Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Intelligent Support Decision in Sugarcane Harvest

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  Computers in Agriculture and Natural Resources, 4th World Congress Conference, Proceedings of the 24-26 July 2006 (Orlando, Florida USA) Publication Date 24 July 2006  701P0606.(doi:10.13031/2013.21917)
Authors:   Flávio Rosendo da Silva Oliveira, Diogo Ferreira Pacheco, Amanda Leonel, Fernando Buarque de Lima Neto
Keywords:   Sugarcane, Harvest, Decision Support Systems, Artificial intelligence, Artificial neural networks. Genetic algorithms

This paper presents a computing approach to support harvest decisions in sugarcane utilizing artificial intelligence (AI). The proposed two-step Decision Support System (DSS) starts with an AI technique called Artificial Neural Network (ANN), which is utilized to forecast agronomical performance indicators. Next, an heuristic that uses Genetic Algorithms (GA) is applied to search, and then recommend, suitable areas to be harvested. This work includes some experiments with real data where the ideas put forward are tested. The results of these experiments proved our approach: (i) useful to decision makers and (ii) easily coupled to current Management Information Systems (MIS) existing in most sugarcane mills.

(Download PDF)    (Export to EndNotes)