Modeling of heat and entropy sorption of maize (cv. Sc704): neural network method

Abstract

Chayjan R.A., Esna-Ashari M., 2010. Modeling of heat and entropy sorption of maize (cv. Sc704): neural network method. Res. Agr. Eng., 56: 69-76.Equilibrium moisture content of maize affects its values of dehydration heat and entropy. Precise prediction of heat and entropy with regard to its equilibrium moisture content is a simple and fast method for proper estimation of energy required for dehydration of maize and simulation of dried maize storage. Artificial neural network and thermodynamic equations for computation of maize heat and entropy of sorption were used, as a new method. The artificial neural network method for prediction of the equilibrium moisture content of maize was utilized. The heat of sorption of maize is predicted by a power model. After well training of equilibrium moisture content data sets using the artificial neural network models, predictive power of the model was found to be high (R 2 = 0.99). A power regression model was also developed for entropy of sorption. At moisture content above 11% (d.b.) the heat and entropy of sorption of maize decreased smoothly and they were highest at moisture content about 8% (d.b.).Keywords: maize; back propagation; entropy; isosteric heat; sorption isothermRes. Agr. Eng. Vol. 56, 2010, No. 2: 69-76 Moisture content and temperature of maize seed affect its storage life. Increasing these factors causes an increase in maize seed respiration and enzymes production. This phenomenon tends to decrease food storage of seed and germination (Copeland, McDonald 1995).Equilibrium moisture content (EMC) of food and agricultural products is a durability criterion and any change in the quality during drying, storage and packaging is crucial and important (Veltchev, Menkov 2000). Fundamental relationship between air temperature, air relative humidity and EMC of food and agricultural products is known as sorption isotherms. Adsorption and desorption characteristics of food and agricultural products are used for designing, modeling and optimizing some postharvest processes such as drying, aeration and storage (Labuza 1975;Bala 1997).Drying time and energy consumption of drying process with regard to final moisture content are important indices for selection of a dryer or type of drying process. Safe storage and packaging as well as keeping the quality of harvested maize, considering its high moisture content at harvesting time, is very important. Maize EMC, that is defined as its moisture content in equilibrium with particular environmental conditions (air temperature and air relative humidity) is a vital parameter in studying the drying and storage processes. Studies showed that if the two environmental factors were not con- 70Vol. 56, 2010, No. 2: 69-76 Res. Agr. Eng.trolled, the mold activities increased. (Brooker et al. 1992). Chen and Morey (1989) studied the sorption isotherm curves of yellow dent maize at the air temperature boundary of 5°C to 45°C. Their results showed that sorption isotherm curves are different for maize cultivars; also air relati...

Application of superabsorbent polymers (SAP) as desiccants to dry maize and reduce aflatoxin contamination

“…In order to extract more information on the optimal storage conditions, such as the desired relative humidity (RH) corresponding to the optimal MC to avoid aflatoxin formation, it is a good practice to look at the moisture sorption isotherm of the system. Figure 4 shows the sorption isotherms of the Kenyan maize modeled by SIPS model alongside that obtained (Chayjan and Esna-Ashari 2010). These have been plotted on the same axes with the sorption isotherms for SAP measured by diffusion vapor sorption analysis (DVS) and modeled by GAB and SIPS models.…”

“…where MC (%) is the moisture content, a w is the water activity, M 0 (%) is the monolayer sorbent content on the internal surface, K G is a dimensionless GAB parameter related to heat of sorption of the monolayer region, k is a dimensionless GAB parameter related to heat of sorption of the multilayer region, K S is the SIPS sorption capacity, n is the sorption intensity and C is the energy of adsorption. The GAB equation is well established as a model for food and it was already employed to follow water sorption in maize (Chayjan and Esna-Ashari 2010;Andrade et al 2011). Unfortunately the GAB model does not converge for the SAP data, for this reason the SIPS model has been introduced in order to fit better the SAP sorption isotherm.…”

Modélisation des isothermes de sorption, caractérisation des propriétés thermodynamiques et détermination des humidités d’équilibre d’usage des bois tropicaux

“…Le séchage du bois est un procédé qui permet de réduire la teneur en eau du bois afin d'obtenir une valeur nécessaire à la stabilité du bois, laquelle valeur est fonction des caractéristiques de l'air ambiant. En effet, la teneur en eau des matériaux hygroscopiques en équilibre avec son environnement (aussi appelé teneur en eau d'équilibre) est un paramètre important dans l'étude du procédé de séchage [1]. Ce paramètre permet de déterminer les conditions optimales de stockage [2], de dimensionner et de modéliser plusieurs appareils de traitement et de conditionnement [3,4 ].…”

Artificial Neural Network Modeling of Greenhouse Tomato Yield and Aerial Dry Matter

“…ANNs allow us to develop models based on the intrinsic relations among the variables, without prior knowledge of their functional relationships [9]. Soft computing for ANN techniques has been widely used to develop models to predict different crop indicators, such as growth, yield, and other biophysical processes, and also because of the commercial importance of tomato [10][11][12][13][14][15][16][17][18][19][20][21][22][23] and other vegetables, such as lettuce [24][25][26][27][28][29][30], pepper [31][32][33][34], cucumber [35][36][37][38], wheat [39][40][41][42][43][44][45], rice [46][47][48], oat [49], maize [50,51], corn [52][53][54], corn and soybean [55], soybean…”