Precision Farming: Sensors vs. Map-Based

By: Mark T. Morgan
Agricultural and Biological Engineering Department
April 1995

Two Methods of Precision Farming

There are two methodologies for implementing precision, or site-specific, farming. Each method has unique benefits and can even be used in a complementary, or combined, fashion:

* The first method, Map-based, includes the following steps: grid sampling a field, performing laboratory analyses of the soil samples, generating a site-specific map of the properties and finally using this map to control a variable-rate applicator. During both the sampling and application steps, a positioning system, usually DGPS (Differential Global Positioning System), is used to identify the current location in the field.

* The second method, Sensor-based, utilizes real-time sensors and feedback control to measure the desired properties on-the-go, usually soil properties or crop characteristics, and immediately use this signal to control the variable-rate applicator (Figure 1). This second method doesn't necessarily require the use of a GPS system.

Map-based Technologies

Currently, the majority of available technologies and applications in site-specific farming utilize the Map-based method of pre-sampling, map generation and variable-rate application. This method is most popular due to the lack of sufficient sensors for monitoring the soil conditions. Also, laboratory analysis is still the trusted and reliable method for determining most soil properties. However, the cost of the soil testing limits the number of samples that a farmer can afford to test. Thus, the usual practice is to grid sample a field every 2 acres. (There is currently much discussion on the optimum number of acres represented by each sample and the location of those samples.)

Detailed mapping of fields is easily performed using a computer program (sometimes a GIS, geographical information system, program). Some programs can even use algorithms for "smoothing" or interpolating the data between sampling points. Others use a constant value for the measured property over the entire area, i.e. 2 acres for example. In either case, the mapping facilitates long term planning and analysis. It provides an opportunity to make decisions regarding the selection and purchase of seed and chemicals well in advance of their time of use.

Maps are especially good for collecting data for variables which do not fluctuate from season to season. Variables such as organic matter, soil texture, and possibly yield potential change slowly, if at all. Soil fertility with regard to particular nutrients such as phosphorous, and potassium may change from year to year but one can probably obtain benefits from sampling only every 2 to 3 years. Other nutrients, such as nitrogen, may vary considerably even during the growing season and require measurements and mapping every year.

In order to use these computer-generated maps they must be converted to a form which can be used by the variable-rate applicator. The applicator's controller then calculates the desired amount of chemical to apply at each moment in time. Again, a DGPS system must be used to continuously correlate the location in the field with a coordinate on the map and the desired application rate for that coordinate. Most variable-rate controllers actually attempt to synchronize the application rate with the position in the field by "looking ahead" on the map for the next change in rate. This takes into account the time required to change the rate coming out of the applicator and the ground speed of the tractor.

Another issue in using precision farming which is related to the needed resolution in the maps is the applicator width and its controllability along this width. If a spray boom is 60 feet wide and each nozzle cannot be controlled independently, then the usefulness of variable-rate application may be limited. However, if each nozzle is independently controllable, then the resolution of the map being used to control the spray must be very good.

One system that utilizes this pre-sampling and map-controlled application is called Soilectiontm and is currently promoted by Soil Teq, Inc., Minnetonka, MN. Variable-rates of up to 5 liquid chemicals, may be applied by this system based on the computerized map. One benefit of the map-based method is the apriori knowledge of the needed amounts of chemicals, or inputs, for the operations. A farmer knows exactly how much fertilizer, for example, he will need before he even enters the field (similar to when constant-rate application is used).

Sensor-based Technologies

Some technology is becoming available utilizing the method which can be described as real-time sensing and variable-rate control. One such system is marketed by Crop Technology, Inc., Houston, TX. Their system, the Soil DoctorR, claims to "examine soil type, organic matter, cation exchange capacity, soil moisture and nitrate nitrogen levels" using a "rolling electrode". By sensing these properties on-the-go, the need for a positioning system is eliminated and the data processing is greatly reduced because no maps are required. However, if the operator desires to record the sensor outputs and use this information for other operations, the system is capable of interfacing with a GPS and generating site-specific maps.

This type of system also has a problem with synchronizing the sensor measurements with the desired application rate for the same site. In some instances, the sensor may have to be mounted on the front of the tractor, or spreader truck, to give the variable-rate applicator's controller enough time to adjust the rate accordingly before it passes the sensed location. In order to effectively accomplish this real-time control, the sensors must respond almost instantaneously to changes in the soil. For example, a bulk fertilizer spreader truck may operate at field speeds of 25 miles per hour. This means that 37 feet will have passed beneath the truck if the lag time of the system is one second.

One sensor which has been developed at Purdue University for this purpose is a soil organic matter sensor (Figure 2). Currently, Tyler, Benson, MN. has licensed this sensor to vary application rates of dry soil-applied herbicides and/or blended fertilizer on-the-go without a map. The organic matter sensor consists of a photodiode surrounded by six LED's (light emitting diodes). The LED's shine red light onto the soil surface and the photodiode measures the amount of reflection. This reflection signal is related to the amount of organic matter in the soil. Moisture can also affect the sensor but as long as the soil is moist, the effects are small.

Other researchers around the country are also actively developing sensors for real-time measurements of nitrate nitrogen (in soils and animal waste), soil pH, potassium and phosphorous and soil texture. If these efforts succeed, site-specific farming will become even more economical possibly even automatic.

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