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Setiyono, T
Monfort, W.S
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Authors
Rothrock, C.S
Monfort, W.S
Griffin, T.W
Spurlock, T.N
Barbosa, M
Duron, D
Rontani, F
Bortolon, G
Moreira, B
Oliveira, L
Setiyono, T
Shiratsuchi, L
Silva, R.P
Holland, K.H
Topics
Precision Crop Protection
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2014
2024
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1. Disease Scouting For Aerial Blight Based On Logical Areas Of Collection In Soybean Fields Rotated With Rice

Rhizoctonia solani AG1-IA causes sheath blight in rice and aerial blight in soybean.  In Arkansas, rice and soybean rotations facilitate a continuous source of R. solani AG1-IA inoculum from one year to the next.    Aerial blight is a two stage disease where colonization of the plant occurs during the early vegetative growth stages and aerial blight symptoms occur during the reproductive growth stages after canopy closure.  At canopy closure,... C.S. Rothrock, W.S. Monfort, T.W. Griffin, T.N. Spurlock

2. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland