213
– While typically not featured in discussions of precision agriculture or big data
analytics, advances in communication capabilities based upon digital technology often are essential to enhancing performance.
8.3 Precision Agriculture: Precursor to Big Data
This section will provide a brief overview of the precision agriculture experience. It
is not intended as comprehensive assessment. It is intended to provide a sense of the
evolution of precision agriculture, identify the more popular technologies employed,
and discuss the admittedly scant evidence as to the economic gains from the use of
these innovations.
It is important to note that precision agriculture and big data are not synonymous.
As noted above, the current tools and techniques of precision agriculture have
existed largely without the application of big data concepts. However, it is hard to
foresee that big data approaches could have significant impact without employing
precision agriculture technologies to capture at least of the data required.
Precision agriculture has several dimensions; indeed the concept itself is not precisely defined. A 1997 report of the National Research Council (National Research
Council 1997) refers to precision agriculture, “...as a management strategy that uses
information technologies to bring data from multiple sources to bear on decisions
associated with crop production.” Key technologies and practices included within
precision agriculture are as follows:
• Georeferenced information
• Global positioning systems
• Geographic information systems and mapping software
• Yield monitoring and mapping
• Variable-rate input application technologies
• Remote and ground-based sensors
• Crop production modeling and decision support systems
• Electronic communications
The term precision agriculture primarily has been linked to crop production.
However, precision practices (and big data techniques for that matter) are equally
applicable in animal agriculture, where georeferencing can refer to both sub areas
of a field and individual animals. The tracking processes and required tools may
differ but the managerial goal is still to separately manage increasingly smaller units
of observation.
Farmers and agribusiness managers played a significant role in the development
of precision agriculture. For example, in the mid-1990s, a group of agribusiness
professionals in Champaign County, Illinois, came together to explore the opportunities associated with two emerging technologies — site-specific agriculture and
that strange thing called the Internet (Sonka and Coaldrake 1996). This group,
called CCNetAg, was part of an initiative co-sponsored by the local Chamber of
8 Digital Technologies, Big Data, and Agricultural Innovation
– While typically not featured in discussions of precision agriculture or big data
analytics, advances in communication capabilities based upon digital technology often are essential to enhancing performance.
8.3 Precision Agriculture: Precursor to Big Data
This section will provide a brief overview of the precision agriculture experience. It
is not intended as comprehensive assessment. It is intended to provide a sense of the
evolution of precision agriculture, identify the more popular technologies employed,
and discuss the admittedly scant evidence as to the economic gains from the use of
these innovations.
It is important to note that precision agriculture and big data are not synonymous.
As noted above, the current tools and techniques of precision agriculture have
existed largely without the application of big data concepts. However, it is hard to
foresee that big data approaches could have significant impact without employing
precision agriculture technologies to capture at least of the data required.
Precision agriculture has several dimensions; indeed the concept itself is not precisely defined. A 1997 report of the National Research Council (National Research
Council 1997) refers to precision agriculture, “...as a management strategy that uses
information technologies to bring data from multiple sources to bear on decisions
associated with crop production.” Key technologies and practices included within
precision agriculture are as follows:
• Georeferenced information
• Global positioning systems
• Geographic information systems and mapping software
• Yield monitoring and mapping
• Variable-rate input application technologies
• Remote and ground-based sensors
• Crop production modeling and decision support systems
• Electronic communications
The term precision agriculture primarily has been linked to crop production.
However, precision practices (and big data techniques for that matter) are equally
applicable in animal agriculture, where georeferencing can refer to both sub areas
of a field and individual animals. The tracking processes and required tools may
differ but the managerial goal is still to separately manage increasingly smaller units
of observation.
Farmers and agribusiness managers played a significant role in the development
of precision agriculture. For example, in the mid-1990s, a group of agribusiness
professionals in Champaign County, Illinois, came together to explore the opportunities associated with two emerging technologies — site-specific agriculture and
that strange thing called the Internet (Sonka and Coaldrake 1996). This group,
called CCNetAg, was part of an initiative co-sponsored by the local Chamber of
8 Digital Technologies, Big Data, and Agricultural Innovation