Prediction of Physical Parameters of Pumpkin Seeds Using Neural Network
Demir, Bünyamin
The design of the machines and equipment used in harvest and post-harvest processing should be compatible with the physical, mechanical and rheological characteristics of the fruits and vegetables. In machine design for agricultural products, several characteristics of relevant products and seeds should be known ahead. Designers can either measure all these design parameters one by one, or they may use intelligent systems to estimate such parameters. Neural networks (NNs) are new computational tools that provide a quick and accurate means of physical properties prediction of agricultural materials, and have been shown to perform well in comparison with traditional methods. In this research, some physical properties of pumpkin (Cucurbita pepo L.) seeds, including linear dimensions, volume, ...
Estimation of the Weights of Almond Nuts Based on Physical Properties through Data Mining
Demir, Bünyamin
Quality attributes are the major parameters designating market values of the agricultural goods and commodities. Several practices are applied to improve quality parameters of the fruits and vegetables. Such quality attributes should also be estimated through various approaches before to design of equipment and tools used in handling and processing of these goods and to design storage facilities. Data mining is a novel approach used to estimate various attributes or quality parameters of the fruits from previously measured attributes. Different algorithms embedded into data mining operations may yield quite accurate and reliable equations for estimation of quality attributes. Almond is a significant cash crop for growers. Since almond is quite tolerant to droughts and salinity, it is prefe...
Prediction of Walnut Mass Based on Physical Attributes by Artificial Neural Network (ANN)
Demir, Bünyamin
Several researchers have investigated the relationships among different physical attributes of the fruits. For proper design and operation of grading systems, important relationships among the mass and other properties of fruits such as length, width, thickness, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, projected area, shape index, aspect ratio and elongations must be known. Recent researches have focused on artificial neural network (ANN) approaches to predict hard-to-find attributes of the fruits from easily-determined and readily available values. In this study, Modular Neural Network (MNN) and Radial Basis Neural Network (RBNN) structures of Artificial Neural Network (ANN) were employed to predict walnut mass from the physical attributes of th...
Estimation of the Colour Properties of Apples Varieties Using Neural Network
Demir, Bünyamin
The consumer acceptance and the quality standard of agricultural products such as apple are determined mostly by their colour. Colour is measured with a colorimeter and quantified using the C.I.E. L*, a*, b* colour space system. It is used commonly by researchers for the classification and identification of apple fruit. To the best of our knowledge, the present study is the first study investigating the prediction of some colour properties of six apple varieties through artificial neural networks (ANN). The apple varieties are ‘Amasya’, ‘Starking’, ‘Granny Smith’, ‘Pink Lady’, ‘Golden Delicious’, ‘Arapkızı’ and the colour properties are L* (lightness), a* (redness), b* (yellowness), C* (chroma), h* (hue angle), CI (chroma index). General Regression Neural Networks (GRNN) and Adaptive Neuro...
Possible Use of Data Mining for Analysis and Prediction of Apple Physical Properties
Demir, Bünyamin
Data mining is used as a popular technique in several scientific researches. In agriculture, application of data mining is a relatively new approach. One of the most popular data mining approaches is to find prediction rules from experimental data sets. The present study was conducted in two stages to find out a rule for estimation of width of stalk cavity, depth of stalk cavity, width of eye basin and depth of eye basin of different apple varieties (‘Amasya’, ‘Starking’, ‘Granny Smith’, ‘Pink Lady’, ‘Golden Delicious’ and ‘Arapkızı’) based on physical properties and to propose an equation for calculating these parameters. In the first stage, data processing was performed and in the second stage, Find Laws was used for prediction of apple properties. Current results revealed that data mini...
Design of Neural Network Predictor for the Physical Properties of Almond Nuts
Demir, Bünyamin
In this study, an adaptive neuro fuzzy interface system (ANFIS) based predictor was designed to predict the physical properties of four almond types. Measurements of the dimensions, length, width and thickness were carried out for one hundred randomly selected samples of each type. With using these three major perpendicular dimensions, some physical parameters such as projected area, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, shape index and aspect ratio were estimated. In in a various Artificial Neural Network (ANN) structures, ANFIS structure which has given the best results was selected. The parameters analytically estimated and those predicted were given in the form of figures. The root mean-squared error (RMSE) was found to be 0.0001 which is ...