ORIGINAL PAPER
Analysis of the nitrogen and magnesium doses effects of two cultivars of maize (Zea mays L.) using multivariate methods
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1
Poznań University of Life Sciences, Department of Mathematical and Statistical Methods ul. Wojska Polskiego 28, 60-637 Poznań, Poland
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Poznań University of Life Sciences, Department of Agronomy ul. Dojazd 11, 60-632 Poznań, Poland
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Institute of Plant Protection – National Research Institute, Department of Pests Methods Forecasting and Plant Protection Economy: ul. Władysława Węgorka 50, 60-318 Poznań, Poznań
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Wroclaw University of Environmental and Life Sciences, Department of Genetics, Plant Breeding and Seed Production pl. Grunwaldzki 24A, 53-363 Wrocław, Poland
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Poznań University of Life Sciences, Department of Gastronomical Sciences and Functional Foods ul. Wojska Polskiego 31, 60-624, Poznań, Poland
Journal of Research and Applications in Agricultural Engineering 2019;64(3):4-9
KEYWORDS
ABSTRACT
The paper presents the results of a multivariable research regarding the evaluation of variability of selected quantitative traits in two cultivars of maize (Zea mays L.): ES Palazzo and ES Paroli after using doses of nitrogen and magnesium. The study took into account 12 traits recorded for three years (2009-2011). The statistical analysis of obtained results was conducted using multivariable methods: multivariate analysis of variance, canonical variable analysis and Mahalanobis distances. The most varied objects were A4B1C2 and A1B2C1 (in 2009), A4B1C1 and A2B2C2 (in 2010), A4B2C1 and A1B2C2 (in 2011) and A4B2C1 and A1B2C2 (for all three years). The most similar objects (with regard to the 12 traits analyzed together) were A4B2C2 and A3B2C2 (in 2009), A4B2C2 and A3B1C2 (in 2010), A2B2C2 and A2B1C2 (in 2011) and A4B2C2 and A3B2C2 (for all three years). The Mahalanobis distances between particular objects in particular years of observations were positive and statistically significantly correlated.
REFERENCES (21)
1.
Adugna W., Labuschagne M.T.: Cluster and canonical variate analyses in multilocation trials of linseed. Journal of Agricultural Science, 2003, 140, 297-304.
2.
Bocianowski J., Liersch A., Bartkowiak-Broda I.: Investigation of phenotypic distance of F1 CMS ogura winter oilseed rape hybrids and parental lines using multivariate statistical methods. Rośliny Oleiste – Oilseed Crops, 2009, XXX, 161-184.
3.
Bocianowski J., Rybiński W.: Use of canonical variate analysis for the multivariate assessment of two- and multi-rowed barley DH lines (Hordeum vulgare L.). Annales UMCS, Sectio E: Agricultura, 2008, LXIII, (3), 53-61.
4.
Bocianowski J., Skomra U.: Use of canonical variate analysis for the multivariate assessment of hop cultivars (Humulus lupulus L.). Pamiętnik Puławski, 2008, 148, 107-118.
5.
Bocianowski J., Stokłosa A.: Estimation of wild oat (Avena fatua L.) botanical varieties germination in differentiated light and temperaturę conditions using canonical variates analysis. Nauka Przyroda Technologie, 2010, 4(5), #65.
6.
Bocianowski J., Warzecha T.: Multivariate characterization of wheat (Triticum L.) and triticale (xTriticosecales Wittm. ex A. Camus) cultivars inoculated with Fusarium culmorum. Nauka Przyroda Technologie, 2012, 6(1), #14.
7.
Boote K.B., Jones J.W., Pickering N.B.: Potential uses and limitations of crop models. Agronomy Journal, 1996, 88, 704-716.
8.
Camussi A., Ottaviano E., Caliński T., Kaczmarek Z.: Genetic distances based on quantitative traits. Genetics, 1985. 111, 945-962.
9.
Chatfield C., Collins A.J.: Introduction to Multivariate Analysis (revised edition). Chapman & Hall, London, 1986.
10.
Eriksson H., Eklundh L., Hall K., Lindroth A. Estimating LAI in deciduous forest stands. Agricultural and Meteorology, 2005, 129, 27-37.
11.
Górczyński J., Mądry W.: A study of genetic divergence of plants by multivariate methods. Genetica Polonica, 1988, 29, 341-352.
12.
Mahalanobis P.C.: On the generalized distance in statistics. Proceedings of the National Institute of Science of India, 1936, 12, 49-55.
13.
Pandey R.K., Maranville J.W., Chetima M.M.: Deficit irrigation and nitrogen effects on maize in a Sahelian environment. II. Shoot growth, nitrogen uptake and water extraction. Agriculture and Water Management, 2000, 46, 15-27.
14.
Rencher A.C.: Multivariate statistical inference and applications. John Wiley and Sons, New, 1998.
15.
Rybiński W., Szot B., Bocianowski J., Rusinek R.: Geometric properties of grass pea seeds and their mechanical loads. International Agrophysics, 2011, 25, 271-280.
16.
Rybiński W., Szot B., Rusinek R., Bocianowski J.: Estimation of geometric and mechanical properties of seed of Polish cultivars and lines representing selected species of pulse crops. International Agrophysics, 2009, 23, 257-267.
17.
Seidler-Łożykowska K., Bocianowski J.: Evaluation of variability of morphological traits of selected caraway (Carum carvi L.) genotypes. Industrial Crops and Products, 2012, 35, 140-145.
18.
Shamsuddin A.K.M.: Genetic diversity in relation to heterosis and combining ability in spring wheat. Theoretical and Applied Genetics, 1985, 70, 306-308.
19.
Szulc P., Bocianowski J., Rybus-Zając M. Influence of soil supplementation with nitrogen and magnesium on the size of assimilation area of maize cultivars (Zea mays L.) differing in genetic profile. Electronic Journal of Polish Agricultural Universities, 2013, 16 (2), #01.
20.
Vaylay R., van Santen E.: Application of canonical discriminant analysis for the assessment of genetic variation in tall fescue. Crop Science, 2002, 42, 534-539.
21.
Yeater K.M., Bollero G.A., Bullock D.G., Rayburn A.L., Rodriguez-Zas S.: Assessment of genetic variation in hairy vetch using canonical discriminant analysis. Crop Science, 2004, 44, 185-189.