Phytocare – Parameters to grow roses #SWI2002
In Agriculture the key point is optimizing the production at limited costs. For decennia already, one has tried for the best and one cannot do without a computer anymore. In present-day greenhouses the control of the inner climate is fully automated.
The inner climate could be held constant, but for the optimization of the production it is necessary to adapt (?) the inner climate to the conditions outside the greenhouse. The importance of this can be illustrated by the effect of passing showers: if the farmer (?) does not anticipate with the, possibly sharp, temperature decrease that is due, this could mean a delay of one week for the production. Hence a swift and adequate reaction is of utmost importance.
Theoretically, many models have been made that try to connect the climatic conditions to the resulting production of the weed (?). Unfortunately, farmers (?) do not profit much from the insight that is obtained by the present models. Most studies are aimed at one particular type of weed (?), but the characteristics of different types often differ significantly. Perhaps even more important: the characteristics are not constant throughout the year, whereas the present models account for them with fixed parameters.
Phytocare would like to turn (?) this situation and be able to advise farmers (?) with this new approach. The idea is the following. The climate computer applies specified amounts of moist, light, nutrients, etc. At the same time, the inner climate is measured: every 5 minutes the computer provides data on a.o. temperature, humidity and light (luminiscence?) in the greenhouse. For each plant, one will know the conditions in which it lived for every 5 minutes. Moreover, one can measure the production from the plants themselves: for tomatoes, for example, one can count the increase of the weight of fruit for each plant within a certain period. For roses, the weed (?) most of Phytocare’s advises deal with, the production can be measured by the growth of branches per week; indeed (immers?), a branch can be harvest as soon as it reaches the required length to be sold. Measuring the production can only be done on a longer timescale however. Usually the production is measured every week. Using the measured climatic conditions in the greenhouse and the production per week, we would like to find species-specific parameters for the plants, for example by fitting them to the data. As explained before, one of the complications is the fact that the climate measurements are carried out every few minutes, whereas the production can be measured on a weekly basis only. With the parameter values obtained, the approach can be reversed again: are their rules of thumb to be given to the farmer (?) by which their climate control can increase the production at reasonale costs? Different scenarios could be calculated to advise the farmer (?).
Questions to be raised are, for example: Can Phytocare advise farmers (?) how to optimize their production using a model which has been fitted to the individual farmer (?) and his greenhouse by the above describe approach? Or at least find out when the photo-synthetic process (?) of the plants is optimal (optimal production is closely related to optimal photo-synthesis)? Is the model accurate enough in order to calculate if, for example, certain investments in the greenhouse (to optimize the production) will increase the production sufficiently to justify the investments?