Abstract
Several potential sources of information exist to support precision management of crop inputs. This study evaluated soil test data, bare-soil remote sensing imagery and yield monitor information for their potential contributions to precision management of maize (Zea mays L.). Data were collected from five farmer-managed fields in Central New York in 1999, 2000, and 2001. Geostatistical techniques were used to analyze the spatial structure of soil fertility (pH, P, K, NO3 and organic matter content) and yield variables (yield, hybrid response and N fertilization response), while remote sensing imagery was processed using principal component analysis. Geographic information system (GIS) spatial data processing and correlation analyses were used to evaluate relationships in the data. Organic matter content, pH, P, and K were highly consistent over time and showed high to moderate levels of spatial autocorrelation, suggesting that grid soil sampling at 2.5–5.5 ha scale may be used as a basis for defining fertility management zones. Soil nitrate levels were strongly influenced by seasonal weather conditions and showed low potential for site-specific N management. Aerial image data were correlated to soil organic matter content and in some cases to yield, mainly through the effect of drainage patterns. Aerial image data were not well correlated with soil fertility indicators, and therefore were not useful for defining fertility management zones. Yield response to hybrid selection and nitrogen fertilization rates were highly variable among years, and showed little justification for site-specific management. In conclusion, we recommend grid-based management of lime, P, and K, but no justification existed within our limited study area for site-specific N or hybrid management.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
S. Arslan T. S. Colvin (2002) ArticleTitleAn Evaluation of the response of yield monitors and combines to varying yields Precision Agriculture 3 107–122
S. Blackmore M. Moore (1999) ArticleTitleRemedial correction of yield map data Precision Agriculture 1 53–66
C. A. Cambardella D. L. Karlen (1999) ArticleTitleSpatial analysis of soil fertility parameters Precision Agriculture 1 5–14
C. Chang D. A. Laird M. J. Mausbach C. R. Hurburgh SuffixJr. (2001) ArticleTitleNear-infrared reflectance spectroscopy—Principal components regression analysis of soil properties Soil Science Society of America Journal 65 480–490
Cornell Cooperative Extension. 1998, 1999, and 2000. Cornell Guide for Integrated Field Crop Management (Cornell University, Ithaca, NY, USA).
Cornell University Nutrient Analysis Laboratory. 2002. Nutrient Testing Information Web page. Online. http://www.css.cornell.edu/soiltest/Advanced.html (verified April, 2004).
W. J. Cox D. J. R. Cherney (2002) ArticleTitleEvaluation of narrow-row corn forage in field-scale studies Agronomy Journal 94 321–325
M. R. Ehsani S. K. Upadhyaya D. Slaughter S. Shafii M. Pelletier (1999) ArticleTitleA NIR technique for rapid determination of soil mineral nitrogen Precision Agriculture 1 217–234
Emerge. 2002. Digital Sensor System Brochure. Online.
http://www.emergeweb.com/Public/info/emerge_DSS.pdf (verified April, 2004).
P. Goovaerts (1999) ArticleTitleGeostatistics in soil science: State-of-the-art and perspectives Geoderma 89 1–45
J. E. Kahabka H. M. Es Particlevan E. J. McClenahan W. J. Cox (2004) ArticleTitleSpatial analysis of maize response to nitrogen fertilizer in Central New York Precision Agriculture 5 463–476
T. W. Katsvairo W. J. Cox H. M. Es Particlevan M. A. Glos (2003a) ArticleTitleSpatial yield response to two corn hybrids at two nitrogen levels Agronomy Journal 95 1012–1022
T. W. Katsvairo W. J. Cox H. M. Es Particlevan (2003b) ArticleTitleSpatial growth and soil responses of two corn hybrids to two N levels Agronomy Journal 95 1000–1011
D. B. Lobell G. P. Asner (2002) ArticleTitleMoisture effects on soil reflectance Soil Science Society of America Journal 66 722–727
F. R. Magdoff (1991) ArticleTitleUnderstanding the Magdoff pre-sidedress nitrate soil test for corn Journal of Production Agriculture 4 297–305
Magdoff, F. R. and van Es, H. M. 2000. Building Soils for Better Crops. 2nd Edn (Sustainable Agriculture Network, Beltsville, MD USA), Handbook Series, Book 4. 230 p.
A. Magri (2003) Integral Evaluation of Soil Test, Aerial Image, Yield Monitor, and Soil Survey Data as Inputs for Precision Fertility Management Under Maize Cornell University Ithaca, NY USA
A. B. McBratney M. J. Pringle (1999) ArticleTitleEstimating average and proportional variograms of soil properties and their potential use in precision agriculture Precision Agriculture 1 125–152
E. Muller H. Décamps (2000) ArticleTitleModeling soil moisture-reflectance Remote Sensing of Environment 76 173–180
Pioneer Hi-Bred International, Inc. 2002. Agronomic Traits Chart. Online.
http://www.pioneer.com/Products/PrdGuide/EC/010/charts/TREC10AG.pdf (verified April, 2004).
G. B. Senay A. D. Ward J. D. Lyon N. R. Fausey S. E. Nokes L. C. Brown (2000) ArticleTitleThe relations between spectral data and water in a crop production environment International Journal of Remote Sensing 21 1897–1910
J. M. Sogbedji H. M. Es Particlevan S. D. Klausner D. R. Bouldin W. J. Cox (2001) ArticleTitleSpatial and temporal processes affecting nitrogen availability at the landscape scale Soil & Tillage Research 58 233–244
M. D. Tomer J. L. Anderson J. A. Lamb (1997) ArticleTitleAssesing corn yield and nitrogen uptake variability with digitized aerial infrared photographs Photogrammetric Engineering and Remote Sensing 63 299–306
Trimble Navigation Limited. 1998. GPS Pathfinder Pro XR/XRS Datasheet and Specifications. Online. http://trl.trimble.com/dscgi/ds.py/Get/File-128929 (verified April, 2004).
USDA, Soil Conservation Service in cooperation with Cornell University Agricultural Experiment Station. 1972. Soil Survey: Seneca County New York USA. 143 pages and maps.
USDA, Soil Conservation Service in cooperation with Cornell University Agricultural Experiment Station. 1973. Soil Survey: Onondaga County New York USA. 235 pages and maps.
G. E. Varvel M. R. Schlemmer J. S. Schepers (1999) ArticleTitleRelationship between spectral data from aerial image and soil organic matter and phosphorous levels Precision Agriculture 1 291–300
Webster, R. 1984. Elucidation and characterization of spatial variation in soil using regionalized variable theory. In: Proceedings of the 2nd NATO ASI, Geostatistics for Natural Resource Characterization, NATO ASI Series. Series C: Mathematical and PhysicalSciences, edited by Verly, G. Daid, M., Journel, A.G. and Marechal, A. Reidel, Dordrecht, The Netherlands, v. 2, pp. 903–913.
R. Webster (2000) ArticleTitleIs soil variation random? Geoderma 97 149–163 Occurrence Handle10.1016/S0016-7061(00)00036-7
B. M. Whelan A. B. McBratney (2000) ArticleTitleThe “Null Hypothesis” of precision agriculture management Precision Agriculture 2 265–279
Wollenahupt, N. C., Mulla, D. J. and Gotway Crawford, C. A. 1997. Soil sampling and interpolation techniques for mapping spatial variability of soil properties. In: The State of Site-Specific Management for Agriculture, edited by Pierce, F. J. and Sadler, E. J. (ASA-CSSA-SSSA, Madison, Wisconsin USA), pp. 19–53.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Magri, A., Van Es, H.M., Glos, M.A. et al. Soil Test, Aerial Image and Yield Data as Inputs for Site-specific Fertility and Hybrid Management Under Maize. Precision Agric 6, 87–110 (2005). https://doi.org/10.1007/s11119-004-0687-7
Issue Date:
DOI: https://doi.org/10.1007/s11119-004-0687-7