EIGENANALYSIS APPLIED IN DIFFERENT AREAS OF AGRONOMICAL SCIENCE AND BIOTECHNOLOGY: A REVIEW
Keywords:
Eigenvalues, eigenvectores, analysis of biological diversity, stability of biorectorsAbstract
Analysis of eigenvalues or eigenanalysis is a mathematical technique, which is part of linear
algebra, and which can be applied to different branches of the science. This article, reviews two specific cases where this mathematical technique has different connotations and interpretations. In the first case, the biological diversity analysis, the three main factorial analysis were
examined: Principal component analysis, principal coordinate analysis, and correspondence analysis. All of these analyses have a similar interpretation: to show the variability of m experimental units with n traits in a Euclidean plane, where both eigenvalues and eigenvectors are
used. In the second case, in the stability of biological reactors, the eigenvalues of bioreactor state matrix were analysed to define and to interpret the bioreactor stability. This review offers a complementary reading about the use and interpretation of eigenanalysis for studies on biological
diversity and on bioreactors stability.
References
Ayangbenro AS, Olanrewaju OS, Babalola OO. 2018. Sulfate-reducing bacteria as an effective tool for sustainable acid mine bioremediation. Frontiers in Microbiology 9: Article 1986. https://doi.org/10.3389/Fmicb.2018.01986
Chiquito?Almanza E, Ochoa?Zarzosa A, López?Meza JE, Pecina?Quintero V, Núñez?Colín CA, Anaya?López JL. 2016. A new allele of ??kafirin gene coding for a protein with high lysine content in Mexican white sorghum germplasm. Journal of the Science of Food and
Agriculture 96(10): 3342-3350. https://doi.org/10.1002/jsfa.7513
Dice LR. 1945. Measure of the amount of ecologic associations between species. Ecology 26(3): 277-302. DOI: 10.2307/1932409
Feio MJ, Zinkevich V, Beech IB, Brossa EL, Eaton P, Schmitt J, Guezennec J. 2004. Desulfovibrio alaskensis sp. nov., a sulphate reducing bacterium from a soured oil reservoir. International Journal of Systematic and Evolutionary Microbiology 54: 1747-1752. https://doi.org/10.1099/ijs.0.63118-0
Gower JC. 1966. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53(3-4): 325-338. https://doi.org/10.1093/biomet/53.3-4.325
Gower JC. 2005. Principal Coordinates Analysis. In: Armitage P, Colton T, editors. Encyclopedia of Biostatistics. Chichester, John Wiley & Sons. Hair JF Jr, Anderson RE, Tatham RL, Black WC. 2001. Análisis multivariante. Prentice Hall Iberia. Madrid, España.
Hamann U. 1961. Merkmalbestand und Verwandtschaftsbeziehungen der Farinosae.
Ein Beitragzum System der Monokotyledonen. Willdenowia 2(5): 639-768.
Han K, Levenspiel O. 1988. Extended Monod kinetics for substrate, product and cell inhibition. Biotechnology and Bioengineering 32(4): 430-447. https://doi.org/10.1002/bit.260320404
Hespanha JP. 2009. Linear Systems Theory. Princeton University Press. Princeton, USA.
Jaccard P. 1908. Nouvelles recherches sur la distribution florale. Bulletin de la Société Vaudoise des Sciences Naturelles 44(163): 223-270. https://doi.org/10.5169/seals-268384
Johnson DE. 1998. Métodos multivariados aplicados al análisis de datos. International Thomson Editores. Ciudad de México, México.
Kamarisima, Miyanaga K, Tanji Y. 2019. The utilization of aromatic hydrocarbon by nitrate- and sulfate-reducing bacteria in single and multiple nitrate injection for souring control. Biochemical Engineering Journal 143: 75-80. https://doi.org/10.1016/j.bej.2018.12.006
Khalil HK. 2002. Nonlinear Systems. Prentice Hall. New Jersey, USA.
Kulczynski S. 1927. Die Pflanzenassoziationen der Pienienen. Bulletin International de l'Academie Polonaise des Sciences et des Lettres, Classe des Sciences Mathematiques et Naturelles B (Suppl. 2): 57-203.
Li YC, Yang XY, Geng B. 2018. Preparation of immobilized sulfate-reducing bacteria-microalgae beads for effective bioremediation of copper-containing wastewater. Water Air and Soil Pollution 229(3): article 54. https://doi.org/10.1007/s11270-018-3709-1
López-Pérez PA, Neria-González MI, Aguilar-López R. 2013. Cadmium concentration stabilization in a class of continuous sulfate reducing bioreactor via sulfide concentration control. Chemical Papers 67(3): 326-335. https://doi.org/10.2478/s11696-012-0274-8
Monod J. 1949. The growth of bacterial cultures. Annual Reviews in Microbiology 3(1): 371-394. https://doi.org/10.1146/annurev.mi.03.100149.002103
Montenegro A, Pardo CE. 1996. Introducción al análisis de datos textuales. Universidad Nacional de Colombia. Santa Fe, Colombia.
Nei M, Li WH. 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Science (USA) 76(10): 5269-5273.
Neria-González I, Wang ET, Ramírez F, Romero JM, Hernández-Rodríguez C. 2006. Characterization of bacterial community associated to biofilms of corroded
oil pipelines from the Southeast of Mexico. Anaerobe 12(3): 122-133. https://doi.org/10.1016/j.
anaerobe.2006.02.001
Nielsen G, Coudert L, Janin A, Blais JF, Mercier G. 2019. Influence of organic carbon sources on metal removal from mine impacted water using sulfate-reducing bacteria bioreactors in cold climates. Mine Water and the Environment 38(1): 104-118. https://doi.org/10.1007/s10230-018-00580-3.
Núñez-Colín CA, Barrientos-Priego AF. 2006. Estimación de la variabilidad interna de muestras poblacionales, mediante el análisis en componentes principales Interciencia 31(11): 802-806.
Núñez-Colín CA, Valadez-Moctezuma E. 2010. Análisis Estadístico de Huellas Genómicas, un Uso Práctico de los Paquetes Computacionales más Populares. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias. Celaya, Guanajuato.
Núñez-Colín CA, Escobedo-López D. 2011. Uso correcto del análisis clúster en la caracterización de germoplasma vegetal. Agronomía Mesoamericana 22(2): 415-427.
Núñez-Colín CA, Escobedo-López D. 2014. Caracterización de germoplasma vegetal: la piedra angular en el estudio de los recursos fitogenéticos. Acta Agrícola y Pecuaria 1(1): 1-6.
Núñez-Colín CA, Rodríguez-Pérez JE, Nieto-Ángel R, Barrientos-Priego AF. 2004. Construcción de dendrogramas de taxonomía numérica mediante el coeficiente de distancia ?2: una revisión. Revista Chapingo Serie Horticultura 10(2): 229-237. https://doi.org/10.5154/r.
rchsh.2003.07.046
Ochiai A. 1957. Zoogeographic studies on the soleoid fishes found in Japan and its neighbouring regions. Bulletin of the Japanese Society of Scientific Fisheries 22(9): 526-530. https://doi.org/10.2331/suisan.22.526
Peña-Caballero V, López-Pérez PA, Neria-González MI, Aguilar-López R. 2012. A class of nonlinear adaptive controller for a continuous anaerobic bioreactor. Journal of Scientific & Industrial Research 71(7): 480-486.
Peña-Caballero V, Aguilar-López R, López-Pérez PA, Neria-González MI. 2016. Reduction of Cr(VI) utilizing biogenic sulfide: an experimental and mathematical modeling approach. Desalination and Water Treatment 57(28): 13056-13065. https://doi.org/10.1080/19443994.2015.1055811
Postgate JR. 1984. The Sulphate-Reducing Bacteria. (2nd edition). Cambridge University Press. Cambridge, UK.
Ravikumar KVG, Argulwar S, Sudakaran SV, Pulimi M, Chandrasekaran N, Mukherjee A. 2018. Nano-Bio sequential removal of hexavalent chromium using polymer-nZVI composite film and sulfate reducing bacteria under anaerobic condition. Environmental Technology & Innovation 9: 122-133. https://doi.org/10.1016/j.eti.2017.11.006
Rogers DG, Tanimoto TT. 1960. A computer program for classifying plants. Science 132(3434): 1115-1118. https://doi.org/10.1126/science.132.3434.1115
Russel PF, Rao TR. 1940. On habitat and association of species of Anopheline larvae in south-eastern Madras. Journal of the Malaria Institute of India 3(1): 153-178.
Searle SR. 2005. Eigenvalue. In: Armitage P, Colton T, editors. Encyclopedia of Biostatistics, 6. Chichester, John Wiley & Sons.
Searle SR. 2006. Matrix Algebra Useful for Statistics. Wiley-Interscience. New Jersey, USA.
Serrano J, Leiva E. 2017. Removal of arsenic using acid/metal-tolerant sulfate reducing Bacteria: a new approach for bioremediation of high-arsenic acid mine waters. Water 9(12): 994. https://doi.org/10.3390/W9120994
Sokal RR, Sneath PHA. 1963. Principles of Numerical Taxonomy. H. Freeman & Company. San Francisco, USA.
Spring S, Sorokin DY, Verbarg S, Rohde M, Woyke T, Kyrpides NC. 2019. Sulfate-reducing bacteria that produce exopolymers thrive in the calcifying zone of a hypersaline cyanobacterial mat. Frontiers in Microbiology 10: a862. https://doi.org/10.3389 /Fmicb.2019.00862
Yule GU. 1911. An Introduction of the Theory of Statistics. Charles Griffin & Company. London, UK.