Developing decision support systems (DSS) for farm soil and crop management

Author(s):  
Matt Aitkenhead ◽  

This chapter provides a review of decision support systems (DSS) in agriculture and addresses several key questions about them. Why are they important, and why are they necessary for the future? What kind of systems currently exist? Different aspects of agricultural DSS design, implementation and operation are covered. These aspects include the fundamentally spatial consideration of DSSs, the need for and use of sensor technology within such systems, modelling and software components, system-operator interfaces, the potential (and current) use of DSSs for directly controlling agricultural management, and a discussion of what is needed to make DSSs more successful and widely-used in agriculture

Author(s):  
L. Lomovskykh ◽  
M. Ponomarova ◽  
L. Chip ◽  
E. Krivosheya ◽  
O. Lisova

Abstract. The analysis of the activity of agricultural enterprises indicated its inherent high degree of risk. Unlike other industries, a significant share of integrated risk for agriculture is weather risk. It is this risk that necessitates the diversification of agricultural marketing into three forms: with a deficit of the main commodity product of the agricultural enterprise in the market; with the balance of sales and supply and with the market surplus of marketable products. It is pointed out that in order to reduce the risk, a significant number of medium-sized producers rely on multi-product production and management has to simultaneously make use of all the intended forms of marketing. It has been established that the marketing activities of agricultural enterprises for a number of reasons: established tradition, lack of financial resources, etc. are often sporadic, fragmented, not a systematic, purposeful activity with defined goals, well considered tools, adequate funding and resources. Therefore, a number of specific steps have been proposed for the implementation of effective agribusiness: changing the traditional way of thinking; formation of a holistic systematic approach to marketing policy as a single coordinated complex of management and marketing; thorough study of the market of products manufactured by the agricultural enterprise, and the formation of the forecast for the next season. To strengthen marketing activities and conduct effective agribusiness, algorithms have been developed to gain a competitive advantage. It is shown that agricultural marketing today is becoming a broader field of activity than providing pure production and marketing using the main levers — price, product, sales and communication. It must best meet the needs and requirements of consumers, in particular, by shifting the main emphasis from price and sales aspects to communication. This is one of the main ways to ensure the function of agribusiness efficiency. It is proposed to use the experience of developed countries and more widely employ modern information technologies of management and marketing, in particular, decision support systems and analysis of risks and forecasts for the next period. The following ways are proposed for the use of modern decision support systems, risk analysis and forecasts in Ukrainian agricultural management and marketing: cooperation, use of these information systems on the basis of lease or, less relevant, expert risk assessment. A mathematical method of taking into account the degree of risk in the business processes of agricultural enterprises is proposed. Keywords: marketing, management, management, manager, agricultural management, agribusiness, information technology marketing. JEL Classification M11, M31, Q13 Formulas: 1; fig.: 3; tabl.: 0; bibl.: 22.


1996 ◽  
Vol 76 (1) ◽  
pp. 9-19 ◽  
Author(s):  
Y. W. Jame ◽  
H. W. Cutforth

Studies on crop production are traditionally carried out by using conventional experience-based agronomic research, in which crop production functions were derived from statistical analysis without referring to the underlying biological or physical principles involved. The weaknesses and disadvantages of this approach and the need for greater in-depth analysis have long been recognized. Recently, application of the knowledge-based systems approach to agricultural management has been gaining popularity because of our expanding knowledge of processes that are involved in the growth of plants, coupled with the availability of inexpensive and powerful computers. The systems approach makes use of dynamic simulation models of crop growth and of cropping systems. In the most satisfactory crop growth models, current knowledge of plant growth and development from various disciplines, such as crop physiology, agrometeorology, soil science and agronomy, is integrated in a consistent, quantitative and process-oriented manner. After proper validation, the models are used to predict crop responses to different environments that are either the result of global change or induced by agricultural management and to test alternative crop management options.Computerized decision support systems for field-level crop management are now available. The decision support systems for agrotechnology transfer (DSSAT) allows users to combine the technical knowledge contained in crop growth models with economic considerations and environmental impact evaluations to facilitate economic analysis and risk assessment of farming enterprises. Thus, DSSAT is a valuable tool to aid the development of a viable and sustainable agricultural industry. The development and validation of crop models can improve our understanding of the underlying processes, pinpoint where our understanding is inadequate, and, hence, support strategic agricultural research. The knowledge-based systems approach offers great potential to expand our ability to make good agricultural management decisions, not only for the current climatic variability, but for the anticipated climatic changes of the future. Key words: Simulation, crop growth, development, management strategy


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.


1993 ◽  
Vol 32 (01) ◽  
pp. 12-13 ◽  
Author(s):  
M. A. Musen

Abstract:Response to Heathfield HA, Wyatt J. Philosophies for the design and development of clinical decision-support systems. Meth Inform Med 1993; 32: 1-8.


2006 ◽  
Vol 45 (05) ◽  
pp. 523-527 ◽  
Author(s):  
A. Abu-Hanna ◽  
B. Nannings

Summary Objectives: Decision Support Telemedicine Systems (DSTS) are at the intersection of two disciplines: telemedicine and clinical decision support systems (CDSS). The objective of this paper is to provide a set of characterizing properties for DSTSs. This characterizing property set (CPS) can be used for typing, classifying and clustering DSTSs. Methods: We performed a systematic keyword-based literature search to identify candidate-characterizing properties. We selected a subset of candidates and refined them by assessing their potential in order to obtain the CPS. Results: The CPS consists of 14 properties, which can be used for the uniform description and typing of applications of DSTSs. The properties are grouped in three categories that we refer to as the problem dimension, process dimension, and system dimension. We provide CPS instantiations for three prototypical applications. Conclusions: The CPS includes important properties for typing DSTSs, focusing on aspects of communication for the telemedicine part and on aspects of decisionmaking for the CDSS part. The CPS provides users with tools for uniformly describing DSTSs.


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