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In‐Field Variability of the Illinois Soil Nitrogen Test and Loss‐on‐Ignition Results for Nitrogen Management
Author(s) -
Maresma Angel,
Ketterings Quirine M.
Publication year - 2017
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2016.10.0334
Subject(s) - spatial variability , loss on ignition , environmental science , soil water , spatial distribution , sampling (signal processing) , hydrology (agriculture) , soil science , environmental chemistry , chemistry , geology , mathematics , statistics , geotechnical engineering , filter (signal processing) , computer science , computer vision
Core Ideas: Spatial and seasonal variability in the Illinois soil N test (ISNT)‐N and loss‐on‐ignition (LOI) at 500°C can impact N recommendations. Loss‐on‐ignition determination at 500°C and 360°C are highly correlated. Loss‐on‐ignition and ISNT‐N show strong spatial structure among soils. Soil nitrate sampling is less practical because of its large spatial variability. Intensification of current sampling protocols is needed for LOI and ISNT‐N. The Illinois soil N test (ISNT) with loss‐on‐ignition at 500°C (LOI 500 ) adjustment can identify fields with low versus high soil N supply potential in New York. However, spatial and seasonal variability in ISNT‐N and LOI 500 can influence soil N supply classifications. We aimed to determine (i) the influence of sample density on the ratio of ISNT‐N to the critical value for interpretations of ISNT results (ISNT‐N Critical ), and N supply classification, (ii) the implications of change in spatial and temporal variability on ISNT‐N interpretations, (iii) the probability of obtaining accurate interpretations as impacted by sampling intensity, and (iv) the influence of using LOI 500 equivalents [derived from loss‐on‐ignition at 360°C (LOI 360 )] on ISNT‐N interpretations. Two 4‐ha silage corn ( Zea mays L.) fields were sampled (150 samples per field, 0–20 cm depth; 64 in regular 25 by 25 or 23 by 27 m grids, the remainder in a pattern optimizing lag distance distribution) in July and November. Semivariograms were constructed to investigate spatial dependence. Soil nitrate showed the weakest spatial dependence. Increasing sampling intensity to 3.75 samples ha ‐1 reduced the confidence interval for ISNT‐N/ISNT‐N Critical while augmenting the probability (>95%) of obtaining estimates within the true field mean (±6.4%), resulting in consistent classifications. The LOI 500 and LOI 360 results correlated well ( r 2 = 0.78); using LOI 500 equivalents derived from LOI 360 produced identical classifications for 92% of the samples. Effective sampling protocols for ISNT‐N should include sampling at 3.75+ samples ha ‐1 for consistent ISNT‐N interpretations, and LOI 500 equivalents can be used to derive ISNT‐N critical values.