RESUMEN
The changes in mineral elements during cider fermentation process were determined using ICP-MS. The results showed that the main minerals in the fermentation liquor included K, Na, Ca, Mg, Fe, Mn, Zn, Cu, Sr and B. The content of K was the highest in both the apple juice and the cider, being 1 853. 83 and 1 654. 38 mg . L-1 respectively. The content of minerals was in dynamic changes along with the fermentation process. As a whole, during 72-120 h and 144-216 h, most of the minerals contents underwent great fluctuation. Especially when fermented for 192 h, the content of most of the minerals reached peak value or valley value. The content of Fe and Zn achieved their peak value, while the content of K, Na, Ca, Mg, Mn and B achieved valley value. But during the following 24 h, the content of minerals underwent a sharp reversal. After fermentation, the content of K, Mg, Cu, Zn and B decreased significantly, while the content of Na, Ca, Mn, Fe and Sr did not change significantly. The correlational analysis was conducted to evaluate the correlation between the mineral elements, and the result showed that the correlation between Ca and Mn was the most significant, with the correlation index reaching 0. 924. The information of this study will supply sufficient data for the fermentation process control and quality improvement of cider.
Asunto(s)
Bebidas Alcohólicas/análisis , Fermentación , Minerales/análisis , Espectrometría de Masas , Espectrofotometría AtómicaRESUMEN
Agricultural fertilizers (AFs) have provided vegetation with necessary nutrients, but unabsorbed constituents have been retarded in soil, potentially affecting the quality of adjacent surface water and groundwater. AFs element contents and stable isotope compositions have often been utilized to assess and calculate AFs pollution to nitrate and sulfate in surface water and groundwater; however, due to various AFs applied, the dissolved ion concentrations and isotope ratios are still unknown. This study collected commercial AF widely utilized in Henan province, China, to constrain their ion concentrations and isotope values. The dissolved ions (1 g AFs dissolved in 1 L ultrapure water), sulfate sulfur, and oxygen isotope values(δ34S and δ18O) were analyzed, and total nitrogen (TN) contents coupled with nitrogen isotope values(δ15N) in solid AFs were determined to elucidate their elemental and isotopic compositions. These characteristics provided a scientific basis for further assessing their contributions to surface water and groundwater contaminations. The results indicated that pH values in the AFs solutions varied from 3.6 to 10.2, with a mean value of 6.7±1.5 (n=30, 1σ). Sulfate (SO42-) and nitrate (NO3-) concentrations ranged from 4.38 mg·L-1 to 827.29 mg·L-1 and from 1.34 mg·L-1 to 208.90 mg·L-1, with median values of 192.80 mg·L-1 and 13.51 mg·L-1 and average values of (256.19±239.83) mg·L-1 (n=30) and (37.07±53.21) mg·L-1 (n=29), respectively. Dissolved sulfate δ34S and δ18O values in AFs varied from -3.5 to 19.0 and from 6.7 to 18.5, with median values of 4.1 and 10.1 and mean values of (5.8±5.5) (n=22, 1σ) and (10.7±2.7) (n=22, 1σ), respectively. TN and δ15N values in AFs ranged from 0.5% to 38.9% and from -2.7 to 3.4, with median values of 13.3% and 0.0 and average values of (14.8±9.3)% (n=25) and 0.0±1.5 (n=24, 1σ), respectively. The lower averaged δ34S values and positive averaged δ18O values potentially resulted from sulfuric acids added as raw materials, giving rise to a negative relationship between pH values and SO42- concentrations (P<0.05). The δ15N values of AFs were close to that of air N2, corresponding to the fact that NO3--N and NH4+-N were synthesized via air N2. Our results revealed the dissolved ion concentrations of SO42-, NO3-, and NH4+ and their δ34S, δ18O, and δ15N values of typically applied AFs in Henan province, which provided the scientific basis for studying the AFs contributions to SO42- and NO3- pollutions in surface water and groundwater surroundings.
RESUMEN
Urban domestic sewage is one of the important nitrate (NO-3) sources for surface water; however, their NO-3 concentrations and nitrogen and oxygen isotope values (δ15N-NO-3 and δ18O-NO-3) remain unclear, and the factors affecting NO-3 concentrations and δ15N-NO-3 and δ18O-NO-3 values of effluents in the waste water treatment plant (WWTP) are still unknown. Water samples in the Jiaozuo WWTP were collected to illustrate this question. Influents, clarified water in the secondary sedimentation tank (SST), and effluents of the WWTP were sampled every 8 h. The ammonia (NH+4) concentrations, NO-3 concentrations, and δ15N-NO-3 and δ18O-NO-3 values were analyzed to elucidate the nitrogen transfers through different treatment sections and illustrate the factors affecting the effluent NO-3 concentrations and isotope ratios. The results indicated that â the mean NH+4 concentration was (22.86±2.16) mg·L-1 in the influent and decreased to (3.78±1.98) mg·L-1 in the SST and continuously reduced to (2.70±1.98) mg·L-1 in the effluent of the WWTP. The median NO-3 concentration was 0.62 mg·L-1 in the influent, and the average NO-3 concentration increased to (33.48±3.10) mg·L-1 in the SST and gradually increased to (37.20±4.34) mg·L-1 in the effluent of the WWTP. â¡ The mean values of δ15N-NO-3 and δ18O-NO-3 were (17.1±10.7) and (19.2±2.2) in the influent of the WWTP, the median values of δ15N-NO-3 and δ18O-NO-3 were 11.9 and 6.4 in the SST, and the average values were (12.6±1.9) and (5.7±0.8) in the effluent of the WWTP. ⢠The NH+4 concentrations of influent had significant differences compared to those in the SST and the effluent (P<0.05). The reduction of NH+4 concentrations in the SST was due to the above nitrification during the aerobic treatment process, which transferred NH+4 to NO-3. The NH+4 concentrations in the SST had no significant differences with that in the effluent of the WWTP (P>0.05). ⣠The NO-3 concentrations in the influent had significant differences with those in the SST and the effluent (P<0.05), and minor NO-3 concentrations but relatively high δ15N-NO-3 and δ18O-NO-3 values in the influent were probably due to denitrification during the pipe sewage transportation. The obviously increased NO-3 concentrations (P<0.05) but decreased δ18O-NO-3 values (P<0.05) in the SST and the effluent resulted from water oxygen incorporation during the nitrification. The above results confirmed the impacts of aerobic and anaerobic treatment processes on NO-3 concentrations and isotope ratios of effluent from the WWTP and provided scientific basis for the identification of sewage contributions to surface water nitrate via average δ15N-NO-3 and δ18O-NO-3 values.
RESUMEN
Fourier transform-near infrared (FT-NIR) spectra of microorganisms reflect the overall molecular composition of the sample. The spectra were specific and can serve as spectroscopic fingerprints that enable highly accurate identification of microorganisms. Bacterial powders of one yeast and five bacteria strains were prepared to collect FT-NIR spectra. FT-NIR measurements were done using a diffuse reflection-integrating sphere. Reduction of data was performed by principal component analysis (PCA) and two identification models based on linear discriminant analysis (LDA) and artificial neural network (ANN) were established to identify bacterial strains. The reproducibility of the method was proved to be excellent (D(yly2) : 1.61 +/- 1.05-10.97 +/- 6. 65) and high identification accuracy was achieved in both the LDA model (Accuracy rate: 100%) and the ANN model (Average relative error: 5.75%). FT-NIR spectroscopy combined with multivariate statistical analysis (MSA) may provide a novel answer to the fields which need for rapid microbial identification and it will have great prospect in industry.
Asunto(s)
Bacterias/clasificación , Espectroscopía Infrarroja por Transformada de Fourier , Espectroscopía Infrarroja Corta , Levaduras/clasificación , Análisis Discriminante , Modelos Lineales , Análisis Multivariante , Redes Neurales de la Computación , Análisis de Componente Principal , Reproducibilidad de los ResultadosRESUMEN
The sugar content and the matrix always are being changed during cider-making fermentation. In order to measure and monitor sugar content accurately and rapidly, it is necessary for the spectra to be sorted. Calibration models were established at different fermentation stages based on near infrared spectroscopy with artificial neural network. NIR spectral data were collected in the spectral region of 12 000-4 000 cm(-1) for the next analysis. After the different conditions for modeling sugar content were analyzed and discussed, the results indicated that the calibration models developed by the spectral data pretreatment of straight line subtraction(SLS) in the characteristic absorption spectra ranges of 7 502-6 472.1 cm(-1) at stage I and 6 102-5 446.2 cm(-1) at stage II were the best for sugar content. The result of comparison of different data pretreatment methods for establishing calibration model showed that the correlation coefficients of the models (R2) for stage I and II were 98.93% and 99.34% respectively and the root mean square errors of cross validation(RMSECV) for stage I and II were 4.42 and 1.21 g x L(-1) respectively. Then the models were tested and the results showed that the root mean square error of prediction (RMSEP) was 4.07 g x L(-1) and 1.13 g x L(-1) respectively. These demonstrated that the models the authors established are very well and can be applied to quick determination and monitoring of sugar content during cider-making fermentation.