ISHS Acta Horticulturae 584: VI International Symposium on Computer Modelling in Fruit Research and Orchard Management
APPLICATION OF AN EXISTING FLOWERING MODEL TO THE STRAWBERRY GUAVA. ANALYSIS OF DISCREPANCIES BETWEEN THE MODEL AND DATA |
| Authors: | F. Normand, R. Habib |
| Keywords: | Psidium cattleianum, flowering model, stochastic model, temperature, phenology, Réunion Island |
| Abstract:
A precise model of flowering at both the individual and the orchard level is an important prerequisite in determining final production for fruit species with particular pollination requirements such as the strawberry guava (Psidium cattleianum). Most flowering models have been designed for orchards while implicitly assuming that all the trees have the same flowering pattern. Their accuracy may be affected by flowering variability among trees, linked to genetic and/or environmental factors. A stochastic, temperature driven, flowering model developed for kiwi orchards was tested on strawberry guava. This model had two parameters: a flowering threshold a and a parameter of variance relative to flowering σ². Data were obtained from the flowering of 3 sets of trees, all genetically different, located at 200, 520 and 890 m of elevation on Réunion Island. Data collected at 520 m were used to fit the model, while data obtained at 200 and 890 m were used to validate it. The model described the flowering at 520 m well, but failed to account for flowering at 200 and 890 m and to represent the individual flowering patterns on each site. Analysis of the discrepancies between the model and the data showed that factors that vary among trees should be considered: number of flowers per tree, time and duration of individual flowering. The previous stochastic model has thus been re-estimated at the tree level and the over-all flowering was considered as the superposition of the individual flowerings weighted by their respective number of flowers. The model then had 2K (K = number of trees) parameters. It described the individual flowering pattern well, and more accurately represented the over-all flowering per site. However, a more general model with a reduced number of parameters needs to be derived from it. | |
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