Skip to main content
Log in

Forecasting Fruit Size and Caliber by Means of Diffusion Processes. Application to “Valencia Late” Oranges

  • Published:
Journal of Agricultural, Biological, and Environmental Statistics Aims and scope Submit manuscript

Abstract

An application of stochastic modeling by means of diffusion processes to the forecasting of fruit size and caliber is presented in the present paper. In a first phase, a diffusion process that adequately fits the available data on the time of fruit growth is constructed and estimated. Then, a proposal is made for a procedure employing the probability transition distributions of the fitted process for the allocation of caliber to each fruit. Tables are constructed with the values that discriminate between calibers at the time of harvest, which allow us to make a prediction from each previous time instant. Finally, the mean conditional functions to predict the percentages of each size (fruit size distribution) at the time of harvest are considered. A practical application is presented to Valencia late oranges through a modified version of the Bertalanffy process. Such a process is modified by including in its trend a time-dependent function used to model the observed deviations in the data about the evolution of the diameter of oranges with respect to the trajectories of the original process.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Albano, G., Giorno, V., Román-Román, P., and Torres-Ruiz, F. (2011), “Inferring the Effect of Therapy on Tumors Showing Stochastic Gompertzian Growth,” Journal of Theoretical Biology, 276, 67–77.

    Article  MathSciNet  Google Scholar 

  • Almeida, A. M., Tomé, J., and Tomé, M. (2010), “Development of a System to Predict the Evolution of Individual Tree Mature Cork Caliber over Time,” Forest Ecology and Management, 260, 1303–1314.

    Article  Google Scholar 

  • Arnold, L. (1974), Stochastic Differential Equations, New York: Wiley.

    MATH  Google Scholar 

  • Avanza, M. M., Bramardi, S. J., and Mazza, S. M. (2008), “Statistical Models to Describe the Fruit Growth Pattern in Sweet Orange ‘Valencia Late’,” Spanish Journal of Agricultural Research, 6 (4), 577–585.

    Article  Google Scholar 

  • Capocelli, R. M., and Ricciardi, L. M. (1974a), “A Diffusion Model for Population Growth in Random Environment,” Theoretical Population Biology, 5, 28–41.

    Article  MATH  Google Scholar 

  • — (1974b), “Growth with Regulation in Random Environment,” Kybernetik, 15, 147–157.

    Article  MATH  Google Scholar 

  • Flores Morán, L. A. (1996), “Elaboración de Modelos para Predecir Tamaño de Manzanas var. Grammy Smith y Red Spur,” In: http://dspace.utalca.cl/handle/1950/460.

  • Gandar, P. W., Hall, A. J., and de Silva, H. N. (1996), “Deterministic Models for Fruit Growth,” Acta Horticulturae (ISHS), 416, 103–112.

    Google Scholar 

  • Garritz, P. I., Bartusch, A. M., and Álvarez, O. A. (1993), “Crecimiento Estacional de Frutos de Manzano cv. “Granny Smith”,” Agro Sur, 21, 136–141.

    Google Scholar 

  • González-Adrados, J. R., González Hernández, F., and Calvo Haro, R. (2000), “La predicción del Calibre del Corcho al Final del Turno y su Aplicación al Muestreo de Producción,” nvestigación Agraria. Sistemas Y Recursos Forestales, 9 (2), 363–374.

    Google Scholar 

  • Gutierrez, R., Román, P., and Torres, F. (1999), “Inference and First-Passage-Times for the Lognormal Diffusion Process with Exogenous Factors: Application to Modelling in Economics,” Applied Stochastic Models in Business and Industry, 15, 325–332.

    Article  MATH  Google Scholar 

  • Gutiérrez, R., Rico, N., Román, P., and Torres, F. (2006), “Approximate and Generalized Confidence Bands for Some Parametric Functions of the Lognormal Diffusion Process with Exogenous Factors,” Scientiae Mathematicae Japonicae, 64, 843–859.

    Google Scholar 

  • Gutiérrez-Jáimez, R., Román, P., Romero, D., Serrano, J. J., and Torres, F. (2007), “A New Gompertz-Type Diffusion Process with Application to Random Growth,” Mathematical Biosciences, 208, 147–165.

    Article  MATH  MathSciNet  Google Scholar 

  • Hall, A. J., and Gandar, P. W. (1996), “Stochastic Models for Fruit Growth,” Acta Horticulturae (ISHS), 416, 113–120.

    Google Scholar 

  • Kaack, K., and Pedersen, H. L. (2010), “Prediction of Diameter, Weight and Quality of Apple Fruit (Malus Domestica Borkh.) Cv. “Elstar” Using Climatic Variables and Their Interactions,” European Journal of Horticultural Science, 75 (2), 60–70.

    Google Scholar 

  • Lande, R., Engen, S., and Saether, B. E. (2003), Stochastic Population Dynamics in Ecology and Conservation, Oxford: Oxford University Press.

    Book  Google Scholar 

  • Lötze, E., and Bergh, O. (2004), “Early Prediction of Harvest Fruit Size Distribution of an Apple and Pear Cultivar,” Scientia Horticulturae, 101, 281–290.

    Article  Google Scholar 

  • Lv, Q., and Pitchford, J. W. (2007), “Stochastic Von Bertalanffy Models, with Applications to Fish Recruitment,” Journal of Theoretical Biology, 244, 640–655.

    Article  MathSciNet  Google Scholar 

  • Mayorano, F. J., Rubiales, A. J., Herrero, V., and Clausse, A. (2006), “Computational Model for Forecasting of Fruit Size,” Revista de Investigaciones Agropecuarias, 35 (2), 143–162.

    Google Scholar 

  • Ortega-Farías, S., Flores, L., and León, L. (2002), “Elaboration of a Predictive Table of Apple Diameter Cv. Granny Smith Using Growing Degree Days,” Agricultura Técnica, 62 (4), 624–632.

    Article  Google Scholar 

  • Ortega-Farías, S., Flores, L., and Retamales, J. (1998), “Modelo Logístico Para Predecir el Crecimiento en Diámetro de las Manzanas (Variedad Granny Smith),” Revista Frutícola, 19, 15–18.

    Google Scholar 

  • Ortega-Farías, S. O., and León, L. (2002), “Models for Predicting Apple Diameter by Using Growing-Degree Days, Cultivar Royal Gala,” Acta Horticulturae (ISHS), 584, 163–167.

    Google Scholar 

  • Ricciardi, L. M. (1979), “On a Conjecture Concerning Population Growth in Random Environment,” Biological Cybernetics, 32, 95–99.

    Article  MATH  Google Scholar 

  • Román-Román, P., Romero, D., and Torres-Ruiz, F. (2010), “A Diffusion Process to Model Generalized von Bertalanffy Growth Patterns: Fitting to Real Data,” Journal of Theoretical Biology, 263, 59–69.

    Article  MathSciNet  Google Scholar 

  • Román-Román, P., and Torres-Ruiz, F. (2012a), “Modelling Logistic Growth by a New Diffusion Process: Application to Biological Systems,” BioSystems, 110, 9–21.

    Article  Google Scholar 

  • — (2012b), “Inferring the Effect of Therapies on Tumor Growth by Using Diffusion Processes,” Journal of Theoretical Biology, 314, 34–56.

    Article  MathSciNet  Google Scholar 

  • Rupšys, P., Bartkevičius, E., and Petrauskas, E. (2011), “A Univariate Stochastic Gompertz Model for Tree Diameter Modeling,” Trends in Applied Sciences Research, 6 (2), 134–153.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to P. Román-Román.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Román-Román, P., Torres-Ruiz, F. Forecasting Fruit Size and Caliber by Means of Diffusion Processes. Application to “Valencia Late” Oranges. JABES 19, 292–313 (2014). https://doi.org/10.1007/s13253-014-0172-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13253-014-0172-3

Key Words

Navigation