Precision Agriculture in the 21st Century Geospatial and Information Technologies in Crop Management (1997) / Chapter Skim
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2 A New Way to Practice Agriculture
2 A New Way to Practice Agriculture
Pages 44-64
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From page 44... ...
At the field and subfield scale, information about the spatial heterogeneity of site characteristics makes it possible to manage the variation rather than attempting to overcome the variation with sufficiently high uniform rates of agricultural inputs. Because of the complex interactions of factors affecting agricultural production, uniform and spatially variable management will result in different inputs and outputs.
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From page 45... ...
_ 150to 160 160tol70 _ ~ 1 70 to 1 80 · 1 80 to 1 SO 1 90 to 200 200 to 210 3~ 210 to 220 _ . ~ greater than 220 Profit ($~0 undefined led than $0 $0 - 40 Be- $40 - 80 $80 - 120 ~ $120 - 160 Ad- $160 - 200 Be- greater than $200 FIGURE 2-1 Crop yield and profit maps.
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From page 46... ...
..;........ Computer en hanced vegetation map of a canta loupe field using aerial imaging technology.
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From page 47... ...
DATE // EMERGEN(::E l WATER ~ it 3rd WATER 1 2nd FIRST . WATER HARVEST ~ ~PICK 1 ' ' 1' ~ an, ~_ _ ~x x GO X x DATE- 1994 20% Initial Greenness ~ 40% Initial Greenness 50% InitialGreenness ~60% Initial Greenness 80% Initial Grecnness Changes in crop growth, open pollinated cantaloupe.
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From page 48... ...
Precision agriculture strategies attempt to adjust field practices to accommodate known variability of important factors. As practiced today, precision agriculture is primarily based on a few parameters, such as soil nutrients or weed maps.
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From page 49... ...
The analysis of these data layers with a GIS and other analysis tools may reveal spatial relationships among agronomic components contributing to yield variation (Skotnikov and Robert, 1996~. Spatial and Temporal Variation The most significant impact of precision agriculture on crop production systems is likely to be on how management decisions are made and on the timespace scales that are addressed, not on actual production practices.
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From page 50... ...
Low soil moisture often causes farm managers to opt for lower initial chemical and fertilizer application rates and thus forego additional crop production should weather conditions turn out more favorable than anticipated. Similar situations occur when the potential for leaching in light sandy soils limits the amount of nitrogen that can be applied in a single application (Booltink et al., 19961.
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From page 51... ...
The investment in obtaining this information will have returns for many growing seasons. Factors such as nutrient availability (except nitrogens, soil-borne pathogens, and perennial weed infestations may exhibit intermediate usefulness because they change slowly.
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From page 52... ...
The following sections attempt to briefly address the potential for precision management strategies for factors that impact crop production. Each section deserves a detailed examination, but the intent here is to highlight possibilities, while leaving the in-depth examination to others.
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From page 53... ...
Knowing the actual plant population at harvest time is important in interpreting yield maps and for management decisions made throughout the growing season. Technology currently under development for corn in the Midwest will measure variability of a plant population and plant spacing (Birrell and Sudduth, 1995; Easton, 1996; Plattner and Hummel, 1996~.
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From page 54... ...
Despite the low spatial resolution needed for many precision agriculture applications (about 20 m by 20 m, or 400 m2) , relative to new spaceborne sensors that can provide 1-5 m resolution, the connection between some soil patterns and apparent crop growth differences is evident in the fields.
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From page 55... ...
Crop yields obtained from a uniformity trial were plotted on a map, and field segments having similar yields were connected by smooth lines. These yield maps were interpreted as soil fertility contour maps.
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From page 56... ...
Second, precision management of soil nutrients allows the producer to set variable yield goals for fields that do not have a uniform productive potential. With variable yield goals, inputs for a
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From page 57... ...
Additional on-farm research is necessary to determine the economic returns from different approaches to soil fertility management in precision agriculture. The evaluation of soil nutrient levels across a field is typically performed by taking soil samples, analyzing them for nutrient content, and interpolating values between the sampling points (Wollenhaupt et al., 1997~.
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From page 58... ...
This figure shows a field with the sites where soil samples were taken and a resulting interpolated phosphorus map. The actual values for soil phosphorus concentration are known only at the sampled points.
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From page 59... ...
Grid sampling and nutrient mapping are most useful for nutrients considered to be relatively stable over time. The information gained from sampling and mapping soil phosphorus, potassium, various micronutrients, and pH is often used for three to five years, allowing sampling and analysis costs to be amortized over several growing seasons.
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From page 60... ...
Improved pest management is likely to increasingly use precision agriculture technologies, with potential benefits to farm workers, the environment, and our food supply. Pesticide Management Producers are interested in saving on input costs and applications.
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From page 61... ...
For example, the new National Oceanic and Atmospheric Administration GOES-8 satellite obtains weather data every half-hour at a spatial resolution of one kilometer, providing an important link in making detailed, spatially distributed weather information available at the farm level. The GOES-8 satellite acquires vertical sounder data on humidity, temperature, and other properties at a spatial resolution of four kilometers.
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From page 62... ...
The rapid proliferation of weather service information providers in the agricultural sector, many with on-line access, has set the stage for accessing other types of information for farm management. Providers already bundle information from public and private sources and combine weather data with crop models to provide specialized data and services to their agricultural customers.
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From page 63... ...
Realtime quality sensors do not exist, but predictive crop models may be a substitute. If crop growth models can use subfield-scale data to predict product quality, a producer may be able to avoid harvesting a portion of the field, for example, that has a high probability of containing aflatoxin.
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From page 64... ...
Regardless of the accuracy of our vision, the crop management practices of the twenty-first century will be significantly affected by these information technologies. Crop yields typically represent only a small portion of the genetic potential of the plants.
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