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HADSS, Pocket HERB, and WebHADSS: Decision Aids for Field Crops

Published online by Cambridge University Press:  20 January 2017

Andrew C. Bennett ,
Andrew J. Price ,
Michael C. Sturgill ,
Gregory S. Buol  and
Gail G. Wilkerson
Andrew C. Bennett
Affiliation:
Crop Science Department, North Carolina State University, Raleigh, NC 27695-7620
Andrew J. Price
Affiliation:
Crop Science Department, North Carolina State University, Raleigh, NC 27695-7620
Michael C. Sturgill
Affiliation:
Crop Science Department, North Carolina State University, Raleigh, NC 27695-7620
Gregory S. Buol
Affiliation:
Crop Science Department, North Carolina State University, Raleigh, NC 27695-7620
Gail G. Wilkerson*
Affiliation:
Crop Science Department, North Carolina State University, Raleigh, NC 27695-7620
*
Corresponding author's E-mail: [email protected]
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Abstract

Row crop weed management decisions can be complex due to the number of available herbicide treatment options, the multispecies nature of weed infestations within fields, and the effect of soil characteristics and soil-moisture conditions on herbicide efficacy. To assist weed managers in evaluating alternative strategies and tactics, three computer programs have been developed for corn, cotton, peanut, and soybean. The programs, called HADSS (Herbicide Application Decision Support System), Pocket HERB, and WebHADSS, utilize field-specific information to estimate yield loss that may occur if no control methods are used, to eliminate herbicide treatments that are inappropriate for the specified conditions, and to calculate expected yield loss after treatment and expected net return for each available herbicide treatment. Each program has a unique interactive interface that provides recommendations to three distinct kinds of usage: desktop usage (HADSS), internet usage (WebHADSS), and on-site usage (Pocket HERB). Using WeedEd, an editing program, cooperators in several southern U.S. states have created different versions of HADSS, WebHADSS, and Pocket HERB that are tailored to conditions and weed management systems in their locations.

Keywords

Corn, Zea mays L.cotton, Gossypium hirsutum L.peanut, Arachis hypogea L.soybean, Glycine max L.Bioeconomic modelscomputer decision aidsdecision support systemsweed managementHADSS, Herbicide Application Decision Support SystemPDS, postemergence-directedPOST, postemergencePPI, preplant-incorporatedPRE, preemergence
Type
Review
Information
Weed Technology , Volume 17 , Issue 2 , June 2003 , pp. 412 - 420
Copyright
Copyright © Weed Science Society of America 

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