The incorporation of information technologies into agricultural production practices began in the mid-1980s and has increased sharply in recent years. While the use of information in agricultural decision making is not new, agriculture is experiencing a vast increase in the amount of information available, and in the timeliness and means by which information can be collected, analyzed, and used to manage inputs and outcomes of agricultural practices. The application of new information technologies in agriculture is known by several terms, including precision agriculture, precision farming, and site-specific management. A variety of definitions have been offered for the concept of integrating information technologies with agronomic practices. Most authors have focused on the ability to obtain data and to vary production inputs on a subfield basis. While this is an important aspect, there are other geographic scales at which information can be obtained and used to facilitate site-specific management. The committee chose to view precision agriculture broadly, adopting the following definition:
Precision agriculture is a management strategy that uses information technologies to bring data from multiple sources to bear on decisions associated with crop production.
A key difference between conventional management and precision agriculture is the application of modern information technologies to provide, process, and analyze multisource data of high spatial and temporal resolution for decision-making and operations in the management of crop production. Advances in the technologies will be an evolutionary process and they will continue to be adapted for agricultural decision making.
Precision agriculture has three components: capture of data at an appropriate scale, interpretation and analysis of that data, and implementation of a management response at an appropriate scale and time. Each particular manageable factor has its own scale of variability. Area-wide management of insects and weather forecasting for crop management decisions are examples of variables that are managed at a scale larger than the individual field. Other factors like soil fertility and pest distributions can vary significantly at the subfield level and over the growing season. Therefore, it is natural and important to perceive precision agriculture in terms of finer spatial or temporal units of decision making.
Advances in information technology and their application in crop production, which are labeled as precision agriculture in this report, are creating the potential for substantial change in management and decision making in agriculture. The word potential in the previous sentence is critically important. The various technologies and practices that will make up tomorrow's precision agriculture are only emerging, being tested and refined, and implemented or rejected