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Ruiz Diaz, D
Almeida, S.L
Rohlmann, L
Rund, Q
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Authors
Rund, Q
Williams, R
Rund, Q
Murrell, S
Erbe, A
Williams, R
Williams, E
Rossi, C
Almeida, S.L
Sysskind, M.N
Moreno, L.A
Felipe dos Santos, A
Lacerda, L
Vellidis, G
Pilcon, C
Orlando Costa Barboza, T
Roa Acosta, G
Ruiz Diaz, D
Grahmann, K
Rohlmann, L
Thielemann, L
Roy, A
Weltzien, C
Topics
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Big Data Mining & Statistical Issues in Precision Agriculture
Artificial Intelligence (AI) in Agriculture
Site-Specific Nutrient, Lime and Seed Management
Agricultural Robotics, Automation, and Mechanization
Type
Oral
Poster
Year
2010
2016
2024
2026
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Filter results5 paper(s) found.

1. Nugis: The Development Of A Nutrient Use Geographic Information System

NuGIS is a project of the International Plant Nutrition Institute (IPNI). The goal was to examine sources of nutrients (fertilizers and manure) and compare this to crop removal. The project used GIS and database analysis to create maps at the state and county level and then used GIS to migrate the budget analysis to the local watershed and regional watershed levels. This paper will cover the sources of data used, how the data was processed to generate county level numbers, and how GIS was used... Q. Rund, R. Williams

2. North American Soil Test Summary

With the assistance and cooperation of numerous private and public soil testing laboratories, the International Plant Nutrition Institute (IPNI) periodically summarizes soil test levels in North America (NA). Soil tests indicate the relative capacity of soil to provide nutrients to plants. Therefore, this summary can be viewed as an indicator of the nutrient supplying capacity or fertility of soils in NA. This is the eleventh summary completed by IPNI or its predecessor, the Potash &... Q. Rund, S. Murrell, A. Erbe, R. Williams, E. Williams

3. Combining Remote Sensing and Machine Learning to Estimate Peanut Photosynthetic Parameters

The environmental conditions in which plants are situated lead to changes in their photosynthetic rate. This alteration can be visualized by pigments (Chlorophyll and Carotenoids), causing changes in plant reflectance. The goal of this study was to evaluate the performance of different Machine Learning (ML) algorithms in estimating fluorescence and foliar pigments in irrigated and rainfed peanut production fields. The experiment was conducted in the southeast of Georgia in the United States in... C. Rossi, S.L. Almeida, M.N. Sysskind, L.A. Moreno, A. Felipe Dos Santos, L. Lacerda, G. Vellidis, C. Pilcon, T. Orlando Costa Barboza

4. Enhancing Phosphorus Nutrient Management in Corn Through Tissue Analysis and Diagnostic Tools

Phosphorus (P) plays a pivotal role in crop growth, and optimizing its application is crucial for sustainable agriculture. This research focuses on advancing nutrient management by precisely evaluating tissue phosphorus concentrations in corn. The study delves into identifying critical P levels during various growth stages, assessing alternative diagnostic tools, and exploring correlations to refine phosphorus nutrition strategies. Across 26 locations in Kansas, field experiments employed a randomized... G. Roa Acosta, D. Ruiz Diaz

5. Results from a Scoping Review: the Role of Autonomous Mechanical Weeding Robots in Climate-smart Soil Management

The growing demand for sustainable agricultural practices has driven advancements in digital agricultural technologies, which is also reflected in the emerging development and market release of agricultural field robots in the last decade. Climate-smart sustainable soil management plays a key role in sustaining soil functions related to productivity, water and nutrient cycling, biodiversity and long-term resilience. The integration of autonomous field robots, for which mechanical weeding is currently... K. Grahmann, L. Rohlmann, L. Thielemann, A. Roy, C. Weltzien