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Bauer, P.J
Engle, J
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Authors
Bauer, P.J
Stone, K.C
Bussher, W.J
Millen, J.A
Evans, D.E
Strickland, E.E
Waltz, L
Khanal, S
Katari, S
Hong, C
Anup, A
Colbert, J
Potlapally, A
Dill, T
Porter, C
Engle, J
Stewart, C
Subramoni, H
Machiraju, R
Ortez, O
Lindsey, L
Nandi, A
Topics
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2008
2024
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1. Site-specific Irrigation of Peanuts on a Coastal Plain Field

Irrigator-Pro is an expert system that prescribes irrigation for corn (Zea mays L.), cotton (Gossypium hirsutum L.) and peanut (Arachis hypogaea). We conducted an experiment in 2007 to evaluate Irrigator-Pro as a tool for variable rate irrigation of peanut using a site-specific center pivot irrigation system. Treatments were irrigation of whole plots based on the expert system, irrigation of individual soils within plots based on the expert system, irrigation of individual...

2. Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision

Advancements in machine learning algorithms and GPU computational speeds over the last decade have led to remarkable progress in the capabilities of machine learning. This progress has been so much that, in many domains, including agriculture, access to sufficiently diverse and high-quality datasets has become a limiting factor.  While many agricultural use cases appear feasible with current compute resources and machine learning algorithms, the lack of software infrastructure for collecting,... L. Waltz, S. Khanal, S. Katari, C. Hong, A. Anup, J. Colbert, A. Potlapally, T. Dill, C. Porter, J. Engle, C. Stewart, H. Subramoni, R. Machiraju, O. Ortez, L. Lindsey, A. Nandi