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Colorimeter for Fruits and Vegetables

Fruits and vegetables color characterizes well their maturity and presence of defects. For a lot of products like tomatoes, apricots, peaches and others are important both the external and the fruit flesh color. For other products the internal (of the fruit flesh) color is even more important, than the external – for example at internal defects in the potatoes.

Chander Mohan

Fruits and vegetable colour characterizes well their maturity and presence of defects. For a lot of products like tomatoes, apricots, peaches and others are important both the external and the fruit flesh colour. For other products, the internal (of the fruit flesh) colour is even more important, than the external – for example at internal defects in the potatoes. Very often the quality index is not straightly (directly) connected with the colour but it is based on spectral parts from the near-infrared (NIR) region – for example dry matter content of green peas.

Fruits and vegetables are checked before processing operations or before packing. Nowadays sorting operations are performed with optical or electronic technology, unlike in the past when it was performed manually through visual inspection.

The new colourimeter is dedicated to fruits and vegetables is now ready. It gives intensity values along the visible spectrum. We have added a Plato-convex lens that allows measuring a large surface on the sample. It works linked to Powerful software and is provided with a calibration mirror.

All researchers, packers and growers should have such a colourimeter dedicated to fruits & vegetable business!

In order to fulfil this task, good lighting conditions were needed. Inadequate lighting led to worker fatigue and eyestrain, therefore the sorting efficiency was very poor. Three major components interact in the visualization process of colour: light energy from a lamp or a luminaire, the reflection potential of a fruit’s colour, called spectral reflectance and eye sensitivity to colour, called receiver’s sensitivity.

Out of these three major components, the light source is the easiest to control. For example, in order to “see” the red color, we must have a light source that contains the red colour, a surface that reflects the red colour and a receiver sensitive to the reflected red colour. The natural light source is the sun, which can play all visible colours. The spectral reflection of fruit is, in fact, the capacity of the fruit to reflect certain colours in the presence of natural light. For fruits, chlorophyll or other natural pigments give the fruit’s colour.

In the circumstance of manual sorting, the human eye is the receiver, the disadvantage being the fact that the human eye can’t be adjusted. In present days most producers from all over the world create sorting machines for fruits, these being classified depending on colour, size, weight. Among these producers Compac Sorting Equipment are listed. Established in 1984, Compac Sorting Equipment is a world leader in the development, supply and manufacture of intelligent solutions and equipment for fruits sorting. Compac sorting technology is the solution to all sorting requirements of apples, being chosen by numerous factories from all over the world, as it is easy to use and the software by colour classification is used for 6 or more colour classes. Compac colour system is designed to perform at speeds of up to12 fruits per second. This system can sort apples by weight, colour, internal quality and flawless. One of the most accurate and easy to use Invision Compac sorting system by color is 5000, which is preferred by the U.S. (40 percent ). Compac Invision 5000 captures multiple images of fruit at standard production speeds up to 15 fruits per second. This colour sorting system is unique because the software is easy to use having advanced features; multiple images (up to 30 images) are captured for each fruit for better accuracy. This model performs the evaluation of fruits depending on many properties, such as: colour (up to 16 different colours), hue, form, diameter, volume, etc. All these systems are based on powerful computer systems which has to do a large number of computations on the captured images with CCD cameras. To reduce the number of computations artificial intelligence algorithms are tested. These systems are very expensive and use a lot of electrical power. In the study that we propose in this paper we bring a possible future alternative to these systems.

Its price: 760 € including transport worldwide.

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