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      Empirical Model With Excellent Statistical Properties for Describing Temperature-Dependent Developmental Rates of Insects and Mites

      1 , 2
      Annals of the Entomological Society of America
      Oxford University Press (OUP)

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          Abstract

          Previous empirical models for describing the temperature-dependent development rates for insects include the Briére, Lactin, Beta, and Ratkowsky models. Another nonlinear regression model, not previously considered in population entomology, is the Lobry–Rosso–Flandrois model, the shape of which is very close to that of the Ratkowsky model in the suboptimal temperature range, but which has the added advantage that all four of its parameters have biological meaning. A consequence of this is that initial parameter estimates, needed for solving the nonlinear regression equations, are very easy to obtain. In addition, the model has excellent statistical properties, with the estimators of the parameters being “close-to-linear,” which means that the least squares estimators are close to being unbiased, normally distributed, minimum variance estimators. The model describes the pooled development rates very well throughout the entire biokinetic temperature range and deserves to become the empirical model of general use in this area.

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          Most cited references30

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          Nonlinear Regression Analysis and Its Applications

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            A Novel Rate Model of Temperature-Dependent Development for Arthropods

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              A flexible sigmoid function of determinate growth.

              A new empirical equation for the sigmoid pattern of determinate growth, 'the beta growth function', is presented. It calculates weight (w) in dependence of time, using the following three parameters: t(m), the time at which the maximum growth rate is obtained; t(e), the time at the end of growth; and w(max), the maximal value for w, which is achieved at t(e). The beta growth function was compared with four classical (logistic, Richards, Gompertz and Weibull) growth equations, and two expolinear equations. All equations described successfully the sigmoid dynamics of seed filling, plant growth and crop biomass production. However, differences were found in estimating w(max). Features of the beta function are: (1) like the Richards equation it is flexible in describing various asymmetrical sigmoid patterns (its symmetrical form is a cubic polynomial); (2) like the logistic and the Gompertz equations its parameters are numerically stable in statistical estimation; (3) like the Weibull function it predicts zero mass at time zero, but its extension to deal with various initial conditions can be easily obtained; (4) relative to the truncated expolinear equation it provides more reasonable estimates of final quantity and duration of a growth process. In addition, the new function predicts a zero growth rate at both the start and end of a precisely defined growth period. Therefore, it is unique for dealing with determinate growth, and is more suitable than other functions for embedding in process-based crop simulation models to describe the dynamics of organs as sinks to absorb assimilates. Because its parameters correspond to growth traits of interest to crop scientists, the beta growth function is suitable for characterization of environmental and genotypic influences on growth processes. However, it is not suitable for estimating maximum relative growth rate to characterize early growth that is expected to be close to exponential.

                Author and article information

                Journal
                Annals of the Entomological Society of America
                Oxford University Press (OUP)
                0013-8746
                1938-2901
                May 2017
                May 01 2017
                February 17 2017
                May 2017
                May 01 2017
                February 17 2017
                : 110
                : 3
                : 302-309
                Affiliations
                [1 ]Tasmanian Institute of Agriculture, Private Bag 98, Hobart, Tasmania 7001, Australia (d.ratkowsky@utas.edu.au)
                [2 ]Montana State University, Western Triangle Ag Research Center, 9546 Old Shelby Rd., P.O. Box 656, Conrad, MT 59425 (reddy@montana.edu),
                Article
                10.1093/aesa/saw098
                c880001a-102e-42dd-9901-ede5605df350
                © 2017
                History

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