Development of monitoring and decision-support systems for integrated pest management of forest defoliators in North America

1991 ◽  
Vol 39 ◽  
pp. 3-13 ◽  
Author(s):  
F.William Ravlin
2011 ◽  
Vol 101 (6) ◽  
pp. 640-643 ◽  
Author(s):  
David H. Gent ◽  
Erick De Wolf ◽  
Sarah J. Pethybridge

Rational management of plant diseases, both economically and environmentally, involves assessing risks and the costs associated with both correct and incorrect tactical management decisions to determine when control measures are warranted. Decision support systems can help to inform users of plant disease risk and thus assist in accurately targeting events critical for management. However, in many instances adoption of these systems for use in routine disease management has been perceived as slow. The under-utilization of some decision support systems is likely due to both technical and perception constraints that have not been addressed adequately during development and implementation phases. Growers' perceptions of risk and their aversion to these perceived risks can be reasons for the “slow” uptake of decision support systems and, more broadly, integrated pest management (IPM). Decision theory provides some tools that may assist in quantifying and incorporating subjective and/or measured probabilities of disease occurrence or crop loss into decision support systems. Incorporation of subjective probabilities into IPM recommendations may be one means to reduce grower uncertainty and improve trust of these systems because management recommendations could be explicitly informed by growers' perceptions of risk and economic utility. Ultimately though, we suggest that an appropriate measure of the value and impact of decision support systems is grower education that enables more skillful and informed management decisions independent of consultation of the support tool outputs.


2016 ◽  
Vol 37 (4) ◽  
Author(s):  
Niranjan Singh ◽  
Neha Gupta

Pests cause significant losses to crop production in India. Excessive and irrational use of chemicals for pest control not only degrades the environment but also affects the human health due to presence of pesticide residue. Integrated Pest Management (IPM) is such a technology, which combines multiple ecologically safer and economically sound pest control methods. IPM being knowledge intensive approach to crop protection emphasizes appropriate decision-making based on knowledge of interaction of the crop, pests, beneficial organisms that prey on pests and whole lot of other information. IPM practitioners or farmers require timely access to the relevant pest management information/knowledge and expertise. So the improved methods of Information and Communication Technology (ICT) such as Decision Support Systems (DSSs) greatly help the farmers in accessing the pest management information and expertise. DSSs are software tools that support decision-making activities. They collect, organize, integrate and analyze all types of information required for decision making and finally use the analysis to recommend the most appropriate action. Many DSSs have been developed for in the field of plant protection by various public and private organizations in the country which have been elaborated in this review.


1988 ◽  
Vol 64 (2) ◽  
pp. 132-135 ◽  
Author(s):  
J. M. Power

Effective forest pest management involves decision-making supported by useful information. The concept of Decision Support Systems is being actively pursued by the Forest Insect and Disease Survey (FIDS) of the Canadian Forestry Service to meet its information needs for analysis of forest pest conditions. The FIDSINFOBASE system was developed to provide FIDS units nationwide access to survey data. Geographic Information System capabilities are being integrated for capture and analysis of infestation maps. Possibilities exist for the integration of systems, data, and models among agencies for information standardization and exchange. Key words: information systems, forest pest management, insect and disease surveys.


1996 ◽  
Vol 35 (01) ◽  
pp. 1-4 ◽  
Author(s):  
F. T. de Dombal

AbstractThis paper deals with a major difficulty and potential limiting factor in present-day decision support - that of assigning precise value to an item (or group of items) of clinical information. Historical determinist descriptive thinking has been challenged by current concepts of uncertainty and probability, but neither view is adequate. Four equations are proposed outlining factors which affect the value of clinical information, which explain some previously puzzling observations concerning decision support. It is suggested that without accommodation of these concepts, computer-aided decision support cannot progress further, but if they can be accommodated in future programs, the implications may be profound.


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