Skip to main content

Advertisement

SpringerLink
Log in

X-ray imaging methods for internal quality evaluation of agricultural produce

  • Review
  • Published:
Journal of Food Science and Technology Aims and scope Submit manuscript

Abstract

A number of non-destructive methods for internal quality evaluation have been studied by different researchers over the past eight decades. X-ray and computed tomography imaging techniques are few of them which are gaining popularity now days in various fields of agriculture and food quality evaluation. These techniques, so far predominantly used in medical applications, have also been explored for internal quality inspection of various agricultural products non-destructively, when quality features are not visible on the surface of the products. Though, safety of operators and time required for tests are of concern, the non-destructive nature of these techniques has great potential for wide applications on agricultural produce. This paper presents insight of X-ray based non-destructive techniques such as X-ray imaging and Computed Tomography (CT). The concepts, properties, equipment and their parameters, systems and applications associated with the use of X-rays and CT for agricultural produce have been elaborated.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Abbott J (1999) A quality measurements of fruits and vegetables. Postharvest Biol Technol 15:207–225

    Article  Google Scholar 

  • Anonymous (2003) Dual energy digital imaging. Available at: http://www.amershamhealth.com/medcyclopaedia/VolumeI/DUALENERGYDIGITALIMAGING.asp. Accessed on 27 April 2003

  • Anonymous (2008) X-ray imaging and computed tomography. Available at www.media.wiley.com/product_data/0471237663.pdf Accessed on 2 November 2008

  • Anonymous (2010) History of radiography. Available on http://www.ndt-ed.org/EducationResources/CommunityCollege/Radiography/Introduction/history.htm. Accessed on 10 December 2010.

  • Anonymous (2010a) Radiographic film. Available on http://www.ndt-ed.org/EducationResources/CommunityCollege/Radiography/EquipmentMaterials/radiographicfilm.htm. Accessed on 10 December 2010.

  • Anonymous (2011a) Attenuation coefficient. Available at http://en.wikipedia.org/wiki/attenuation_coefficient. Accessed on 21 March 2011.

  • Anonymous (2011b) Computed tomography. Available at www.ecse.rpi.edu/censsis/SSI-Course/Lectures.2004/Lecture%205/9%2520Computed%2520Tomography.pdf Accessed on 14 July 2011.

  • Ayalew G, Holden NM, Grace PK, Ward SM (2004) Detection of glass contamination in horticultural peat with dual-energy x-ray absorptiometry (DXA). Comput Electron Agric 42:1–17

    Article  Google Scholar 

  • Arslan S, Inanc F, Gray JN, Colvin TS (2000) Grain flow measurements with X-ray techniques. Comput Electron Agric 26(200):65–80

    Article  Google Scholar 

  • Barcelon EG, Tojo S, Watanabe K (1999a) X-ray computed tomography for internal quality evaluation of peaches. J Agric Eng Res 73(4):323–330

    Article  Google Scholar 

  • Barcelon EG, Tojo S, Watanabe K (1999b) Relating X-ray absorption and some quality characteristics of Mango fruit (Mangifera indica L.). J Agric Food Chem 47:3822–3825

    Article  CAS  Google Scholar 

  • 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

    Google Scholar 

  • Brennan JG, Butters JR, Cowell ND, Lilley AEV (1990) Food engineering operation, IIIth edn. Elsevier, London

    Google Scholar 

  • Brosnan T, Sun DW (2004) Improving quality inspection of food products by computer vision- a review. J Food Eng 61(1):3–16

    Article  Google Scholar 

  • Buzzell P, Pintauro S (2003) Dual energy X-ray absorptiometery. Department of food sciences and nutrition. University of Vermont. Available at http://nutrition.uvm.edu/bodycomp/dexa/. Accessed on January 6, 2003

  • Casasent DA, Sipe MA, Schatzki TF, Keagy PM, Lee LC (1998) Neural net classification of X-ray pistachio nut data. Lebensm-Wiss u-Technol (Food Sci + Technol) 31(2):122–128

    Article  CAS  Google Scholar 

  • Casasent D, Talukder A, Keagy P, Schatzki T (2001) Detection and segmentation of items in X-ray imagery. Trans ASAE 44(2):337–345

    Google Scholar 

  • Chen P, Sun Z (1991) A review of non-destructive methods for quality evaluation and sorting of agricultural products. J Agric Eng Res 49:85–98

    Article  Google Scholar 

  • Cunningham IA, Judy PF (2000) Computed tomography. In: Bronzino JD (ed) The biomedical engineering handbook, secondth edn. CRC Press LLC, Boca Raton

    Google Scholar 

  • Curry TS, Dowdey JE, Murry RC Jr (1990) Christensen’s physics of diagnostic radiology, 4th edn. Williams and Wilkins, Baltimore

    Google Scholar 

  • Diener RG, Mitchell JP, Rhoten ML (1970) Using an X-ray image scan to sort bruised apples. Agric Eng 356–361

  • Dogan H (2007) Nondestructive imaging of agricultural products using X-ray microtomography. Microsc Microanal 13(2):1316 CD–1317 CD

    Google Scholar 

  • Du CJ, Sun DW (2006) Learning techniques used in computer vision for food quality evaluation: a review. J Food Eng 72:39–55

    Article  Google Scholar 

  • Farkas J (2006) Irradiation for better foods. Tr Food Sci Technol 17:148–152

    Article  CAS  Google Scholar 

  • Farkas J, Csilla M-F (2011) History and future of food irradiation. Tr Food Sci Technol 22:121–126

    Article  CAS  Google Scholar 

  • Fornal J, Jelinski T, Sadowska J, Grundas S, Nawrot J, Niewiada A, Warchalewski J, Blaszczak W (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

    Article  Google Scholar 

  • Gonzalez RC, Woods RE (2001) Digital image processing, 2nd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Gruner SM, Tate MW, Eikenberry EF (2002) Charged couple device area X-ray detectors. Review Scientific Instru 73(8):2815–2842

    Article  CAS  Google Scholar 

  • Gunasekaran S, Paulsen MR, Shove GC (1985) Optical methods for nondestructive quality evaluation of agricultural and biological materials. J Agric Eng Res 32:209–241

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Han YJ, Bowers SV, Dodd RB (1992) Nondestructive detection of split-pit peaches. Trans ASAE 35(6):2063–2067

    Article  Google Scholar 

  • Harrison RD, Gardner WA, Tollner WE, Kinard DJ (1993) X-ray computed tomography studies of the burrowing behavior of fourth-instar pecan weevil (Coleoptera:Curculionidae). J Econ Ent 86(6):1714–1719

    Google Scholar 

  • Haseth TT, Egelandsdal B, Bjerke F, Sorheim O (2007) Computed tomography for quantitative determination of sodium chloride in ground pork and dry cured hams. J Food Sci 72(8):E-420–E427

    Article  CAS  Google Scholar 

  • Haseth TT, Kongsro HJ, Kohiler A, Sorheim O, Egelandsdal B (2008) Determination of sodium chloride in pork meat by computed tomography at different voltages. J Food Sci 73(7):E333–E339

    Article  CAS  Google Scholar 

  • 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

  • Jiang JA, Chang HY, Wu KH, Ouyang CS, Yang MM, Yang EC, Chen TW, Lin TT (2008) An adaptive image segmentation algorithm for X-ray quarantine inspection of selected fruits. Comput Electron Agric 60:190–200

    Article  Google Scholar 

  • Karunakaran C, Jayas DS, White NDG (2003a) X-ray image analysis to detect infestations caused by insects in grain. Cereal Chem 80(5):553–557

    Article  CAS  Google Scholar 

  • Karunakaran C, Jayas DS, White NDG (2003b) Soft X-ray inspection of wheat kernels infested by Sitophilus Oryzae. Trans ASAE 46(3):739–745

    Google Scholar 

  • Karunakaran C, Jayas DS, White NDG (2004a) Detection of infestations by Cryptolestes ferrugineus inside wheat kernels using soft X-ray method. Can Biosyst Eng 46:7.1–7.9

    Google Scholar 

  • Karunakaran C, Jayas DS, White NDG (2004b) An on-line X-ray system for grain inspection—a future perspective. In: Proc. 2004 CIGR Int. Conf. Paper No. 30-211A,Beijing, China

  • Karunakaran C, Jayas DS, White NDG (2004c) Detection of internal wheat seed infestation by Rhyzopertha dominica using X-ray imaging. J Stored Prod Res 40:507–516

    Article  Google Scholar 

  • Karunakaran C, Jayas DS, White NDG (2004d) Identification of wheat kernels damaged by the red flour beetle using X-ray images. Biosyst Eng 87(3):267–274

    Article  Google Scholar 

  • Karunakaran C, Paliwal J, Jayas DS, White NDG (2005) Comparison of soft X-rays and NIR spectroscopy to detect insect infestations in grain. ASAE Paper Number: 053139 ASAE Annual International Meeting, Sponsored by ASAE Tampa Convention Center, Tampa, Florida,17–20 July 2005

  • Katz R, Lee MR, Milner M (1950) X-ray inspection of wheat. Nondestr Test 9(2):16–18

    Google Scholar 

  • Keagy PM, Schatzki TF (1991) Effect of image resolution on insect detection in wheat radiographs. Cereal Chem 68(4):339–343

    Google Scholar 

  • Keagy PM, Parvin B, Schatzki TF (1996) Machine recognition of navel orange worm damage in X-ray images of pistachio nuts. Lebensmittel-Wissenschaft + Technologie (Food Sci + Technol) 29(1&2):140–145

    CAS  Google Scholar 

  • Kim S, Schatzki TF (2000) Apple water-core sorting system using X-ray imagery: I. Algorithm development. Trans ASAE 43(6):1695–1702

    Article  Google Scholar 

  • Kim S, Schatzki TF (2001) Detection of pinholes in almonds through X-ray imaging. Trans ASAE 44(4):997–1003

    Google Scholar 

  • Kirkpatrick RL, Wilbur DA (1965) The development and habits of the granary weevil, Sitophilus granaries within the kernel of wheat. J Econ Ent 58:979

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Kotwaliwale N, Subbiah J, Weckler PR, Brusewitz GH, Kranzler GA (2007a) Calibration of a soft X-ray digital imaging system for biological materials. Trans ASABE 50(2):661–666

    Article  Google Scholar 

  • Kotwaliwale N, Weckler PR, Brusewitz GH, Kranzler GA (2007b) Non-destructive quality determination of pecans using soft X-rays. Postharvest Biol Techno 45:372–380

    Article  CAS  Google Scholar 

  • Kotwaliwale N, Kalne A, Singh K (2011) Radiography, CT and MRI. In: Jha SN (ed) Book chapter in non destructive evaluation of food quality-theory and practice. Springer, Berlin

    Google Scholar 

  • Kroger C, Bartle CM, West JG, Purchas RW, Devine CE (2006) Meat tenderness evaluation using dual energy X-ray absorptiometry (DEXA). Comput Electron Agric 54:93–100

    Article  Google Scholar 

  • Lammertyn J, Jancsok P, Dresselaers T, Van Hecke P, Wevers M, De Baerdemaeker J, Nicolai B (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

    Article  CAS  Google Scholar 

  • Lenker DH, Adrian PA (1971) Use of soft X-rays for selecting mature lettuce heads. Trans ASAE 14:894–898

    Article  Google Scholar 

  • Leonard A, Blacher S, Nimmol C, Devahastin S (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

    Article  Google Scholar 

  • Lim KS, Barigou M (2004) X-ray micro-computed tomography of cellular food products. Food Res Int 37:1001–1012

    Article  Google Scholar 

  • Martel P, Belanger A (1977) Xerography, a new tool for in situ study of insects. Can Ent 109:317

    Article  Google Scholar 

  • Mathanker SK, Weckler PR, Bowser TJ, Wang S, Maness NO (2011) AdaBoost classifiers for pecan defect classification. Comput Electron Agric 77:60–68

    Article  Google Scholar 

  • Mills RB, Wilbur DA (1967) Radiographic studies of Angoumois grain moth development in wheat, corn and sorghum kernels. J Econ Ent 60(3):671–677

    Google Scholar 

  • Milner M, Lee MR, Katz R (1950) Application of X-ray technique to the detection of internal insect infestation of grain. J Econ Ent 43(6):933

    Google Scholar 

  • Milner M, Lee MR, Katz R (1952) Radiography applied to grain and seed. Food Technol 6:44–45

    Google Scholar 

  • Mohsenin NN (1986) Physical properties of plant and animal materials. G&B Scientific, NY

    Google Scholar 

  • Morita K, Tanaka S, Thai CN, Ogawa Y (1997) Development of soft X-ray imaging for detecting internal defects in food and agricultural products. Proc. Sensors for nondestructive testing: Measuring quality of Fresh Fruits & Vegetables- Florida (Feb 18–21, 1997):305–315

  • Mousavi R, Miri T, Cox PW, Fryer PJ (2007) Imaging food freezing using X-ray microtomography. Int J Food Sci Technol 42:714–727

    Article  CAS  Google Scholar 

  • Narvankar DS, Singh CB, Jayas DS, White NDG (2009) Assessment of soft X-ray imaging for detection of fungal infection in wheat. Biosyst Eng 103:49–56

    Article  Google Scholar 

  • Neethirajan S, Karunakaran C, Symonsc S, Jayas D (2006a) Classification of vitreousness in durum wheat using soft X-rays and transmitted light images. Comput Electron Agric 53:71–78

    Article  Google Scholar 

  • Neethirajan S, Karunakaran C, Jayas DS, White NDG (2006b) X-ray computed tomography image analysis to explain the airflow resistance differences in grain bulks. Biosyst Eng 94:545–555

    Article  Google Scholar 

  • Neethirajan S, Jayas DS, Karunakaran C (2007a) Dual energy X-ray image analysis for classifying vitreousness in durum wheat. Postharvest Biol Technol 45:381–384

    Article  Google Scholar 

  • Neethirajan S, Jayas DS, White NDG (2007b) Detection of sprouted wheat kernel using soft X-ray image analysis. J Food Eng 81:509–513

    Article  Google Scholar 

  • Neethirajan S, Jayas DS, White NDG, Zhang H (2008) Investigation of 3D geometry of bulk wheat and pea pores using X-ray computed tomography images. Comput Electron Agric 63:104–111

    Article  Google Scholar 

  • Okochi T, Hoshino Y, Fujii H, Mitsutani T (2007) Nondestructive tree-ring measurements for Japanese oak and Japanese beech using micro-focus X-ray computed tomography. Dendrochronologia 24:155–164

    Article  Google Scholar 

  • Ogawa Y, Morita K, Tanaka S, Setoguchi M, Thai CN (1998) Application of X-ray CT for detection of physical foreign materials in foods. Trans ASAE 41(1):157–162

    Article  Google Scholar 

  • Oghabian MA (2008) Medical physics. Tehran University of medical Sciences. Available at www.oghabian.net/download/MD%202%20X-ray%20Production.ppt. Accessed on 17 October 2008

  • Paiva RFD, Lynch J, Rosenberg E, Bisiaux M (1998) A beam hardening correction for X-ray microtomography. NDTE Int 31(1):17–22

    Article  Google Scholar 

  • Pearce KL, Ferguson M, Gardner G, Smith N, Greef J, Pethick DW (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

    Article  CAS  Google Scholar 

  • Schatzki TF, Fine (Brayant) TA (1988) Analysis of radiograms of wheat kernels for quality control. Cereal Chem 65(3):233–239

    Google Scholar 

  • Schatzki TF, Haff RP, Young R, Can I, Le LC, Toyofuku N (1997) Defect detection in apples by means of X-ray imaging. Trans ASAE 40(5):1407–1415

    Article  Google Scholar 

  • Shahin MA, Tollner EW (1997) Detection watercore in applies using X-ray linescans feature extraction and classification. Proceedings: Sensors for nondestructive testing: Measuring quality of Fresh Fruits & Vegetables- Florida (Feb 18–21, 1997):389–400

  • Shahin MA, Tollner EW, Prussia SE (1999) Filter design for optimal feature extraction from X-ray images. Trans ASAE 42(6):1879–1887

    Article  Google Scholar 

  • Sharifi S, Mills RB (1971a) Developmental activities and behaviour of the rice weevil inside wheat kernels. J Econ Ent 64(5):1114–1118

    Google Scholar 

  • Sharifi S, Mills RB (1971b) Radiographic studies of Sitophilus zeamais Mots. in wheat kernels. J Stored Prod Res 7:195

    Article  Google Scholar 

  • Sonego L, Ben-Arie R, Raynal J, Pech JC (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

    Article  Google Scholar 

  • Stermer RA (1972) Automated X-ray inspection of grain for insect infestation. Trans ASAE 1081–1085

  • Tao Y, Ibarra JG (2000) Thickness-compensated X-ray imaging detection of bone fragments in deboned poultry-Model analysis. Trans ASAE 43(2):453–459

    Article  Google Scholar 

  • Thai CN, Tollner EW, Morita K, Kays SJ (1997) X-ray characterization of sweet potato weevil larvae development and subsequent damage in infested roots. In: Proceedings Sensors for nondestructive testing: Measuring quality of Fresh Fruits & Vegetables- Florida (Feb 18–21, 1997):361–368

  • Thomas P, Kannan A, Degwekar VH, Ramamurthy MS (1995) Non-destructive detection of seed weevil-infested mango fruits by X-ray imaging. Postharvest Biol Technol 5(1–2):161–165

    Article  Google Scholar 

  • Thompson AK (1996) Post harvest technology of fruits and vegetables. Blackwell Science Ltd, Oxford

    Google Scholar 

  • Tillet RD (1991) Image analysis for agricultural processes. J Agric Eng Res 50:247–258

    Article  Google Scholar 

  • Tollner EW, Murphy C (1991) Factors affecting soil X-ray absorption coefficients with computed tomography. Trans ASAE 34(3):1047–1053

    Article  Google Scholar 

  • Tollner EW, Hung YC, Upchurch BL, Prussia SE (1992) Relating X-ray absorption to density and water content in apples. Trans ASAE 35(6):1921–1928

    Article  Google Scholar 

  • Tollner EW, Gitaitis RD, Seebold KW, Maw BW (2005) Experiences with a food product X-ray inspection system for classifying onions. Trans ASAE 21(5):907–912

    Google Scholar 

  • Webb S (1988) The physics of medical imaging. Adam Hilger, Bristol

    Book  Google Scholar 

  • Yacob Y, Ahmad H, Saad P, Aliana R, Raof A, Ismail S (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 Eng Res 63:161–170

    Article  Google Scholar 

  • Zwiggelaar R, Bull CR, Mooney MJ, Czarnes S (1997) Detection of “soft” materials by selective energy X-ray transmission imaging and computer tomography. J Agric Eng Res 66(3):203–212

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Agricultural Innovation Project, Indian Council of Agricultural Research through its subproject entitled “Development of non-destructive systems for evaluation of microbial and physico-chemical quality parameters of mango” (C1030).

Author information

Authors and Affiliations

  1. Central Institute of Agricultural Engineering, Nabibagh, Bhopal, 462 038, India

    Nachiket Kotwaliwale, Karan Singh & Abhimannyu Kalne

  2. Central Institute of Post Harvest Engineering and Technology, Ludhiana, 141 004, India

    Shyam Narayan Jha

  3. College of Agricultural Engineering and Technology, Godhra, India

    Neeraj Seth

  4. Indian Agricultural Research Institute, Pusa, New Delhi, 110 012, India

    Abhijit Kar

Authors
  1. Nachiket Kotwaliwale
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Karan Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abhimannyu Kalne
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shyam Narayan Jha
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Neeraj Seth
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Abhijit Kar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nachiket Kotwaliwale.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kotwaliwale, N., Singh, K., Kalne, A. et al. X-ray imaging methods for internal quality evaluation of agricultural produce. J Food Sci Technol 51, 1–15 (2014). https://doi.org/10.1007/s13197-011-0485-y

Download citation

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13197-011-0485-y

Keywords

Search

Navigation