Abstract
Understanding the dynamic behaviour of plants is vital for realization of precision agriculture systems. This paper proposes a dynamic response model of root diameter to changes in temperature and relative humidity for commercial epiphytic orchids. A Vanda hybrid orchid is used for this study. Root diameter changes, temperature, and relative humidity measurements are logged for fifty-one days. The dynamic response of the root diameter changes is analysed and modelled using non-linear autoregressive with exogenous input neural network. The best performance is obtained with Levenberg-Marquardt algorithm, yielding the best overall regression, lowest mean squared error, and fastest training speed.
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