Showing results for: canopy sensing Articles
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Optimization of crop canopy sensor placement for measuring nitrogen status in corn
Active canopy sensors can be used to assess corn (Zea mays L.) N status and direct spatially-variable in-season N application. The goal of this study was to determine optimal sensor spacing for controlling whole- and/or split-boom N application scenarios for a hypothetical 24-row applicator. Sensor readings were collected from 24 consecutive rows at eight cornfields during vegetative growth in ...
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Spatial analysis of early wheat canopy normalized difference vegetative index
Efficient use of real-time canopy sensors requires knowledge of the scale (resolution) of variation in the measured canopy property. Knowing the amount of needed optical data requires estimation of the optimal combination of physical sensor density (number of sensors along the applicator boom) and sensor output density (sensor readings per unit distance along the travel path). The objective of ...
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Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization
Nitrogen available to support corn (Zea mays L.) production can be highly variable within fields. Canopy reflectance sensing for assessing crop N health has been proposed as a technology to base side-dress variable-rate N application. Objectives of this research were to evaluate the use of active-light crop-canopy reflectance sensors for assessing corn N need, and derive the N fertilizer rate ...
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Will variable-rate nitrogen fertilization using corn canopy reflectance sensing deliver environmental benefits?
Within-field variability of corn (Zea mays L.) N need calls for development of precision fertilizer application strategies. One approach many are investigating is in-season canopy reflectance sensing. Justification for this strategy partly rests with the premise it will improve N use and reduce N loss from fields. The objective of this study was to determine the potential environmental benefits ...
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Spatial analysis of early wheat canopy normalized difference vegetative index: determining appropriate observation scale
Efficient use of real-time canopy sensors requires knowledge of the scale (resolution) of variation in the measured canopy property. Knowing the amount of needed optical data requires estimation of the optimal combination of physical sensor density (number of sensors along the applicator boom) and sensor output density (sensor readings per unit distance along the travel path). The objective of ...
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Evaluating multiple indices from a canopy reflectance sensor to estimate corn n requirements
With the increasing cost of fertilizer N, there is a renewed emphasis on developing new technologies for quantifying in-season N requirements for corn (Zea mays L.). The objectives of this research are (i) to evaluate different vegetative indices derived from an active reflectance sensor in estimating in-season N requirements for corn, and (ii) to consider the influence of the N:Corn price ratio ...
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What lies beneath: with technology becoming more affordable and accessible, growers are embracing its precision-farming power to improve soil health.
Healthy soil makes for optimal crops and today, there are seemingly countless ways to monitor and test soil health, from physical samples to sap flow and moisture monitoring, aerial imagery, and beyond. Here are some of the most recent developments, as well as how technologies are being used in the field. Fruition Sciences Precision agriculture company Fruition Sciences takes data measurements ...
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How to grow more food with less water
Scientists and farmers collaborate on a quest for more efficient irrigation This story was co-published with Civil Eats, a daily news source for critical thought about the American food system. From reading the weather to choosing a crop, farming has always been a hands-on enterprise. When a farmer wonders how much water a crop needs, a simple test has always sufficed: Grab a handful of soil ...
By Ensia
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