Agriculture Reference
In-Depth Information
at the time they are needed. For example, it is critical for the operator of a fertilizer
applicator to know “how much” nitrogen is to be applied at a specific location in a
field, in order to perform effective variable-rate fertilization. Such location-specific
“how much” information directly usable by operators is an example of necessary
task instructions for precision farming operations.
Effective precision implementation of agricultural production relies on the ability
to handle a large amount of production-related data and other relevant information.
For example, a typical yield monitor installed on a combine harvester can collect
more than 600 data point sets per hectare, and each likely carries at a minimum
characteristic data such as the location (latitude, longitude), the yield, and the mois-
ture content of harvested grain. The overwhelming amount of data, plus the require-
ment for special skills and tools in real-time data processing, and implementing
commands extraction from those data, makes the on-machinery data management
a very difficult task for producers in field operations. Agricultural infotronic system
(AIS) technology offers a solution to remove such an obstacle for effectively imple-
menting precision farming operations.
3.2 DEFINITION OF AGRICULTURAL INFOTRONIC SYSTEMS
The concept of AIS was first created to specifically name an integrated data manage-
ment system for automatically updating, transmitting, and presenting precision crop
production information on agricultural machinery during field operations (Zhang
and Benson, 2000). Supported by a machine-area network, this AIS technology was
soon successfully used to support a field crop sensing system, to detect crop health
condition in field scouting (Kim
et al., 2000a), and applied to support map-based
fertilization, by precisely varying the application rate in terms of the actual need on
fertilizer applicators, and to support map-based tillage through continuous control of
both tractor speed and plow depth, based on soil type, soil moisture, and other field
conditions (Zhang
et al., 2000).
A formal definition of AIS was first clearly described in a communication pub-
lished in January 2003 issue of the
Resource
magazine (Zhang, 2003). It states that
the “AIS is an integrated automatic data sensing, processing, and presenting sys-
tem”. Based on this definition, an AIS system is designed to collect crop production-
related data from all relevant sources, including on-board electronic sensors,
space-based field observation images, and historic production databases. The AIS
will then automatically process the obtained data to support “on-the-go” decision-
making during field operations to obtain “ready-to-use” field work instructions for
implementation.
Although the original AIS definition offers an innovative functionality of creating
optimal task instructions in a transparent way to users through integrating data sens-
ing, processing, and communication, to enhance the efficiency of precision farming
operations, the inclusion of sensing and display devices in the system requires each
AIS to be specifically designed for a particular application, which creates an obstacle
for the new technology adoption. To solve this problem, a redefinition of AIS was
made in 2007 as follows: “AIS is an integrated information management system
to provide farmers an effective and reliable means for getting optimal operation
