A multi-agent cellular automaton for grapevine growth and crop simulation

Date
2011-08
Authors
Shanmuganathan, S
Narayanan, A
Robinson, N
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
IJMLC
Abstract

A multi-agent (MA) cellular automaton (CA) model framework for simulating grapevine growth and crop in Chardonnay cultivated in northern New Zealand is presented. Estimating or projecting grape crop (quantity of grapes in tons per hectare (ha) and berry quality in Brix (sugar content) is an extremely complex and challenging task as the crop depends on many factors that interact with each other at varying degrees and over different time intervals in a “chaotic” manner. These key factors and their influences are simulated using CA rules, MA behaviour and interactions. Two sets of CA lattices and rules are used to simulate individual grapevine growth and vineyard phonological dynamics. The results achieved show potential for simulating vine growth and yield in different grape varieties (Pinot Noir, Pinot Gris, Merlot and other wine styles) and scales, such as New Zealand’s major wine regions and that of world’s, in ways which that have not been explored previously.

Description
Keywords
Component , Climate effects , Yield , Vineyard
Source
International Journal of Machine Learning and Computing (IJMLC) vol. 1, no. 3, pp. 291-296, 2011.
DOI
Rights statement
NOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version)