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Analysis of Within-Field Spatial Variation of Rice Growth and Yield in Relation to Soil Properties  

Ahn Nguyen Tuan (Department of Plant Science, Seoul National University)
Shin Jin Chul (National Institute of Crop Science, RDA)
Lee Byun-Woo (Department of Plant Science, Seoul National University)
Publication Information
KOREAN JOURNAL OF CROP SCIENCE / v.50, no.4, 2005 , pp. 221-237 More about this Journal
Abstract
For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.
Keywords
spatial variation; yield; soil property; rice; precision farming;
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1 Bruce, R R, A. W White, A. W. Thomas, W M. Snyder, G. W. Langdale, and H F. Perkins. 1988. Characterization of soilcrop yield relations over a range of erosion on a landscape. Geoderma 43 99-116
2 Cambardella, C. A. and D. L. Karlen 1999 Spatial analysts of soil fertility parameters Precision Agri 1 . 5-14   DOI   ScienceOn
3 Choi H C. 2001 Achievements and advanced technology of new production in Korea. In. S.K Kwon ed. Rice Culture in Asia. Korean National Committee on Irrigation and Drainage (KNCID) pp 55-80
4 De Datta, S. K. 1987. Principles and Practices of Rice Production Malabar, FL
5 Dobermann, A., A. F. Pampolino, and H U. Neue. 1995. Spatial and temporal variability of transplanted nee at field scale. Agron. J. 87 .712-720   DOI   ScienceOn
6 James, I. T. and R. J. Godwin, 2003. Soil, water and yield relationship in developing strategies for the precision application of nitrogen fertiliser to Winter barley. Brosystems Engineering 84 (4). 467-480   DOI   ScienceOn
7 Kravchenko, A. Nand D. G Bullock. 2000. Correlation of com and soybean gram yield with topography and soil properties Agron. J. 92 . 75-83   DOI
8 Mann.T, C 1987. Misuses of linear regression In earth sciences In. W B. Size (Editor)
9 Ovalles, F. A. and M. E Collins. 1986 Soil landscape relationships and soil variability in north central Flonda. Soill Sci. Soc. Am. J. 50 . 401-408   DOI   ScienceOn
10 Pierce, F S, D. D. Warncke, and M. W Everett. 1994. Yield and nutrient availability m glacial soils of Michigan. In: P.C Robert et al. (Ed) Proc 2nd Int. Conf. on Site Specific Management for Agriculture Systems 27-30 March 1994 pp. 133-150
11 Sadler, E. J , B. K. Gerwig, D. E. Evans, W J. Busscher, and P. J. Bauer. 2000. Site-specific modeling of com yield in the SE coastal plain. Agri Syst. 64 . 189-207   DOI   ScienceOn
12 SAS Institute. 2001. SAS System for Windows. Release 8.01. SAS Instrtute Inc. Cary, N.C
13 Sinclair, T. R. and W I. Park. 1993 Inadequacy of the Liebig limiting factor paradgm for explaining varying crop yield. Agron. J. 85: 742-746   DOI   ScienceOn
14 Webster, R. 1997. Regression and functional relations. Eur. J. Soil Sci 48 : 557-566   DOI   ScienceOn
15 Nguyen Tuan Anh, K. J. Choi, J. C ShIN, C. K. Lee, and B.W Lee. 2003. Boundary line analysts of rice yield response to soil chemical properties and its application to the analysis of spatial yield variability, Korean J. Crop Sci (Supl 4) : 123-127
16 Miller, PM., M. J. Singer, and D. R Nielsen. 1995 Spatial variability of wheat yield and soil properties on complex hills, Soil Sci. Soc Am. J 52: 1133-1141   DOI   ScienceOn
17 Casanova, D., J. Goudnaan, J Bouma, and G. F Epema. 1999 Yield gap analysts in relation to Soil properties in direct-seeded flooded rice Geoderma 91(3-4) : 191-216   DOI   ScienceOn
18 Kim, H. Tan. 1996. Soil Sampling, Preparation and Analysis, Marcel Dekker, Inc., Madison Avenue, New York
19 Machada, S 2002. Spatial and temporal variability of sorghum gram yield Influence of Soil, water, pests, and disease relationships, Precision Agri 3 : 389-406   DOI   ScienceOn
20 Machado, S., E. D. Bynum, J. R. Archer, J. Bordovsky, D. T. Rosenow, Peterson C., Bronson K., D. M. Nesmith, R. J. Lascano, L.T. Wilson, and E. Segarra. 2002. Spatial and temporal variation of sorghum gram yield: influence of soil, water, pests, and diseases relationship. Precision Agri 3 : 389-406   DOI   ScienceOn
21 Dobermann, A, K. G. Cassman, P. C. Sta Cruz, M. A. A. Adviento, and M. E Pampolino 1996. Fertilizer inputs, nutrients balance and soil nutrient supplying power In intensive, irrigated nee systems: III. Phosphorous. Nutr Cyc. Agroecosyst. 46 : 111-125   DOI   ScienceOn
22 Cox, M. S., P. D. Gerard, M. C. Wardlaw, and M. J Abshire. 2003. Variability of selected soil properties and their relationships with soybean yield, Soil Sci. Soc. Am. J. 67 : 1296-1302   DOI
23 Sudduth, K A., S. T. Drummond, S. J. Birrell, and N. R. Kitchen. 1996. Analysis of spatial factors influencing crop yield, In: P.C. Robert, R H. Rust, and WE. Larson (ed.). Proceedings of the Third International Conference on Precision Agriculture. ASA, CSSA, SSSA. Madison, WI. pp. 129-140
24 Huang, Z. Wand F. E. Broadbent. 1988. The efficiency of potassium nitrate and urea fertilizers on nee In flooded soil Soil. Sci. 146: 461-465   DOI
25 Sawyer, J. E. 1994. Concepts of van able rate technology with considerations for fertilizer application. J. Prod Agric, 7 : 195-201   DOI
26 Dobermann, D. 1994. Factors causing field variation of direct-seeded flooded rice Geoderma 62(1-3).125-150   DOI   ScienceOn
27 Environmental Systems Research Institute. Acview GIS (ESRI), 1996
28 Timlin, D. J., Y. Pachepsky, V. A Snyder, and R. B Bryant 1998. Spatial and temporal variability of com gram yield on hillslope, Soil Sci. Soc. Am. J. 62 : 764-773   DOI   ScienceOn
29 Cui, R. X. and B. W. Lee. 2002. Spiklet number estimation model using nitrogen nutrition status and biomass at panicle initiation and heading stage of rice. Korean J. Crop Sci. 47 (5): 390-394
30 Cambardella, C A., T. S. Colvin, D L. Karlen, S. D. Logsdon, E C. Berry, J. K Radke, T C. Kaspar, T. B. Parkin, and D B Jaynes 1996 Soil property contributions to yield variation pattern. In P.C. Robert, R H Rust, and WE. Larson (eds) Proceedings of the Third International Conference on Precision Agnculture. ASA, CSSA, SSSA, Inc., Madison, WI. pp. 417-224
31 Cui, R. X., M. H. KIm, J H KIm, H. S. Nam, and B. W Lee 2002. Determination of critical nitrogen dilution curves for nee growth. Korean J. Crop Sci. 47 (2) : 127-131
32 von Liebig, J. 1855. Principles of agricultural chemistry with special reference to the late researches made in England. In: Pomeroy, L.R. Ed., Cycles of Essential Elements
33 Waggoner, P E and W A. Norvell. 1979 Fitting the Law of the Minimum to fertilizer applications and crop yield. Agron. J. 71 : 353-354
34 Walworth, J. L., W. S. Letsch, and M. E. Summer. 1986 Use of boundary lines in establishing diagnostic norms. Soil Sci. Soc. Am. J. 50 : 123-128   DOI   ScienceOn
35 Hair, J. E, R. E. Anderson, R L. Tatham, and W. C. Black. 1992. Multivariate Data Analysis. Macmillan, New York
36 Schnug, E.,J Heym, and D. P Murphy. 1995 Boundary line determination technique BOLIDES. In: Robert, PC, Rust, R.H., Larson, WE. Eds., Site-Specific Management for Agricultural Systems. ASArCSSArSSSA, Madison, WI, pp. 899-908
37 Inamura, T, K Goto, M. Iida, K. Nonarm, H. Inoue, and Mikio 2004 Geostatistical analysis of Yield, soil properties and crop management practices In paddy nee fields. Plant. Proc. Sci. 7 . 230-239
38 Webb, R. A. 1972. Use of the boundary line in the analysis of biological data J. Horncult. Sci 47.309-319
39 Casanova, D , J. Goudman, M. M. Catala Forner, and J. C. M Withagen, 2002. Rice yield prediction from yield components and limiting factors. Eur. J. of Agron. 17 : 41-61   DOI   ScienceOn
40 Trangmar, B. B , R. S. Yost, and G. Uehara. 1985 Application of geostatistics to spatial studies of soil properties. Adv. Agron. 38 : 45-93
41 Geypens, M. 1999. Spatial variability of agricultural soil fertility parameters in a Gleyic Podzol of Belgium. Precision Agri. 1 : 319-326   DOI   ScienceOn