Proceedings

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Dota, M.A
Chien, L
Phillips, L
Lukach, J
Corassa, G
Bareth, G
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Authors
cugnasca, C.E
Dota, M.A
Yao, Y
Miao, Y
Huang, S
Gnyp, M.L
Khosla, R
Jiang, R
Bareth, G
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Yao, Y
Miao, Y
Huang, S
Gnyp, M.L
Jiang, R
Chen, X
Bareth, G
Phillips, L
Gnyp, M.L
Panitzki, M
Reusch, S
Jasper, J
Bolten, A
Bareth, G
Huang, S
Miao, Y
Yuan, F
Gnyp, M.L
Yao, Y
Cao, Q
Lenz-Wiedemann, V
Bareth, G
Bareth, G
Jenal, A
Hüging, H
Carcedo, A
Antunes de Almeida, L.F
Horbe, T
Corassa, G
Pott, L.P
Ciampitti, I
Hintz, G.D
Hefley, T
Schwalbert, R.A
Prasad, V
Chien, L
Topics
Engineering Technologies and Advances
Sensor Application in Managing In-season Crop Variability
Precision A-Z for Practitioners
Sensor Application in Managing In-season Crop Variability
eXtension: Precision Agriculture on the Internet
Remote Sensing Applications in Precision Agriculture
Applications of Unmanned Aerial Systems
Weather and Models for Precision Agriculture
Type
Poster
Oral
Year
2012
2010
2016
2022
2024
2025
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1. Assessing Soybean Water Stress Patterns and ENSO Occurrence in Southern Brazil: an in Silico Approach

Water stress (WS) is one of the most important abiotic stresses worldwide, responsible for crop yield penalties and impacting food supply. The frequency and intensity of weather stresses are relevant to delimitating agricultural regions. In addition, El Nino Southern Oscillation (ENSO) has been employed to forecast the occurrence of seasonal WS. Lastly, planting date and cultivar maturity selection are key management strategies for boosting soybean (Glycine max (L.) Merr.) yield... A. Carcedo, L.F. Antunes De Almeida, T. Horbe, G. Corassa, L.P. Pott, I. Ciampitti, G.D. Hintz, T. Hefley, R.A. Schwalbert, V. Prasad