Investigation of sorbate-induced plasticization of Pahokee peat by solid-state NMR spectroscopy

Purpose

Sorbate-induced swelling and plasticization of sorbent have been linked to sorption hysteresis of organic compounds in the natural organic matter of isolated humic acids, soils, and coals. The above processes, which have important implications for the fate and bioavailability of organic and inorganic contaminants, are mostly based on macroscopic changes and require molecular-level confirmation. This study aimed to investigate the presence or absence of sorbate-induced plasticization of Pahokee peat soil as a function of different sorbates.

Materials and methods

The plasticization of Pahokee peat soil was studied upon sorption of different proton-free solutes including C₆D₆, CDCl₃, CCl₄, C₂Cl₄, CBr₄, C₆D₅Cl, and C₅D₅N, covering apolar and polar aromatic and aliphatic compounds. The swelling and plasticization of Pahokee peat soil were verified at the molecular level by ¹H wideline and two-dimensional wideline separation (2D WISE) NMR. The use of ¹H wideline shapes is the traditional technique for studying molecular dynamics but hampered by the lack of spectral resolution, with one dimension displaying ¹³C chemical shifts and the second showing ¹H wideline shapes, is capable of providing information on molecular dynamics of specific functional groups.

Results and discussion

Our results showed that the segments of Pahokee peat soil sorbed with C₆D₆, C₂Cl₄, and C₅D₅N became more mobile, but the changes due to the plasticization were small. Both C₆D₆ and C₅D₅N selectively increased the mobility of specific components, C₆D₆ of the nonpolar alkyl domains, and C₅D₅N of both the nonpolar alkyl domains and aromatic components.

Conclusions

Some liquid solutes at high concentrations (2–5 wt%) are capable of slightly “softening” natural organic matter of a soil, and this provides support for the hypothesis that natural organic matter in Pahokee peat soil is in a glassy state that is subject to plasticization.

     

Bayesian Semiparametric Model for Pathway-Based Analysis with Zero-Inflated Clinical Outcomes

In this paper, we propose a semiparametric regression approach for identifying pathways related to zero-inflated clinical outcomes, where a pathway is a gene set derived from prior biological knowledge. Our approach is developed by using a Bayesian hierarchical framework. We model the pathway effect nonparametrically into a zero-inflated Poisson hierarchical regression model with an unknown link function. Nonparametric pathway effect was estimated via a kernel machine, and the unknown link function was estimated by transforming a mixture of the beta cumulative density function. Our approach provides flexible nonparametric settings to describe the complicated association between gene expressions and zero-inflated clinical outcomes. The Metropolis-within-Gibbs sampling algorithm and Bayes factor were adopted to make statistical inferences. Our simulation results support that our semiparametric approach is more accurate and flexible than zero-inflated Poisson regression with the canonical link function, which is especially true when the number of genes is large. The usefulness of our approach is demonstrated through its applications to the Canine data set from Enerson et al. (Toxicol Pathol 34:27–32, 2006). Our approach can also be applied to other settings where a large number of highly correlated predictors are present.Supplementary materials accompanying this paper appear on-line.     

Dynamic Modelling of Spatially Variable Catchment Hydrochemistry for Critical Loads Assessment

Concern about acidification in upland areas has brought about the need to model the stream hydrochemical response to deposition and land-use changes and calculate critical loads. Application of dynamic models such as MAGIC are preferable to steady-state methods, since they are able to produce an estimate of the time scale required to meet some water chemistry target given a reduction in acid deposition. These models typically consider annual changes in stream chemistry at one point. However, in order to protect biota from 'acid episodes', quantification of temporal variability needs to encompass event responses; in addition spatial variability across the catchment also needs to be considered. In this paper, modelling of both spatial and temporal variability is combined in a new framework which enables quantification of catchment hydrochemical variability in time and space. Both low and high flow hydro-chemical variability are quantified in terms of statistical distributions of ANC (Acid Neutralisation Capacity). These are then input as stochastic variables to an EMMA (End-Member Mixing Analysis) model which accounts for temporal variability and ANC is hence predicted as a function of time and space across the whole catchment using Monte-Carlo simulation. The method is linked to MAGIC to predict future scenarios and may be used by iteration to calculate critical loads. The model is applied to the headwaters of the River Severn at Plynlimon, Wales, to demonstrate its capabilities.     

Blind inlets: conservation practices to reduce herbicide losses from closed depressional areas

Purpose

In a 6-year study, we investigated the effectiveness of blind inlets as a conservation practice in reducing pesticide losses compared to tile risers from two closed farmed depressional areas (potholes) in the US Midwest under a 4-year cropping rotation.

Materials and methods

In two adjacent potholes within the same farm and having similar soils, a conventional tile riser and blind inlet were installed. Each draining practice could be operated independent of each other in order to drain and monitor each depression with either practice. Sampling events (runoff events) were collected from the potholes from 2008 to 2013 using autosamplers. The samples were analyzed for atrazine, metolachlor, 2,4-D, glyphosate, and deethylatrazine.

Results and discussion

The results of this study demonstrated that the blind inlet reduced analyzed pesticide losses; however, the level of reduction was compound dependent: atrazine (57 %), 2,4-D (58 %), metolachlor (53 %), and glyphosate (11 %).

Conclusions

Results from this study corroborate previous research findings that blind inlets are an effective conservation practice to reduce discharge and pollutants, including pesticides from farmed pothole surface runoff in the US Midwest.

     

Genetic diversity in <Emphasis Type="Italic">Eremostachys superba</Emphasis> Royle ex Benth. (Lamiaceae), an endangered Himalayan species,as assessed by RAPD

Eremostachys superba Royle ex Benth. (Lamiaceae) has undergone a severe decline in population size since its discovery in the North-western Himalayas in late 19th century. One hundred and seventy-two plants from six populations in the Indian states of Uttar Pradesh and Jammu & Kashmir, located between 0.45 km and 455.72 km apart from each other were evaluated for RAPD polymorphism. Sixteen random primers generated 92 bands overall, 77 of which were polymorphic. Shannon’s index of genetic diversity within populations (H _o) ranged between 0.305 and 0.421; the average within-population diversity (H _pop) was 0.389; and the total species diversity (H _sp) was 0.478. The population from Mohand (representing the type locality) had the fewest plants, at 18, and was genetically the most depauperate. Among the other populations, ranging in size between 52 and 1,022 individuals, no relation between population size and genetic diversity was evident. It is suggested that these six populations represent relics of a larger, extended population, in which the presence of perennating rootstocks has helped preserve historic patterns of genetic diversity. AMOVA revealed that 83.01% of the variation exists within populations, which was consistent with earlier studies on the reproductive biology of E. superba, which indicated this species is predominantly allogamous. FST distances between all populations were significant, indicating geographic differentiation despite some of them being closely separated. Habitat restoration and protection from indiscriminate harvesting are proposed as primary strategies for conserving E. superba. Rejuvenation of the Mohand population through intrapopulation crossing between plants bearing diverse molecular phenotypes is also suggested.     

Development of EST-SSR in foxtail millet (<Emphasis Type="Italic">Setaria italica</Emphasis>)

The development of EST-SSR in foxtail millet (Setaria italica) for polymorphism and transferability study was reported here. From 1213 EST sequences, 30 SSRs were obtained and primers were designed for 26 SSRs. Among them, four pairs of SSR primers amplified polymorphic products in 12 foxtail millet cultivars and one accession of Setaria viridis, a wild relative of foxtail millet, with 10 alleles detected for the four loci and 2.5 alleles per locus. In addition, ten SSR markers could be transferred to other nine Gramineae species. The putative functions of 11 ESTs containing polymorphic and transferable SSRs were also identified.     

Near-infrared spectroscopy for analysis of chemical and microbiological properties of forest soil organic horizons in a heavy-metal-polluted area

In industrial areas, heavy metals may accumulate in forest soil organic horizons, affecting soil microorganisms and causing changes in the chemical composition of the accumulated organic matter. The objectives of this study were to test the ability of near-infrared spectroscopy (NIRS) to detect heavy metal effects on the chemical composition of forest soil O horizons and to test whether NIRS may be used to quantitatively determine total and exchangeable concentrations of Zn and Pb (Zn_t, Pb_t, Zn_ex, Pb_ex) and other chemical and microbial properties in forest soil O horizons polluted with heavy metals. The samples of O horizons (n = 79) were analyzed for organic C (C_org), total N and S (N_t, S_t), Zn_t, Pb_t, Zn_ex, Pb_ex, basal respiration (BR), microbial biomass (C_mic) and C_mic-to-C_org ratio. Spectra of the samples were recorded in the Vis-NIR range (400–2,500 nm). To detect heavy-metal-induced changes in the chemical composition of O horizons principal components (PC1–PC7) based on the spectral data were regressed against Zn_t + Pb_t values. A modified partial least squares method was used to develop calibration models for prediction of various chemical and microbial properties of the samples from their spectra. Regression analysis revealed a significant relationship between PC3 and PC5 (r = −0.27 and −0.34, respectively) and Zn_t + Pb_t values, indicating an effect of heavy metal pollution on the spectral properties of the O horizons and thus on their chemical composition. For quantitative estimations, the best calibration model was obtained for C_org-to-N_t ratio (r = 0.98). The models for C_org, N_t, and microbial properties were satisfactory but less accurate. NIRS failed to accurately predict S_t, C_org-to-S_t, Zn_t, Pb_t, Zn_ex, and Pb_ex.     

Spatial patterns of diversity and genetic erosion of traditional cassava (<Emphasis Type="Italic">Manihot esculenta</Emphasis> Crantz) in the Peruvian Amazon: An evaluation of socio-economic and environmental indicators

This study evaluates quantitatively the suitability of the use of site-specific socio-economic and environmental data as indicators to rapidly assess patterns of diversity and genetic erosion risk in cassava. Socio-economic data as well as farmers’ estimation of genetic erosion were collected in the study area, the Ucayali region of the Peruvian Amazon, through interviews with 285 cassava farmers in 50 communities, while diversity was assessed based on agromorphological characterization of 295 cassava accessions. Using multivariate regression analyses, 50 and 45% of the variation in respectively diversity and genetic erosion estimation could be explained by a selected set of socio-economic and environmental indicators. In both regression models four out of the total of 38 variables proved to contribute significantly (at p < 0.10 level). Additionally, the study revealed that farmers are a good direct source of information on the diversity present at community level, which can contribute to the development of methodologies to assess diversity more rapidly. The results of this study are valuable for the development of models to rapidly assess diversity dynamics in large areas.     

Genetic diversity of potato landraces from northwestern Argentina assessed with simple sequence repeats (SSRs)

Andean potato varieties are cultivated in the northwest of Argentina and constitute the most important staple food for the local farmers. The genetic diversity of 155 accessions conserved at the Genebank of Balcarce (INTA) was tested using four microsatellites. Three commercial potato varieties of Tuberosum group and one accession of Curtilobum group were used as outgroups. The presence of bands was scored for each microsatellite and for each accession and the data were analysed by principal coordinate analysis. The polymorphism information content was obtained for each molecular marker from banding patterns. Analysis of molecular variance was carried out with a variable number of accessions for each landrace, from different departments and sites within departments. More than one genotype was detected in the majority of the potato landraces. Some accessions within each landrace did not differentiate. AMOVA revealed that most of the genetic variation occurred among sites within departments and among local varieties. These findings are discussed considering the agricultural practices carried out in the Andean farming system.