Influences of Nitrogen Application Levels on Properties of Humic Acids in Chernozem Amended with Different Types of Organic Materials

FTIR Photoacoustic and ATR Spectroscopies of Soils with Aggregate Size Fractionation by Dry Sieving

Granulometric fractionation as a source of additional information on organic-matter and inorganic matrix components of soils using FTIR-photoacoustic spectroscopy (FTIR-PAS) supported by attenuated-total reflection FTIR spectroscopy (ATR-FTIR) for a wide range of aggregate fractions (10-5000 μm) was used to compare the sensitivity, reproducibility, information contents, and representativity of fractionated samples. For chernozem and sod-podzolic soils and different agricultural-use chernozem samples, differences in the composition were found, manifested in normalized spectra of microaggregate fractions, with the range of 10-100 μm bearing the complete information. Most changes are observed in the soil organic matter range (1900-1340 cm-1), although these changes are slight, and in the soil-matrix region (550-300 cm-1). The latter region increases the intensity of bands corresponding to amorphous silica and clay minerals in fine fractions, while the intensity of bands attributed to quartz lattice vibrations decreases. FTIR-PAS spectra do not differ considerably at high interferometer modulation frequencies as the signal-penetration depth is comparable with particle sizes. The soil fractions below 20 μm result in the maximum sensitivity, reproducibility, and signal-to-noise ratio, showing no changes from coarser fractions by the information content and, thus, providing representative samples for analysis. The fractionation shows more differences in the sod-podzolic and chernozem soil fractions than the whole soil spectra. FTIR-PAS provides better sensitivity and reproducibility in the 4000-2000 cm-1 region and ATR-FTIR in the 2000-100 cm-1 region.

FTIR photoacoustic spectroscopy for identification and assessment of soil components: Chernozems and their size fractions

FTIR photoacoustic spectroscopy was used to approach inorganic matrix components and organic-matter constituents of chernozem size fractions (1-5000 μm, by dry sieving) with a different history of use (from intact steppe to permanent bare fallow, a continuous long-term field experiment). The conditions of FTIR photoacoustic measurements in continuous-scan modes were compared with attenuated total reflection measurements, the advantages of photoacoustic measurements resulting from a higher intensity of the incident radiation and signal-generating volume were discussed. Overtone peaks of quartz as a soil matrix component at 2000-1700 cm-1 were selected as a possible internal-standard (guide) bands for the comparison of photoacoustic spectra. For different land-use samples, differences in the composition were found, which are differently manifested in normalized spectra of size fractions, with millimeter-size, 20-100 μm, and silt fraction bearing the maximum information.

Predicting Microbial Species in a River Based on Physicochemical Properties by Bio-Inspired Metaheuristic Optimized Machine Learning

The main goal of the analysis of microbial ecology is to understand the relationship between Earth’s microbial community and their functions in the environment. This paper presents a proof-of-concept research to develop a bioclimatic modeling approach that leverages artificial intelligence techniques to identify the microbial species in a river as a function of physicochemical parameters. Feature reduction and selection are both utilized in the data preprocessing owing to the scarce of available data points collected and missing values of physicochemical attributes from a river in Southeast China. A bio-inspired metaheuristic optimized machine learner, which supports the adjustment to the multiple-output prediction form, is used in bioclimatic modeling. The accuracy of prediction and applicability of the model can help microbiologists and ecologists in quantifying the predicted microbial species for further experimental planning with minimal expenditure, which is become one of the most serious issues when facing dramatic changes of environmental conditions caused by global warming. This work demonstrates a neoteric approach for potential use in predicting preliminary microbial structures in the environment.