dc.contributorUniv Laval
dc.contributorUniversidade Estadual Paulista (Unesp)
dc.contributorAgr & Agri Food Canada
dc.date.accessioned2014-05-20T13:17:15Z
dc.date.available2014-05-20T13:17:15Z
dc.date.created2014-05-20T13:17:15Z
dc.date.issued2009-08-01
dc.identifierCanadian Journal of Soil Science. Ottawa: Agricultural Inst Canada, v. 89, n. 4, p. 383-390, 2009.
dc.identifier0008-4271
dc.identifierhttp://hdl.handle.net/11449/3786
dc.identifierWOS:000270489000002
dc.identifier0618605154638494
dc.description.abstractParent, L. E., Natale, W. and Ziadi, N. 2009. Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index. Can. J. Soil Sci. 89: 383-390. Compositional nutrient diagnosis (CND) provides a plant nutrient imbalance index (CND - r(2)) with assumed chi(2) distribution. The Mahalanobis distance D(2), which detects outliers in compositional data sets, also has a chi(2) distribution. The objective of this paper was to compare D(2) and CND - r(2) nutrient imbalance indexes in corn (Zea mays L.). We measured grain yield as well as N, P, K, Ca, Mg, Cu, Fe, Mn, and Zn concentrations in the ear leaf at silk stage for 210 calibration sites in the St. Lawrence Lowlands [2300-2700 corn thermal units (CTU)] as well as 30 phosphorus (2300-2700 CTU; 10 sites) and 10 nitrogen (1900-2100 CTU; one site) replicated fertilizer treatments for validation. We derived CND norms as mean, standard deviation, and the inverse covariance matrix of centred log ratios (clr) for high yielding specimens (>= 9.0 Mg grain ha(-1) at 150 g H(2)O kg(-1) moisture content) in the 2300-2700 CTU zone. Using chi(2) = 17 (P < 0.05) with nine degrees of freedom (i.e., nine nutrients) as a rejection criterion for outliers and a yield threshold of 8.6 Mg ha(-1) after Cate-Nelson partitioning between low- and high-yielders in the P validation data set, D(2) misclassified two specimens compared with nine for CND -r(2). The D(2) classification was not significantly different from a chi(2) classification (P > 0.05), but the CND - r(2) classification differed significantly from chi(2) or D(2) (P < 0.001). A threshold value for nutrient imbalance could thus be derived probabilistically for conducting D(2) diagnosis, while the CND - r(2) nutrient imbalance threshold must be calibrated using fertilizer trials. In the proposed CND - D(2) procedure, D(2) is first computed to classify the specimen as possible outlier. Thereafter, nutrient indices are ranked in their order of limitation. The D(2) norms appeared less effective in the 1900-2100 CTU zone.
dc.languageeng
dc.publisherAgricultural Inst Canada
dc.relationCanadian Journal of Soil Science
dc.relation1.085
dc.relation0,520
dc.rightsAcesso restrito
dc.sourceWeb of Science
dc.subjectNutrient balance
dc.subjectsimplex closure
dc.subjectvariance-covariance matrix
dc.subjectchi(2) distribution
dc.subjectgrain corn
dc.subjectnitrogen and phosphorus fertilization
dc.titleCompositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index
dc.typeArtículos de revistas


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