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WSU-TFREC/Postharvest Information Network/Lighting Systems for Fruit Sorting



Lighting Systems for Fruit Sorting


Introduction

Fruits and vegetables are inspected prior to most processing or packing operations. While some sorting is accomplished with optical or electronic technology, much sorting is done by manual visual inspection. Each worker must look at a few hundred items each minute and accurately discard those that are unacceptable. Good lighting conditions are required to perform this task.

Sorting table lighting may not currently match the specific task for which it is intended. Specific guidelines for lighting system design in fruit and vegetable sorting and packinglines in the U.S. do not exist. Manufacturers of packingline equipment have left lighting decisions up to the individual operation.

Sorting table lighting must have both adequate intensity and color quality to enhance or reveal defects rather than obscure or mask them. Improper lighting design promotes worker fatigue and eye strain, resulting in poor sorting efficiency. Studies of several operations involving inspection of a range of commodities have shown that many lighting systems are not adequate for the required task. These studies suggested that improved sorting results could be expected if relatively inexpensive changes in illumination sources, illumination intensities, and background colors were adopted in sorting areas.


Principles of Lighting and Color

Two common uses of lighting are general area lighting and task lighting. General area lighting's purpose is to illuminate a room or building for general activity. This type of lighting is usually mounted in the ceiling or well above the floor area. Task lighting is much more specific and is concentrated in an area to enhance the ability to perform a task. Task lighting is the primary concern of this article which focuses on the task of manually sorting fruits and vegetables.

Three major components interact in the process of visualizing a "color":

  1. Light energy from a lamp or light fixture
  2. Color reflectance potential of a fruit, called spectral reflectance
  3. Sensitivity of the eye to color, called receptor sensitivity

For example, to "see" the color red there must exist a light source containing red color light, a surface which can reflect the red light and a receptor sensitive to reflected red light.


Light Energy

Light energy, or a source of light, is required to produce the actual visible color light which the eye can detect. The natural light source is the sun which produces all visible colors in addition to energy outside the visible spectrum (ultraviolet, infrared, etc.). Colors produced by artificial light are influenced by tube coatings, such as phosphor in fluorescent tubes, gases, or other components contained in filament bulbs.

Artificial light sources are rated by:

  • Color temperature; black body temperature generation
  • CRI: Color Rendering Index
  • CPI: Color Preference Index

These ratings are briefly explained in the footnotes of Table 1.

Table 1. Artificial lighting characteristics and visual effects on common produce colors, 1992.*

Light source
(fluorescent tubes)
Mfgr Rel
cost
Color
temp
CRI CPI Rel
light
Visual effect on specified color
MaRe GrBr BlPu Ye
SP-30 11.830007080 105EEBE DEE
SPX-30 15.9300082100 105EEBE DEE
Ultralume-30 23.7300085100 105EEBE DEE
Warm White 21.330005337 102EEDE DDE
Warm White Dlx 22.130007990 68EEDE DEE
Optima-32 34.9320082-- 81EEBE DEE
Natural 23.134008193 66EEED EEW
Cool White 21.041006758 100DDEW EDW
SPX-41 16.5410082100 103EEEW EEW
Cool White Dlx 23.242008994 70EEDD EED
Colortone-50 13.250009092 70EEEW EEW
Ultralume-50 24.1500085 100105EEE WEEW
Optima-50 35.2500091-- 81EEEW EEW
Vita-Lite Plus 35.7550091-- 100EEEW WED
Daylight 21.765007972 83DDEW EDW
Colortone-75 14.275009597 64EEEW EEW
*Manufacturer: 1=General Electric; 2=Phillips; 3=Duro Test.
Rel cost: Relative bulb cost ration to Cool White.
Color temp: Lamp appearance in degrees Kelvin.
CRI: Color Rendering Index=effect the light source has on appearance of colored objects; 100=perfect appearance
CPI: Color Preference Index=how well people recognize colors in that light; 100=perfect recognition.
Rel light: Relative initial lumen/watt output as a percentage of Cool White.
Ma=Maroon; Re=Red; Gr=Green; Br=Brown; Bl=Blue; Pu=Purple; Ye=Yellow
Visual effect of tube on specified color: B=brownish cast; D=darker; E=enhanced; W=whitish cast. Cool White effects are relative to midday diffuse outdoor light; other tubes are relative to Cool White.

Of the three major components in visualizing color, light energy is the one most easily controlled. The important factor relating to artificial light is the spectral irradiance curve for a given light source. A spectral irradiance curve is a measured representation of a given light source showing the amount of specific light energy or color contained in the source over the spectrum of colors. Spectral irradiance curves are generally available from lamp manufacturers. The spectral irradiance for a light source can be altered with various types of "filters" covering the lamp. These include undesirable coatings of dust and dirt.


Spectral Reflectance

Spectral reflectance of an object is basically the "color" of the object, the ability of a fruit to reflect certain colors of light in the presence of natural light. In fruits, the chlorophyll, anthocyanin, or other natural pigments dictate the item's color. The apparent color of an item can be altered by changing the light source or by incomplete color receptor capability. Some defective and nondefective measurements for the same commodity vary in their reflectance over the entire spectrum while others either vary only in certain regions of the spectrum or they vary little at all.

Many defects that need to be detected on fruits and vegetables are of brown or grayish color.

One might assume, therefore, that simply finding the light source with the most energy in the color regions making up the brown color would be ideal for all applications. The objective in selecting the best light source for a given task, however, is to light a commodity with a source that will accentuate the color difference between the sound tissue and the defects. For example, if we wish to find brown discoloration on red cherries, then we want to use an inspection light of a color that will accentuate brown against the normal red color of the cherry. The key is to find a color of inspection lighting that will make the defects show up the most, i.e., to make the commodity look its worst.


Receptor Sensitivity

The third component in perceiving a color is the receiving or sensing of the light. In this case, the human eye is the receptor. There is no adjustment to the human eye. The only variability is in the individual's sensitivity to the color and quantity of the light. Sensitivity decreases with age and this should be a consideration during lighting design.

Perceived Color

Figure 1 demonstrates the combining of all components (spectral irradiance, reflectance curves, and receptor sensitivity) which affect color perception. The perceived color is termed the total spectral energy distribution and is the product of the spectral irradiance x spectral reflectance x human eye sensitivity or response. The goal of the lighting design is to have "peaks" in the distribution at the wavelengths or colors of the commodity and at the defect color, thus resulting in a good perceivable contrast.

Figure 1


Performance of Commercially Available Light Sources

Theoretically the product of the spectral irradiance, spectral reflectance, and eye sensitivity should provide the information to design a proper lighting scheme. USDA-ARS researchers at Michigan State University evaluated several commercially available light sources. They measured individual spectral irradiance, using color chips to subjectively analyze and compare performance in color perception tests. Table 1 summarizes their findings and provides technical and relative cost information. Results indicated the "image" curves resulting from the combination of spectral reflectance x spectral power x eye sensitivity generally agree with the subjective/visual results for the test with the color chips and real produce items.

The ability to recognize differences between good and defective areas on produce was lowest under Cool White (CW) light, which was very similar to that for CW Deluxe, Warm White, Warm White Deluxe, Daylight, Natural, Optima 32, Optima 50, C-50, and C-75. Consequently, these lights should not be used for task lighting in fruit and vegetable inspection areas. U.S. federal energy standards may eliminate CW and similar type fluorescent lamps by 1994 or 1995 because they do not meet proposed efficiency levels. Fluorescent tubes of 8-foot lengths of all types are also scheduled to be removed from production.

Visual color comparisons suggested that although the SP-30 light had a low color rendering index (CRI), it performed better than higher CRI fluorescent lights for the visual sorting of most fruits and vegetables. The relative light output of the SP-30 lamp is among the highest tested. Its relative cost is only 1.8 times that of CW. These factors indicate that it should be an appropriate choice for most sorting operations when both sorting performance and lighting cost are considered (Figure 1a). Note how the spectral irradiance curve of SP-30 closely matches the perceived cherry color.

Except for metal halide, the high intensity discharge (HID) lights were undesirable for produce sorting as they severely darkened most colors. Tests will be necessary using metal halide light to determine if sorting performance is acceptable. Tungsten halogen quartz (quartz) light also produced good color recognition and enhanced ability to see brown-colored defects on dark-colored produce. Both metal halide and quartz lighting will be more costly than SP-30 fluorescent lighting. More specific discussion of the tests will not be covered here but can be found in the cited reference.


Requirements of Light Intensity

The average illumination intensity needed on produce items for effective visual sorting seems to be in the range of 250 to 500 foot-candles, based on the reactions of workers 20 to 70 years old. The lower intensity seems adequate for light-colored (high reflectance) produce and the higher intensity for dark-colored (low reflectance) produce. The actual light intensity may need to be adjusted, depending on the design considerations discussed below. In situations where kinds or varieties of produce covering the entire color range must be inspected on the same packing line, the low and high intensity levels should be selectable by the sorting workers. This can easily be accomplished by using 4-tube fluorescent fixtures wired so that either the 2 outside tubes or all 4 tubes can be turned on. The amount of light falling upon a surface can be measured with commercially available light (foot-candle) meters.

Design Considerations

Several physical design characteristics will impact sorting efficiency and overall worker attitude and performance:
  • Background color of sorting surface (belt). Reflected light energy from the sorting surface should not be greater than that from the produce. (Note: some food handling systems are required to have white belts.) Use belts which are black or dark gray, but not glossy finish.
  • Surrounding colors. Surfaces near sorting areas and the clothing of inspection personnel should not be bright or highly reflective and should not cause glare.
  • Placement of fixtures. Placement should be such that the light source will not be directly in the sorters' eyes, i.e., unshielded, or too low so as to obstruct the sorters' view of the sorting surface. The fixture must also be placed at such a height as to provide the proper level of light at the sorting surface. This will depend on the amount and type of light used and the considerations mentioned above. For an SP-30 light, this height will be about 32 inches above the sorting surface, as shown in Figure 2.

Figure 2

  • Type of lighting. Light type should be appropriate for the sorting task and the colors involved. Area lighting should also be considered as it can have negative impacts on the color evaluation and on eyestrain.
  • Screen, block, or direct all task light sources ao that they cannot glare in the workers' eyes.
  • Use SP-30 (or equivalent) illumination at the sorting area of most fresh produce packinglines.
  • Adjust lamp power levels (number of tubes) and fixture height so that lightly colored produce receives approximately 250 foot-candles of illumination and darkly colored produce, approximately 500 foot-candles.
  • Minimize the influence of natural, stray, and general area lighting in the sorting area.
  • Select similar dark colors for equipment parts and worker clothing in the sorting area so that bright areas cannot interfere with the workers' established vision conditions.
  • Use a dark background color (black, gray, dark brown) on the conveyor surface carrying the produce so that reflected light energy from this surface is not graeter than that from the produce; avoid a glossy finish on the belt surface.

References for More Information

Request a copy of the paper summarized above from the editors.

Affeldt, H. A. and P. W. Winner. 1991. Lighting practice and principles for manual citrus inspection. Paper No. 913549, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Brown, G. K. 1991. Lighting for manual sorting of apples and sweet cherries. Paper No. 913553, ASAE, 2950 Niles Rd., St Joseph, MI 49085.

Brown, G. K., D. E. Marshall and E. J. Timm. 1993. Lighting for fruit and vegetable sorting. Paper No. 936069, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Davies, J. and R. M. Perkins. 1991. Effect of illumination in grading dates. Paper No. 913547, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Delwiche, M. J., J. F. Thompson and R. S. Johnson. 1991. Sorting table illumination on stone fruit packing lines in California Paper No. 913551, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Hyde, G. A. 1991. Lighting environment for manual sorting of potatoes and onions. Paper No. 913548, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Kantowitz, B. and R. Sorkin. 1983. Human factors, understanding people-system relationships. John Wiley & Sons, Inc., pp. 102.

Kupferman, E. M. 1991. Cherry sorting table lighting. Paper No. 913552, ASAE, 2950 Niles Rd., St. Joseph, MI 49085.

Daniel Guyer, Roger Brook, and Edward Timm

Department of Agricultural Engineering, Michigan State University

Tree Fruit Postharvest Journal 5(1):22-28
April 1994

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