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Fluid Journal : Fluid Journal 2002-2004
(NIR) reflectance is highly correlated with the amount of living vegetation in the field of view (i.e., more living biomass results in more NIR reflectance). Concurrently, diminished blue and red reflectance is closely associated with the harvest of light in these visible wavelengths by chlorophyll molecules during photosynthesis (i.e., less blue and red reflectance translates into more photosynthesis and biomass). Thus, healthy and vigorous corn plants appear deep green in color while nutrient-deficient plants often appear yellow, purple or otherwise discolored. Likewise, the presence of vegetation causes the reflectance of large amounts of NIR radiation even though it cannot be detected by the human eye. Spectral procedures to differentiate between anthocyanin and chlorophyll related reflectance have been developed. The potential exists, therefore, for appropriate optical and NIR sensors to measure both biomass and photosynthetic activity. Various approaches for measuring crop canopy reflectance have been developed and tested using remote sensing data for differing spatial resolution. Because of the diverse range in crops, situation, and intended application of the information, no single technique has emerged as working the best. Space-based platforms generally lack the desired spatial resolution and timeliness required for most site- specific management applications. Aircraft platforms offer an appropriate level of spatial resolution and provide a "whole-field" glimpse of the situation, but are plagued by problems with clouds, high winds, and time of day restrictions (i.e., sun angle). Mobile, ground-based sensors offer excellent Table 1. Quantity of nutrients in corn plants and nutrient uptake at silking and harvest. Nutrient Silking Silking Grain Grain lbs/A % of total lbs/A % of total Dry matter 4,199 37 8,428* 55 N 81 58 103 70 P 12 41 30 83 K 125 89 33 22 Zn 0.13 47 0.15 53 S 5.5 51 7.5 58 Mg 5.8 34 10.8 57 Ca 9.90 61 0.23 1 Mn 0.21 88 0.03 12 Cl 13.1 58 4.5 19 Cu 0.03 59 0.02 21 ______________________________________________________ *Irrigated corn population of 30,000 plants/A. Data averaged across six hybrids and with three replications. Average yield of 178 bu/A at 15.5% moisture. spatial resolution and can be integrated with material delivery systems to facilitate real-time applications. Remote sensing. The problem with remote sensing tools is that they rely on natural radiation to generate the reflectance that is then measured by a sensor and interpreted by a human. As such, light intensity, viewing angle, time of day, shadows, atmospheric interference, crop growth stage, and weather conditions are all factors that must be considered. In the mid-'80s, technologies were introduced to provide auxiliary light and thereby extend the useful period of operation for specialized applications such as weed detection and spot spraying. In the early '90s, the concept of using modulated or pulsed auxiliary light was introduced to differentiate between reflectance attributed to natural radiation and that coming from auxiliary light. Improvements in these technologies have led to the products such as the Patchen weed sprayer system and the GreenSeeker developed to make site-specific N applications to wheat. In some cases, remote sensing or other techniques might be useful to estimate the optimum yield and related spatial variability. The use of remote sensing for monitoring some specific types of crop stresses is currently not possible with existing technologies. Even the most sophisticated sampling or imaging techniques available today are unable to accomplish the spatial integration of colors and patterns that humans can accomplish in a fraction of a second. We believe these limitations will be overcome as technologies advance, though it still will require the human touch to make instantaneous sense of any patterns within leaves. Put Early Spring 2003
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