Foliar Nutrient Balance Standards for Maize (Zea mays L.) at High-Yield Level

Viviane Cristina Modesto, Serge-Étienne Parent, William Natale, Léon Etienne Parent

Departamento de Solos e Adubos, Unesp, Universidade Estadual Paulista, Jabotocabal, Brazil.
ERSAM, Department of Soils and Agrifood Engi-neering, Université Laval, Québec, Canada.

DOI: 10.4236/ajps.2014.54064                

Abstract

Maize is one of the most nutrient demanding staple crops. Tissue nutrient diagnosis of maize is currently conducted using critical nutrient concentration or dual ratio ranges, but such diagnoses are pathological as biased by data redundancy, sub-compositional incoherence and non-normal distribution. The use of orthogonal balances, a compositional data analysis technique, avoids such biases. Our objective was to develop foliar nutrient balance standards for maize. We collected 758 grain yields (15.5% moisture content) and foliar samples at silk stage in maize fields of southern Quebec, Canada, and analyzed ten nutrients in tissues (N, P, K, Ca, Mg, B, Cu, Zn, Mn, Fe). Nutrients were arranged into ad hoc balances and computed as isometric log ratios (ilr). An optimized binary classification performed by a customized receiver operating characteristic procedure showed that a critical Mahalanobis distance of 4.21 separated balanced from imbalanced specimens about yield cut-off of 11.83 Mg grain·ha^-1 with test performance of 86%. Quebec maize balance standards differed from published standards computed from DRIS norms collected in other agroecosystems. The Redfield N/P ratio in maize leaves was found to be the least variable balance across regions of the world. The DRIS dual ratios and raw concentration values were found to be geometrically inadequate for conducting diagnosis. The unbiased nutrient balance diagnosis combined the critical Mahalanobis distance and a mobile representation of nutrient balances with ilr means of true negative (TN) specimens centered at fulcrums and back-transformed ilr values of TN specimens into raw concentrations loading the buckets below. Nutrients can be appreciated as relative shortage, adequacy or excess in the concentration domain following statistical analysis and diagnosis in the unbiased balance domain.

Keywords

Compositional Data Analysis; Critical Range; Diagnosis and Recommendation Integrated System; DRIS; Ionomics; Nutrient Balance; Nutrient Interactions

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	J. B. Jones Jr., B. Wolf and H. A. Mills, “Plant Analysis Handbook: A Practical Sampling, Preparation, Analysis, and Interpretation Guide, Micro Macro Intl.,” Athens, 1991.
[2]	E. Malavolta, “Manual de Nutrição de Plantas,” Editora Agronomica Ceres, São Paulo, 2006, p. 638.
[3]	S. R. Wilkinson, “Nutrient Interactions in Soil and Plant Nutrition,” In: M. E. Sumner, Ed., Handbook of Soil Science, CRC Press, Boca Raton, 2000, pp. D89-D112.
[4]	J. L. Walworth and M. E. Sumner, “The Diagnosis and Recommendation Integrated System (DRIS),” Advances in Soil Science, Vol. 6, 1987, pp. 149-188. http://dx.doi.org/10.1007/978-1-4612-4682-4_4
[5]	J. Aitchison and M. Greenacre, “Biplots of Compositional Data,” Journal of the Royal Statistical Society Series C Applied Statistics, Vol. 51, No. 4, 2002, pp. 375-392. http://dx.doi.org/10.1111/1467-9876.00275
[6]	S.-é. Parent, L. E. Parent, D. E. Rozane, A. Hernandes and W. Natale, “Nutrient Balance as Paradigm of Soil and Plant Chemometrics,” In: R. N. Issaka, Ed., Soil Fertility, Intech, 2012, pp. 83-114. http://dx.doi.org/10.5772/53343
[7]	P. G. S. Wadt and D. J. Silva, “Acurácia Do Diagnóstico Nutricional de Pomares de Mangueiras Obtido Por Três Fórmulas DRIS,” Pesquisa Agropecuária Brasileira, Vol. 45, No. 10, 2010, pp. 1180-1188. http://dx.doi.org/10.1590/S0100-204X2010001000018
[8]	S.-é. Parent, L. E. Parent, D. E. Rozane and W. Natale, “Nutrient Balance Ionomics: Case Study with Mango (Mangifera indica),” Frontiers in Plant Science, Vol. 4, 2013, Article 449.
[9]	S.-é. Parent, L. E. Parent, J. J. Egozcue, D. E. Rozane, A. Hernandes, L. Lapointe, V. Hébert-Gentile, et al., “The Plant Ionome Revisited by the Nutrient Balance Concept,” Frontiers in Plant Science, Vol. 4, No. 39, 2013, pp. 1-10.
[10]	G. G. C. Da Silva, J. C. L. Neves, V. H. Alvarez and F. P. Leite, “Nutritional Diagnosis for Eucalypt by DRIS, MDRIS, and CND,” Scientia Agricola, Vol. 61, No. 5, 2004, pp. 507-515. http://dx.doi.org/10.1590/S0103-90162004000500008
[11]	F. R. Blanco-Macías, R. D. Magallanes-Quintanar, R. Valdez-Cepeda, E. Vázquez-Alvarado, E. Olivares-Sáenz, E. Gutiérrez-Ornelas and J. A. Vidales-Contreras, “Comparison between CND Norms and Boundary-Line Approach Nutrient Standards: Opuntia Ficus-Indica L. Case. R. Chapingo,” Serie Horticultura, Vol. 15, No. 2, 2009, pp. 217-223.
[12]	H. Huang, C. X. Hu, Q. Tan, X. Hu, X. Sun and L. Bi, “Effects of Fe-EDDHA Application on Iron Chlorosis of Citrus Trees and Comparison of Evaluations on Nutrient balance with Three Approaches,” Scientia Horticulturae, Vol. 146, 2012, pp. 137-142. http://dx.doi.org/10.1016/j.scienta.2012.08.015
[13]	L. W. I. Wairegi and P. J. A. Van Asten, “Norms for Multivariate Diagnosis of Nutrient Imbalance in Arabica and Rosusta Coffee in the East African Highlands,” Experimental Agriculture, Vol. 48, No. 3, 2012, pp. 448-460. http://dx.doi.org/10.1017/S0014479712000142
[14]	P. Marschner, “Marschner’s Mineral Nutrition of Higher Plants,” 3rd Edition, Academic Press, London, 2011.
[15]	J. Aitchison, “The Statistical Analysis of Compositional Data, Monographs on Statistics and Applied Probability,” Chapman & Hall Ltd., London, 1986. http://dx.doi.org/10.1007/978-94-009-4109-0
[16]	J. Bacon-Shone, “A Short History of Compositional Data Analysis,” In: V. Pawlowsky-Glahn and A. Buccianti, Eds., Compositional Data Analysis: Theory and Applications, John Wiley and Sons, New York, 2011, pp. 3-11. http://dx.doi.org/10.1002/9781119976462.ch1
[17]	J. J. Egozcue, V. Pawlowsky-Glahn, G. Mateu-Figueras and C. Barceló-Vidal, “Isometric Logratio Transformations for Compositional Data Analysis,” Mathematical Geology, Vol. 35, No. 3, 2003, pp. 279-300. http://dx.doi.org/10.1023/A:1023818214614
[18]	L. E. Parent and M. Dafir, “A Theoretical Concept of Compositional Nutrient Diagnosis,” Journal of the American Society for Horticultural Science, Vol. 117, No. 2, 1992, pp. 239-242.
[19]	L. E. Parent, “Diagnosis of the Nutrient Compositional Space of Fruit Crops,” Revista Brasileira de Fruticultura, Vol. 33, No. 1, 2011, pp. 321-334. http://dx.doi.org/10.1590/S0100-29452011000100041
[20]	P. Filzmoser, K. Hron and C. Reimann, “Univariate Statistical Analysis of Environmental (Compositional) Data: Problems and Possibilities,” Science of Total Environment, Vol. 407, No. 23, 2009, pp. 6100-6108. http://dx.doi.org/10.1016/j.scitotenv.2009.08.008
[21]	L. E. Parent, S.-é. Parent, V. Hébert-Gentile, K. Naess and L. Lapointe, “Mineral Balance Plasticity of Cloudberry (Rubus Chamaemorus) in Quebec-Labrador,” American Journal of Plant Science, Vol. 4, No. 7, 2013, pp. 1508-1520.
[22]	L. E. Parent, S.-é. Parent, D. E. Rozane, D. A. Amorim, A. Hernandes and W. Natale, “Unbiased Approach to Diagnose the Nutrient Status of Guava,” Proceedings of the 3rd International Symposium on Guava and Other Myrtaceae, Acta Horticulturae, Vol. 959, 2012, pp. 145-159.
[23]	J. J. Egozcue and V. Pawlowsky-Glahn, “Groups of Parts and Their Balances in Compositional Data Analysis,” Mathematical Geology, Vol. 37, No. 7, 2005, pp. 795-828. http://dx.doi.org/10.1007/s11004-005-7381-9
[24]	V. Pawlowsky-Glahn, J. J. Egozcue and R. Tolosana-Delgado, “Principal Balances,” In: 4th International Workshop on Compositional Data Analysis (Codawork 2011), San Feliu de Guixols, Spain, 2011.
[25]	G. De Rijk and E. Schrevens, “Distribution of Nutrients and Water in Rockwool Slabs,” Scientia Horticulturae, Vol. 72, No. 3-4, 1998, pp. 277-285. http://dx.doi.org/10.1016/S0304-4238(97)00144-1
[26]	I. Loladze and J. J. Elser, “The Origins of the Redfield Nitrogen-to-Phosphorus Ratio Are in a Homoeostatic Protein-to-rRNA Ratio,” Ecology Letters, Vol. 14, No. 3, 2011, pp. 244-250. http://dx.doi.org/10.1111/j.1461-0248.2010.01577.x
[27]	J. B. Jones Jr. and V. W. Case, “Sampling, Handling, and Analyzing Plant Tissue Samples,” In: R. L. Westerman, Ed., Soil Testing and Plant Analysis, Book Series 3, Soil Science Society of America, Madison, 1990, pp. 389-427.
[28]	R Development Core Team, “R: A Language and Environment for Statistical Computing,” R. T. D. Core, Ed., R Foundation for Statistical Computing, Vienna, 2013.
[29]	K. G. van den Boogaart, R. Tolosana-Delgado and M. Bren, “‘Compositions’: Compositional Data Analysis in R Package,” 2013. http://cran.rproject.org/package=compositions
[30]	P. Filzmoser and M. Gschwandtner, “‘Mvoutlier’: Multivariate Outlier Detection Based on Robust Methods,” CRAN Repository, Vienna, 2013.
[31]	J. Daunis-i-Estadella, C. Barceló-Vidal, C. and A. Buccianti, “Exploratory Compositional Data Analysis,” In: A. Buccianti, G. Mateu-Figueras and V. Pawlowsky-Glahn, Eds., Compositional Data Analysis in the Geosciences: From Theory to Practice, Geological Society, London, Special Publications 264, 2001, pp. 161-174.
[32]	Z. Prekopcsák and L. Lemire, “Time Series Classification by Class-Specific Mahalanobis Distance Measures. Learning,” Advances in Data Analysis and Classification, Vol. 6, No. 3, 2012, pp. 185-200. http://dx.doi.org/10.1007/s11634-012-0110-6
[33]	J. A. Swets, “Measuring the Accuracy of Diagnostic Systems,” Science, Vol. 240, No. 4857, 1988, pp. 1285-1293. http://dx.doi.org/10.1126/science.3287615
[34]	W. J. Youden, “Index for Rating Diagnostic Tests,” Cancer, Vol. 3, No. 1, 1950, pp. 32-35. http://dx.doi.org/10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3
[35]	M. E. Sumner, “Effect of Corn Leaf Sampled on N, P, K, Ca and Mg Content and Calculated DRIS Indices,” Communications in Soil Science and Plant Analysis, Vol. 8, No. 3, 1977, pp. 269-280. http://dx.doi.org/10.1080/00103627709366719
[36]	A. M. O. Elwali, G. J. Gascho and M. E. Sumner, “DRIS Norms for 11 Nutrients in Corn Leaves,” Agronomy Journal, Vol. 77, No. 3, 1985, pp. 506-508. http://dx.doi.org/10.2134/agronj1985.00021962007700030032x
[37]	T. D. Needham, J. A. Burger and R. G. Oderwald, “Relationship between Diagnosis and Recommendation Integrated System (DRIS) Optima and Foliar Nutrient Critical Levels,” Soil Science Society of America Journal, Vol. 54, No. 3, 1990, pp. 883-886. http://dx.doi.org/10.2136/sssaj1990.03615995005400030045x
[38]	P. N. Soltanpour, M. J. Malakouti and A. Ronaghi, “Comparison of Diagnosis and Recommendation Integrated System and Nutrient Sufficiency Range for Corn,” Soil Science Society of America Journal, Vol. 59, No. 1, 1995, pp. 133-139. http://dx.doi.org/10.2136/sssaj1995.03615995005900010021x
[39]	K. Singh, H. S. Hundal and D. Singh, “Monitoring Nutrient Status for Maize in Northwestern India through Diagnosis and Recommendation Integrated System Approach,” Communications in Soil Science and Plant Analysis, Vol. 43, No. 22, 2012, pp. 2915-2923. http://dx.doi.org/10.1080/00103624.2012.728267
[40]	A. C. D. Rocha, W. M. Leandro, A. O. Rocha, J. D. G. Santana and J. W. D. S. Andrade, “DRIS Norms for Corn Planted in Reduced Row Spacing in Hidrolandia, State of Goias, Brazil,” Bioscience Journal, Vol. 23, No. 4, 2007, pp. 50-60.
[41]	G. D. Dagbenonbakin, A. K. Srivastava, T. Gaiser and H. Glodbach, “Maize Nutrient Assessment in Benin Republic: Case of Upper Ouémé Catchment,” Journal of Plant Nutrition, Vol. 36, No. 4, 2013, pp. 587-606. http://dx.doi.org/10.1080/01904167.2012.754031
[42]	S. T. Dara, P. E. Fixen and R. H. Gerlderman, “Sufficiency Level and Diagnosis and Recommendation Integrated System Approaches for Evaluating the Nitrogen Status of Corn,” Agronomy Journal, Vol. 84, No. 6, 1992, pp. 1006-1010. http://dx.doi.org/10.2134/agronj1992.00021962008400060020x
[43]	C. R. Escano, C. A. Jones and G. Uehara, “Nutrient Diagnosis in Corn Grown on Hydric Dystradepts: II. Comparison of Two Systems of Tissue Diagnosis,” Soil Science Society of America Journal, Vol. 45, No. 6, 1981, pp. 1140-1144. http://dx.doi.org/10.2136/sssaj1981.03615995004500060026x
[44]	H. Delacour, A. Servonnet, A. Perrot, J. F. Virgezzi and J. M. Ramirez, “La Courbe ROC (Receiver Operating Characteristic): Principes et Principales Applications en Biologie Clinique,” Annales de Biologie Clinique, Vol. 63, No. 2, 2005, pp. 145-154.
[45]	R. Beverly, “Comparison of DRIS and Alternative Diagnostic Methods for Soybean,” Journal of Plant Nutrition, Vol. 1, No. 8, 1987, pp. 901-920. http://dx.doi.org/10.1080/01904168709363619
[46]	L. E. Parent, W. Natale and N. Ziadi, “Compositional Nutrient Diagnosis of Corn Using the Mahalanobis Distance as Nutrient Imbalance Index,” Canadian Journal of Soil Science, Vol. 89, No. 4, 2009, pp. 383-390. http://dx.doi.org/10.4141/cjss08050
[47]	S. Güsewwell, “N:P Ratios in Terrestrial Plants: Variation and Functional Significance,” New Phytologist, Vol. 164, No. 2, 2004, pp. 243-266. http://dx.doi.org/10.1111/j.1469-8137.2004.01192.x
[48]	C. Bould, “Leaf Analysis as a Diagnostic Method and Advisory Aid in Crop Production,” Experimental Agriculture, Vol. 4, No. 1, 1968, pp. 17-27. http://dx.doi.org/10.1017/S0014479700022316