Image analysis – Applications – Animal – plant – or food inspection
Patent
1996-11-05
1999-04-27
Johns, Andrew W.
Image analysis
Applications
Animal, plant, or food inspection
382165, G06K 900
Patent
active
058987924
DESCRIPTION:
BRIEF SUMMARY
METHODS AND DEVICES FOR AUTOMATIC ASSESSMENT OF CORN
The present invention relates to methods and devices for determining the flour yield, the protein content and the bulk density for a plurality of cereal kernels.
The flour yield is defined as the amount of flour obtained from an amount of corn of a given weight, for instance one tonne, and is expressed in % by weight. When purchasing corn for a flour mill, it is desirable to be able to predict the flour yield for different corn consignments, thereby making it possible to select the consignments that give the highest flour yield and, thus, the largest profits for the flour mill.
Today, the flour yield is predicted by determining the bulk density (also called volumetric weight) for a sample from the corn consignment. Generally, one litre of kernels of the corn concerned is simply weighed. It is in fact considered that the bulk density provides a rough measure of the flour yield.
In the article "Effects of Grain Shape and Size on Milling Yields in Wheat" by D. R. Marshall, D. J. Mares, H. J. Moss and F. W. Ellison in Aust. J. Agric. Res., 1986, 37, p. 340, it is, however, said that the correlation between bulk density and flour yield depends on both the site and the kind of corn and that the bulk density thus cannot be used to reliably predict the flour yield.
In the patent literature, there are examples of experiments of determining the flour yield in other ways than by means of the bulk density.
For example, FR 2,416,465 discloses an instrument for transillumination of corn samples and determination of the flour yield by the transmitted light.
The results obtained by means of this instrument are not known. However, it may be established that there is today no commercially available and practically applicable alternative to using the bulk density, if the flour yield is to be determined.
The above-mentioned article by Marshall, Mares, Moss and Ellison describes an investigation of the effects of the size and shape of the cereal kernels on the flour yield. In the discussion on p. 340, it is stated that the effect of the size of the kernels on the flour yield is small compared with the effects of other factors and is not always easy to demonstrate. Of the other parameters investigated (for example protein content, hardness, depth of crease, bran-layer thickness), only bulk density showed a significant relationship with flour yield.
A first object of the present invention thus is to provide a method and a device which permit accurate determination of the flour yield for a plurality of cereal kernels before milling.
There is also a great interest in quick and easy determination of the protein content in a consignment of corn. Different end users, for example flour mills, malt-houses and fodder factories, require different protein contents. It would therefore be advantageous if already at an early stage in the handling of corn it would be possible to select consignments of corn having the desired protein content, or possibly mix different consignments so as to obtain the desired protein content.
Today, the protein content is usually determined by analysis using infrared light. The analysis can be carried out on reflected or transmitted infrared light and on entire kernels or on flour.
The article "Relation of Kernel Color to Wheat Class and Grade", Cereal Science Today, Vol. 17, November 1972, describes an investigation in which a Hunter Color Difference Meter is used to measure the colour of wheat in an experiment of specifying the colour of wheat and distinguishing among different wheat grades by objective colour measurements. Simple, multiple and partial correlation techniques are used to evaluate the correlations between the Hunter colour values and the grading factors. Among other things, the correlations between on the one hand the protein content in five different grades of wheat and, on the other hand, the Hunter colour values were studied. The highest correlation, -0.645, was obtained between soft white wheats and the Hunter colour value B (blue-yellow
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Zayas et al., "Discrimination Between Wheat Classes and Varieties by Image Analysis," Cereal Chemistry, vol. 63, No. 1, 1986, pp. 52-56.
Chen et al., "Relation of Kernal Color to Wheat Class and Grade," Cereal Science Today, vol. 17, No. 11, Nov. 1972, pp. 340-343.
Neuman et al., "Discrimination of Wheat Class and Variety by Digital Image Analysis of Whole Grain Samples," Journal of Cereal Science, vol. 6, 1987, pp. 125-132.
Winter et al., "Discrimination of Hard-to-Pop Popcorn Kernels by Machine Vision and Neural Network," Paper No. Mansask 96-107 presented at the 1996 North-Central Intersectional ASAE/CSAE Meeting, Sep. 27-28 1996.
D. R. Marshall et al., Aust. J. Agric. Res., vol. 37, pp. 331-342, 1986, "Effects of Grain Shape and Size on Milling Yields in Wheat II--Experimental Studies".
Egelberg Peter
M.o slashed.nsson Olle
Oste Rickard
Peterson Carsten
Svensson Eivor
Agrovision AB
Johns Andrew W.
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