Artificial Neural Networks To Predict the Behavior of Sugars Obtained by Acid Hydrolysis Process from Spent Coffee Grounds

Author(s)

dos Santos, Matheus Costa Monteiro ; Fogarin, Henrique Maziero ; Murillo-Franco, Sarha Lucia ; de Souza, Jonas Paulino ; Filletti, Erica Regina ; Dussan, Kelly Johana

• Document type: Journal article
• Source: WASTE AND BIOMASS VALORIZATION; v. N/A, p. 14-pg., 2025-05-26.

Abstract

The utilization of lignocellulosic biomass, such as spent coffee grounds (SCG), for bioprocesses such as fermentation presents challenges due to the complex structure of its components. Effective pretreatment methods are needed to overcome these difficulties. This study investigates the use of artificial neural networks (ANN's) to predict the behavior of the hydrolysis process (pretreatment), with a focus on efficient sugar extraction from SCG. By developing a feedforward neural network with input parameters such as temperature (130-190 degrees C), sulfuric acid concentration (0.5-2.0% v/v), solid/liquid ratio (1:4 - 1:40), and reaction time (20-120 min), the research aims to estimate the hydrolysis process using the Levenberg-Marquardt backpropagation algorithm in MATLAB R2024b software. With a neural model structure of four neurons in a single hidden layer, the model successfully predicts the amount of hemicellulosic sugars obtained from the hemicellulose fraction based on the input variables. The results demonstrate the effectiveness of the model in identifying the optimal conditions for converting polysaccharides in coffee waste into simple sugars, with an R-2 of 0.99 for validation, training, and test. The model showed an average percentage error of 9.20% (calculated by comparing experimental data with the values obtained with the ANN's). This innovative approach uses the power of artificial intelligence, specifically machine learning, to accurately measure the hydrolysis behavior of spent coffee grounds (SCG). (AU)

• FAPESP's process: 23/15075-8 - Evaluating the prebiotic effect of mannan-oligosaccharides derived from spent coffee grounds.
• Grantee: Henrique Maziero Fogarin
• Support Opportunities: Scholarships abroad - Research Internship - Master's degree
• FAPESP's process: 22/11905-3 - Optimization of spent ground coffee pretreatment to obtain a hydrolysate rich in fermentable sugars
• Grantee: Matheus Costa Monteiro dos Santos
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• FAPESP's process: 23/01752-8 - Optimization of the extraction of prebiotic oligosaccharides from acid hydrolysis of spent coffee ground.
• Grantee: Henrique Maziero Fogarin
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 22/03000-0 - Obtaining high value-added bioproducts from a by-product of the coffee production chain
• Grantee: Kelly Johana Dussán Medina
• Support Opportunities: Research Grants - Initial Project
• FAPESP's process: 24/05646-0 - Comparative Life Cycle Assessment for Different Spent Coffee Grounds Utilization Strategies.
• Grantee: Matheus Costa Monteiro dos Santos
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• FAPESP's process: 24/01232-7 - Sustainable Strategies for the Valorization of Coffee Grounds: An Integrated Analysis of Environmental and Economic Aspects
• Grantee: Sarha Lucia Murillo Franco
• Support Opportunities: Scholarships in Brazil - Doctorate