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ISHS Acta Horticulturae 276: II International Symposium on Computer Modelling in Fruit Research and Orchard Management

THE CASH SYSTEM OF ON-FARM DECISION TOOLS FOR HORTICULTURAL ENTERPRISES

Authors:   F. R. Hall, James R. Lemon
Abstract:
The Computer Advisory Service for Horticulture (CASH) project was initiated in 1985 at The Ohio State University upon receipt of a grant from the Kellogg Foundation. The DSS component of the CASH project seeks to identify and target generic decision making tasks inherent in farm and pest management which apply to various agricultural commodities. Such tasks often can be implemented via sophisticated application of spread-sheet software. The CASH/DSS software attempts to organize and present the decision making process per generic task in a manner that facilitates grower implementation and analysis of the end result.

Simply stated, the CASH system of decision tools is designed to present an alternative view of how information may be better utilized at the farm level. Specifically, the initial tools allow an identification of the key factors which influence net economic return and the extent to which they influence the "bottom line."

Initial thrusts are for simple but robust management tools, "what if" programs, which as grower expertise grows, new ideas and expanded "what if" programs are incorporated. An important point is that growers already have more information available to them than they are currently utilizing for crop management decisions. The greatest potential for helping growers improve decision making appears to be through payoff matrix and decision tree concepts. Growers can be taught to utilize risk management concepts for decision making in uncertain environments. This will require (1) identification of key factors influencing net return, (2) learning how to manipulate return, and (3) learning how to assess the "objective" probability of key variables of insects and disease and their impact on cash return. The array of CASH DSS tools now available provides a beginning for accomplishing these decision tasks. This paper provides an overview of the DSS tools produced by the CASH project.

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