![Theses and Dissertations](../../assets/md5images/007ba8c2f9f7b20b26ed4b229bc29542.jpg)
Theses and Dissertations
ORCID
https://orcid.org/0009-0006-9184-9596
Issuing Body
Mississippi State University
Advisor
Lowe, J. Wesley
Committee Member
Chesser, G. Daniel
Committee Member
Pieralisi, Brian K.
Date of Degree
5-12-2023
Document Type
Graduate Thesis - Open Access
Major
Agriculture
Degree Name
Master of Science (M.S.)
College
College of Agriculture and Life Sciences
Department
Department of Agricultural and Biological Engineering
Abstract
Weed control is an integral part of a successful overall production strategy in row- cropping systems and has the potential to reduce or eliminate yield losses that negatively affect profitability. Timely and correctly selected herbicide applications are the major keys for effective weed control in a majority of instances. However, there are negative factors that contribute to ineffectiveness and weed escape issues that currently lack viable options for management. Sparsely populated late-season weeds that emerge after lay-by herbicide applications and weeds that have become tolerant and resistant to traditional herbicide chemistries are of greatest concern. Historically, these weeds would have been pulled or chopped by hand or removed by cultivation, but with current production strategies built around conservation tillage and herbicide management practices, blanket disturbance of the soil through plowing is not a viable option. There is an immediate need for site-specific weed management to address these weed escapes while minimizing soil disturbance that reduces residual herbicide efficacy and lessens moisture losses that negatively effects the growing crop
Sponsorship
Cotton Incorporated
Recommended Citation
Friday, Grace McCormick, "Development and evaluation of an automated tactical tillage tool to control weeds in row-crop production systems" (2023). Theses and Dissertations. 5745.
https://scholarsjunction.msstate.edu/td/5745
Included in
Agricultural Science Commons, Agriculture Commons, Agronomy and Crop Sciences Commons, Artificial Intelligence and Robotics Commons, Soil Science Commons, Sustainability Commons, Weed Science Commons