Articles
THE VALUE OF CROP AND GREENHOUSE MODELS IN GREENHOUSE ENVIRONMENTAL CONTROL
Article number
456_35
Pages
295 – 304
Language
Abstract
Models of greenhouse environments and crop responses have been successful in explaining major features of crop performance and defining better protected crop environments.
There has recently been an increasing argument that models can be of direct use for environmental control.
The potential benefit has been identified in theoretical analyses and demonstrated in controlled experiments, but there has been less progress in the practical realisation of optimal control.
This in part reflects the fact that research is still revealing shortcomings in some of our quantitative understanding.
However realising benefits is not going to be dependent on improved models alone – or perhaps at all.
Where simple models can be used, e.g. for heating control, some practical capability has been demonstrated.
There is now an expectation that simplified approaches may be useful for more complex problems like the optimisation of enhanced CO2 levels.
In this and similar problems, gaining and sustaining growers’ confidence in the models and procedures being used will be a critical step.
Ultimately it may call for a careful mix of quantitative modelling and artificial intelligence tools to ensure that the appropriate balance between grower knowledge and model prediction is achieved.
There has recently been an increasing argument that models can be of direct use for environmental control.
The potential benefit has been identified in theoretical analyses and demonstrated in controlled experiments, but there has been less progress in the practical realisation of optimal control.
This in part reflects the fact that research is still revealing shortcomings in some of our quantitative understanding.
However realising benefits is not going to be dependent on improved models alone – or perhaps at all.
Where simple models can be used, e.g. for heating control, some practical capability has been demonstrated.
There is now an expectation that simplified approaches may be useful for more complex problems like the optimisation of enhanced CO2 levels.
In this and similar problems, gaining and sustaining growers’ confidence in the models and procedures being used will be a critical step.
Ultimately it may call for a careful mix of quantitative modelling and artificial intelligence tools to ensure that the appropriate balance between grower knowledge and model prediction is achieved.
Publication
Authors
W. Day
Keywords
models, environmental control, greenhouse environment
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