Agriculture Reference
In-Depth Information
4.1 INTRODUCTION
Precision agriculture is a new farming practice that has been developing since the
late 1980s. Research activities in precision agriculture started with the development
of yield monitors, grid soil sampling, soil sensors, positioning systems, and variable-
rate technology at universities in the United States and Europe in the late 1980s.
By the early 1990s, grain yield monitors and variable rate controllers became com-
mercially available. With advances in global positioning systems (GPS), geographic
information systems (GIS), remote sensing, and sensor technology, the agricultural
community has witnessed a rapid growth of a new body of precision agriculture
technologies since the mid-1990s. The first biannual international conference on
precision agriculture was held in 1992. The first biannual European and Asian con-
ferences on precision agriculture were held in 1997 and 2005, respectively. The first
international journal entitled
Precision Agriculture
was launched in 1999, and preci-
sion agriculture has been an important topic in many agriculture-related journals.
Several topics on this topic have been published, including
The Precision-Farming
Guide for Agriculturists
by Ess and Morgan (2010) and
Handbook of Precision
Agriculture: Principles and Applications
, which was edited by Srinivasan (2006).
These conferences, proceedings, journals, and books provide effective forums for
disseminating original and fundamental research and experiences in the fast grow-
ing area of precision agriculture.
Precision agriculture has been variously referred to as precision farming, pre-
scription farming, spatially variable farming, site-specific crop management, vari-
able rate technology, to name but a few. There are numerous definitions for precision
agriculture, but the central concept is to identify within-field variability and manage
that variability. More specifically, precision agriculture uses a suite of electronic
sensors and spatial information technologies (i.e., GPS, GIS, and remote sensing)
to map within-field soil and crop growth variability and to optimize farming inputs
(fertilizers, pesticides, seeds, water, etc.) to the specific conditions for each area of
a field with the aim of increasing farm profits and reducing environmental impacts.
To automatically implement the concept of precision agriculture, the following
four main steps are generally involved:
1. Measuring spatial variability. Ground-based sensors, GPS receivers, and
remote sensing systems are needed to map crop yield, soil attributes,
pest conditions, and other important variables affecting crop production.
Computerized data acquisition devices that can integrate field sensors and
GPS receivers are necessary for effective data collection.
2. Analyzing data and making decisions. Spatial data analysis tools, includ-
ing GIS and image processing, are needed to manage field-collected data
and information from other sources such as topographic maps and soil
maps. Statistical and geostatistical techniques need to be used to analyze
data and identify the patterns of spatial variability in measured variables
and the relationships among the variables. Fields need to be divided into
either irregular management zones or regularly gridded cells for manage-
ment based on field spatial variability. The optimal management plans for
