Can mineralization of soil organic nitrogen meet maize nitrogen demand?

Aims High-yielding maize-based crop systems require maize to take up large quantities of nitrogen over short periods of time. Nitrogen management in conventional crop systems assumes that soil N mineralization alone cannot meet rapid rates of crop N uptake, and thus large pools of inorganic N, typically supplied as fertilizer, are required to meet crop N demand. Net soil N mineralization data support this assumption; net N mineralization rates are typically lower than maize N uptake rates. However, net N mineralization does not fully capture the flux of N from organic to inorganic forms. Gross ammonification may better represent the absolute flux of inorganic N produced by soil N mineralization. Methods Here we utilize a long-term cropping systems experiment in Iowa, USA to compare the peak rate of N accumulation in maize biomass to the rate of inorganic N production through gross ammonification of soil organic N. Results Peak maize N uptake rates averaged 4.4 kg N ha−1 d−1, while gross ammonification rates over the 0–80 cm depth averaged 23 kg N ha−1 d−1. Gross ammonification was highly stratified, with 63% occurring in the 0–20 cm depth and 37% in the 20–80 cm depth. Neither peak maize N uptake rate nor gross ammonification rate differed significantly among three cropping systems with varied rotation lengths and fertilizer inputs. Conclusions Gross ammonification rate was 3.4 to 4.5 times greater than peak maize N uptake across the cropping systems, indicating that inorganic N mineralized from soil organic matter may be able to satisfy a large portion of crop N demand, and that explicit consideration of gross N mineralization may contribute to development of strategies that reduce crop reliance on large soil inorganic N pools that are easily lost to the environment

A sensitive soil biological indicator to changes in land-use in regions with Mediterranean climate

The demand for reliable indicators to quantify soil health has increased recently. We propose and test the use of soil microbial functional diversity as an indicator of multifunctional performance in agriculturally important areas. Agricultural fields in the Mediterranean and semiarid regions of Israel were selected as test sites and measured in Spring and Autumn seasons. Measurements included microbial parameters, basic soil abiotic properties and biological responses to agricultural management relative to measures of a natural ecosystem. Using a canonical correlation analysis we found that soil moisture was the most important basic soil property with different responses in Spring and Autumn. In Spring, it had a strongly negative relation with microbial biomass (MB), community level physiological profiling (CLPP) and the Shannon-Weaver index H', while in Autumn it had a strong relation with CLPP. We further show a significant interaction between CLPP and climate for land-use type "orchards". CLPP measured in the autumn season was thus identified as a useful and rapid biological soil health indicator, recommended for application in semiarid and Mediterranean agricultural regions. Apart from obtaining a better understanding of CLPP as the soil indicator, the study concludes that CLPP is well suited to differentiate between soils in different climates, seasons and land use types. The study shows a promising direction for further research on characterizing soil health under a larger variety of conditions.</p

Can mineralization of soil organic nitrogen meet maize nitrogen demand?

Aims High-yielding maize-based crop systems require maize to take up large quantities of nitrogen over short periods of time. Nitrogen management in conventional crop systems assumes that soil N mineralization alone cannot meet rapid rates of crop N uptake, and thus large pools of inorganic N, typically supplied as fertilizer, are required to meet crop N demand. Net soil N mineralization data support this assumption; net N mineralization rates are typically lower than maize N uptake rates. However, net N mineralization does not fully capture the flux of N from organic to inorganic forms. Gross ammonification may better represent the absolute flux of inorganic N produced by soil N mineralization. Methods Here we utilize a long-term cropping systems experiment in Iowa, USA to compare the peak rate of N accumulation in maize biomass to the rate of inorganic N production through gross ammonification of soil organic N. Results Peak maize N uptake rates averaged 4.4 kg N ha−1 d−1, while gross ammonification rates over the 0–80 cm depth averaged 23 kg N ha−1 d−1. Gross ammonification was highly stratified, with 63% occurring in the 0–20 cm depth and 37% in the 20–80 cm depth. Neither peak maize N uptake rate nor gross ammonification rate differed significantly among three cropping systems with varied rotation lengths and fertilizer inputs. Conclusions Gross ammonification rate was 3.4 to 4.5 times greater than peak maize N uptake across the cropping systems, indicating that inorganic N mineralized from soil organic matter may be able to satisfy a large portion of crop N demand, and that explicit consideration of gross N mineralization may contribute to development of strategies that reduce crop reliance on large soil inorganic N pools that are easily lost to the environment.This is a manuscript of an article is published as Osterholz, William R., Oshri Rinot, Matt Liebman, and Michael J. Castellano. "Can mineralization of soil organic nitrogen meet maize nitrogen demand?." Plant and Soil 415, no. 1-2 (2017): 73-84. doi: 10.1007/s11104-016-3137-1. Posted with permission.</p

Organic matter in aqueous soil extracts: Prediction of compositional attributes from bulk soil mid-IR spectra using partial least square regressions

Water-extractable organic matter (WEOM) is labile and a key component of soil organic matter. Thus, the prediction of soil WEOM concentration and composition-related characteristics is of great interest. The main objective of this study was to model and predict dissolved organic C (DOC) concentration and WEOM composition-related attributes of aqueous soil extracts using mid-infrared (IR) spectra of bulk soils coupled with partial least square (PLS) regression. Absorbance of UV light at 254 nm (Abs254), considered proportional to the concentration of aromatic substances in soil extracts, and light emission intensities proportional to concentrations of some components controlling WEOM fluorescence, were used as composition-related attributes of the soil extracts. The DOC-normalized Abs254 and emission intensities were used as composition-related attributes of WEOM. Application of PLS regressions for predicting spectroscopy-based composition-related attributes of aqueous soil extracts, using bulk soil IR spectra, is novel. Mid-IR spectra were determined for 216 soil samples collected from different (i) Israeli climate regions (Mediterranean and Semi-arid), (ii) types of land use (field crops, orchard and non-cultivated land), (iii) two depths (0–10 and 30–60 cm), (iv) sampling seasons (Fall and Spring). Prediction of DOC concentrations in the soil extracts was of limited and variable success evaluated by the coefficient of determination and slope of the linear regression of predicted vs measured values, with some soil subsets yielding no satisfactory predictions. However, Abs254 and emission intensities of fluorescent humic-like components were predicted more successfully than DOC concentrations, suggesting that WEOM aromatic and fluorescent components are better presented in soil IR spectra compared to WEOM aliphatic substances. Yet, prediction of the specific UV absorbance (SUVA), using bulk soil IR spectra, was less successful than prediction of Abs254. Prediction of DOC-normalized emission intensities of fluorescent components (analogous to SUVA in fluorescence spectroscopy) was not successful. The differences between the success of predicting extract properties, i.e., Abs254 and fluorescence emission intensities, and the prediction of DOC-normalized derivatives, suggest that concentrations of aromatic (fluorescent) components in soil extracts are better predicted using PLS regression analysis of bulk soil mid-IR spectra than the WEOM composition