GREEN SEED COAT COLOUR RETENTION IN LENTIL - University ...

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perceive colour. Cone cells are used in brighter conditions and are responsible for perception of colour. People that are colour blind do not have fully functioning cone cells (Montgomery, 2007). The colour that is perceived by the cone cell of the eye is the wavelength that the object reflects (Lew, 2001). Every person sees different colours somewhat differently. Across a population of people the range of colour perception is very large from complete colour blindness to an ability to perceive colours in the two extremes of the visible light range. This variability makes the use of machines intriguing. If machines are calibrated properly and have the ability to consistently classify colour, the opportunity exists to have reliable and repeatable measurement of colour across many different environments. With machines it is possible to have repeatable measurements across machines, which is not possible between humans. Instruments can be used to accurately and consistently determine the colour of seed samples. The Acurum ® machine (Figure 2.1) is a computerized colour analyzing machine developed by DuPont. The computer used a Windows ® based personal computer operating at 3 gigahertz. Before each sample was analyzed the machine calibrated itself using an internal colour card. This was important because the machine operated in a dusty environment that could affect analysis. The colour card had proprietary colour definitions, not from any international standards. The machine uses a camera to record digital images of one side of individual seeds as a sample passes by in a single layer on a conveyor belt. The camera captures digital images at a size of 768 × 1024 pixels as white LED strobe lights flash. The images are analyzed in a bitmap format with an eight bit colour display. Neural networks 8
process and categorize the data into predefined colour categories. As the machine analyzes each image it uses mathematical models to define each seed in the image. Each seed within the image is then subjected to colour analysis through the use of algorithms to classify each seed. The machine operates at a speed of 2.5 images per second. Approximately 30 lentil seeds are captured in each frame (Van Natto, 2007). The colour categories that were used in this research were defined by Larry Michta, a former Canadian Grain Commission grader (Table 2.2). The colour categories were designed to match commercial industry standards and were not all the same size in the 3-D colour spectrum. This was the basis of the colour categories used in the commercial interface for the machine. The desirability of the lentil seeds are measured numerically by the Acurum ® machine. The categories are numbered one through 20 with the lowest numbers representing most desired colour. The higher numbered categories represent decreasing desirability and show definite yellow and brown colours. Table 2.2 can be structured to show approximate grades that would be assigned by the CGC to the lentil sample. Scores 1 through 3 would be a Canada number 1. Scores 4 through 7 would be a Canada number 2. A Canada extra 3 grade would be 8 through 10. A Canada number 3 would be 11 through 13. Scores 14 through 20 would all be sample or feed grade lentils. Samples that are composed of many different lentils seeds from many scores are graded lower than the best individual seeds scores. 9
Page 1 and 2: GREEN SEED COAT COLOUR RETENTION IN
Page 3 and 4: ABSTRACT Poor seed coat colour desi
Page 5 and 6: ACKNOWLEDGEMENTS The author would l
Page 7 and 8: 7.2 Maturity and Index Score ......
Page 9 and 10: Table 4.13 Acurum index score, tota
Page 11 and 12: 1.0 INTRODUCTION Green lentil has b
Page 13 and 14: example canola. In wheat it is used
Page 15 and 16: carbohydrate, and micronutrient req
Page 17: It would also be useful for lentil
Page 21 and 22: Table 2.2 Descriptions of the colou
Page 23 and 24: 2.4 Perceived seed colour in green
Page 25 and 26: 2.6 Cotyledon chlorophyll degradati
Page 27 and 28: temperatures. The more enzyme activ
Page 29 and 30: the seed produces bleached seeds wi
Page 31 and 32: correlation between seed weight in
Page 33 and 34: used widely as a desiccant is that
Page 35 and 36: prevailing winds. A problem that oc
Page 37 and 38: and the higher the heritability est
Page 39 and 40: 4.1 Heritability Study Objectives 4
Page 41 and 42: Plant material for the study includ
Page 43 and 44: Table 4.4 Herbicide and desiccant a
Page 45 and 46: was a=0.05. The heritability was ca
Page 47 and 48: during the time taken to remove the
Page 49 and 50: normally distributed data. In 2006
Page 51 and 52: location and year explained a large
Page 53 and 54: The tester set that was included in
Page 55 and 56: etween field and phytotron index sc
Page 57 and 58: Table 4.10 shows the mean index sco
Page 59 and 60: Sutherland in 2005 produced the mos
Page 61 and 62: Table 4.12 Effect of changing the n
Page 63 and 64: wrinkling as sound seeds. It is dif
Page 65 and 66: negative relationship. The regressi
Page 67 and 68: Chlorophyll b content (mg/g) 120 10
Page 69 and 70:
1994). It is important to note howe
Page 71 and 72:
estimates of which lines produced t
Page 73 and 74:
in both years to produce two differ
Page 75 and 76:
At the time of desiccation or swath
Page 77 and 78:
a significant genotype x environmen
Page 79 and 80:
Table 5.7 Mean green index score of
Page 81 and 82:
All three groups for both desiccati
Page 83 and 84:
index score was not equal for each
Page 85 and 86:
Alternatively, the samples had less
Page 87 and 88:
sclerotinia white mold (Sclerotinia
Page 89 and 90:
6.0 GENERAL DISCUSSION Knowing whic
Page 91 and 92:
The Acurum ® machine has some pote
Page 93 and 94:
process. If small gains in desirabi
Page 95 and 96:
for more efficient selection sooner
Page 97 and 98:
8.0 REFERENCES AAFC. 2007. Agricult
Page 99 and 100:
Guiamét, J.J., E. Schwartz, E. Pic
Page 101 and 102:
Shearer, S.A., G.M. Turner, M. Coll
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