Innovative Technology for Irrigation
There are many different types of innovative technologies available to reduce the amount of irrigation water. In the Desiras project the Agri Yield Management system of Dacom has been applied and tested. Besides Desiras several other parallel projects with respect to desertification are running at this moment. These projects are applying different types of technology. At this page more details about the Dacom technology are given.
Agri Yield Management
Agri Yield Management systems provide the farmer with the necessary tools for profitable and sustainable agriculture. The AYM system as developed by Dacom in The Netherlands. It makes use of advanced technologies like intelligent sensors, internet and GPS. Software combines the collected information into practical solutions that supports the farmer in his daily operations. This AYM system is unique because it integrates multiple aspects of the crop production such as water, chemicals and fertilizer in relation to the yield. The flowchart below symbolizes the system.
Precision timing of these agri-inputs and using the right product has proven to be profitable through the years. The system for disease control was evaluated in field trials around the world and consistently demonstrated a reduction of chemical inputs. Also the use of intelligent soil moisture sensors in combination with weather forecast proved to lead to a much more efficient use of water. Around the world reductions of 49% of water and 31% yield increase have been shown.
Sensor measurements from weather stations and soil moisture stations from local fields are important input in real time yield management systems. Hourly collection of reliable and accurate sensor information is a laborious undertaking. The sensors are usually put in the field and exposed to all kinds of climatic conditions and possible mechanical maltreatment. Constant validation of the produced information is a necessity. The Dacom AYM system handles data of thousands data collection points with multiple sensors like soil moisture content, temperature, leaf wetness, solar radiation, rainfall, wind speed and wind direction from locations all around the world. Raw data is collected through telemetry systems and internet in a central databank. In the control room, a quality check is applied both automatically and manually by a team of technicians to ensure reliable data before it is distributed to farmers and advisors. Automated collection of real time crop data and the development of more intelligent sensors are some of the challenges that lay ahead.
The sensor data is extended with a 10 day hourly weather forecast. This forecast is indispensable to plan activities ahead as a lot of them need to be taken preventative, but are only needed under certain conditions. The sensor data from the field is used as feedback to improve the quality of the weather forecast. This technique has lead to a significant improvement of the forecasting ability of the available general forecasting model. This unique agricultural weather forecast has improved precision timing of the right product in AYM systems significantly.
The software provides the linkage between the farmer and all the gathered information. The farmer will have to record information about his crops: GPS location of the field, type of crop, variety, field activities such as planting, crop protection, fertilization and harvesting. Multiple crop observations are required to feed the advice models to make optimal recommendations. Currently most of those observations are entered manually, but other solutions are being sought in Remote Sensing techniques and crop growth models.
Scientific knowledge and farmer feedback are the basis of the development of the models that provide solutions to the growers. The strong feature of AYM systems is that all knowledge concerning one topic is collected and becomes part of integrated algorithms. The outcome is presented in user-friendly graphs and comments whereas the complex models run in the background of the system.
Using the software means that the latest scientific knowledge is applied in practice. This shortens the learning curve of farmers and advisors tremendously. Whereas understanding the behaviour of the fungal disease Phytopthora infestans in potatoes usually takes several growing seasons a farmer or advisor can predict critical periods of this disease the moment the AYM system is in operation and the user is able to operate the software. The time consuming learning curve can be reduced from years to weeks. Also the latest knowledge from the experts can be integrated and released to the users each moment, even throughout the growing season. When the farmer retrieves the latest data from his field he automatically receives the latest adjustments in the system. Examples are the latest numbers on efficacy of chemicals or new knowledge about the sexual reproduction of Phytopthora infestans.
Disease models calculate practical, real time advice. Traditionally these models are based on local conditions with mathematical algorithms called DSV’s (Disease Severity Values). These systems are based on a standard weekly spraying strategy. The interval between two sprayings will be enlarged or reduced when the number of DSV points are lower or higher. The new generation AYM models are biological models that simulate the life cycle of the fungus. In addition to the critical periods that are calculated based on the life cycle of the fungus, spraying advices are related to the degree of protection of the crop by chemicals and new growth of leaves. As the new generation AYM models are based on biological and physical laws that apply worldwide and use local weather data and weather forecast they can be applied worldwide. For example the Dacom Phytophthora model for potatoes has been successfully applied over more than a decade under conditions ranging from desert climate to sea climate.
The water consumption of a crop is becoming more and more important as water is getting scarce in many parts of the world. The AYM system interprets readings of soil moisture sensors in such a way that the farmer can see if his crop is getting into drought stress or that he is overwatering. Unique feature of the Dacom irrigation model is that it incorporates the weather forecast. Growers can look ahead into what will happen with the soil moisture content 5 days ahead. This is the dark grey area at the right side of graph 2. The system calculates the amount of millimetres irrigation needed to fill up the water depletion of the root zone by comparing the historical water consumption of the crop based on evapotranspiration (ETo) with the forecasted ETo. Evapotranspiration is the loss of water from a vegetative surface through the combined processes of plant transpiration and soil evaporation. In practice this results in the applied amount of water to be in line with the crop’s needs.
Pilot projects in e.g. the Netherlands and Egypt have shown yield increase in winter wheat up to 31% on the one hand and water savings up to 49% in strawberry on the other hand (unpublished data).