Skip to main content
Log in

Spatial assessment of the correlation of seeding depth with emergence and yield of corn

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Germination conditions are determined by hydraulic, thermal and mechanical properties of the soils. In heterogeneous fields, the most favourable seeding depth varies spatially. To investigate the influence of seeding depth on emergence and grain yield of corn, corn was planted in depths of 40, 50, 60, 70, 80 and 90 mm in three experimental years (2006–2008). The apparent soil electrical conductivity was measured with an EM38. The apparent electrical conductivity was used as a proxy for soil texture, top-soil thickness, effective root zone thickness, soil water content and soil structure. The spatial dependencies among emergence, yield and apparent electrical conductivity were considered by including spatial models into the statistical analysis. The results showed significant correlations of the apparent soil electrical conductivity, of the experimental year, and of the seeding depth with the emergence of corn. Deeper planted corn (80 or 90 mm) resulted in more emergence than shallow planted corn (+4.4% in 2006, +1.2% in 2007 and +1.5% in 2008). The emergence decreased with increasing apparent soil electrical conductivity values. The corn grain yield was significantly affected by the soil electrical conductivity, by emergence and by the experimental year. Increasing apparent soil electrical conductivity values were correlated with decreasing yield (from 7.5 to 3.4 Mg ha−1 in 2006, from 10.8 to 5.3 Mg ha−1 in 2007 and from 8.4 to 2.9 Mg ha−1 in 2008). Increasing emergence resulted in increasing yield.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723.

    Article  Google Scholar 

  • Aldrich, S., Scott, W., & Leng, E. (1975). Modern corn production (2nd ed.). Champaign: A & L Publications.

    Google Scholar 

  • Alessi, J., & Power, J. F. (1971). Corn emergence in relation to soil temperature and seeding depth. Agronomy Journal, 63, 717–719.

    Article  Google Scholar 

  • Becker, R., Chambers, J., & Wilks, A. (1988). The new S language: A programming environment for data analysis and graphics. Monterey: Wadsworth and Brooks/Cole.

    Google Scholar 

  • Berry, D., & Lindgren, B. (1996). Statistics: Theory and methods. Belmont: Duxbury Press.

    Google Scholar 

  • Blacklow, W. M. (1972). Influence of temperature on germination and elongation of the radicle and shoot of corn. Crop Science, 12, 647–650.

    Article  Google Scholar 

  • Buchner, W. (2003). Optimales Bodengefüge sichert Maiserträge (optimum soil structure ensures corn yield). Mais, 31, 120–123.

    Google Scholar 

  • Buckle, J. A., & Grant, P. M. (1974). Effects of soil temperature on plumule growth and seedling emergence of maize. The Rhodesian Journal of Agricultural Research, 12, 149–161.

    Google Scholar 

  • Bundestag. (2007). Gesetz zur Schätzung des landwirtschaftlichen Kulturbodens (Federal law of Germany on taxation of agricultural soils). Bundesgesetzblatt I, 3150, 3176.

    Google Scholar 

  • Bunting, ES. (1978) Agronomic and physiological factors affecting forage maize production. In ES. Bunting, BF. Pain, RH. Phipps, JM. Wilkinson & RE. Gunn (Eds.), Forage Maize production and utilization (pp. 57–85). London: Agricultural Research Council.

  • Coffman, F. A. (1923). The minimum temperature of germination of seeds. Journal of the American Society of Agronomy, 15, 257–270.

    Article  Google Scholar 

  • Collis-George, N., & Sands, J. E. (1959). The control of seed germination by moisture as a soil physical property. Australian Journal of Agricultural Research, 10, 628–637.

    Article  Google Scholar 

  • Corwin, D., & Lesch, S. (2003). Application of soil electrical conductivity to precision agriculture: Theory, principles, and guidelines. Agronomy Journal, 95, 455–471.

    Article  Google Scholar 

  • Corwin, D., & Lesch, S. (2005). Apparent soil electrical conductivity measurements in agriculture. Computers and Electronics in Agriculture, 46, 11–43.

    Article  Google Scholar 

  • Corwin, D., Lesch, S., Shouse, P., Soppe, R., & Ayars, J. (2003). Identifying soil properties that influence cotton yield using soil sampling directed by apparent soil electrical conductivity. Agronomy Journal, 95, 352–364.

    Article  Google Scholar 

  • Crawley, M. (2005). Statistics: An introduction using R. Chichester: Wiley.

    Book  Google Scholar 

  • Crawley, M. (2007). The R Book. Chichester: Wiley.

    Book  Google Scholar 

  • Cummins, D. G., & Parks, W. L. (1961). The germination of corn and wheat as affected by various fertilizer salts at different soil temperatures. Soil Science Society of America Proceedings, 25, 47–49.

    Article  CAS  Google Scholar 

  • Dasberg, S., & Mendel, K. (1971). The effect of soil water and aeration on seed germination. Journal of Experimental Botany, 22, 992–998.

    Article  Google Scholar 

  • Dexter, A. R., & Bird, N. R. A. (2001). Methods for predicting the optimum and the range of soil water contents for tillage based on the water retention curve. Soil and Tillage Research, 57, 203–212.

    Article  Google Scholar 

  • Erickson, R. O. (1959). Integration of plant growth process. American Naturalist, 93, 225–235.

    Article  Google Scholar 

  • FAO (1998) World reference base for soil resources. In World soil resource report (84 edn). Rome, Italy: FAO.

  • Geonics Limited. (1997). Application of electromagnetic methods: Soil salinity. Mississauga, Canada: Geonics Limited.

    Google Scholar 

  • Geyer, O., & Gwinner, M. (1991). Regional Geology of the State of Baden Württemberg, Germany. Stuttgart, Germany: Schweizerbart.

    Google Scholar 

  • Grossmann, W. (1976). Geodätische Rechnungen und Abbildungen in der Landesvermessung (geodetic calculations and figures for state land survey). Stuttgart, Germany: Konrad Wittwer.

    Google Scholar 

  • Gupta, S., Schneider, E., & Swan, J. B. (1988). Planting depth and tillage interactions on corn emergence. Soil Science Society of America Journal, 52, 1122–1127.

    Article  Google Scholar 

  • Hadas, A. (1970). Factors affecting seed germination under soil moisture stress. The Israel Journal of Agricultural Research, 20, 3–14.

    Google Scholar 

  • Hadas, A., & Russo, D. (1974). Water uptake by seeds as affected by water stress, capillary conductivity, and seed-soil water contact. Agronomy Journal, 66, 643–647.

    Article  Google Scholar 

  • Hadas, A., & Stibbe, E. (1973). An analysis of soil water movement towards seedlings prior to emergence. In A. Hadas, D. Swartzendruber, P. E. Rijtema, M. Fuchs, & B. Yaron (Eds.), Physical Aspects of Soil Water and Salts in Ecosystems (4th ed., pp. 97–106). Berlin, Germany: Springer-Verlag.

    Chapter  Google Scholar 

  • Hunter, J. R., & Erickson, A. E. (1952). Relation of seed germination to soil moisture tension. Agronomy Journal, 44, 107–109.

    Article  CAS  Google Scholar 

  • Inman, D., Freeland, R., Ammons, J., & Yoder, R. (2002). Soil investigations using electromagnetic induction and ground-penetrating radar in southwest Tennessee. Soil Science Society of America Journal, 66, 206–211.

    Article  CAS  Google Scholar 

  • Itabari, J., Gregory, P., & Jones, R. (1993). Effect of temperature, soil water status and depth of planting on germination and emergence of maize. Experimental Agriculture, 29, 351–364.

    Article  Google Scholar 

  • King, J., Dampney, P., Lark, M., Mayr, T., & Bradley, R. (2001). Sensing soil spatial variability by electro-magnetic induction (emi): Its potential in precision farming. In G. Grenier & S. Blackmore (Eds.), Proceedings of the 3rd European Conference on Precision Agriculture (pp. 419–424). Montpellier, France: Agro Montpellier.

    Google Scholar 

  • Kitchen, N., Sudduth, K., & Drummond, S. (1999). Soil electrical conductivity as a crop productivity measure for claypan soils. Journal of Production Agriculture, 12, 607–617.

    Google Scholar 

  • Knappenberger, T., & Köller, K. (2006) The dynamic variation of seeding depth of corn. In Proceedings of the 8th international conference on precision agriculture and other precision resources management. Minneapolis, USA. CDROM.

  • Labouriau, L. G. (1978). Seed germination as a thermobiological problem. Radiation and Environmental Biophysics, 15, 345–366.

    Article  PubMed  CAS  Google Scholar 

  • Lehenbauer, P. A. (1914). Growth of maize seedlings in relation to temperature. Physiological Researches, 1, 247–288.

    Google Scholar 

  • McNeill, J. D. (1980). Electromagnetic terrain conductivity measurements at low induction numbers. Technical note TN-6. Mississauga, Canada: Geonics Limited.

    Google Scholar 

  • Miedema, P. (1982). The effects of low temperature on zea mays. Advances in Agronomy, 35, 93–128.

    Article  Google Scholar 

  • Miltner, R. (2003). Ursachen für schlechten Feldaufgang (reasons for low emergence). Mais, 31, 48–50.

    Google Scholar 

  • Molatudi, R., & Mariga, I. (2009). The effect of maize seed size and depth of planting on seedling emergence and seedling vigour. Journal of Applied Sciences Research, 5, 2234–2237.

    Google Scholar 

  • Mueller, T., Hartsock, N., Stombaugh, T., SA, S., Cornelius, P., & Barnisel, R. (2003). Soil electrical conductivity map variability in limestone soils overlain by loess. Agronomy Journal, 95, 496–507.

    Article  Google Scholar 

  • Muldoon, J. F., & Daynard, T. B. (1981). Effect of within-row plant uniformity on grain yield of maize. Canadian Journal of Plant Science, 61, 887–894.

    Article  Google Scholar 

  • Murungu, F. S., Nyamugafata, P., Chiduza, C., Clark, L. J., & Whalley, W. R. (2003). Effects of seed priming, aggregate size and soil matric potential on emergence of cotton and maize. Soil and Tillage Research, 74, 161–168.

    Article  Google Scholar 

  • Nielsen, D. R., & Wendroth, O. (2003). Spatial and temporal statistics: Sampling field soils and their vegetation. Reiskirchen, Germany: Catena Verlag.

    Google Scholar 

  • Nsr, H. M., & Selles, F. (1995). Seedling emergence as influenced by aggregate size, bulk density, and penetration resistance of the seedbed. Soil and Tillage Research, 34, 61–76.

    Article  Google Scholar 

  • Petersen, R. (1996). Agricultural field experiments: Design and analysis. New York, USA: Marcel Dekker.

    Google Scholar 

  • Pinheiro, J., & Bates, D. (2000). Mixed effect models in S and S-Plus. New York, USA: Springer.

    Book  Google Scholar 

  • Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Development Core Team (2011) NLME: Linear and nonlinear mixed effects models. R package version 3.1–101. URL http://cran.r-project.org/web/packages/nlme/.

  • Pommel, B. (1990). Influence du poids de la semence et de la profondeur de semis sur la croissance et le developpement de la plantule de mais (effects of seed weight and sowing depth on growth and development of maize seedlings). Agronomie, 10, 699–708.

    Article  Google Scholar 

  • Rodgers, J., & Nicewander, A. (1988). Thirteen ways to look at the correlation coefficient. The American Statistician, 42, 59–66.

    Article  Google Scholar 

  • Saey, T., Simpson, D., Vermeersch, H., Cockx, L., & van Meirvenne, M. (2009). Comparing the em38dd and dualem-21 s sensors for depth-to-clay mapping. Soil Science Society of America Journal, 73, 7–12.

    Article  CAS  Google Scholar 

  • Saey, T., Simpson, D., Vitharana, U., Vermeersch, H., Vermang, J., & van Meirvenne, M. (2008). Reconstructing the paleotopography beneath the loess cover with the aid of an electromagnetic induction sensor. Catena, 74, 58–64.

    Article  Google Scholar 

  • Schabenberger, O., & Pierce, F. (2002). Contemporary statistical models for the plant and soil science. Boca Ration, USA: CRC Press.

    Google Scholar 

  • Schneider, E. C., & Gupta, S. C. (1985). Corn emergence as influenced by soil temperature, ma-tric potential, and aggregate size distribution. Soil Science Society of America Journal, 49, 415–422.

    Article  Google Scholar 

  • Schutte, B. (2005) Bestimmung von Bodenunterschieden durch Zugkraftmessungen bei der Bodenbearbeitung (determination of soil heterogeneity through draught force measurements during soil tillage). PhD thesis, University of Hohenheim, Germany.

  • Shaykewich, C. F. (1973). Proposed method for measuring swelling pressure of seeds prior to germination. Journal of Experimental Botany, 24, 1056–1061.

    Article  Google Scholar 

  • Sheets, K., & Hendrickx, J. (1995). Non-invasive soil water content measurement using electromagnetic induction. Water Resources Research, 31, 2401–2409.

    Article  Google Scholar 

  • ISO standard 11277 (1998) Soil quality––determination of particle size distribution in mineral soil material––method by sieving and sedimentation (ISO 11277:1998). Geneva, Switzerland: International Organization for Standardization.

  • Sudduth, K., Drummond, S., & Kitchen, N. (2001). Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture. Computers and Electronics in Agriculture, 31, 239–264.

    Article  Google Scholar 

  • R Development Core Team (2009) R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. URL http://www.R-project.org.

  • Thomason, W., Phillips, S., Alley, M., Davis, P., Lewis, M. & Johnson, S. (2008) In-row subsoil tillage and planting depth influence on corn plant population and yield on sandy-textured mid-atlantic coastal plain soils. Crop Management. doi:10.1094/CM-2008-0519-01-RS.

  • Thompson, A., Gantzer, C., & Anderson, S. (1991). Topsoil depth, fertility, water management, and weather influences on yield. Soil Science Society of America Journal, 55, 1085–1091.

    Article  Google Scholar 

  • Warrick, A., Myers, D., & Nielsen, D. (1986). Geostatistical methods applied to soil science. In G. Campbell, D. Nielsen, R. Jackson, A. Klute, & M. Mortland (Eds.), Methods of soil analysis Part 1: physical and mineralogical methods (2nd ed., pp. 53–90). Madison, USA: Soil Science Society of America.

    Google Scholar 

  • Zscheischler, J. (1990). Handbuch Mais (corn guide) (Vol. 4). Frankfurt am Main, Germany: DLG-Verlags-GmbH.

    Google Scholar 

  • Zuur, A., Ieno, E., Walker, N., Saveliev, A., & Smith, G. (2009). Mixed effects models and extensions in ecology with R. New York, USA: Springer.

    Book  Google Scholar 

Download references

Acknowledgments

We thank the Amazone company and the Federal Ministry of Education and Research for funding this study.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to T. Knappenberger.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Knappenberger, T., Köller, K. Spatial assessment of the correlation of seeding depth with emergence and yield of corn. Precision Agric 13, 163–180 (2012). https://doi.org/10.1007/s11119-011-9235-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-011-9235-4

Keywords

Navigation