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Clark, J.J
Melnitchouck, A
Fiorentino, C
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Authors
Basso, B
Fiorentino, C
Cammarano, D
D'Errico, A
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
Hoffmann Silva Karp, F
Adamchuk, V
Melnitchouck, A
Dutilleul, P
Hoffmann Silva Karp, F
Adamchuk, V
Dutilleul, P
Melnitchouck, A
Biswas, A
Topics
Remote Sensing Applications in Precision Agriculture
Robotics, Guidance and Automation
Geospatial Data
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2018
2022
2024
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1. Understanding Spatial and Temporal Variability of Wheat Yield: An Integrated System Approach

Spatial variation in soil water and nitrogen are often the causes of crop yield spatial variability due to their influence on the uniformity of plant stand at emergence and for in-season stresses. Natural and acquired variability in production capacity or potential within a field causes uniform agronomic management practices for the field to be correct in some parts and inappropriate in others. To achieve... B. Basso, C. Fiorentino, D. Cammarano, A. D'errico

2. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

3. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processing... F. Hoffmann silva karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

4. Predicting Soil Chemical Properties Using Proximal Soil Sensing Technologies and Topography Data: a Case Study

Using proximal soil sensors (PSS) is widely recognized as a strategy to improve the quality of agricultural soil maps. Nevertheless, the signals captured by PSS are complex and usually relate to a combination of processes in the soil. Consequently, there is a need to explore further the interactions at the source of the information provided by PSS. The objectives of this study were to examine the relationship between proximal sensing techniques and soil properties and evaluate the feasibility... F. Hoffmann silva karp, V. Adamchuk, P. Dutilleul, A. Melnitchouck, A. Biswas