation of the food component of interest. The original properties of the product are, therefore, destroyed during sample preparation and analysis. Oftentimes, such analyses are expensive, time consuming, and require sophisticated instrumentation, and hence are not suited for “on-line” quality control of food products. Recent progress in the development of instrumentation utilizing the some physical, optical, acoustic and electromagnetic properties of food products has provided several nondestructive techniques for quality evaluation. Many such methods are highly sensitive, rapid, and reproducible, and have been successively used in routine “on-line” quality control of a large number of samples.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abbott J (1999) A quality measurements of fruits and vegetables. Postharvest Biol Technol 15:207–225
Arslan S, Inanc F, Gray JN et al (2000) Grain flow measurements with X-ray techniques. Comput Electron Agric 26(200):65–80
ASPECT AI (2010). Aspect AI: MRI applications – agriculture. http://www.aspect-ai.com/applications/agriculture.php/. Accessed 18 Jan 2010
Ayalew G, Holden NM, Grace PK et al (2004) Detection of glass contamination in horticultural peat with dual-energy x-ray absorptiometry (DXA). Comput Electron Agric 42:1–17
Barcelon EG, Tojo S, Watanabe K (1999) X-ray computed tomography for internal quality evaluation of peaches. J Agric Eng Res 73(4):323–330
Barcelon EG, Tojo S, Watanabe K (2000) Nondestructive ripening assessment of mango using an X-ray computed tomography. Agric Eng J 9(2):73–80
Barreiro P, Ortiz C, Ruiz-Altisent M et al (2000) Mealiness assessment in apples and peaches using MRI techniques. Magn Reson Imaging 18:1175–1181
Brusewitz GH, Stone ML (1987) Wheat moisture by NMR. Trans ASAE 30(3):858–862
Buzzell P, Pintauro S (2003) Dual energy X-ray absorptiometery. Department of Food Sciences and Nutrition, University of Vermont. http://nutrition.uvm.edu/bodycomp/dexa /. Accessed 6 Jan 2003
Casasent DA, Sipe MA, Schatzki TF et al (1998) Neural net classification of X-ray pistachio nut data. Lebenson Wiss Technol 31(2):122–128
Casasent D, Talukder A, Keagy P et al (2001) Detection and segmentation of items in X-ray imagery. Trans ASAE 44(2):337–345
Chen P, McCarthy MJ, Kauten R (1989) NMR for internal quality evaluation of fruits and vegetables. Trans ASAE 32(5):1747–1753
Chen P, McCarthy MJ, Kauten R et al (1993) Maturity evaluation of avocados by NMR methods. J Agr Eng Res 55:177–187
Cho BK, Chayaprasert W, Stroshine RL (2008) Effects of internal browning and watercore on low field (5.4 MHz) proton magnetic resonance measurements of T2 values of whole apples. Postharvest Biol Technol 47:81–89
Clark CJ, Hockings PD, Joyce DC et al (1997) Application of magnetic resonance imaging to pre- and post-harvest studies of fruits and vegetables. Postharvest Biol Technol 11:1–21
Cuningham IA, Judy PF (2000) Computed tomography. In: JD Bronzino (ed) The biomedical engineering handbook, 2nd edn. CRC Press, Boca Raton, FL. http://www.kemt.fei.tuke.sk/. Accessed 2 Nov 2009
Curry TS, Dowdey JE, Murry RC (1990) Christensen’s physics of diagnostic radiology, 4th edn. Williams and Wilkins, Baltimore, MD
Diener RG, Mitchell JP, Rhoten ML (1970) Using an X-ray image scan to sort bruised apples. Agric Eng 51:356–361
Dogan H (2007) Nondestructive imaging of agricultural products using X-ray microtomography. Microsc Microanal 13(2):1316 CD–1317 CD
Fornal J, Jelinski T, Sadowska J et al (2007) Detection of granary weevil Sitophilus granarius (L.) Eggs and internal stages in wheat grain using soft X-ray and image analysis. J Stored Prod Res 43:142–148
Gonzalez JJ, Valle RC, Bobroff S et al (2001) Detection and monitoring of internal browning development in ‘fuji’ apples using MRI. Postharvest Biol Technol 22:179–188
Haff RP, Slaughter DC (2004) Real-time X-ray inspection of wheat for infestation by the granary weevil, Sitophilus granarius (L.). Trans ASAE 47(2):531–537
Han YJ, Bowers SV, Dodd RB (1992) Nondestructive detection of split-pit peaches. Trans ASAE 35(6):2063–2067
Haseth TT, Egelandsdal B, Bjerke F et al (2007) Computed tomography for quantitative determination of sodium chloride in ground pork and dry cured hams. J Food Sci 72(8):E–420–E427
Hubbell JH, Seltzer SM (1995) Tables of X-ray mass attenuation coefficients and mass energy absorption coefficients and mass energy absorption coefficients 1 keV to 20 MeV for elements Z = 1 to 92 and 48 additional substances of dosimetric interest. NISTIR 5632. National Institute of Standards and Technology, US Department of Commerce, Gaithersburg, MD, USA.
Karunakaran C, Jayas DS, White NDG (2004) Identification of wheat kernels damaged by the red flour beetle using X-ray images. Biosyst Eng 87(3):267–274
Keagy PM, Parvin B, Schatzki TF (1996) Machine recognition of navel orange worm damage in X-ray images of pistachio nuts. Lebenson Wiss Technol 29(1&2):140–145
Kim SM, Chen P, McCarthy MJ et al (1999) Fruit internal quality evaluation using on-line nuclear magnetic resonance sensors. J Agric Eng Res 74:293–301
Kim S, Schatzki TF (2000) Apple water-core sorting system using X-ray imagery: I Algorithm development. Trans ASAE 43(6):1695–1702
Kim S, Schatzki TF (2001) Detection of pinholes in almonds through X-ray imaging. Trans ASAE 44(4):997–1003
Kotwaliwale N, Subbiah J, Weckler PR et al (2007a) Calibration of a soft X-ray digital imaging system for biological materials. Trans ASABE 50(2):661–666
Kotwaliwale N, Weckler PR, Brusewitz GH (2006) X-ray attenuation coefficients using polychromatic X-ray imaging of pecan components. Biosyst Eng 94(2):199–206
Kotwaliwale N, Weckler PR, Brusewitz GH et al (2007b) Non-destructive quality determination of pecans using soft X-rays. Postharvest Biol Technol 45:372–380
Kroger C, Bartle CM, West JG et al (2006) Meat tenderness evaluation using dual energy X-ray absorptiometry (DEXA). Comput Electron Agric 54:93–100
Lammertyn J, Jancsok P, Dresselaers T et al (2003) Analysis of the time course of core breakdown in ‘conference’ pears by means of MRI and X-ray CT. Postharvest Biol Technol 29:19–28
Leonard A, Blacher S, Nimmol C et al (2008) Effect of far-infrared radiation assisted drying on microstructure of banana slices: an illustrative use of X-ray microtomography in microstructural evaluation of a food product. J Food Eng 85:154–162
Lim KS, Barigou M (2004) X-ray micro-computed tomography of cellular food products. Food Res Int 37:1001–1012
Marigheto N, Venturi L, Hills B (2008) Two-dimensional NMR relaxation studies of apple quality. Postharvest Biol Technol 48:331–340
McCarthy MJ (1994) Magnetic resonance imaging in foods. Chapman and Hall, New York
Mousavi R, Miri T, Cox PW et al (2007) Imaging food freezing using X-ray microtomography. Int J Food Sci Technol 42:714–727
Narvankar DS, Singh CB, Jayas DS et al (2009) Assessment of soft X-ray imaging for detection of fungal infection in wheat. Biosyst Eng 103:49–56
Neethirajan S, Jayas DS, Karunakaran C (2007) Dual energy X-ray image analysis for classifying vitreousness in durum wheat. Postharvest Biol Technol 45:381–384
Neethirajan S, Karunakaran C, Jayas DS et al (2006b) X-ray computed tomography image analysis to explain the airflow resistance differences in grain bulks. Biosyst Eng 94:545–555
Neethirajan S, Karunakaran C, Symonsc S et al (2006a) Classification of vitreousness in durum wheat using soft X-rays and transmitted light images. Comput Electron Agric 53:71–78
Ogawa Y, Morita K, Tanaka S et al (1998) Application of X-ray CT for detection of physical foreign materials in foods. Trans ASAE 41(1):157–162
Paiva RFD, Lynch J, Rosenberg E et al (1998) A beam hardening correction for X-ray microtomography. NDT&E Int 31(1):17–22
Pearce KL, Ferguson M, Gardner G et al (2009) Dual X-ray absorptiometry accurately predicts carcass composition from live sheep and chemical composition of live and dead sheep. Meat Sci 81:285–293
Schatzki TF, Haff RP, Young R et al (1997) Defect detection in apples by means of X-ray imaging. Trans ASAE 40(5):1407–1415
Sonego L, Ben-Arie R, Raynal J et al (1995) Biochemical and physical evaluation of textural characteristics of nectarines exhibiting woolly breakdown: NMR imaging, X-ray computed tomography and pectin composition. Postharvest Biol Technol 5:187–198
Thomas P, Kannan A, Degwekar VH et al (1995) Non-destructive detection of seed weevil-infested mango fruits by X-ray imaging. Postharvest Biol Technol 5(1–2):161–165
Tollner EW, Gitaitis RD, Seebold KW et al (2005) Experiences with a food product X-ray inspection system for classifying onions. Trans ASAE 21(5):907–912
Tollner EW, Hung YC, Upchurch BL et al (1992) Relating X-ray absorption to density and water content in apples. Trans ASAE 35(6):1921–1928
Yacob Y, Ahmad H, Saad P et al (2005) A comparison between X-ray and MRI in postharvest non-destructive detection method. Proceedings of the International Conference on Information Technology and Multimedia at UNITEN (ICIMU ’05), Malaysia
Zwiggelaar R, Bull CR, Mooney MJ (1996) X-ray simulations for imaging applications in the agricultural and food industries. J Agric Engng Res, 63, 161–170
Zwiggelaar R, Bull CR, Mooney MJ (1997) Detection of “soft” materials by selective energy X-ray transmission imaging and computer tomography. J Agric Eng Res 66(3):203–212
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kotwaliwale, N., Kalne, A., Singh, K. (2010). Radiography, CT and MRI. In: Jha, S. (eds) Nondestructive Evaluation of Food Quality. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15796-7_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-15796-7_5
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15795-0
Online ISBN: 978-3-642-15796-7
eBook Packages: Chemistry and Materials ScienceChemistry and Material Science (R0)