/AnMtgsAbsts2009.55296 Spatial Variability of Illinois Soil Nitrogen Test Results in New York Soils.

Wednesday, November 4, 2009
Convention Center, Exhibit Hall BC, Second Floor

Kulbhushan Grover1, Scott Grandt2 and Quirine Ketterings2, (1)Plant and Environmental Sciences, New Mexico State University, Las Cruces, NM
(2)Animal Science, Cornell Univ., Ithaca, NY
Poster Presentation
  • ISNT-Poster-ASA2009-Final-Presented.pdf (359.2 kB)
  • Abstract:
    The Illinois Soil Nitrogen Test (ISNT) was developed to assess soil N release potential. In research in New York State, the ISNT, with critical value adjustments based on organic matter derived by loss-on-ignition (LOI), was 84% accurate in predicting corn (Zea mays L.) responsiveness for 2nd or higher year corn. For implementation of an ISNT-based N management system, it is important to understand the spatial and temporal variability of the ISNT and its effect on sampling distribution for accurate measurements of this pool of soil organic N. The objectives of the current study were to: (1) evaluate the accuracy of soil sampling protocols (number of samples per field) during the growing season and after harvest, with and without manure application, (2) quantify implications of a change in spatial and temporal variability for ISNT results, (3) determine the 95% confidence interval and probability of obtaining a mean within the 95% CI as impacted by sampling intensity. The study was conducted at two 4-ha corn fields selected on a dairy farm in central NY. Fields were sampled in the first week of July and 2 wk after harvest at the end of Nov. For each sampling round, 150 samples were taken per field. The sampling protocol consisted of a regular grid sampling to ensure coverage of the fields with additional points to give the most uniform distribution of lag distances possible using lag distance classes of 20 m. Manure was applied at a rate of 110 Mg ha-1 to Field 2 after corn harvest. Field 1 did not receive manure. Results will be presented on descriptive statistics (mean, standard deviation, minimum, maximum) derived from samples taken on the regular grid. Additionally, non-directional, semi-variograms will be presented derived using all samples for each field and each sampling time.