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Statistical Analysis of Photopyroelectric Signals using Histogram and Kernel Density Estimation for differentiation of Maize Seeds

Authors
  • Rojas-Lima, J. E.1
  • Domínguez-Pacheco, A.1
  • Hernández-Aguilar, C.1
  • Cruz-Orea, A.2
  • 1 Instituto Politécnico Nacional, SEPI-ESIME, Zacatenco, Unidad Profesional “Adolfo López Mateos”, Col. Lindavista, Ciudad de Mexico, C.P. 07738, Mexico , Ciudad de Mexico (Mexico)
  • 2 CINVESTAV-IPN, Departamento de Física, A. P. 14-740, Ciudad de Mexico, C.P. 07360, Mexico , Ciudad de Mexico (Mexico)
Type
Published Article
Journal
International Journal of Thermophysics
Publisher
Springer US
Publication Date
Aug 01, 2016
Volume
37
Issue
9
Identifiers
DOI: 10.1007/s10765-016-2097-2
Source
Springer Nature
Keywords
License
Yellow

Abstract

Considering the necessity of photothermal alternative approaches for characterizing nonhomogeneous materials like maize seeds, the objective of this research work was to analyze statistically the amplitude variations of photopyroelectric signals, by means of nonparametric techniques such as the histogram and the kernel density estimator, and the probability density function of the amplitude variations of two genotypes of maize seeds with different pigmentations and structural components: crystalline and floury. To determine if the probability density function had a known parametric form, the histogram was determined which did not present a known parametric form, so the kernel density estimator using the Gaussian kernel, with an efficiency of 95 % in density estimation, was used to obtain the probability density function. The results obtained indicated that maize seeds could be differentiated in terms of the statistical values for floury and crystalline seeds such as the mean (93.11, 159.21), variance (1.64×103,1.48×103)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(1.64\times 10^{3}, 1.48\times 10^{3})$$\end{document}, and standard deviation (40.54, 38.47) obtained from the amplitude variations of photopyroelectric signals in the case of the histogram approach. For the case of the kernel density estimator, seeds can be differentiated in terms of kernel bandwidth or smoothing constant h of 9.85 and 6.09 for floury and crystalline seeds, respectively.

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