Prediction of moisture content in the cocoa drying process by simple linear regression. - Duque-Aldaz, Francisco Javier; Haymacaña Moreno, Edwin Ronny; Zapata Aspiazu, Leonor Alejandrina; Carrasco Choque, Freddy (Ingeniería Química y Desarrollo, 2024)
The research addressed the development of a predictive model for moisture control in the cocoa production process. Cocoa is an important crop for Ecuador, being the fourth largest exporter in the world in the last ten years. Moisture control during drying is critical to guarantee the quality and safety of the final product. The general objective was to establish a forecasting model for moisture control in the cocoa drying process using simple linear regression. First, the factors that affect the drying process were identified. Then, the variability of each factor was analyzed using historical data. Next, a mathematical model was developed using simple linear regression. Finally, the model was validated with real production data. The results showed that the model had a high predictive capacity of 90.16%, meaning that the variation in moisture could be explained by the independent variable. Validation with real data confirmed the goodness of fit. Initial moisture was the most influential factor, explaining this variation. It was concluded that the simple linear regression model was an effective tool for forecasting final moisture based on initial moisture. The model will allow companies to improve control of this critical parameter through informed measurements. The research was able to successfully validate the methodology proposed for this production problem.
Keywords: Forecasting; Cocoa moisture; Production process; Simple linear regression; Quality control