ISHS Acta Horticulturae 313: III International Symposium on Computer Modelling in Fruit Research and Orchard Management
THE DYNAMIC APPLE TREE SYSTEM: RELATIONSHIPS TO AID MANAGEMENT STRATEGIES |
| Authors: | G.F. Thiele, J. Zhang |
| Abstract:
For management planning it is necessary to relate yield, fruit quality and size distribution, revenue and cost data, in order to calculate annual gross margins. Based on three years Royal Gala apple data obtained from monitoring a total of fifteen orchards in three main New Zealand fruitgrowing districts, a set of dynamic mathematical models developed by J. Zhang as part of his Ph.D thesis are presented to demonstrate the interrelationship of factors influencing apple production and profitability. One orchard is in the third additional year (6 years) of monitoring for the purpose of model validation. The models deal with biological factors such as flower number, setting, thinning, fruit growth and harvest characteristics rather than just harvest data alone. The incorporation of revenue and cost data has provided more realistic relationships than interpretations based solely on yield. The effectiveness of the model as a management tool is governed by the reliability and extent of the database. To date, climatic and biological data for production of Gala apples is incorporated in the database. The more this data is extended to other cultivars, fruit types and districts the more refined the models will become. It is possible for users to view average flowering, fruit set, thinning and harvest data as well as labour and financial inputs and outputs as a basis of comparison at individual or district level. At various stages of the annual production cycle, model users may specify their own property details (eg flower numbers) and predict yield, fruit size distribution and labour and financial estimates. The models allow annual climatic data to be balanced against biological parameters (eg fruit numbers) in order to minimise costs and maximise gross income and annual gross margins. For example, the required fruit number per tree after thinning can be correlated with the size grade distribution which will maximise returns, incorporating weather, cost and other key management parameters. | |
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