Journal of Soils and Sediments - Humic acids (HA) have several environmental roles, but are particularly important in aquatic environments, being recognized as redox active natural organic matter... 相似文献
Aglime application can promote carbon dioxide (CO2) emissions from acid soils. However, the controlling mechanisms are still poorly understood, particularly the role of fertiliser-ammonium oxidation. This study therefore assessed the effects of aglime on soil inorganic C (SIC)– and soil organic C (SOC)–derived CO2 emissions from acid soils amended with ammonium.
Materials and methods
Ammonium at three N rates [0% (A0), 0.005% (A1), and 0.2% (A2) w/w] and labelled aglime (Ca13CO3,13C 5.94% aa) at three rates [0% (L1), 0.067% (L1), and 0.392% (L2) w/w] were applied to two contrasting acid soils (Nariva series, Mollic Fluvaquents; and Piarco series, Typic Kanhaplaquults) and incubated in 1-l media bottles for 23 days. A calcareous soil (Princes Town series, Aquentic Eutrudepts, carbonate δ13C of ??4.79‰) was included as a control that only received ammonium at the three rates.
Results and discussion
The application of ammonium at the A2 rate significantly (p?<?0.05) increased cumulative SIC-CO2 emissions by 15.8 and 27.1% in comparison to the A0 rate for the Nariva and Piarco soils, respectively, when they were limed at the L2 rate. The lower rate of ammonium (A1), however, had no effect on these emissions, which suggests that enough acidity may not have been generated at this rate to significantly enhance the release of SIC-CO2. Furthermore, no effect of ammonium rates was observed on SIC-CO2 emissions from the calcareous soil, which refutes the hypothesis that this amendment plays a greater role in regulating these emissions from calcareous soils compared with acid soils. Also, in contradiction to another hypothesis, the aglime-induced priming effect on SOC decomposition was more apparent in the low-C Piarco soil. This effect was also significantly (p?<?0.05) greater at the L2 rate (above the lime requirement for Piarco), which demonstrates the negative impact that over-liming could have on the sequestration of C in this soil. Our results also showed that ammonium addition may also help to reduce the magnitude of the aglime-induced priming effect in the Piarco soil when it is not over-limed.
Conclusions
Overall, the findings of this study suggest that ammonium fertiliser broadcast at conventional rates may not serve as a significant regulator of SIC-CO2 emissions from highly to moderately acidic soils amended with aglime. Our findings also indicate a need to consider nitrogen management as an important factor regulating the effects of aglime on SOC-CO2 emissions.
In this study, films of chitosan and 2-amino-4,5,6,7-tetrahydrobenzo[b]thiophene-3-carbonitrile (6CN), a 2-aminothiophene derivative with great pharmacological potential, were prepared as a system for a topical formulation. 6CN-chitosan films were characterized by physicochemical analyses, such as Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray diffraction (XRD), and scanning electronic microscopy (SEM). Additionally, the antifungal potential of the films was evaluated in vitro against three species of Candida (C. albicans, C. tropicalis, and C. parapsilosis). The results of the FTIR and thermal analysis showed the incorporation of 6CN in the polymer matrix. In the diffractogram, the 6CN-chitosan films exhibited diffraction halos that were characteristic of amorphous structures, while the micrographs showed that 6CN particles were dispersed in the chitosan matrix, exhibiting pores and cracks on the film surface. In addition, the results of antifungal investigation demonstrated that 6CN-chitosan films were effective against Candida species showing potential for application as a new antifungal drug. 相似文献
The presence of illicit drugs and their metabolites in surface waters has to be considered a new type of hazard, still unknown, for the aquatic ecosystem, due to the potent pharmacological activities of all the illicit drugs. Our research was therefore aimed at evaluating the impact of illicit drugs on the aquatic fauna, till now still undervalued. To this aim, we verified the ability of the European eel (Anguilla anguilla), a well-known biomonitor of environmental contamination, to bioaccumulate cocaine, one of the most abundant illicit drugs found in surface waters. Silver eels were exposed to a nominal cocaine concentration of 20?ng/l for 1?month; at the same time, control, carrier, and post-exposure recovery groups were made. Brains, gills, liver, kidney, muscle, gonads, spleen, digestive tract, and sections of dorsal skin were assayed by high-pressure liquid chromatography. Cocaine was found in the tissues of the treated eels and, at low concentrations, in almost all tissues of post-exposure recovery eels. These results indicate that cocaine is able to accumulate into the eel tissues; its presence suggests potential risks for eels since cocaine could affect their physiology and contribute to their decline, and for humans consuming contaminated fish. 相似文献
The objectives of this study were: (1) to predict the rumen fermentation pattern from milk fatty acids using a machine learning technique, i.e. artificial neural networks (ANN) combined with feature selection and (2) to compare the prediction accuracy of the resulting model to that of a statistical multi-linear regression model, based on odd and branched chain milk fatty acids. Data were collected from 10 experiments with rumen fistulated dairy cows, resulting in a dataset of 138 observations. Feature selection was based on correlation and principal component analysis, and background physiological knowledge. Different ANN architectures and training algorithms were assessed. The evaluation of the model performance, based on the test dataset, showed a root mean square prediction error, expressed relative to the observed mean, of 2.65%, 7.67% and 7.61% of the observed mean for acetate, propionate and butyrate, respectively. Compared to a multi-linear regression model, the ANN revealed not to perform significantly better. However, the results confirm that milk fatty acids have great potential to predict molar proportions of individual volatile fatty acids in the rumen. 相似文献