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Identification of Nitrogen Management Categories by Corn Stalk Nitrate Sampling Guided by Aerial Imagery
Author(s) -
Kyveryga P. M.,
Tao H.,
Morris T. F.,
Blackmer T. M
Publication year - 2010
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2009.0401
Subject(s) - stalk , agronomy , environmental science , nitrate , fertilizer , manure , ammonium nitrate , soil test , drainage , soil water , mathematics , biology , ecology , chemistry , horticulture , organic chemistry , soil science
Past studies on N management in corn ( Zea mays L.) have shown insurmountable difficulties predicting N supply from soil and fertilizer sources. New tools are needed for collecting feedback about the N status of corn from large areas at a low cost. We used adaptive management to compare major N management practices by organizing many grower groups across Iowa and conducting a guided corn stalk nitrate survey of 683 fields in 2006 and 824 in 2007. Aerial images of corn canopy taken in late August were used to select three sampling areas, one within each predominant soil type within a field. Ordinal logistic regressions (OLRs) were used to calculate the cumulative probability of a stalk sample to test in a higher stalk test category and to identify important factors affecting stalk test values. The analyses revealed significant differences in corn N status among management categories based on combinations of forms and timing of fertilizer and manure applications, previous crop, and soil drainage classes. In both years, fields receiving spring anhydrous ammonia (AA) were more likely to test higher than fields receiving fall liquid swine ( Sus scrofa ) manure (LSM), spring urea‐ammonium nitrate (UAN) solution, or fall AA. The large amounts of rainfall in June 2006 and cumulative spring rainfall in 2007 significantly decreased the likelihood to test in a higher stalk test category. A guided corn stalk nitrate survey as part of an adaptive management program allows documenting relatively efficient management practices within large areas of spatially variable soils and rainfall patterns.