Computerised decision support systems: Aids to rational and sustainable weed management

1996 ◽  
Vol 76 (1) ◽  
pp. 3-7 ◽  
Author(s):  
John T. O'Donovan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Weed Management ◽  
Support Systems ◽  
The United States ◽  
Fertilizer Application ◽  
Weed Species ◽  
Relative Time ◽  
Weed Density ◽  
Crop Density

Computerised decision support systems offer an ideal means of achieving economical, environmentally safe, and sustainable weed management. Systems based on weed economic threshold concepts have been developed in the United States and Europe. In several of these, weed density is the sole variable used for estimating crop yield losses due to weeds. In Canada, there have been few attempts to develop computerised decision support systems to facilitate rational weed management. A notable exception is a microcomputer program developed by the Manitoba Department of Agriculture for assessing the economics of wild oat (Avena fatua L.) control in cereal and oilseed crops. A relative time of emergence variable is a crucial component of the program There is a need to develop a more comprehensive system for managing multiple weed species in a range of crops grown in Canada. For reliable recommendations to be made, input requirements for the system should include information on the relative time of emergence of the crop and weed, crop density, environmental factors and method of fertilizer application, as well as weed density. In terms of output, the system should indicate realistic weed monitoring procedures, and the long-term bioeconomic implications of seed production by uncontrolled weeds. Key words: Bioeconomic models, weed economic thresholds, decision support systems, rational weed management

scholarly journals Benefits and Limitations of Decision Support Systems (DSS) with a Special Emphasis on Weeds

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 548 ◽  
Author(s):  
Panagiotis Kanatas ◽  
Ilias S. Travlos ◽  
Ioannis Gazoulis ◽  
Alexandros Tataridas ◽  
Anastasia Tsekoura ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Weed Management ◽  
Crop Production ◽  
Support Systems ◽  
Management Strategies ◽  
Farming Systems ◽  
Climatic Conditions ◽  
Management Options ◽  
The Right

Decision support systems (DSS) have the potential to support farmers to make the right decisions in weed management. DSSs can select the appropriate herbicides for a given field and suggest the minimum dose rates for an herbicide application that can result in optimum weed control. Given that the adoption of DSSs may lead to decreased herbicide inputs in crop production, their potential for creating eco-friendly and profitable weed management strategies is obvious and desirable for the re-designing of farming systems on a more sustainable basis. Nevertheless, it is difficult to stimulate farmers to use DSSs as it has been noticed that farmers have different expectations of decision-making tools depending on their farming styles and usual practices. The function of DSSs requires accurate assessments of weeds within a field as input data; however, capturing the data can be problematic. The development of future DSSs should target to enhance weed management tactics which are less reliant on herbicides. DSSs should also provide information regarding weed seedbank dynamics in the soil in order to suggest management options not only within a single period but also in a rotational view. More aspects ought to be taken into account and further research is needed in order to optimize the practical use of DSSs for supporting farmers regarding weed management issues in various crops and under various soil and climatic conditions.

scholarly journals Feasibility of using existing web services for on-demand data access within distributed environmental decision support systems

2017 ◽  
Vol 20 (2) ◽  
pp. 263-280
Author(s):  
Stuart F. Sheffield ◽  
Jonathan L. Goodall ◽  
Mohamed M. Morsy ◽  
Alexander B. Chen
Keyword(s):  
Decision Support ◽  
Web Services ◽  
Decision Support Systems ◽  
Support Systems ◽  
Response Times ◽  
Data Access ◽  
The United States ◽  
Environmental Data ◽  
Project Area ◽  
On Demand

Abstract Web services providing machine-accessible interfaces to environmental data are now commonplace. Building on this, a current trend is to expand these web services to provide on-demand access to model and analysis services. This progression suggests the future possibility of cloud-based decision support systems (DSSs) integrating distributed data and analysis services delivered through a host of providers. Such distributed environmental DSSs have many potential benefits, but would require highly scalable and responsive web services. The objective of this study is to assess the current feasibility of building distributed environmental DSSs from existing web services in the United States. Results show that, of the many available web services providing information about soils, river network topology, watersheds, streamflow, etc., response times are often only a few seconds for a small project area, but can grow exponentially as the project area increases. On-demand watershed delineation remains a slow-to-respond service relative to the other services tested. Also, the results suggest the need to better co-locate servers near client applications to speed up response times. Collectively, these results provide specific areas where future research is needed in order to achieve the vision of on-demand distributed environmental DSSs.

Historical Overview of Decision Support Systems (DSS)

2011 ◽  
pp. 1753-1758 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
United States Of America ◽  
Support Systems ◽  
The United States ◽  
Future Trends ◽  
Historical Overview ◽  
Essential Information ◽  
Organizational Perspective ◽  
The Subject

During the late 1970s the term “decision support systems” was first coined by P. G. W. Keen, a British Academic then working in the United States of America. In 1978, Keen and Scott Morton published a book entitled, Decision Support Systems: An Organizational Perspective (Keen & Scott Morton, 1978), wherein they defined the subject title as computer systems having an impact on decisions where computer and analytical aids can be of value but where the manager’s judgment is essential. Information systems (IS) researchers and technologists have developed and investigated decision support systems (DSS) for more than 35 years (Power, 2003b). The structure of this article is as follows: The background to DSS will be given. Some DSS definitions, a discussion of DSS evolution, development of the DSS field and frameworks are then presented. Some future trends for DSS are then suggested.

Weed Management in a Legume-Cereal Cover Crop with the Rotary Hoe

2006 ◽  
Vol 20 (3) ◽  
pp. 733-737 ◽  
Author(s):  
Nathan S. Boyd ◽  
Eric B. Brennan
Keyword(s):  
Weed Management ◽  
Cover Crop ◽  
Weather Conditions ◽  
Weed Species ◽  
Common Vetch ◽  
Weed Biomass ◽  
Weed Density ◽  
Crop Density ◽  
Before And After ◽  
Density And Biomass

Substantial weed growth often occurs in legume-cereal cover-crop mixes commonly grown on organic vegetable farms. A 2-yr study at the USDA-ARS in Salinas, CA, was conducted to test the effect of zero, one, and two passes with a rotary hoe on weed control in a mixed cover crop of 10% rye, 15% common vetch, 15% purple vetch, 25% peas, and 35% bell bean. Rotary hoeing occurred 14–15 days after planting (DAP) in the one-pass treatment, and 14 and 28 DAP in the two-pass treatment. Rotary hoeing did not affect total cover-crop density or biomass in either year, but reduced rye density and biomass in year 2. One pass reduced total weed density by 69% in year 1 and 49% in year 2. A second pass did not affect weed density in year 1 but reduced weed density an additional 33% in year 2. One pass decreased weed biomass in year 1, whereas two passes were required to reduce weed biomass in year 2. Rotary hoeing reduced seed shed by chickweed and shepherd's-purse seeds, the two predominant weed species, by 80 to 95% in both years. Rotary hoe efficacy depended on weather conditions directly before and after cultivation. The decision to repeat rotary hoeing should be based upon field scouting and weather conditions following the initial pass with the rotary hoe.

scholarly journals An interactive online database for the selection of woody ornamental plants

2003 ◽  
Vol 13 (3) ◽  
pp. 562-568
Author(s):  
Jonathan M. Lehrer ◽  
Mark H. Brand
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Survey Data ◽  
Web Site ◽  
Support Systems ◽  
Ornamental Plants ◽  
The United States ◽  
Online Questionnaire ◽  
Woody Ornamental ◽  
Strongly Agree

Web sites such as the University of Connecticut (UConn) Plant Database allow large volumes of information and images to be stored, published and accessed by users for the purpose of informed decision-making. Sorting information on the World Wide Web (Web) can be difficult, especially for novice users and those interested in quick results. The advent of Internet search and retrieval software fosters the creation of interactive decision support systems. The Plant Selector was designed to complement the UConn Plant Database plant encyclopedia by allowing Web site users to generate lists of woody ornamental plants that match specific criteria. On completion of an HTML-based search form by users, a Web-enabled database is searched and lists of matching plants are presented for review. To facilitate analysis of the Plant Selector's efficacy, an online questionnaire was implemented to solicit user feedback. Survey data from 426 responses to the online evaluation tool were analyzed both to understand user demographics and gauge satisfaction with the Plant Selector module. Survey data revealed that most Plant Selector users are between 40 to 65 years of age and homeowners with minimal horticultural experience. A large percentage of Web site visitors (68%) is located across the United States beyond Connecticut and the New England region. The great majority of survey respondents (65%) use this tool to select plants for the home landscape. Most (77%) either agree or strongly agree that the Plant Selector is easy to use and delivers results that are useful (66%), while 70% agree or strongly agree that the categories used by the Plant Selector are sufficient. The survey results in general suggest that Web-based decision support systems may serve useful roles in the field of horticulture education.

scholarly journals The Human Dimensions of Spatial, Pre-Wildfire Planning Decision Support Systems: A Review of Barriers, Facilitators, and Recommendations

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 483
Author(s):  
Melanie Colavito
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
The United States ◽  
Human Dimensions ◽  
Wildfire Risk ◽  
Forest Fuels ◽  
Fuels Treatment ◽  
Wildfire Planning

Decision support systems (DSSs) are increasingly common in forest and wildfire planning and management in the United States. Recent policy direction and frameworks call for collaborative assessment of wildfire risk to inform fuels treatment prioritization using the best available science. There are numerous DSSs applicable to forest and wildfire planning, which can support timely and relevant information for decision making, but the use and adoption of these systems is inconsistent. There is a need to elucidate the use of DSSs, specifically those that support pre-wildfire, spatial planning, such as wildfire risk assessment and forest fuels treatment prioritization. It is important to understand what DSSs are in use, barriers and facilitators to their use, and recommendations for improving their use. Semi-structured interviews with key informants were used to assess these questions. Respondents identified numerous barriers, as well as recommendations for improving DSS development and integration, specifically with respect to capacity, communication, implementation, question identification, testing, education and training, and policy, guidance, and authorities. These recommendations can inform DSS use for wildfire risk assessment and treatment prioritization to meet the goals of national policies and frameworks. Lastly, a framework for organizing spatial, pre-wildfire planning DSSs to support end-user understanding and use is provided.

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