Prediction and Determination of Weight and Lycopene Contents of Stored Tomatoes <i>(Lycopersicon esculentum)</i>

Abstract

The need to develop empirical model equations that describe the changes in the nutritional compositions of stored tomatoes under different environmental conditionsA study was carried out to predict and determine the weight and lycopene contents of stored tomatoes. Three sets of four different types of passive evaporative cooling structures made of clay and aluminium were designed and constructed as part of the study. One set consists of four separate cooling chambers. Two cooling chambers were made with aluminium container (cylindrical and square shapes) and the other two were made of clay container (cylindrical and square). These four containers were separately inserted inside a bigger clay pot inter-spaced with clay soil of 5 cm (to form tin-in-pot, pot-in-pot, tin-in-wall and wall-in wall) with the outside structure wrapped with jute sack. The other two sets followed the same pattern with interspacing of 7 cm and 10 cm, respectively. The set with 7 cm interspace served as the control in which the interspace soil and the jute sacks were constantly wetted at intervals of between 2 to 4 hours depending on the rate of evaporation with water at room temperature. The 5 cm and 10 cm interspaced soil were constantly wetted with salt solution (sodium chloride) at the same interval to keep the soil in moist condition. Freshly harvested matured tomatoes (globe variety) were used for the experiments and the temperature and relative humidity inside the cooling chambers were monitored daily . The weight, lycopene contents, bacterial and fungal counts of these produce were determined at intervals of three days for a period of sixteen days. Mathematical models (using essential regression software package) were developed to predict the weight and lycopene contents of the stored produce at various conditions considered in the study. By substituting different values of predictor variables into the model equations, the expected values of weight and lycopene contents of stored tomatoes were predicted. Further analysis was done using a paired sample t-test using SPSS 16.0 computer software package to show the level of significance between the mean of observed and the predicted values for all the models developed. The mathematical models developed are reasonably accurate to predict the storability of fruits and vegetables in passive evaporative cooling structures.