Compositional nutrient diagnosis of corn using the Mahalanobis distance as nutrient imbalance index

Canadian Journal of Soil Science

Volumn 89, Issue 4, 2009, Pages 383-390

  Parent, Léon Etienne ^a   Natale, William ^b   Ziadi, Noura ^c  

^a UNIVERSITÉ LAVAL   (Canada)

^b SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^c AGRICULTURE AND AGRI FOOD CANADA   (Canada)

Author keywords

2 distribution; Grain corn; Nitrogen and phosphorus fertilization; Nutrient balance; Simplex closure; Variance covariance matrix

Indexed keywords

CALIBRATION; CLASSIFICATION; CROP YIELD; EQUATION; FERTILIZER APPLICATION; LOWLAND ENVIRONMENT; MAIZE; MEASUREMENT METHOD; MODEL VALIDATION; MOISTURE CONTENT; NUTRIENT AVAILABILITY; NUTRIENT DYNAMICS; PARTITIONING;

NORTH AMERICA; SAINT LAWRENCE LOWLANDS;

ZEA MAYS;

EID: 68949156321     PISSN: 00084271     EISSN: None     Source Type: Journal    
DOI: 10.4141/cjss08050     Document Type: Article

References (26)

1. We thank the Natural Sciences and Engineering Research Council of Canada (NSERC-DG 2254-04) for financial support.
2. Agriculture and Agri-Food Canada. 2008. Thermal units (corn) (Quebec region). [Online] Available: http://www.agr.gc.ca/pfra/drought/maps/qc- ch-tmp-s-f.pdf.
3. Aitchison, J. 1986. Statistical analysis of compositional data. Chapman & Hall, New York, NY.
4. Baldock, J. O. and Schulte, E. E. 1996. Plant analysis with standardized scores combines DRIS and sufficiency range approaches for corn. Agron. J. 88: 448-456.
5. Bates, T. E. 1971. Factors affecting critical nutrient concentrations in plants and their evaluation: A review. Soil Sci. 12: 116-130.
6. Beaufils, E. R. 1973. Diagnosis and recommendation integrated system (DRIS). Soil Sci. Bull. No. 1, University of Natal, Pietermaritzburg, South Africa.
7. Benton Jones, J., Jr., Wolf, B. and Mills, H. A. 1991. Plant analysis handbook. A practical sampling, preparation, analysis, and interpretation guide. Micro-Macro Publ. Inc., Athens, GA.
8. Dara, S. T., Fixen, P. E. and Gelderman, R. H. 1992. Sufficiency level and diagnosis and recommendation integrated system approaches for evaluating the nitrogen status of corn. Agron. J. 84: 1006-1010.
9. Elwali, A. M. O., Gascho, G. J. and Sumner, M. E. 1985. DRIS norms for 11 nutrients in corn leaves. Agron. J. 77: 506-508.
10. Filzmoser, P. and Hron, K. 2008. Outlier detection for compositional data using robust methods. Math. Geosci. 40: 233-248.
11. Giampietro, M. 2004. Multi-scale integrated analysis of agroecosystems. CRC Press, Boca Raton, FL.
12. Hadi, A. 1992. Identifying multiple outliers in multivariate data. J. R. Statist. Soc. B 54: 761-771.
13. Hadi, A. 1994. A modification of a method for the detection of outliers in multivariate samples. J. R. Statist. Soc. B 56: 393-396.
14. Hollander, M. and Wolfe, D. A. 1999. Nonoparametric statistical methods. 2nd ed. Wiley Interscience Publ., New York, NY.
15. Khiari, L., Parent, L. E. and Tremblay, N. 2001a. Critical compositional nutrient indexes for sweet corn at early growth stage. Agron. J. 93: 809-814.
16. Khiari, L., Parent, L. E. and Tremblay, N. 2001b. Selecting the high-yield subpopulation for diagnosing nutrient imbalance in crops. Agron. J. 93: 802-808.
17. Martin-Fernandez, J. A., Barcelo-Vidal, C. and Pawlowsky, V. 2003. Dealing with zeros and missing values in compositional data sets using nonparametric imputation. Math. Geol. 35: 253-278.
18. Nelson, L. A. and Anderson, R. L. 1984. Partitioning of soil test-crop response probability. Pages 19-38 in M. Stelly, ed. Soil testing: Correlating and interpreting the analytical results. ASA Special Publication 29. ASA, Madison, WI.
19. Parent, L. E. and Dafir, M. 1992. Theoretical concept of compositional nutrient diagnosis. J. Am. Soc. Hortic. Sci. 117: 239-242.
20. Parent, A. C., Bélanger, M. C., Parent, L. E., Santerre, R., Viau, A. A., Anctil, F., Bounder, M. A. and Tremblay, C. 2008. Soil properties and landscape factors affecting corn yield under wet spring conditions in eastern Canada. Biosyst. Eng. 99: 134-144.
21. Reis, Jr., R. D. A. 2002. DRIS norms universality in the corn crop. Commun. Soil Sci. Plant Anal. 33: 711-735.
22. Ross, S. M. 1987. Introduction to probability and statistics for engineers and scientists. John Wiley & Sons, New York, NY.
23. Skyue, M. L., Shu-Ching, C., Sarinnapakorn, K. and Chang, L. W. 2006. Principal component-based anomaly detection scheme. Studies Comput. Intell. 9: 311-329.
24. Soltanpour, P. N., Malakouti, M. J. and Ronaghi, A. 1995. Comparison of diagnosis and recommendation integrated system and nutrient sufficient range of corn. Soil Sci. Soc. Am. J. 59: 133-139.
25. Umesh, U. N., Peterson, R. A., McCann-Nelson, M. and Vaidyanathan, R. 1996. Type IV error in marketing research: The investigation of ANOVA interactions. J. Acad. Marketing Sci. 24: 17-26.
26. Urricariet, S., Lavado, R. S. and Martin, L. 2004. Corn response to fertilization and SR, DRIS, and PASS interpretation of leaf and grain analysis. Commun. Soil Sci. Plant Anal. 35: 413-425.