TY - JOUR
T1 - Modeling the decision process for barley yellow dwarf management
AU - Walls, Joseph T.
AU - Caciagli, Piero
AU - Tooker, John F.
AU - Russo, Joseph M.
AU - Rajotte, Edwin G.
AU - Rosa, Cristina
N1 - Publisher Copyright:
© 2016
PY - 2016/9/1
Y1 - 2016/9/1
N2 - Since the 1980s, expert decision support systems (DSSs) have been explored for enhancement of agricultural decision-making. Combinations of expert DSSs and cyber-age technology, such as mobile devices, is increasing adoption and accuracy of these systems and will allow DSSs to be easily modified to incorporate new information and web-based resources as they become available. Using barley yellow dwarf (BYD), a disease complex caused by several aphid-vectored viruses, as a model system we created a DSS for winter wheat growers based on dependency networks. At key points throughout the growing season the networks interpret how field conditions may affect management recommendations for BYD in winter wheat. To address nine possible management recommendations the networks analyze 72,387 combinations of input field conditions. This method of decision modeling can potentially be used to provide support to enable the efficient management of other crop pests and diseases and enable a more sustainable agroecosystem. The DSS was created for use in a mobile device app which will produce real-time recommendations, emulating disease management experts. Coupling this expert DSS with high resolution weather, pest, and disease forecasts will prove to be a powerful management tool in the future.
AB - Since the 1980s, expert decision support systems (DSSs) have been explored for enhancement of agricultural decision-making. Combinations of expert DSSs and cyber-age technology, such as mobile devices, is increasing adoption and accuracy of these systems and will allow DSSs to be easily modified to incorporate new information and web-based resources as they become available. Using barley yellow dwarf (BYD), a disease complex caused by several aphid-vectored viruses, as a model system we created a DSS for winter wheat growers based on dependency networks. At key points throughout the growing season the networks interpret how field conditions may affect management recommendations for BYD in winter wheat. To address nine possible management recommendations the networks analyze 72,387 combinations of input field conditions. This method of decision modeling can potentially be used to provide support to enable the efficient management of other crop pests and diseases and enable a more sustainable agroecosystem. The DSS was created for use in a mobile device app which will produce real-time recommendations, emulating disease management experts. Coupling this expert DSS with high resolution weather, pest, and disease forecasts will prove to be a powerful management tool in the future.
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U2 - 10.1016/j.compag.2016.08.005
DO - 10.1016/j.compag.2016.08.005
M3 - Article
AN - SCOPUS:84983084776
SN - 0168-1699
VL - 127
SP - 775
EP - 786
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
ER -