Proceedings
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| Filter results7 paper(s) found. |
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1. Deriving Nitrogen Indicators of Maize Using the Canopy Chlorophyll Content IndexMany spectral indices have been proposed to derive aerial nitrogen (N) status parameters of crops in recent decades. However, most of red light based spectral indices easily loss sensitivity at moderate-high aboveground biomass. The objective of present study is to assess the performance of red edge based... Y. Miao, F. Li |
2. Different Leaf Sensing Approaches for the Estimation of Winter Wheat Nitrogen StatusNondestructive real time diagnosis of crop N status is crucial to the development of precision nitrogen (N) management strategies. Chlorophyll meter has been a popular sensor for such purposes and different approaches to use this sensor has been developed using a threshold value, nitrogen sufficiency index (NSI) or ratio of... B. Liu, Y. Miao, G. Feng, S. Yue, F. Li, X. Gao |
3. Near Real-time Meter-resolution Airborne Imagery For Precision Agriculture: AerocamPrecision agriculture often relies on high resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require meter-solution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration... X. Zhang, C.R. Streeter, H. Kim, D.R. Olsen |
4. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen |
5. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China PlainThe sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu |
6. Computer Vision by UAVs for Estimate Soybean Population Across Different Physiological Growth Stages and Sowing SpeedsSoybean (Glycine max (Linnaeus) Merrill) production in the United States plays a crucial role in agriculture, occupying a considerable amount of cultivated land. However, the costs associated with soybean production have shown a notable increase in recent years, with seed-related expenses accounting for a significant proportion of the total. This increase in costs is attributed to a number of factors, including the introduction of patented and protected genetic traits, as well as inflationary... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. Deri setiyono, S. campos |
7. Optimizing Soybean Management with UAV RGB and Multispectral Imagery: a Neural Network Method and Image ProcessingPrecision agriculture (PA) has emerged as a fundamental approach in contemporary agricultural management, aimed at maximizing efficiency in the use of resources and improving crop productivity. The transition to so-called "agriculture 4.0" represents a revolution in the way technology is applied in the field, with an emphasis on digital and automated solutions such as UAVs (Unmanned Aerial Vehicles). These devices offer new capabilities for capturing high-resolution images, enabling... F. Pereira de souza, L. Shiratsuchi, H. Tao, M. Acconcia dias, M. Barbosa, T. deri setiyono, S. Campos |