Identification of Nitrogen Management Categories by Corn Stalk Nitrate Sampling Guided by Aerial Imagery

Abstract

Past studies on N management in corn (Zea mays L.) have shown insurmountable diffi culties 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 fi elds 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 fi eld. 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 aff ecting stalk test values. Th e analyses revealed signifi cant diff erences 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, fi elds receiving spring anhydrous ammonia (AA) were more likely to test higher than fi elds receiving fall liquid swine (Sus scrofa) manure (LSM), spring urea-ammonium nitrate (UAN) solution, or fall AA. Th e large amounts of rainfall in June 2006 and cumulative spring rainfall in 2007 signifi cantly 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 effi cient management practices within large areas of spatially variable soils and rainfall patterns. P.M.

Strengths and Limitations of Nitrogen Rate Recommendations for Corn and Opportunities for Improvement

“…The CSNT results give an estimate of the N status of the field during the growing season, and the information can be assessed in the context of the environmental conditions during the growing season before deciding on an N rate for the upcoming season. When the CSNT is paired with aerial images of corn fields collected shortly after tasseling the results accurately estimate the N status of corn fields at the end of the season (Kyveryga et al, 2010). The results of CSNTs collected over 2 or more years from the same field when combined with field history and rainfall information is an excellent technique to refine N recommendations.…”

On‐Farm Evaluations to Calibrate Tools for Estimating Late‐Season Nitrogen Status of Corn

“…Digital aerial imagery can be used in different ways. For example, a large study conducted across Iowa used digital aerial imagery to guide CSNT sampling within about 1500 corn fields during 2 yr to identify differences between N management categories, which were formed based on a combination of N source and the timing of application (Kyveryga et al, 2010). Also, late‐season digital aerial imagery was used to estimate the percentage of area with sufficient and deficient corn N status within about 1600 corn fields during 3 yr (Kyveryga et al, 2011).…”

Nutrient Applications Reported by Farmers Compared with Performance‐Based Nutrient Management Plans

“…Management of manure and fertilizer on dairy farms could be improved by using a longer timeframe than the 3‐ to 5‐yr plans typically used for NMPs, by providing farmers with detailed evaluations about the effects of management and biological factors on N and P status of corn fields, and by a more organized and concerted program for farmer learning from information collected about the N and P status of individual fields in NMPs. The NMPs implemented using a process of adaptive management for N (USDA‐NRCS, 2011), which provides detailed evaluations to farmers about the N status of their corn fields and a structured learning environment to effectively use the evaluations have been shown to improve N management (Kyveryga et al, 2010c, 2011).…”

“…The test levels for the ordinal response variables included two levels for the PSNT, deficient (<25 mg NO 3 –N kg −1 ) and sufficient (≥25 mg NO 3 –N kg −1 ) (Binford et al, 1992), and four levels for the CSNT, deficient (<0.25 g kg −1 ), marginal (0.25–0.70 g kg −1 ), optimal (0.70–2.0 g kg −1 ) and excessive (>2.0 g kg −1 ) (Binford et al, 1992a; Blackmer and Mallarino, 1996). Ordinal logistic regressions (OLRs) were used to identify parameter significance for different explanatory variables including N from different sources (Kyveryga et al, 2010b). In the OLR models, manure applications for the growing season were defined as a binary variable equal to 1 if manure was applied and 0 otherwise.…”