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Predicting Economic Optimal Nitrogen Rate with the Anaerobic Potentially Mineralizable Nitrogen Test.
- Source :
- Agronomy Journal; Nov/Dec2019, Vol. 111 Issue 6, p3329-3338, 10p
- Publication Year :
- 2019
-
Abstract
- Estimates of mineralizable N with the anaerobic potentially mineralizable N (PMN<subscript>an</subscript>) test could improve predictions of corn (Zea mays L.) economic optimal N rate (EONR). A study across eight US midwestern states was conducted to quantify the predictability of EONR for single and split N applications by PMNan. Treatment factors included different soil sample timings (pre-plant and V5 development stage), planting N rates (0 and 180 kg N ha<superscript>-1</superscript>), and incubation lengths (7, 14, and 28 d) with and without initial soil NH<subscript>4</subscript>--N included with PMN<subscript>an</subscript>. Soil was sampled (0-30 cm depth) before planting and N application and at V5 where 0 or 180 kg N ha<superscript>-1</superscript> were applied at planting. Evaluating across all soils, PMNan was a weak predictor of EONR (R² ≤ 0.08; RMSE, ≥67 kg N ha<superscript>-1</superscript>), but the predictability improved (15%) when soils were grouped by texture. Using PMN<subscript>an</subscript> and initial soil NH<subscript>4</subscript>--N as separate explanatory variables improved EONR predictability (11-20%) in fine-textured soils only. Delaying PMN<subscript>an</subscript> sampling from pre-plant to V5 regardless of N fertilization improved EONR predictability by 25% in only coarse-textured soils. Increasing PMN<subscript>an</subscript> incubations beyond 7 d modestly improved EONR predictability (R² increased ≤0.18, and RMSE was reduced ≤7 kg N ha<superscript>-1</superscript>). Alone, PMN<subscript>an</subscript> predicts EONR poorly, and the improvements from partitioning soils by texture and including initial soil NH<subscript>4</subscript>--N were relatively low (R² ≤ 0.33; RMSE ≥ 68 kg N ha<superscript>-1</superscript>) compared with other tools for N fertilizer recommendations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00021962
- Volume :
- 111
- Issue :
- 6
- Database :
- Supplemental Index
- Journal :
- Agronomy Journal
- Publication Type :
- Academic Journal
- Accession number :
- 141038324
- Full Text :
- https://doi.org/10.2134/agronj2019.03.0224