Journal of Agricultural Science and Technology
Journal of Agricultural Science and Technology
JAST
Agriculture
http://jast.modares.ac.ir
1
admin
1680-7073
2345-3737
10.22034/jast
en
jalali
1394
2
1
gregorian
2015
5
1
17
3
online
1
fulltext
en
Determination of Cherry Color Parameters during Ripening by Artificial Neural Network Assisted Image Processing Technique
Among the different classes of physical properties of foods, color is considered the most important visual attribute in quality perception. Consumers tend to associate color with quality due to its good correlation with physical, chemical and sensorial evaluations of food quality. This study used an inexpensive method to predict sweet cherries color parameters by combining image processing and artificial neural network (ANN) techniques. The color measuring technique consisted of a CCD camera for image acquisition, MATLAB software for image analysis, and ANN for modeling. To demonstrate the usefulness of this technique, changes of cherry color during ripening were studied. After designing, training, and generalizing several ANNs using Levenberg-Marquardt algorithm, a network with 7-14-11-3 architecture showed the best correlation (R<sup>2</sup>= 0.9999) for <em>L*, a*</em> and <em>b*</em> values from Chroma meter and the machine vision system. <em>L*</em> and <em>b*</em> parameters decreased during ripening of cherries and <em>a*</em> parameter increased at first and then decreased. Evaluation of <em>L*</em>, <em>a*</em> and <em>b*</em> values showed the possibility of reliable use of this system for determination of absolute color values of foodstuffs with a much lower cost in comparison with Chroma meter.
Cherry fruit,Color parameters L*a*b*,Artificial Neural Network,Modeling,Image processing
589
600
http://jast.modares.ac.ir/browse.php?a_code=A-23-1000-5769&slc_lang=en&sid=23
S.
Taghadomi-Saberi
S.
Taghadomi-Saberi
100319475328460056759
100319475328460056759
Yes
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
M.
Omid
M.
Omid
100319475328460056758
100319475328460056758
No
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
Z.
Emam-Djomeh
Z.
Emam-Djomeh
100319475328460056757
100319475328460056757
No
Department of Food Sciences and Technology, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
Department of Food Sciences and Technology, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Islamic Republic of Iran.
Kh.
Faraji-Mahyari
Kh.
Faraji-Mahyari
100319475328460056756
100319475328460056756
No
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran
Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran