Quantifying terpenes in tomato leaf extracts from different species using gas chromatography-mass spectrometry (GC-MS).

Terpenes play a vital role in plant defense; tomato plants produce a diverse range of terpenes within specialized glandular trichomes, influencing interactions with herbivores, predators, and pollinators. This study employed two distinct methods, namely leaf dip and maceration, to extract trichomes from tomato leaves. Terpene quantification was carried out using Gas Chromatography-Mass Spectrometry (GC-MS). The leaf dip method proved effective in selectively targeting trichome content, revealing unique extraction patterns compared to maceration. The GC-MS method demonstrated high linearity, accuracy, sensitivity, and low limits of detection and quantification. Application of the method to different tomato species (Solanum pennellii, Solanum pimpinellifolium, Solanum galapagense, Solanum habrochaites, and Solanum lycopersicum) identified significant variation in terpene content among these species, highlighting the potential of specific accessions for breeding programs. Notably, the terpene α-zingiberene, known for its repellency against whiteflies, was found in high quantities (211.90-9155.13 µg g-1) in Solanum habrochaites accession PI209978. These findings provide valuable insights into terpenoid diversity for plant defense mechanisms, guiding future research on developing pest-resistant tomato cultivars. Additionally, the study underscores the broader applications of terpenes in agriculture.

Investigating the Relationship between Surface Water Pollution and Onsite Wastewater Treatment Systems.

Onsite wastewater treatment systems (OWTSs) are important nonpoint sources (NPSs) of pollution to consider in watershed management. However, limited OWTS data availability makes it challenging to account for them as an NPS of water pollution. In this study, we succeeded in obtaining OWTS permits and integrated them with environmental data to model the pollution potential from OWTSs at the watershed scale using GIS-based multicriteria decision analysis. Then, in situ water quality parameters─Escherichia coli (E. coli), total nitrogen, total phosphorus, temperature, and pH─were measured along the main tributary at base-flow conditions. Three general linear models were developed to relate E. coli to water quality parameters and OWTS pollution indicators. It was found that the model with the OWTS pollution potential had the lowest corrected Akaike information criterion (AICc) value (35.01) compared to the models that included classified OWTS pollution potential input criteria (AICc = 36.76) and land cover (AICc = 36.74). These results demonstrate that OWTSs are a significant contributor to surface water pollution, and future efforts should be made to improve access to OWTS data (i.e., location and age) to account for these systems as an NPS of water pollution.

Arsenic-dissolved organic matter complexation in water soluble extracts from lignite.

Arsenic in groundwater is a global threat to public health. Recently, As mobility has been tied to the concentration and chemical characteristics of dissolved organic matter (DOM) through formation of As-DOM complexes. To date, there has been a wide range of DOM types studied to understand As-DOM interactions, but most of these have focused on surface water derived materials and not groundwater DOM. We address this gap in knowledge by simulating groundwater DOM using water extractable organic matter (WEOM) from two lignite deposits and treating the extracts with increasing concentrations of As. As-DOM complexes were measured using size-exclusion chromatography coupled to multiple detectors including an inductively coupled plasma mass spectrometer (ICPMS) for As detection as well as fluorescence and variable wave detectors for organic matter detection. First, we found two different size fractions of As-DOM, one of ∼1 kDa and another of ∼15 kDa, depending on the DOM types. The smaller As-DOM complex (∼1 kDa) was approximately 10 times more abundant than the larger complex (∼15 kDa). Second, we found that the lignite derived DOMs showed higher conditional distribution coefficients than did the surface water reference material (Suwanee River Natural Organic Matter, SRNOM). Finally, the data showed good fit (R2 > 0.92) to one-site ligand binding models, and the lignite derived DOMs showed higher maximum sorbate concentrations (Bmax) compared to SRNOM. Together, this study shows that As-DOM complexation is an important control on As speciation, even in groundwater systems.

Contribution of sedimentary organic matter to arsenic mobilization along a potential natural reactive barrier (NRB) near a river: The Meghna river, Bangladesh.

Elevated dissolved arsenic (As) concentrations in the shallow aquifers of Bangladesh are primarily caused by microbially-mediated reduction of As-bearing iron (Fe) (oxy)hydroxides in organic matter (OM) rich, reducing environments. Along the Meghna River in Bangladesh, interactions between the river and groundwater within the hyporheic zone cause fluctuating redox conditions responsible for the formation of a Fe-rich natural reactive barrier (NRB) capable of sequestering As. To understand the NRB's impact on As mobility, the geochemistry of riverbank sediment (<3 m depth) and the underlying aquifer sediment (up to 37 m depth) was analyzed. A 24-hr sediment-water extraction experiment was performed to simulate interactions of these sediments with oxic river water. The sediment and the sediment-water extracts were analyzed for inorganic and organic chemical parameters. Results revealed no differences between the elemental composition of riverbank and aquifer sediments, which contained 40 ± 12 g/kg of Fe and 7 ± 2 mg/kg of As, respectively. Yet the amounts of inorganic and organic constituents extracted were substantially different between riverbank and aquifer sediments. The water extracted 6.4 ± 16.1 mg/kg of Fe and 0.03 ± 0.02 mg/kg of As from riverbank sediments, compared to 154.0 ± 98.1 mg/kg of Fe and 0.55 ± 0.40 mg/kg of As from aquifer sediments. The riverbank and aquifer sands contained similar amounts of sedimentary organic matter (SOM) (17,705.2 ± 5157.6 mg/kg). However, the water-extractable fraction of SOM varied substantially, i.e., 67.4 ± 72.3 mg/kg in riverbank sands, and 1330.3 ± 226.6 mg/kg in aquifer sands. Detailed characterization showed that the riverbank SOM was protein-like, fresh, low molecular weight, and labile, whereas SOM in aquifer sands was humic-like, older, high molecular weight, and recalcitrant. During the dry season, oxic conditions in the riverbank may promote aerobic metabolisms, limiting As mobility within the NRB.

GIS interpolation is key in assessing spatial and temporal bioremediation of groundwater arsenic contamination.

Arsenic (As) contamination in groundwater is a global crisis that is known to cause cancers of the skin, bladder, and lungs, among other health issues, and affects millions of people around the world. Due to the time and financial constraints associated with establishing in-depth monitoring programs, it is difficult to monitor and map arsenic concentrations over time and across large areas. The goal of this study was to determine the most accurate Geographic Information Systems (GIS) interpolation method for mapping the effects of bioremediation on groundwater arsenic sequestration across a local-scale study area in northwest Florida (~900 m2) over the duration of a nine-month period (pre-injection, one-month post-injection, and nine-months post-injection). We used groundwater data collected from 2018 to 2019 to visualize arsenic contamination over time. Measured arsenic concentrations from 23 wells were grouped into three categories: (1) decreasing, (2) fluctuating, or (3) largely unaffected by the bioremediation procedure. The accuracy of three interpolation methods was also investigated: Inverse Distance Weighted (IDW), Ordinary Kriging (OK), and Empirical Bayesian Kriging (EBK). Statistical results using the leave-one-out cross validation (LOOCV) process showed that OK consistently provided the most accurate predictions of arsenic concentrations across space and time ([Root Mean Square Error (RMSE) = 0.265] and accurately predicted regulatory arsenic concentrations below 0.05 mg/L in nine of 11 wells, while IDW and EBK only accurately predicted four and five wells, respectively. While it was shown that OK tends to underpredict arsenic maxima, this did not affect the overall accuracy of the interpolation compared to results from EBK (RMSE = 0.297) and IDW (RMSE = 0.272). Overall, these interpolations aided in the interpretation of the extent of bioremediation, revealing the need for repeated injections to continuously remove arsenic from the groundwater. The study will provide guidance and evaluation methods for international and governmental organizations, industrial companies, and local communities on how to understand spatial and temporal distributions of arsenic contamination and inform bioremediation efforts at various scales in the future.

ESRD and ESRD-DM associated with lignite-containing aquifers in the U.S. Gulf Coast region of Arkansas, Louisiana, and Texas.

Balkan endemic nephropathy (BEN) is an irreversible, lethal kidney disease that occurs in regions of the Balkans where residents drink untreated well water. A key factor contributing to the development of BEN may be consumption of dissolved organic matter leached from low-rank coal called lignite. This hypothesis-known as lignite-water hypothesis-was first posed for areas of the Balkans. It is possible that a BEN-like condition exists in the United States (US) Gulf Coast region in parts of the Mississippi Embayment and the Texas Coastal Uplands aquifers -Arkansas, Louisiana, and Texas, for instance-that rely heavily on groundwater from aquifers that contain lignite. This study utilizes a geographic information system (GIS) to map the distributions of end-stage renal disease (ESRD) in relation to water from lignite-containing aquifers in the tri-state region. Regional patterns emerged from geospatial analysis, suggesting that counties that relied on lignite-containing aquifers for their main water source had higher rates of ESRD in comparison to other populations in the region that rely on other water sources, including surface water and groundwater from aquifers not associated with lignite seams. Statewide rates of ESRD and diabetes associated ESRD (ESRD-DM) showed strong correlations to the percent of families at or below poverty level and the percentage of African Americans. These confounding factors somewhat mitigate the association seen between ESRD and lignite-containing regions at the state level. However, at the larger tri-state view, there is a significant (p = 0.002) increase in incidence rates where groundwater is connected to lignite-containing aquifers when considering both race and poverty. Additionally, no relationship was observed between the rate of public water supply withdrawal from lignite-bearing aquifers and rates of ESRD or ESRD-DM at the state or tri-state regions, supporting the observation that the risk associated with water from lignite-containing aquifers is limited to water from untreated domestic supply.