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Color as a Physical Property
Color is the most physical property allowing the first consumer judgement of product quality. The visual perception is psychologically associated to product taste and flavor. There isn't a physical scale of color but different methodology to express it on numerical scales, there is not a reference color for each nuance (color, pigment, texture, light changes).
Attributing a verbal description to colors is very difficult, it's subjective and if lights/texture change.
Issue
How to objectively measure visually perceived color? It is highly improbable that two persons would use the same words to describe a given color, influenced by HUMAN FACTOR and ENVIRONMENTAL FACTOR.
Food color results from natural occurring pigments (chlorophylls, anthocyanins, carotenoids, polyphenols, melanoidins, caramel...) and from colorings intentionally added to provide food desired appearance. The freeze-dried products will appear white because of the scattering of the light due to the product.
The aim of food color determination is the determination of added colorings, determination of natural pigments which are taken as indices of economic value, and the evaluation of food process and storage.
In order to see colors, you need a light source, an object, and an observer. To build an instrument that can quantify human color perception, each item in the visual observing situation must be represented as a table of numbers.
A light source usually appears white, but when a light is scattered by a prism, it can produce different compounds. The visible part of the spectrum is a small part and ranges from 400 to 700 nm.
A light source is a real physical source of light, while an illuminant is a plot or table of relative energy versus wavelength that represents the spectral characteristics of different types of light sources. Some examples of illuminants are:
- Incandescent (A)
- Average Daylight (C)
- Noon Daylight (D65)
- Cool white Fluorescent (F2)
- Ultralume (U30)
Colorants can modify the color by changing the amount of reflected or transmitted light at each wavelength, and this can be quantified.
This is a spectral curve of the object's color characteristics. Detector = sensitivity of human eyes. We are very sensitive in the yellow-orange zone, it is difficult for us to identify different shades of red or blue. This is due to the fact that we have a number of receptors on the bottom of eyes that are sensitive to 3 colors: Red, Green, Blue. In fact, we can say that each pixel has an RGB value between 0 and 255.
Standard observer 2°, who looks inside the hole sees the yellow light and I must adjust the light composed of the 3 colors (RGB) to reach the same intensity as yellow (because each color is a combination of R, B, and G). Their combination will give me that color. What I get is the tristimulus value (xyz). Each color can be described by x, y, and z (tristimulus value of the standard observer). Describe ability to describe colors: CIE = body that has performed the system. The CIE Tristimulus color values X, Y, Z, of any color are obtained by multiplying together the data values.
For the illuminant, the reflectance or transmittance of the object, and the standard observer functions. The product is then summed for the wavelengths in the visible spectrum to give the resulting X, Y, Z, tristimulus values. I multiply the data of the intensity, of the reflection of the object by the intensity of the light, and I get the visual stimulus that is divided into red, green, blue. I multiply this stimulus for the observer standard to get the red/green/blue component. The yellow of the bus is made up of a lot of red, little blue and little green.
METHODS TO MEASURE COLOR:
Visual methods of specifying colors are subjective, measuring color using an instrument gives objective results:
Spectrophotometer (Diode):
A spectrophotometer uses a light source to light the specimen being measured. The light reflected by the object then passes to a grating which breaks it into the spectrum. The spectrum falls onto a diode array which measures the amount of light at each wavelength. This spectral data
| Parameter | Description |
|---|---|
| X | The amount of light reflected off the object |
| Y | The amount of light absorbed by the object |
| Z | The amount of light transmitted through the object |
A tristimulus colorimeter or colorimeter uses a light source to light the specimen being measured. The light reflected off the object then passes through a red, green, and blue glass filter to simulate the standard observer functions for a particulate illuminant (typically C). A photodetector beyond each filter then detects the amount of light passing through the filters. These signals are then displayed as X, Y, Z. It's more common because unlike a spectrophotometer, it can be moved and is also simpler and more portable. The array diode is replaced with a photodetector, which is a light filter or RGB that gives me the data directly calculated as X, Y, Z.
Visual organization of color:
- Lightness: Defines the ratio between reflected and absorbed light, independently of light
Xyz values are mentally difficult to translate into a color, so the colors are organized in 3 parameters:
- Lightness: Defines the ratio between reflected and absorbed light, independently of light
I can image a cylinder A visual method of specifying color is subjective while an instrument measurement gives an objective result. In the middle of the cylinder there isn't color but a scale of grey which from white at the top to black at the bottom. Going around cylinder color change.
blue-yellow coder. When you look at the white screen your vision tries to balance, and you see the red, white and blue after-image.
Hunter L, a, b Color Space.
This is a 3-dimensional rectangular color space based on the opponent colors theory. There are:
- L (lightness) axis, where 0 is black and 100 is white
- a (red, green) axis, where positive values are red, negative values are green and 0 is neutral
- b (blue, yellow) axis, where positive values are yellow, negative values are blue and 0 is neutral
All colors can be visually perceived can be plotted in this L, a, b, rectangular color space. The following slideshows where the yellow schools bus falls in this structure.
So, for every color there are some coordinates ads for the yellow bus they are:
L=61.4
A=18.1
B=32.1
There are two popular L, a, b, color scales, the Hunter L, a, b and the CIE L*, a*, b*, that have a similar organization but different numerical values.
The CIE L*, a*, b*, for the yellow bus is:
L=67.8
A=19.5
B=58.1
Both scales
are mathematically derived from the x, y, z, values. Neither scales is visually uniform infact, the Hunter L, a, b, is over expanded in the blue region while the CIE L*, a*, b*, is over expanded in the yellow part. The current CIE recommendation is to use the CIE L*, a*, b*,
For example, in an oxidation process the color will lose intensity and move to center axis whit decreasing color and increase the light.
Polar CIE L*, C*, h
This is a polar representation of the CIE L*, a*, b* rectangular coordinate system. Numerically CIE L*, C*, h, describes color in the same way that verbally communicate color in terms of lightness, chroma and hue. This is mathematically derived from CIE L*, a*, b* and its visual uniformity is no better than CIE L*, a*, b*. Furthermore, it is not easy to understands as the L, a, b.
Example: If the Maillard reaction occurs, L goes down, if there is an oxidation reaction, instead, the color loose intensity = loose saturation = loosing content of pigments but the lightness
<p>increases.Freeze dried tomato powder:The initial color is orange/red, in storage turns into more yellow, lose red.This happens because the lycopene is oxidated and I see carotenoidswitch are more yellow.What is the acceptable color difference?The acceptability change in base of the application, for example in the automotive paint theacceptability is closer than the minimum perceptible limit while for a snack food this is closer than themaximum acceptable limit which defined the tolerance of acceptance.ΔL*, Δa* Δb*Color differences are always calculated as sample standard values so there is a delta between the twostates and could be calculated.If ΔL* is positive the sample is lighter than the standard, if it is negative the sample is darker than thestandard.If Δa* is positive the sample is more red (or less green) than the standard, if it is negative the sampleis more green (or less red) than the standard.If Δb* is positive the sample is more yellow</p>(or less blue) than the standard, if it is negative the sample is more blue (or less yellow) than the standard.
For example, two square of different yellow have the following L*, a*, b* with the consequence color difference:
ΔE* total color difference
ΔE* is based on L*, a*, b* color difference and was intended to be a single number metric for pass or fail decision. ΔE* changes during the process, for example during cooking ΔE* at the beginning is 0 (no difference between the original and the final color), then I can see ΔE* increasing, the color is changing. I don’t tell which of the parameter is changing, but there is a change in color. This work very well to follow a process but not so well when I compare two colors whit ΔE*.
Non-uniformity of ΔE* in color space
ΔE* isn’t always reliable by itself. In the following example bat
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