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Souza, I.R
Reyes Gonzalez, J
Gardezi, M
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Authors
Mostaço, G.M
Campos, L.B
Cugnasca, C.E
Souza, I.R
Capolicchio, J
Mennuti, D
Milani, I
Fortunato, M
Petix, R
Reyes Gonzalez, J
Sunkevic, M
Kumari, S
Rathore, J
Mitra, S
Gardezi, M
Walsh, O
Gardezi, M
Walsh, O
Joshi, D
Kumari, S
Clay, D.E
Rathore, J
Topics
Decision Support Systems
Precision Agriculture and Global Food Security
Site-Specific Nutrient, Lime and Seed Management
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2018
2022
2024
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1. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor Networks

Mobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is talking... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza

2. Agriculture Machine Guidance Systems: Performance Analysis of Professional GNSS Receivers

GNSS (Global Navigation Satellite Systems) plays nowadays a major role in different civilian activities and is a key technology enabling innovation in different market sectors. For instance, GNSS-enabled solutions are widespread within the Precision Agriculture and, among them, applications in the field of machinery guidance are commonly employed to optimize typical agriculture practices. The scope of this paper is to present the outcomes of the agriculture testing campaign performed,... J. Capolicchio, D. Mennuti, I. Milani, M. Fortunato, R. Petix, J. Reyes gonzalez, M. Sunkevic

3. Predicting Soybean Yield Using Remote Sensing and a Machine Learning Model

Soybean (Glycine max L.), a nutrient-rich legume crop, is an important resource for both livestock feed and human dietary needs. Accurate preharvest yield prediction of soybeans can help optimize harvesting strategies, enhance profitability, and improve sustainability. Soybean yield estimation is inherently complex because yield is influenced by many factors including growth patterns, varying crop physiological traits, soil properties, within-field variability, and weather conditions. The objective... M. Gardezi, O. Walsh, D. Joshi, S. Kumari, D.E. Clay, J. Rathore

4. Optimizing Soil Nutrient Management: Agricultural Policy/environmental Extender (APEX) Model Simulation for Field Scale Phosphorous Loss Reduction in Virginia

Managing soil nutrients is crucial for enhancing crop productivity and meeting consumptions demands while minimizing environmental impacts. Sustainable agriculture relies on well-planned soil nutrient management strategies. Phosphorous (P) stands out among the 16 essential soil nutrients, particularly in Virginia, where natural P levels are typically low. Adequate amount of P is necessary for the early root formation and plant growth. However, excess amount of P in the soil leads to increase the... S. Kumari, J. Rathore, S. Mitra, M. Gardezi, O. Walsh