Sensors vs. Map Based Precision Farming Chris Sechrest

Sensors vs. Map Based Precision Farming There are two methods for implementing precision agriculture. They are: Map-based methods Sensor based methods

Map-Based Map based methods involve the following steps: Sampling the field Running sample analysis Generating a site specific map of the properties Using this map to control a variable rate applicator

Map-Based During both the sampling and application steps, GPS technology is used to identify current location in the field.

Sampling the Field Field sampling for precision ag can be accomplished in one of two ways: Grid sampling Zone sampling

Sampling the Field Times to choose grid sampling over zone: Field history is unknown Fertility levels are high due to high fertilization There is a history of manure application Non-mobile nutrient levels are of primary importance (P,K,Zn)

Sampling the Field Times to choose zone sampling Yield monitor data show a relationship with topography Relatively low fertility levels are present Low rates of non-mobile nutrients have been applied recently Mobile nutrients (especially N) are important to map.

Map Based Precision Farming Map based technologies are especially good for collecting data for variables which do not fluctuate from season to season, such as organic matter and soil texture.

Map Based Precision Farming Due to high testing costs and labor requirements, map based precision farming is not as effective for variables that are quickly changing, such as nitrogen.

Sensor Based Precision Farming This method utilizes real-time sensors and feedback control to measure the desired properties on-the-go and immediately uses this signal to control the variable rate applicator.

Sensor Based Precision Farming While map-based programs take a few samples from areas (1 to 2 acres) of the field, a sensor based system can collect dozens of samples from each acre This gives a more accurate assessment of your field variability.

Sensor Based Precision Farming The main problem faced by sensor methods is “lag time”. Developers must synchronize the sensor measurement with the desired application rate for the same site. In order to be effective on-the-go, these sensors have to respond to changes in the soil or crop almost instantly. With advancing technology, this will become less of a problem.

Advantages of Map-Based Variable Rate Application Systems are already available for most crop production units The user has a database useful for a number of management decisions User can employ multiple sources of information in the process of formulating a variable rate application plan User has significant control regarding the function of such systems because of the involvement in application rate planning

Advantages of sensor based Variable Rate Application Pre-application data analysis time requirements can be eliminated Sensors produce higher data resolution than traditional sampling methods No time delay between measurement and application with real-time systems Systems are self-contained

Conclusions As technology continues to develop, farmers should expect great increases in the number of options for both map-based and sensor- based variable rate application methods.