Beta Function Law to Model the Dynamics of Fruit’s Growth Rate in Tomato: Parameter Estimation and Evaluation

Abstract : The calculation of fruit growth rate (FGR) is the main part of fruit-bearing crop growth models. In this paper, greenhouse tomato was used as a research material. The purpose of this study is to better understand the regulation of single fruit growth response to environmental or genetic factors. A FGR model of tomato fruit was described based on Beta function law because it has flexible ability to generate different curve shape when adjusting its parameters. A field experiments with 4 planting densities in 2012 spring was carried out in China, using the cultivar Weichi. The parameters of Beta-law FGR model were estimated with data from the fruits in the first truss by using the optimization algorithm Nelder-Mead The results showed that the optimization procedure described in this paper found best fitted and robust parameters, which implied that those parameters are cultivar specific, and little environmental dependence. The validation against the data from the second truss and third truss with variations in planting density was found to be acceptable (R2 = 0.9117). This modeling methodology and software program have the potential to become a powerful tool for optimization of ideotype design.
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Daoliang Li; Zhenbo Li. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. IFIP Advances in Information and Communication Technology, AICT-478 (Part I), pp.19-26, 2016, Computer and Computing Technologies in Agriculture IX. 〈1010.1007/978-3-319-48357-3_3〉
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Qiaoxue Dong, Lili Yang, Mei Qu, Qinglan Shi, Shangfeng Du. Beta Function Law to Model the Dynamics of Fruit’s Growth Rate in Tomato: Parameter Estimation and Evaluation. Daoliang Li; Zhenbo Li. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. IFIP Advances in Information and Communication Technology, AICT-478 (Part I), pp.19-26, 2016, Computer and Computing Technologies in Agriculture IX. 〈1010.1007/978-3-319-48357-3_3〉. 〈hal-01557843〉

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