Main Article Content
dehulling; image, lentil, plumpness, seed shape, seed size
Introduction Seed size and shape are important factors influencing trade in pulse grains. Lentil plumpness (determined by shape and size characteristics such as seed diameter, thickness, edge curvature, etc) is an important seed characteristic commonly believed to affect dehulling quality of lentils. Physical measurements of lentil shape and size characteristics are monotonous and time consuming. Objectives The focus of this research was to develop an imaging method to measure seed size and shape characteristics for predicting dehulling efficiency of red lentils. Methods A side-mounted camera system was used to image individual lentil seeds to determine seed size and shape characteristics. Results Regression models based on image analysis measurements of seed diameter, thickness, plumpness and degree of edge roundness predicted lentil dehulling efficiency highly accurately with an R2 approaching 0.90 and root-mean-squared-error <2%. Conclusion Image analysis can be used to measure lentil seed size and shape characteristics, which in turn can predict dehulling efficiency of red lentils.
Dalen G. (2004) Determination of the size distribution and percentage of broken kernels of rice using flatbed scanning and image analysis. Food Research International, 37(1), 51–58.
Drobny H.G., Boyer R., Kokko E. (2004) New digital imaging system for measuring grain quality parameters. Getreidetechnologie, 58 (6), 374–375. (in German).
Erasmus C., Taylor J.R.N. (2004) Optimising the determination of maize endosperm vitreousness by a rapid non-destructive image analysis technique. Journal of the Science of Food and Agriculture, 84(9), 920–930.
Erskine W., Williams P.C., Nakhoul H. (1991) Splitting and dehulling lentils (Lens culinaris): effects of size and different pretreatments. Journal of the Science of Food and Agriculture, 57(1), 77–84.
Falk J.D., Sokhansanj S., Besant R.W. (1996) Continuous measurement of the size and mass of wheat kernels using Michelson interferometry. Computers and Electronics in Agriculture,14 (1), 1–8.
Paliwal J., Visen N.S., Jayas D.S., White N.D.G. (2003) Cerealgrain and dockage identification using machine vision. Biosystems Engineering, 85(1), 51–57.
Sakai N., Yonekawa S. (1991) Three-dimensional image analysis of the shape of soybean seed. Journal of Food Engineering, 5(3), 221–234.
Sapirstein H.D., Kohler J.M. (1999) Effects of sampling and wheat grade on precision and accuracy of kernel features determined by digital image analysis. Cereal Chemistry,76(1), 110–115.
Shahin M.A., Symons S.J. (2003) Lentil type identification using machine vision.Canadian BioSystems Engineering, 45(3), 5–11.
Shahin M.A., Symons S.J. (2005) Seed sizing from images of non-singulated grain samples. Canadian BioSystems Engineering, 47(3), 49–55.
Shahin M.A., Symons S.J., Poysa V.W. (2006a) Determining soyabean seed size uniformity with image analysis. BioSystems Engineering, 94(2), 191–198.
Shahin M.A., Symons S.J., Schepdael L.V., Tahir A.R. (2006b)Three dimensional seed shape and size measurement with orthogonal cameras. ASABE Paper #063079; In Proceedings of the ASABE Annual International Meeting, Portland, OR(July 2006).
Tahir A.R., Jayas D., Shahin M., Symons S., White N.D.G.(2007) Evaluation of the effect of moisture content on cereal grains by digital image analysis. Food Research International, 40(9), 1140–1145.
Tanska M.D., Kozirok R.W., Konopka I. (2005) Measurement of the geometrical features and surface color of rapeseeds using digital image analysis. Food Research International, 38(7),741–750.
Venora G., Grillo O., Shahin M.A., Symons S.J. (2007) Identification of Sicilian landraces and Canadian cultivars of lentil by image analysis system. Food Research International, 40(1), 161–166.
Wang N. (2005) Optimization of a laboratory dehulling process for lentils (Lens culinaris). Cereal Chemistry, 82(6), 671–676.
Wang N. (2008) Effect of variety and crude protein on dehulling quality and on the resulting chemical composition of red lentil (Lens culinaris). Journal of the Science of Food and Agriculture, 88(5), 885–890.
Zayas I.Y., Martin C.R., Steele J.L., Katsevich A. (1996) Wheat classification using image analysis and crush-force parameters. Transactions of the ASAE. American Society of Agricultural Engineers, 39 (6), 2199–2204.