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Journal ArticleDOI

A Decision Theoretic Approach to Crop Disease Prediction and Control

01 May 1970-American Journal of Agricultural Economics (Oxford University Press)-Vol. 52, Iss: 2, pp 216-223
TL;DR: In this article, Bayesian decision theory procedures are used to arrive at optimal crop disease control practices, and subjective probabilities of disease loss intensity are measured and used in the decision model, and the optimal pesticide use actions are computed for three different objective functions, maximum subjective expected returns, mean-standard deviation of returns, and maximum expected returns with a minimum income side condition.
Abstract: The pesticide application practices of California peach growers in controlling peach brown‐rot are used to demonstrate how Bayesian decision theory procedures can be used to arrive at optimal crop disease control practices. Subjective probabilities of disease loss intensity are measured and used in the decision model. Information from an analyst (this researcher) is combined with farmers' subjective probabilities of disease loss by means of Bayes' theorem. Optimal pesticide use actions are computed for three different objective functions—maximum subjective expected returns, mean‐standard deviation of returns, and maximum expected returns with a minimum income side condition.
Citations
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Journal ArticleDOI
TL;DR: This paper focuses on the individual farmer as a decision maker and the services the pathologist can render him; it deals with tactical decisions.
Abstract: Crop loss has become so broad a subject that a comprehensive review of the topic would be limited to generalities that are rather well known by now (2, 11-13,31,39,88). For this reason, I have chosen to limit this review to the exploration of a single theme, the threshold theory, which I feel confident discussing because of my experience. This paper focuses on the individual farmer as a decision maker and the services the pathologist can render him; it deals with tactical (17, 101) decisions.

217 citations

Journal ArticleDOI
TL;DR: The economics of decision making in pest management is not just concerned with the dollars and cents of pest damage and control but with the goals and behavior of those who make pest management decisions.
Abstract: strategy is better than another, according to specific, subjective criteria. The important point for the entomologist to note is that both positive and normative aspects of economics can be useful in assessing the performance of pest management activities and in making recommendations. Entomologists should also be aware that actual pest management decisions are based on normative considerations and therefore are subjective, no matter how carefully the costs and benefits have been assessed. Consequently, the economics of decision making in pest management is not just concerned with the dollars and cents of pest damage and control but with the goals and behavior of those who make pest management decisions.

207 citations

Journal ArticleDOI
TL;DR: In this paper, the effect of increasing pest resistance to insecticides on the optimal control of a pest population is investigated by constructing a single-pest, single-crop management model and analyzing the resulting optimality conditions.
Abstract: The effect of increasing pest resistance to insecticides on the optimal control of a pest population is investigated by constructing a single-pest, single-crop management model and analyzing the resulting optimality conditions. Use of insecticides under these conditions results in both monetary costs and user costs. It is suggested that growers do not generally consider these user costs and therefore do not obtain maximum profits. The dynamic formulation of the model results in an extension of the literature dealing with the "economic-threshold," which under reasonable conditions is shown to be increasing during the course of the season.

196 citations

Journal ArticleDOI
TL;DR: Decision making is a key aspect of current integrated pest management (IPM) programs and will continue to play an important role as IPM programs mature, and decision­ making protocols can be used to reduce pesticide use.
Abstract: Decision making is a key aspect of current integrated pest management (IPM) programs and will continue to play an important role as IPM programs mature (71, 106). In an IPM context, decision making relies on protocols for deciding on the need for some management action based on an assessment of the state of a pest population (and ideally its natural enemies). These protocols, which we refer to as control decision rules, consist of at least two components and may include a third: (a) a procedure for assessing the density of the pest population, (b) an economic threshold (63)';�and (c) a phenological forecast (e.g. 49), which is often necessary to determine the appropriate time to assess popUlation densities. Assessment of pest density usually requires obtaining actual counts of the pests, and therefore, sampling is important. Because sampling is time consuming and expensive, one must know how to gather enough information about pest abundance to be able to make correct decisions without incurring excessive costs. Decision making in IPM is important for two reasons. First, decision­ making protocols can be used to reduce pesticide use. Ideally, IPM relies on benign tactics such as biological control, plant resistance, and cultural prac­ tices to maintain fluctuating pest populations below economic injury levels.

176 citations

Journal ArticleDOI
TL;DR: This paper describes the planning problems of both the crop and livestock sectors and outline the models that have been proposed for solving these problems and provides an OR-oriented introduction to the problems involved in agricultural planning, particularly at the farm level.
Abstract: Farm planning has increased in complexity and importance as agriculture in the developed world has become concentrated in larger, more specialized farm units. These changes have stimulated the development of formal planning techniques based on mathematical models. Although this approach is characteristic of operations research, the profession's direct involvement in agricultural planning has been limited: much of the published work is associated with agricultural economics. In this paper, we provide an OR-oriented introduction to the problems involved in agricultural planning, particularly at the farm level. We describe the planning problems of both the crop and livestock sectors and outline the models that have been proposed for solving these problems. Researchers, and agricultural extension and advisory services, have been the main users of these models, but the widespread availability of microcomputers gives considerable scope for developing models for use by farmers.

140 citations

References
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Journal ArticleDOI
TL;DR: The paper presents a method of attack which splits the problem into two non-linear or linear programming parts, i determining optimal probability distributions, ii approximating the optimal distributions as closely as possible by decision rules of prescribed form.
Abstract: A new conceptual and analytical vehicle for problems of temporal planning under uncertainty, involving determination of optimal sequential stochastic decision rules is defined and illustrated by means of a typical industrial example. The paper presents a method of attack which splits the problem into two non-linear or linear programming parts, i determining optimal probability distributions, ii approximating the optimal distributions as closely as possible by decision rules of prescribed form.

2,477 citations


"A Decision Theoretic Approach to Cr..." refers methods in this paper

  • ...15 This objective function is closely akin to that used in chance-constrained programming [3]and utility depending upon the probability of ruin or some focus of loss [16]....

    [...]

Book ChapterDOI
TL;DR: A reprint of Frank P. Ramsey's seminal paper "Truth and Probability" written in 1926 and first published posthumous in the 1931 The Foundations of Mathematics and other Logical Essays, ed. R.B. Braithwaite, London: Routledge & Kegan Paul Ltd as discussed by the authors.
Abstract: This chapter is a reprint of Frank P. Ramsey’s seminal paper “Truth and Probability” written in 1926 and first published posthumous in the 1931 The Foundations of Mathematics and other Logical Essays, ed. R.B. Braithwaite, London: Routledge & Kegan Paul Ltd.

1,708 citations

Journal ArticleDOI

561 citations


"A Decision Theoretic Approach to Cr..." refers background or methods in this paper

  • ...Savage [20] outlines the choice measurement procedure in the form of a standard lottery (or standard gamble)....

    [...]

  • ...3 Ramsey [18] and Savage [20] have forcefully argued that if a set of reasonable axioms of behavior is satisfied, then the best guide for decisions is the one based on subjective expected utility maximization....

    [...]

  • ...De Finetti [5] and Savage [20] can be credited with giving probability a personalistic definition and using it in decision theory problems....

    [...]

Journal ArticleDOI
TL;DR: "`But the authors can't agree whether A or B is correct,' he concluded, `and so they're collecting expert opinions, weighting them appropriately, and programming WESCAC to arbitrate the whole question.'"
Abstract: “‘But we can't agree whether A or B is correct,' he concluded, ‘and so we're collecting expert opinions, weighting them appropriately, and programming WESCAC to arbitrate the whole question.’” (John Barth, Giles Goat-Boy, p. 664.) In the Bayesian framework, quantified judgments about uncertainty are an indispensable input to methods of statistical inference and decision. If a decision maker has little knowledge with regard to the parameters of interest, he may decide to consult a number of experts and obtain their quantified judgments in the form of subjective probability distributions. If this is the case, the decision maker must somehow combine the distributions assessed by the experts and form a single distribution to be used as an input to a formal Bayesian analysis. Several methods for combining the distributions are suggested, some involving mathematical formulae and some involving feedback and/or group discussion. These methods are compared under certain assumptions regarding the form of the distri...

375 citations

Book
01 Jan 1969

232 citations