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Czarnecki, J
Campos, S
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Authors
Czarnecki, J
Brooks, J.P
Reeks, M.C
Hu, J
Muller, I
Czarnecki, J
Li, M
Smith, B.K
Pereira de Souza, F
Shiratsuchi, L
tao, H
Acconcia Dias, M
Barbosa, M
Deri Setiyono, T
Campos, S
Topics
Land Improvement and Conservation Practices
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Artificial Intelligence (AI) in Agriculture
Type
Poster
Year
2024
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1. Spatial and Temporal Variability of Soil Biological and Chemical Parameters Following the Introduction of Cover Crops into a Conventional Corn-cotton Rotational System

Methods to characterize soil microbial diversity and abundance are labor intensive and require destructive sampling that incurs a per unit cost. There are advantages to replacing current methods with remote sensing approaches; the most obvious of which is spatially explicit representation of microbes on agricultural landscapes. Such a method will ultimately address open questions related to (1) the spatial scale of variability in soil microbial activity, and (2) the behavior of microbes in cover... J. Czarnecki, J.P. Brooks, M.C. Reeks, J. Hu

2. Predicting Soil Cation Exchange Capacity from Satellite Imagery Using Random Forest Models

Crop yield variability is often attributed to spatial variation in soil properties. Remote sensing offers a practical approach to capture soil surface properties over large areas, enabling the development of detailed soil maps. This study aimed to predict cation exchange capacity (CEC), a key indicator of soil quality, in the agricultural fields of the Lower Mississippi Alluvial Valley using digital soil mapping techniques. A total of 15,586 soil samples were collected from agricultural fields... I. Muller, J. Czarnecki, M. Li, B.K. Smith

3. Optimizing Soybean Management with UAV RGB and Multispectral Imagery: a Neural Network Method and Image Processing

Precision 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