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Fluid Journal : Fluid Journal 1996-1998
2 Fluid Journal Spring 1996 from drinking water also show that in a majority of the cases there was excessive bacterial contamination. Because of consumer demand for high quality food, producers are more inclined to follow a strategy of "better safe than sorry" rather than "better never late" or "better late than never" when it comes to nutrient management. The problem of N nutrition is confounded because the impact of organic matter mineralization on NO; is difficult to predict. Considering the uncertainties with nutrient control of animal wastes, uniformity of manure application rates, mineralization of manure, and climate, it is no wonder producers migrate toward a "better safe than sorry" strategy for N management. Carrying the fight One mighty tool helping producers to address water quality issues is an unfolding new technology known as precision farming or site-specific management. This rapidly spreading concept recognizes the existence of spatial variability in fields and offers a variety of farm management tools. In essence, it is little more than a strategy to compensate for natural and man- made variability in fields by altering those factors we think influence yield, profitability, environmental quality, etc. Tools that make site-specific management possible are many and varied. Two basic approaches that have evolved for corn production are: 1) harvesting with a yield monitoring combine, and 2) grid sampling and variable rate fertilizer application. Yield monitoring. This approach is more conservative in that it first assesses spatial variability in crop growth and yield, which has a major impact on profitability. Unfortunately, a yield map alone does little to explain the causes of yield variability in a field. The reality of examining a yield map for the first time can be rather emotional because variability translates into everything from embarrassment (because it implies poor management) to irritation over reduced profits. After the initial shock of seeing a yield map (assuming yield variability is obvious), producers can frequently account for variability in terms of soil features, cropping history, or cultural practices. Many times, producers have difficulty grasping the magnitude of yield map variability. Grid sampling. Spatial variability in yield is good justification for considering grid sampling and variable rate nutrient application. Here producers assume soil fertility is a major source of spatial variability in crop growth and yield. The perception is that variable rate fertilizer application must be more environmentally sound than uniform rate. The goal is that fertilizer rates will be reduced enough to offset the extra cost of soil sampling, chemical analysis and variable rate fertilizer application, or that increased yields will cover these costs. However, without a comparison or source of reference, it is hard to know if anything would be gained by the extra effort and cost involved in variable rate fertilizer application. That is why it is best accompanied by yield monitoring to evaluate how much of the variability was removed. Producers who have generated yield maps over several years frequently comment on the lack of similarities between maps. In essence, these maps express the net interaction between soil, climate, management, and crop growth. Considering that crop yield integrates these factors and others over an entire growing season, it would be unusual for yield maps to resemble one another. That is why a series of yield maps over three to five years is needed to make a comprehensive statement about the role of site-specific management on crop yield and environmental stewardship. This time can be reduced if some type of in- season assessment of crop growth is available to compare with a yield map. A cheaper way Remote sensing is another valuable environmental tool that holds promise in site-specific management. Early in a year, an aerial photograph of bare soil color (after planting) provides a good indication of relative soil organic matter content. With minimal computer hardware and software, such a photo-graph can be digitized and the colors grouped into categories. Reasonable calibration usually can be attained by sampling a range of five to six representative colors, analyzing the samples for organic matter content by using the digitized version or the original color map and the calibration data. Such a map can be used to predict relative N mineralization, or adjust herbicide application rates. The cost of generating an organic matter map in this way is considerably less expensive and much more informative than using grid sampling. High-intensity grid sampling and chemical analysis are usually cost prohibitive. Decreasing the sampling frequency introduces considerable uncertainty unless soil type, topography, and landscape position are used to select the sampling sites. Only a few studies exist where sampling intensity was great enough to evaluate the effect of sample spacing. In a study from a center-pivot irrigated corn field (160 acres) in the Platte River Valley of
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