Modeling of physical properties of apple slices (Golab variety) using artificial neural networks

 Apple is one of the most popular fruits and of high economic value.  Sorting and grading of apple is needed for the fruit to be presented to local and foreign markets.  A study of apple physical properties therefore is imperative.  In this work, some physical properties of apples (Golab variety) such as main diameter, mass, volume and fruit density were determined and relation between mass and other parameters were modeled by using artificial neural networks.  In this study, we used Feed-Forward Back Propagation (FFBP) network with training algorithms, Levenberg-Marquard and Momentum.  The results show that Levenberg-Marquard algorithm give better result than Momentum algorithm do, and Feed-Forward Back Propagation (FFBP) network with topology 3-6-4-1, 3-6-1, 3-4-2-2-1 and 3-6-6-1; and Levenberg-Marquard algorithm could predict relation between mass and other parameters with error percentages 0.999999, 0.999999, 0.999999 and 0.999999; and mean square error 0.000078, 0.000118, 0.000158 and 0.000194. Keywords: apple (Golab variety), artificial neural network, Feed-Forward Back Propagation, Levenberg-Marquard algorithm, Momentum algorithm, physical propertie

Some Physical Properties of Apple cv. ‘Golab’

Apple is among the popular fruits and of a high economic value. Sorting and grading of apple is needed for the fruit to be presented to local and foreign markets. A study of apple physical properties therefore is imperative. Some physical properties of apples were determined. These properties include: dimensions, mass, volume, surface area, porosity, packaging coefficient and coefficient of static friction. The maximum, average and minimum diameters of apple were 65.04, 53.50 and 35.14 mm respectively. Average volume and mass were 104.5 cm3 and 74.87 g respectively. As for an apple pile, the density and apparent density were respectively calculated as 0.7427 and 0.2401 g/cm3. Maximum, average and minimum porosity of apples were 57.24, 54.13 and 50.17 percent with their sphericity being 1.0028, 0.93 and 0.84 respectively. Average static friction angle of apple on galvanized, glass and plywood surfaces were 20, 26.3 and 26.8 degrees respectively. Average packaging coefficient for the apples studied was 0.45

Mathematical Modeling of Kinetics of Thin-layer Drying of Apple (var. Golab)

Mathematical models of thin-layer drying of apple were studied and verified with experimental data. Fourteen different mathematical drying models were compared according to three statistical parameters, i.e. root mean square error (RMSE), chi-square (X2) and modeling efficiency (EF). The thin-layer drying kinetics of apple slices was experimentally investigated in a laboratory convective dryer and the mathematical modeling, using thin-layer drying models present in the literature, was performed. The main objective of the study was the verification of models already developed. Experiments were performed at air temperature between 40 and 80 °C, velocity of 0.5, 1 and 2 m/s, and thickness of thin layer of 2, 4, 6 mm. Besides the effects of drying air temperature and velocity, effects of slice thickness on the drying characteristics and drying time were also determined. Drying curves obtained from the experimental data were fitted to the-thin layer drying models. The results have shown that, model introduced by Midilli et al. (2002) obtained the highest value of EF = 0.99972, the lowest value of RMSE = 0.00292 and X2 = 10-5. Therefore this model was the best for describing the drying curves of apples. The effects of drying air temperature, velocity and thickness on the drying constant and coefficient were shown to compare the circumstances of drying

On-site measurement of soil moisture content using an acoustic system

Precision agriculture is a farming management concept based on observing and responding to intra-field variations.  One of the most important soil properties in farming is soil moisture content and it is necessary to develop new technique for measuring this property in a precision farming system.  This study investigates the measurement of moisture content in soil using an on-site, easy to use and real-time acoustic wave system.  The system consists of the propagation of acoustic waves such as sweep frequency sound wave (10-300 Hz) and multiple tone sound waves (120 Hz) through the soil.  Some properties of these acoustic waves enable estimation of soil water content such as peak amplitude (A), total power (TP), total harmonic distortion (THD) and signal to noise ratio (SNR).  The results showed that the best model for estimating the soil moisture content was the model that expressed relationship between A and soil moisture content with R2 = 0.999 (using sweep frequency) and relationship between TP and soil moisture content with R2 = 0.999 (using multiple tone).  It is argued that the change in the sound characteristics related to the soil moisture content can be used for a continuous monitoring and control of irrigation of crops.   Keywords: acoustic waves, soil moisture content, sound propertie