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Hammond, J
Sullivan, D.G
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Authors
Ortiz, B
Perry, C
Sullivan, D.G
Kemerait, R.C
Davis, R.F
Lu, P
Smith, A
Karampoiki, M
Todman, L
Mahmood, S
Murdoch, A
Paraforos, D
Hammond, J
Ranieri, E
Topics
Precision Conservation
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2010
2022
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Filter results2 paper(s) found.

1. Variable Rate Application Of Nematicides On Cotton Fields: A Promising Site-specific Management Strategy

  The impact of two nematicides [ 1,3 – Dichloropropene (Telone® II) and Aldicarb (Temik)] applied at two rates on RKN population density and cotton (Gossypium hirsutum L.) lint yield were compared across previously determined RKN management zones (MZ) in commercial fields between 2007 and 2009. The MZ were delineated using fuzzy clustering of various surrogate data for soil texture. All treatments were randomly allocated among... B. Ortiz, C. Perry, D.G. Sullivan, R.C. Kemerait, R.F. Davis, P. Lu, A. Smith

2. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri