Skip to main content

Currently Skimming:

1 Dimensions of Precision Agriculture
Pages 16-43

The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.


From page 16...
... For the most part, whole fields have been considered to be the basic agricultural production units, and have been managed for the mean condition or, in the case of pest management, managed intensively to overcome variability within that field. Historically, a desire to improve production efficiency and farm income has stimulated interest in innovative technologies.
From page 17...
... 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.
From page 18...
... These two characteristics apply to traditional crop production settings. The uncertainties associated with the rapid evolution of information technologies and the dynamics of the process of adopting precision agriculture represented a significant challenge in the preparation of this report.
From page 19...
... This impact will be felt directly through the coupling of newly acquired information with recently developed tools for agricultural production, on-demand products and services, and increased access to information and services. A number of scales characterize crop production systems of today.
From page 20...
... For example, digital data could be collected by an on-the-go yield monitor in a combine, sent via a wireless cellular link to the operator's home computer, and retrieved via a highspeed Internet connection by an agricultural chemical dealer. The dealer may then add the yield data to a nutrient management analysis and send recommended fertilizer application rates for various subfield units back to the farm operator's computer.
From page 21...
... Even precise management based on variability of the physical and chemical properties within soil types may or may not be sufficient for optimal management of crop production activities. As producers try to manage smaller areas, the law of limits comes into play more strongly.
From page 22...
... While this report focuses on subfield level precision agricultural practices, a discussion of two key larger-scale strategies follows. Data Warehousing Large amounts of spatially referenced data on individual fields are, or soon will be, generated by yield monitors, real-time and remote sensors, on-the-ground sampling and observation by producers and consultants.
From page 23...
... is a computerized crop weather information system that producers can access by modem or the Internet to obtain hourly and daily weather conditions. Producers combine regional evapotranspiration data and local soil- and crop-specific coefficients for their fields to determine the daily water use and water demand of their farms (see Box 1-1~.
From page 26...
... 26 PRECISION AGRICULTURE IN THE 21ST CENTURY ENABLING TECHNOLOGIES A fascinating aspect of precision agriculture is that a single technology is not being undertaken to improve a single practice. Instead, across the crop-production sector of the United States, precision agriculture is emerging as the convergence of several technologies with application to several management practices.
From page 27...
... In the past century, of course, other developments such as the internal combustion engine, electrical power, telephone, and weather satellites produced outside of agriculture have been introduced to the agriculture sector. Precision agriculture technologies such as the global positioning system (GPS)
From page 28...
... It is expected that data referenced to physical location will allow different types of information to be compared and quantitatively analyzed at multiple locations. For example, physical properties of soil core samples collected from a field could be compared with other spatially explicit data available for decision making, such as characteristics of the mapped soil unit and topography, yield monitor data, and irrigation, nutrient, or pesticide applications recorded during variablerate applications.
From page 29...
... If the sensed parameters and application rates are recorded and georeferenced, these data can be included in the management database. Adoption of GPS and other spatial referencing technologies will have a widespread impact on data collection and analysis.
From page 30...
... The data layers derived from combinations of raw data can generate information about spatial variability among factors in crop production. It is expected that adequately co-registered data will be quantitatively analyzed through the use of geostatistical and other procedures.
From page 31...
... Since 1992, grain yield mapping has been done by using mass flow and moisture sensors to determine grain mass and using GPS receivers to record position. Yield monitors measure wet grain flow, grain moisture, and area harvested to determine moisture-corrected yield per acre.
From page 32...
... Commercially available sensors employed for VRT include those responsive to organic matter, cation exchange capacity (CEC) , topsoil depth, soil moisture, soil nitrates, and crop spectral reflectance.
From page 33...
... Vary herbicide rates in response to soil organic matter variations. Vary starter fertilizer in response to soil CEC variance.
From page 34...
... Soil conductivity is appropriate for concurrent real-time assays of salinity, soil moisture, organic matter, cation exchange capacity, soil type and soil texture. Recently, this work was ex
From page 35...
... Basic research in the sensors arena is fundamental to an improved understanding of the variations in site-specific crop production in a wide variety of regional production systems. Remote Sensing Remote sensing the acquisition of information from remote locations such as an airplane or satellite is a potentially important source of data for precision agriculture.
From page 36...
... Nevertheless, the understanding of crop spectral and radiometric relationships gained from past research is relevant to crop management applications (Bauer, 19853. Jackson (1984)
From page 37...
... Detailed spatially distributed multitemporal information, in visual form, is not readily obtainable from conventional crop management systems or from site-specific crop management methods. Remotely sensed images (i.e., color infrared aerial photographs or multispectral images acquired from satellites or airplanes)
From page 39...
... Landscape elements affect many properties relevant to plant growth, including soil texture, soil organic matter, and temperature. Landscape morphology affects soil moisture available to crops by its influence on drainage and catchment area.
From page 40...
... However, crop modeling is currently an important tool for gaining a theoretical understanding of a crop production system. Decision Support Systems Decision support systems (DSS)
From page 41...
... Similarly, decision support systems do not address the problem of spatial heterogeneity. This is true for weed management DSS such as HERB, WeedS OFT, and PC-Plant Protection, and for insect and disease management programs; irrigation and crop selection programs are all whole-field based.
From page 42...
... For example, relatively little is known about the suitability of crop cultivars for specific soil types or cultivar-fertility-pesticide interactions. Little is known about the interactions between agronomic practices and their environment at the subfield scale.
From page 43...
... A suite of tools will be used to assess and manage agronomic factors important to crop production. For these new tools to function properly, however, they will need to be user friendly for producers and consultants.


This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More information on Chapter Skim is available.