Month: June 2020

Student Project – Agricultural productivity pathways to avoid deforestation in Brazil: application of neural networks

SGI undergraduate student Matheus Mansour has been working on a project relating to agricultural productivity pathways to avoid deforestation in Brazil.

Many models are created with the objective of estimating some kind of economic output, either by a country’s industry or agricultural sector. Time series, general and partial equilibrium models and many other methodologies have been used in the past. However, with the advent of new deep learning methods, powerful tools could be of great use in planning and economic forecasting. In Brazil, a considerable share of GDP is produced by the livestock and agriculture sectors, which have considerable environmental impacts on land use-related issues such as deforestation and biodiversity loss. To avoid these impacts, it is necessary to plan ahead and identify the necessary improvements in productivity for the long ran, if deforestation is to be avoided.

Using data from the last 35 years and 11 of the most important agricultural crops and livestock in Brazil, neural networks will be trained and used as basis for the analysis of scenarios of productivity gains necessary to avoid deforestation in the country and evaluate how reforestation could affect the supply of future agricultural demand. This project is being developed in partnership with Prof. Celma Ribeiro of University of São Paulo, Brazil.

Student Project – Inserting lignin in the sugarcane mills product portfolio: A study using robust optimization approach

SGI PhD student Raphael Dutenkefer has been working on a project looking at insertion of lignin in the sugarcane mills product portfolio.

The use of residues from the sugarcane in industry has been of considerable interest in the last decade. There is a great interest in producing high added value products from residues that today are used solely for the generation of electricity. Lignin, one of the components of lignocellulosic residues derived from sugarcane, is a class of complex organic polymers that can serve as feedstock for the production of many chemicals, materials and even energy carriers. However, its processing technologies are still in an immature technological phase and need further development to become an economically viable option for producers and consumers.

In partnership with Prof. Celma Ribeiro of University of São Paulo, Brazil, this project intends to deeper understand how lignin could improve the economic efficiency of sugarcane mills and what are the best processes being developed today, from an economic perspective. Using a methodology to define the best portfolio for a certain range of products, this project intends to evaluate the investments, maintenance costs, selling price and efficiencies necessary to make lignin a viable feedstock for materials, chemicals and energy carriers.