RE SEARCH Potatoes and soil moisture: when should I start irrigating? every day with a resolution of 3 metres x 3 metres. The advantage of a model approach is that both the spatial and the temporary distribution are taken into account. With the use of weather forecasts, an irrigation forecast can even be made a few days in advance. By linking to crop growth models, it becomes possible to make a link between soil moisture and yield. But are model simulations reliable? In fact, models also have their own quirks. It is a simulation instead of a measurement. The soil map is an input parameter for models, so is that map sufficiently accurate? What is the influence of the preceding crop, the organic matter content and soil cultivation on the water-binding capacity? The depth of the roots will not be the same everywhere, because they adapt to the micro-growth conditions. A local shower above a plot may differ from the nearest KNMI weather station (especially in a case of heavy showers). The reel sprinkler is effected by wind, so that the water can never be distributed uniformly over a plot. The fifth conclusion is that simulation models for soil moisture cannot calculate the actual situation without additional information. However, if a model is trained with surface-covering data, much of this uncertainty is removed. In the example below a soil map has been used that is derived from bare-ground drone flights in the spring. The root depth is made variable in the example by making smart use of thermal drone images. The similarity in the distribution of volumetric soil moisture gives the user renewed courage: many patterns correspond well. It will not be possible to do much better, because all management factors cannot be simulated and the field measurements are insufficiently reliable. By carrying out model simulations every day, the need for irrigation can be determined per day for every 3 metres x 3 metres. The sixth conclusion is that a farmer can decide to start irrigating if, for example, 5 or 20 percent of the land is too dry. This year, the first experiments will be put into practice with a number of potato farmers. If the assessvolemetric soil moisture 0 [cm3/ cm3] op 29/06/2018 model simulation thermal drone flight Figure 3: Comparison of the soil moisture simulated by a model that has been trained with a thermal drone flight (source: Aurea Imaging) ment is positive, this spatial moisture monitor will become available in practice next year. Combining individual measurement principles provides valuable information What is the conclusion of this story? There is no direct measurement method for soil moisture (unless you take a soil sample and dry it in an oven), but there are several methods that actually all measure indirectly. By combining individual measurement principles, something valuable suddenly emerges. A simulation model at plant level provides a strong basis, but two aspects have to be calibrated: (i) the spatial variation within a plot or field must be measured with a thermal drone and (ii) the temporary variation must be measured with an installed soil moisture sensor. It is a bit like 1 + 1 + 1 = 5. In this way the best of different worlds can be combined. The soil moisture monitor of the future will be a spatial picture (for example how many days it takes for the critical moisture content to be reached). It is expected that DroneWorkers and suppliers of soil moisture sensors will tackle this jointly. ● Table 2: Advantages and disadvantages of the various measuring techniques. A combination appears to give the best results and is feasible in practice. Measurement techniques Field sensors Advantages Indicate dehydration of the soil Disadvantages • Local representation • No absolute moisture content • Moment of irrigation unreliable • Stress level is constant (does not vary with the weather) Thermal drone • Measures every plant and every piece of soil; excellent spatial distribution • Also measures indirectly management factors such as preceding crop, organic fertilisation, tractor tracks etc. Simulation model • Space and time patterns are described • Role of soil moisture on stress is clear • Linking with crop growth and fertilisation becomes possible • Irrigation advice based on surface-covering information • Only a few measurements per season possible (otherwise expensive) unless drone robots are used • Correction for thermodynamic processes necessary; expertise needed • Measures stress, but not its cause; role of soil moisture is not clear • Model requires accurate soil map • Model must be trained with field sensors (for time) and thermal drone (for space) after which the influence of human action can be described Potato World 2018 • number 4 27 Pagina 26

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