KEYWORDS: Nitrogen, RGB color model, Cameras, Digital color imaging, Neurons, Reflectivity, Neural networks, Image segmentation, Data modeling, Sensors
The advancements in remote sensing in combination with sensor technology, both passive and active, enable growers to analyze an entire crop field, its local features and crop conditions. Nutrient deficiency, and in particular nitrogen deficiency, may cause substantial crop losses. This deficiency needs to be identified immediately. A faster the detection and correction, a lesser the damage to the crop yield. In the present work, an applicability of digital color imaging to monitor nitrogen uptake in crops is demonstrated. The measurements were performed in a carrot and wheat fields as well as in a greenhouse. The images of canopy were taken during the entire growing season by use a hand held digital color (RGB) camera together with plants collection for lab analysis. The nitrogen weight in plant leaves, kg/ha, was obtained by image processing and compared with the standard laboratory analysis. Applicability of digital color imaging to monitor N uptake in crops instead of laboratory test is successfully demonstrated. The availability of RGB image-based data for N uptake is faster, timely and less expensive than that of laboratory test and can be obtained by low-cost ground-based imaging devices, unmanned aerial vehicles (UAV) and satellites.
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