Exploring Bayesian models to evaluate control procedures for plant disease

  1. Danilo Alvares 1
  2. Carmen Armero 1
  3. Anabel Forte 1
  4. Luis Rubio 2
  1. 1 Universitat de València
    info

    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

  2. 2 Instituto Valenciano de Investigaciones Agrarias
    info

    Instituto Valenciano de Investigaciones Agrarias

    Moncada i Reixac, España

    ROR https://ror.org/00kx3fw88

Revista:
Sort: Statistics and Operations Research Transactions

ISSN: 1696-2281

Año de publicación: 2016

Volumen: 40

Número: 1

Páginas: 139-152

Tipo: Artículo

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Otras publicaciones en: Sort: Statistics and Operations Research Transactions

Resumen

Tigernut tubers are the main ingredient in the production of orxata in Valencia, a white soft sweet popular drink. In recent years, the appearance of black spot s in the skin of tigernuts has led to important economic losses in orxata production because severely diseased tubers must be discarded. In this paper, we discuss three complementary st atistical models to assess the dis- ease incidence of harvested tubers from selected or treated seeds, and propose a measure of effectiveness for different treatments against the diseas e based on the probability of germina- tion and the incidence of the disease. Statistical methods f or these studies are approached from Bayesian reasoning and include mixed-effects models, Diri chlet-multinomial inferential processes and mixed-effects logistic regression models. Statistica l analyses provide relevant information to carry out measures to palliate the black spot disease and ach ieve a high-quality production. For instance, the study shows that avoiding affected seeds incr eases the probability of harvesting asymptomatic tubers. It is also revealed that the best chemi cal treatment, when prioritizing ger- mination, is disinfection with hydrochloric acid while sod ium hypochlorite performs better if the priority is to have a reduced disease incidence. The reducti on of the incidence of the black spots syndrome by disinfection with chemical agents supports the hypothesis that the causal agent is a pathogenic organism.

Referencias bibliográficas

  • Agresti, A. (2013). Categorical Data Analysis. 3rd edition. John Wiley and Sons.
  • Alvares, D. (2015). Distribuciones previas objetivas para el modelo Dirichlet-multinomial: una aplicación en la agricultura. Master’s thesis, University of Valencia, Spain.
  • Berger, J. O., Bernardo, J. M. and Sun, D. (2015). Overall objective priors. Bayesian Analysis, 10, 189–221.
  • Garcı́a-Jiménez, J., Busto, J., Vicent, A. and Armengol, J. (2004). Control of Dematophora necatrix on Cyperus esculentus tubers by hot-water treatment. Crop Protection, 23, 619–623.
  • Gelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A. and Rubin, D. (2013). Bayesian Data Analysis. Texts in Statistical Science, 3th edition. Chapman and Hall/CRC.
  • Good, I. (1965). The Estimation of Probabilities: an Essay on Modern Bayesian Methods. 1st edition. MIT Press.
  • Grondeau, C., Samson, R. and Sands, D. (1994). A review of thermotherapy to free plant materials from pathogens, especially seeds from bacteria. Critical Reviews in Plant Sciences, 13, 57–75.
  • Kass, R.E., Carlin, B.P., Gelman, A. and Neal, R.M. (1998). Markov chain Monte Carlo in practice: a roundtable discussion. The American Statistician, 52, 93–100.
  • Lindley, D. (1964). The Bayesian analysis of contingency tables. The Annals of Mathematical Statistics, 35, 1622–1643.
  • Liu, I. and Agresti, A. (2005). The analysis of ordered categorical data: an overview and a survey of recent developments. Test, 14, 1–73.
  • Lunn, D.J., Thomas, A., Best, N. and Spiegelhalter, D. (2000). Winbugs – a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing, 10, 325–337.
  • Marin, J.M., Mengersen, K.L. and Robert, C. (2005). Bayesian Modelling and Inference on Mixtures of Distributions. D. Dey and C. Rao (editors), Handbook of Statistics, volume 25. Elsevier.
  • Morell, J. and Barber, S. (1983). Chufa y horchata: caracterı́sticas fı́sicas, quı́micas y nutritivas. Technical report, Institute of Agrochemistry and Food Technology, Valencia, Spain.
  • Nandram, B. (1998). A Bayesian analysis of the three-stage hierarchical multinomial model. Journal of Statistical Computation and Simulation, 61, 97–126.
  • Ntzoufras, I. (2009). Bayesian Modeling using WinBUGS. John Wiley and Sons.
  • Perks, W. (1947). Some observations on inverse probability including a new indifference rule. Journal of the Institute of Actuaries, 73, 285–334.
  • Sauer, D.B. and Burroughs, R. (1986). Disinfection of seeds surfaces with sodium hypochlorite. Phytopathology, 76, 745–749.
  • Shepard, J.F. and Claftin, L.E. (1975). Critical analyses of the principles of seed potato certification. Annual Review of Phytopathology, 13, 271–293.
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