INFORMATION-MANAGEMENT-SYSTEM FOR GROWTH CONTROL OF FICUS BENJAMINA

An information-management-system can be a helpful tool to measure, grade and control development of plants in order to achieve a defined marketable product.
Research has been carried out to develop such a system with Ficus benjamina ‘Exotica’ as pilot crop.
Former research has led to the conclusion that subjective, visual quality of Ficus benjamina can be linked to objective measurement by image processing.
This measuring technique is used in this research for monitoring plant development during growth, in order to 1) create homogenous groups of plants by grading and/or 2) adjust growth of Ficus benjamina by changing temperature or plant density.
Grading of plants is carried out using a neural network.
Control of crop development and plant quality is based on an empiric growth control model using greenhouse temperature and light as main factors.

A prototype of the information-management-system was tested last year at the Research Station using half-grown plants as starting material.
Plants were graded into three groups using a neural network and were grown to 1.20 m with three different cultivation programs.
Plant development was monitored using image processing and/or hand measurements.
It was concluded that image features can be used as an adequate input for the neural network and the growth control model.
The different cultivation programs led to the expected final quality and specified delivery date.
The information-management-system is currently being tested at three commercial companies in The Netherlands.

XXV International Horticultural Congress, Part 9: Computers and Automation, Electronic Information in Horticulture

M.W.C. Dijkshoorn-Dekker, J. Meuleman

Decision-support system, Ficus benjamina, image processing, neural network, growth control, growth, quality features, grading

https://doi.org/10.17660/ActaHortic.2000.519.21