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Kolmogorov–Smirnov Test for Statistical Characterization of Photopyroelectric Signals Obtained from Maize Seeds

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Abstract

Photothermal techniques are useful experimental methodologies for characterization of the optical and thermal parameters of different materials like maize seeds due to its advantages such as non-invasive and non-destructive nature. Among these techniques, the photopyroelectric microscopy was applied in the present research to obtain thermal images where each of their coordinates represents amplitude values of the photopyroelectric signal, indicating differences in the structural components of both genotypes of maize seeds. The random variations of the amplitude of the photopyroelectric signal caused by the heterogeneous nature of the thermal properties of the samples, were represented by histograms to identify the probability density function underlying the data sample, observing that in the case of the maize seed with floury structure, the amplitude variations could be described statistically by the transformed Moyal distribution when a linear transformation with censored data was applied to the data set obtained from the thermal image with a significance level of 0.001, according to the Kolmogorov–Smirnov statistical test for goodness-of-fit. In the case of the photopyroelectric signal obtained from a maize seed with crystalline structure, it was not possible to describe statistically the amplitude variations of the signal by means of the transformed Moyal distribution because it did not pass the Kolmogorov–Smirnov test, so the same statistical test for goodness of fit was applied to both genotypes of maize seeds for analyzing the populations of the data sample, in order to find the distributions that best fit each population with a significance level of at least 0.05 increasing in this way the power of the test. The distributions with the best fit were logistic, log-logistic, uniform, least extreme value and normal.

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References

  1. A. Domínguez-Pacheco, C. H-Aguilar, A. Cruz-Orea, E.I. Alemán, E. M-Ortiz, Int. J. Thermophys. 34, 1499 (2013)

    Article  ADS  Google Scholar 

  2. A. Mandelis, M.M. Zver, J. Appl. Phys. 57, 4421 (1985)

    Article  ADS  Google Scholar 

  3. A. Salazar, A. Oleaga, Rev. Sci. Instrum. 76, 034901 (2005)

    Article  ADS  Google Scholar 

  4. J.A. Balderas-López, A. Mandelis, Int. J. Thermophys. 24, 463 (2003)

    Article  Google Scholar 

  5. B.R. Briseño-Tepepa, J.L. Jiménez-Pérez, R. Saavedra, R. González-Ballesteros, E. Suaste, A. Cruz-Orea, Int. J. Thermophys. 29, 2200 (2008)

    Article  ADS  Google Scholar 

  6. A. Domínguez-Pacheco, C. Hernández-Aguilar, R. Zepeda-Bautista, E. Martínez-Ortiz, A. Cruz-Orea, Superficies y Vacío 25, 92 (2012)

    Google Scholar 

  7. H.M. Taylor, S. Karlin, An Introduction To Stochastic Modeling (Academic Press CRC, Boca Raton, 2014)

    MATH  Google Scholar 

  8. J. Walpole, J.A. Papin, S.M. Peirce, Annu. Rev. Chem. Biomol. Eng. 15, 137 (2013)

    Article  Google Scholar 

  9. S. Torquato, Random Heterogeneous Materials: Microstructure and Macroscopic Properties, vol. 16 (Springer Science & Business Media, Berlin, 2013)

    MATH  Google Scholar 

  10. J. Banks, J.S. Carson, B.L. Nelson, D.M. Nicol, Discrete-Event system simulation, 3rd edn. (Prentice Hall, Upper Saddle River, 2000)

    Google Scholar 

  11. T.T. Soong, Fundamentals of Probability and Statistics for Engineers (John Wiley & Sons Ltd., England, 2004)

    MATH  Google Scholar 

  12. C. Walk, Handbook on Statistical Distributions for Experimentalists, No. SUF-PYF/96-01 (University of Stockholm Press, Stockholm, 1996)

    Google Scholar 

  13. J.E. Moyal, Phil. Mag. 46, 263 (1955)

    Article  Google Scholar 

  14. G.M. Cordeiro, J.S. Nobre, R.R. Pescim, E.M. Ortega, Int. J. Res. Rev. Appl. Sci. 10, 171 (2012)

    MathSciNet  Google Scholar 

  15. S.G. Meintanis, Sankhyā: The Indian. J. Stat. 66, 304 (2004)

    Google Scholar 

  16. A.K. Dey, D. Kundu, Commun. Stat. Theory. Methods 39, 280 (2009)

    Google Scholar 

  17. T. Kernane, Z. Raizah, Estimation of the Parameters of Extreme Value Distributions from Truncated Data Via the EM Algorithm, < hal-00503252v2 > (2014)

  18. R.E. Walpole, R.H. Myers, S.L. Myers, K. Ye, Probability & Statistics for Engineers & Scientist (Pearson Education Inc, USA, 2012)

    MATH  Google Scholar 

  19. F.J. Massey Jr., J. Am. Stat. Assoc. 46, 68 (1951)

    Article  Google Scholar 

  20. A. Justel, D. Peña, R. Zamar, Stat. Probabil. Lett. 35, 251 (1997)

    Article  Google Scholar 

  21. H.W. Lilliefors, J. Am. Stat. Assoc. 62, 399 (1967)

    Article  Google Scholar 

  22. M.C. Romay, M.J. Millard, J.C. Glaubitz, J.A. Peiffer, K.L. Swarts, T.M. Casstevens, M.D. McMullen, Genome Biol. 14, R55 (2013)

    Article  Google Scholar 

  23. J.T. Alexander, V. Bochko, B. Martinkauppi, S. Saranwong, T. Mantere, Int. J. Spectrosc. (2013). https://doi.org/10.1155/2013/341402

    Article  Google Scholar 

  24. J.E. Rojas-Lima, A. Domínguez-Pacheco, C. Hernández-Aguilar, A. Cruz-Orea, Int. J. Thermophys. 37, 98 (2016)

    Article  ADS  Google Scholar 

  25. J.L. Devore, Probability & Statistics for Engineering and the Sciences, 8th edn. (Boston MA, USA, Brooks Cole, 2010), p. 687

    Google Scholar 

  26. K.L. Wuensch, in Chi-Square Tests, ed. by M. Lovric. International Encyclopedia of Statistical Science, vol. 252 (Springer, Berlin, Heidelberg, 2011)

    Google Scholar 

  27. I.T. Young, J. Histochem. Cytochem. 25, 935 (1977)

    Article  Google Scholar 

  28. StatPoint, Inc., Probability Distributions, (Statgraphics Centurion XVI.II, 2005)

  29. W.J. Da Silva, B.C. Vidal, M.E.Q. Martins, H. Vargas, A.C. Pereira, M. Zerbetto, L.C. Miranda, Nature 362, 417 (1993)

    Article  ADS  Google Scholar 

  30. K.Y. Sastry, L. Froyen, J. Vleugels, E.H. Bentefour, C. Glorieux, Int. J. Thermophys. 25, 1611 (2004)

    Article  ADS  Google Scholar 

  31. W.W. Hines, D.C. Montgomery, Probability and Statistics in Engineering and Management Science (John Wiley, New York, 1990)

    MATH  Google Scholar 

  32. A. Ortega-Corona, M.J. Guerrero-Herrera, R.E. Preciado-Ortiz, Diversidad y distribución del maíz nativo y sus parientes silvestres en México, 1a Edición, (BBA, Edit. Colegio de Posgraduados) (INIFAP, México, 2013)

    Google Scholar 

  33. O.R. Leyva-Ovalle, A. Carballo-Carballo, J.A. Mejía-Contreras, M.G. Vázquez-Carrillo, Revista Fitotecnia Mexicana 25, 355 (2002)

    Google Scholar 

  34. F.J. Pérez, A. Carballo-Carballo, A. Santacruz-Varela, A. Hernández-Livera, J.C. Molina-Moreno, Agricultura técnica en México 33, 53 (2007)

    Google Scholar 

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Acknowledgments

The authors thank the Instituto Politécnico Nacional (IPN), through the CONACYT, COFAA, EDI, SIP Scholarship Projects. One of the authors (J.E. Rojas-Lima) is grateful for all the support provided by the IPN through the PIAS-2016-2017 Academic Project. One of the authors (A. Cruz-Orea) is grateful for the economic support of CONACYT through Project 241330. Also, we thank Ing. Esther Ayala at the Physics Department of CINVESTAV-IPN for her technical support.

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Authors and Affiliations

  1. Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Sección de Estudios de Posgrado e Investigación (SEPI), Instituto Politécnico Nacional (IPN), Edif. 5, 3er Piso. Av. IPN s/n, 07738, Mexico City, México

    J. E. Rojas-Lima, F. A. Domínguez-Pacheco, C. Hernández-Aguilar & L. M. Hernández-Simón

  2. Departamento de Física, Centro de Investigación y de Estudios Avanzados (CINVESTAV) del IPN, Av. IPN No. 2508, 07360, Mexico City, México

    A. Cruz-Orea

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  1. J. E. Rojas-Lima
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  2. F. A. Domínguez-Pacheco
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  3. C. Hernández-Aguilar
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  4. L. M. Hernández-Simón
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  5. A. Cruz-Orea
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Corresponding author

Correspondence to F. A. Domínguez-Pacheco.

Additional information

This article is part of the selected papers presented at the 19th International Conference on Photoacoustic and Photothermal Phenomena.

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Rojas-Lima, J.E., Domínguez-Pacheco, F.A., Hernández-Aguilar, C. et al. Kolmogorov–Smirnov Test for Statistical Characterization of Photopyroelectric Signals Obtained from Maize Seeds. Int J Thermophys 40, 4 (2019). https://doi.org/10.1007/s10765-018-2462-4

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