Advertisement

Precision Agriculture

, Volume 18, Issue 5, pp 823–842 | Cite as

Long-term impact of a precision agriculture system on grain crop production

  • M. A. Yost
  • N. R. Kitchen
  • K. A. Sudduth
  • E. J. Sadler
  • S. T. Drummond
  • M. R. Volkmann
Article

Abstract

Research is lacking on the long-term impacts of field-scale precision agriculture practices on grain production. Following more than a decade (1993–2003) of yield and soil mapping and water quality assessment, a multi-faceted, ‘precision agriculture system’ (PAS) was implemented from 2004 to 2014 on a 36-ha field in central Missouri. The PAS targeted management practices that address crop production and environmental issues. It included no-till, cover crops, growing winter wheat (Triticum aestivum L.) instead of corn (Zea mays L.) for field areas where corn was not profitable, site-specific N for wheat and corn using canopy reflectance sensing, variable-rate P, K and lime using intensively grid-sampled data, and targeting of herbicides based on weed pressure. The PAS assessment was accomplished by comparing it to the previous decade of conventional, whole-field corn-soybean (Glycine max L.) mulch-tillage management. In the northern part of the field and compared to pre-PAS corn, relative grain yield of wheat in PAS was greatly improved and temporal yield variation was reduced on shallow topsoil, but relative grain yield was reduced on deep soil in the drainage channel. In the southern part of the field where corn remained in production, PAS did not lead to increased yield, but temporal yield variation was reduced. Across the whole field, soybean yield and temporal yield variation were only marginally influenced by PAS. Spatial yield variation of all three crops was not altered by PAS. Therefore, the greatest production advantage of a decade of precision agriculture was reduced temporal yield variation, which leads to greater yield stability and resilience to changing climate.

Keywords

Precision conservation Precision nutrient management Integrated precision practices Crop production No-till Cover crops 

Notes

Acknowledgements

The authors sincerely thank Don and Vicki Collins, Matt Volkmann, Kurt Holiman, Michael Krumpelman, Bill Wilson, Larry Mueller, Kevin Austin, and numerous other personnel for assisting in the maintenance and management of the field used in this study. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.

References

  1. Berry, J. K., Delgado, J. A., Khosla, R., & Pierce, F. J. (2003). Precision conservation for environmental sustainability. Journal of Soil and Water Conservation, 58(6), 332–339.Google Scholar
  2. Bianchini, A. A., & Mallarino, A. P. (2002). Soil-sampling alternatives and variable-rate liming for a soybean–corn rotation. Agronomy Journal, 94(6), 1355–1366. doi: 10.2134/agronj2002.1355.CrossRefGoogle Scholar
  3. Blackmore, S. (2000). The interpretation of trends from multiple yield maps. Computers and Electronics in Agriculture, 26(1), 37–51. doi: 10.1016/S0168-1699(99)00075-7.CrossRefGoogle Scholar
  4. Blackmore, S., Godwin, R. J., & Fountas, S. (2003). The analysis of spatial and temporal trends in yield map data over six years. Biosystems Engineering, 84(4), 455–466. doi: 10.1016/S1537-5110(03)00038-2.CrossRefGoogle Scholar
  5. Bongiovanni, R., & Lowenberg-Deboer, J. (2000). Economics of variable rate lime in Indiana. Precision Agriculture, 2(1), 55–70. doi: 10.1023/A:1009936600784.CrossRefGoogle Scholar
  6. Buchholz, D. D., Brown, J. R., Garret, J., Hanson, R., & Wheaton, H. (2004). Soil test interpretations and recommendations handbook. Columbia, MO, USA: University of Missouri-College of Agriculture, Division of Plant Sciences.Google Scholar
  7. Carr, P. M., Carlson, G. R., Jacobsen, J. S., Nielsen, G. A., & Skogley, E. O. (1991). Farming soils, not fields: A strategy for increasing fertilizer profitability. Journal of Production Agriculture, 4(1), 57–61. doi: 10.2134/jpa1991.0057.CrossRefGoogle Scholar
  8. Delgado, J. A., Khosla, R., & Mueller, T. (2011). Recent advances in precision (target) conservation. Journal of Soil and Water Conservation, 66(6), 167A–170A. doi: 10.2489/jswc.66.6.167A.CrossRefGoogle Scholar
  9. Dinnes, D. L., Karlen, D. L., Jaynes, D. B., Kaspar, T. C., Hatfield, J. L., Colvin, T. S., et al. (2002). Nitrogen management strategies to reduce nitrate leaching in tile-drained midwestern soils. Agronomy Journal, 94(1), 153–171. doi: 10.2134/agronj2002.1530.CrossRefGoogle Scholar
  10. Dobermann, A., Ping, J. L., Adamchuk, V. I., Simbahan, G. C., & Ferguson, R. B. (2003). Classification of crop yield variability in irrigated production fields. Agronomy Journal, 95(5), 1105. doi: 10.2134/agronj2003.1105.CrossRefGoogle Scholar
  11. Drummond, S. T., Sudduth, K. A., Joshi, A., Birrell, S. J., & Kitchen, N. R. (2003). Statistical and neural methods for site-specific yield prediction. Transactions of the ASAE, 46(1), 5–14. doi: 10.13031/2013.12541.CrossRefGoogle Scholar
  12. Drury, C. F., Tan, C.-S., Welacky, T. W., Oloya, T. O., Hamill, A. S., & Weaver, S. E. (1999). Red clover and tillage influence on soil temperature, water content, and corn emergence. Agronomy Journal, 91(1), 101–108. doi: 10.2134/agronj1999.00021962009100010016x.CrossRefGoogle Scholar
  13. Jiang, P., Anderson, S. H., Kitchen, N. R., Sudduth, K. A., & Sadler, E. J. (2007). Estimating plant-available water capacity for claypan landscapes using apparent electrical conductivity. Soil Science Society of America Journal, 71(6), 1902–1908. doi: 10.2136/sssaj2007.0011.CrossRefGoogle Scholar
  14. Kitchen, N. R., Sudduth, K. A., & Drummond, S. T. (1999). Soil electrical conductivity as a crop productivity measure for claypan soils. Journal of Production Agriculture, 12(4), 607–617.CrossRefGoogle Scholar
  15. Kitchen, N. R., Sudduth, K. A., Myers, D. B., Massey, R. E., Sadler, E. J., Lerch, R. N., et al. (2005). Development of a conservation-oriented precision agriculture system: Crop production assessment and plan implementation. Journal of Soil and Water Conservation, 60(6), 421–430.Google Scholar
  16. Kitchen, N. R., Sudduth, K. A., Drummond, S. T., Scharf, P. C., Palm, H. L., Roberts, D. F., et al. (2010). Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agronomy Journal, 102(1), 71–84. doi: 10.2134/agronj2009.0114.CrossRefGoogle Scholar
  17. Larson, W. E., Lamb, J. A., Khakural, B. R., Ferguson, R. B., & Rehm, G. W. (1997). Potential of site-specific management for nonpoint environmental protection. In F. J. Pierce & E. J. Sadler (Eds.), The state of site-specific management for agriculture (pp. 337–367). Madison, WI, USA: ASA, CSSA, SSSA.Google Scholar
  18. Lerch, R. N., Kitchen, N. R., Kremer, R. J., Donald, W. W., Alberts, E. E., Sadler, E. J., et al. (2005). Development of a conservation-oriented precision agriculture system: Water and soil quality assessment. Journal of Soil and Water Conservation, 60(6), 411–421.Google Scholar
  19. Lowenberg-DeBoer, J., & Aghib, A. (1999). Average returns and risk characteristics of site specific P and K management: Eastern corn belt on-farm trial results. Journal of Production Agriculture, 12(2), 276–282. doi: 10.2134/jpa1999.0276.CrossRefGoogle Scholar
  20. A, Mallarino, Wittry, P., Dousa, J., & Hinz, P. N. (1999). Variable-rate phosphorus fertilization: On-farm research methods and evaluation for corn and soybean. In P. C. Robert, R. H. Rust, & W. E. Larson (Eds.), Proceedings of the 4th international conference on precision agriculture (pp. 687–696). Madison, WI, USA.: ASA-CSSA-SSSA.Google Scholar
  21. Massey, R. E., Myers, D. B., Kitchen, N. R., & Sudduth, K. A. (2008). Profitability maps as an input for site-specific management decision making. Agronomy Journal, 100(1), 52–59.CrossRefGoogle Scholar
  22. Myers, D. B., Kitchen, N. R., & Sudduth, K. A. (2003). Assessing spatial and temporal nutrient dynamics with a proposed nutrient buffering index. Proceedings of the north central extension-industry soil fertility conference (Vol. 19, pp. 19–20). Brookings, SD, USA: Potash and Phosphate Institute.Google Scholar
  23. Sadler, E. J., Evans, D. E., Gerwig, B. K., Millen, J. A., Thomas, W., & Fussell, P. (2005). Severity, extent and persistence of spatial yield variation in production fields in the SE US Coastal Plain. Precision Agriculture, 6(4), 379–398. doi: 10.1007/s11119-005-2416-2.CrossRefGoogle Scholar
  24. Sadler, E. J., Sudduth, K. A., Drummond, S. T., Vories, E. D., & Guinan, P. E. (2015). Long-term agroecosystem research in the central Mississippi river basin: Goodwater creek experimental watershed weather data. Journal of Environmental Quality, 44(1), 13–17. doi: 10.2134/jeq2013.12.0515.CrossRefPubMedGoogle Scholar
  25. SAS Institute Inc. (2011). Statistical analysis system. Cary, NC, USA: SAS Institute Inc.Google Scholar
  26. Scharf, P. C., Shannon, D. K., Palm, H. L., Sudduth, K. A., Drummond, S. T., Kitchen, N. R., et al. (2011). Sensor-based nitrogen applications out-performed producer-chosen rates for corn in on-farm demonstrations. Agronomy Journal, 103(6), 1683–1691. doi: 10.2134/agronj2011.0164.CrossRefGoogle Scholar
  27. Sudduth, K. A., & Drummond, S. T. (2007). Yield editor: Software for removing errors from crop yield maps. Agronomy Journal, 99(6), 1471–1482. doi: 10.2134/agronj2006.0326.CrossRefGoogle Scholar
  28. Sudduth, K. A., & Kitchen, N. R. (2006). Increasing information with multiple soil electrical conductivity datasets. ASABE paper No. 061055. American Society of Agricultural & Biological Engineers. St. Joseph, MI, USA. doi: 10.13031/2013.21088.
  29. Sudduth, K. A., Kitchen, N. R., Myers, D. B., & Drummond, S. T. (2010). Mapping depth to argillic soil horizons using apparent electrical conductivity. Journal of Environmental and Engineering Geophysics, 15(3), 135–146.CrossRefGoogle Scholar
  30. Sudduth, K. A., Myers, D. B., Kitchen, N. R., & Drummond, S. T. (2013). Modeling soil electrical conductivity–depth relationships with data from proximal and penetrating ECa sensors. Geoderma, 199, 12–21. doi: 10.1016/j.geoderma.2012.10.006.CrossRefGoogle Scholar
  31. Teasdale, J. R., & Mohler, C. L. (1993). Light transmittance, soil temperature, and soil moisture under residue of hairy vetch and rye. Agronomy Journal, 85(3), 673–680. doi: 10.2134/agronj1993.00021962008500030029x.CrossRefGoogle Scholar
  32. Unger, P. W., & Kaspar, T. C. (1994). Soil compaction and root growth: A review. Agronomy Journal, 86(5), 759–766. doi: 10.2134/agronj1994.00021962008600050004x.CrossRefGoogle Scholar
  33. USDA-Natural Resource Conservation Service. (2009). Variable-rate nitrogen fertilizer application in corn using in-field sensing of leaves or canopy. Missouri NRCS Agronomy Tech Note 35. Retrieved September 14, 2016 from http://extension.missouri.edu/sare/documents/AgronomyTechnicalNote2012.pdf.
  34. Weisz, R., Heiniger, R., White, J. G., Knox, B., & Reed, L. (2003). Long-term variable rate lime and phosphorus application for piedmont no-till field crops. Precision Agriculture, 4(3), 311–330. doi: 10.1023/A:1024908724491.CrossRefGoogle Scholar
  35. Wells, M. S., Reberg-Horton, S. C., & Mirsky, S. B. (2014). Cultural strategies for managing weeds and soil moisture in cover crop based no-till soybean production. Weed Science, 62(3), 501–511. doi: 10.1614/WS-D-13-00142.1.CrossRefGoogle Scholar
  36. Yost, M. A., Kitchen, N. R., Sudduth, K. A., Sadler, E. J., Baffaut, C., Volkmann, M. R., et al. (2016). Long-term impacts of cropping systems and landscape positions on claypan-soil grain crop production. Agronomy Journal, 108(2), 713–726.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2016

Authors and Affiliations

  • M. A. Yost
    • 1
  • N. R. Kitchen
    • 1
  • K. A. Sudduth
    • 1
  • E. J. Sadler
    • 1
  • S. T. Drummond
    • 1
  • M. R. Volkmann
    • 1
  1. 1.Cropping Systems and Water Quality Research Unit, U.S. Department of Agriculture-Agricultural Research ServiceUniversity of MissouriColumbiaUSA

Personalised recommendations