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Smith, A.P
Liu, J
Siqueira, R.D
Lacroix, R
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Authors
Dong, T
Shang, J
Meng, J
Liu, J
Cheng, Z
Meng, J
Shang, J
Liu, J
Qian, B
Jing, Q
Shinde, S
Adamchuk, V
Lacroix, R
Tremblay, N
Bouroubi, Y
Mandal, D
Siqueira, R.D
Longchamps, L
Khosla, R
Straw, C
Wyatt, B
Smith, A.P
Watkins, K
Hong, S
Floyd, W
Williams, D
Garza, C
Jansky, T
Topics
Remote Sensing Applications in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Type
Oral
Poster
Year
2014
2018
2022
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Filter results5 paper(s) found.

1. An Evaluation Of HJ-CCD Broadband Vegtation Indices For Leaf Chlorophyll Content Estimation

Leaf chlorophyll content is one of the most important biochemical variables for crop physiological status assessment, crop biomass estimation and crop yield prediction in precision agriculture. Vegetation indices were considered effective for chlorophyll content estimation. Although hyperspectral reflectance is proven to be better than multispectral reflectance for leaf chlorophyll content retrieval, the scarcity of available data from satellite hyperspectral... T. Dong, J. Shang, J. Meng, J. Liu

2. Developing an Integrated Approach for Estimation of Soil Available Nutrient Content Using the Modified WOFOST Model and Time-Series Multispectral UAV Observations

Soil available nutrient (SAN) plays an important role in crop growth, yield formation, and plant-soil-atmosphere system exchange. Nitrogen (N), phosphorus (P) and potassium (K) are recognized as three primary nutrients in crop production. Accurate and timely information on SAN conditions at key crop growth stages is important for developing beneficial management practices. While traditional field sampling can obtain reliable information for limited number of sites, it is infeasible for spatially... Z. Cheng, J. Meng, J. Shang, J. Liu, B. Qian, Q. Jing

3. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. This... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

4. Machine Learning Techniques for Early Identification of Nitrogen Variability in Maize

Characterizing and managing nutrient variability has been the focus of precision agriculture research for decades. Previous research has indicated that in-situ fluorescence sensor measurements can be used as a proxy for nitrogen (N) status in plants in greenhouse conditions employing static sensor measurements. Indeed, practitioners of precision N management require determination of in-season plant N status in real-time at field scale to enable the most efficient N fertilizer... D. Mandal, R.D. Siqueira, L. Longchamps, R. Khosla

5. Investigating Spatial Relationship of Apparent Electrical Conductivity with Turfgrass and Soil Characteristics in Sand-capped Golf Course Fairways

Turfgrass quality decreases when grown on fine textured soils that are irrigated with poor quality water. As a result, sand-capping (i.e., a sand layer above existing native soil) is now considered during golf course fairway renovation and construction. Mapping spatial variability of soil apparent electrical conductivity (ECa) has recently been suggested to have applications for precision turfgrass management (PTM) in native soil fairways, but sand-capped fairways have received less... C. Straw, B. Wyatt, A.P. Smith, K. Watkins, S. Hong, W. Floyd, D. Williams, C. Garza, T. Jansky