Soil Samples Research Articles

Evaluating Source Complexity in Blended Milk Cheese: Integrated Strontium Isotope and Multi-Elemental Approach to PDO Graviera Naxos.

Graviera Naxos, a renowned cheese with Protected Designation of Origin status, is crafted from a blend of cow, goat, and sheep milk. This study focused on assessing the Sr isotopic and multi-elemental composition of both the processed cheese and its ingredients, as well as the environmental context of Naxos Island, including samples of milk, water, soil, and feed. The objective was to delineate the geochemical signature of Graviera Naxos cheese and to explore the utility of Sr isotopes as indicators of geographic origin. The 87Sr/86Sr values for Graviera Naxos samples ranged from 0.70891 to 0.70952, indicating a relatively narrow range. However, the Sr isotopic signature of milk, heavily influenced by the feed, which originates from geologically distinct areas, does not always accurately reflect the local breeding environment. Multi-elemental analysis revealed variations in milk composition based on type and season; yet, no notable differences were found between raw and pasteurized milk. A mixing model evaluating the contributions of milk, sea salt, and rennet to the cheese's Sr isotopic signature suggested a significant average contribution of 73.1% from sea salt. This study highlights the complexities of linking dairy products with their geographical origins and emphasizes the need for sophisticated geochemical authentication methods.

Assessment and genomic analysis of Salmonella and Campylobacter from different stages of an integrated no-antibiotics-ever (NAE) broiler complex: a longitudinal study

The objective of this study was to determine prevalence and perform genomic analysis of Salmonella spp. and Campylobacter spp. isolated from different stages of an integrated NAE broiler complex. Environmental samples were screened with 3M-Molecular Detection System (MDS) and MDS positive samples were further processed for confirmation of results and identification. Core genome-based phylogenies were built for both bacteria isolated from this study along with selected NCBI genomes. The odds ratios and 95% confidence limits were compared among stages and sample types (α < 0.05) using multivariable model. Based on MDS results, 4% and 18% of total samples were positive for Salmonella spp. and Campylobacter spp. respectively. The odds of Salmonella detection in hatchery samples were 2.58 times as likely as compared to its detection in production farms' samples (P = 0.151) while the odds of Campylobacter detection in production farms' samples were 32.19 times as likely as its detection in hatchery (P = 0.0015). Similarly, the odds of Campylobacter detection in boot swabs, soil, water, and miscellaneous samples were statistically significant (P < 0.05) as compared with fly paper as reference group. The serovars identified for Salmonella were Typhimurium, Barranquilla, Liverpool, Kentucky, Enteritidis, Luciana, and Rough_O:r:1,5. For Campylobacter, the species identified were Campylobacter jejuni and Campylobacter coli. Phylogeny results show close genetic relatedness among bacterial strains isolated from different locations within the same stage and between different stages. The results show possibility of multiple entry points of such bacteria entering broiler complex and can potentially contaminate the final raw product in the processing plant. It suggests the need for a comprehensive control strategy with strict biosecurity measures and best management practices to minimize or eliminate such pathogens from the poultry food chain.

Woody species’ carbon sequestration and soil seed bank conservation potentials of traditional rangeland management strategies in Western Guji, Southern Ethiopia

Rangelands are important for mitigating climate change and rehabilitating land by storing carbon from woody plants and seeds in the soil. However, there is a lack of empirical data on how traditional rangeland management practices (such as enclosure, communal grazing and prescribed fire) affect the carbon storage of woody species and the conservation potential of soil seed banks. This study evaluates the carbon sequestration and soil seed bank conservation potential of traditional rangeland management practices in the Western Guji zone, Ethiopia. A total of 32 sample plots were established using systematic random sampling, with 12 in each management practice, to measure woody biomass and estimate carbon stock using a nondestructive method. Additionally, 72 soil samples were collected for soil seed bank analysis, with 24 samples taken from each type of rangeland management practice. The study found that enclosures had the highest amount of carbon stocks 63.1 tons per hectare (t ha−1), with a corresponding carbon dioxide equivalent (CO2e) sequestration of 231.58 t ha-1, followed by communal grazing areas that stored 27.05 t ha−1 of carbon with a CO2e sequestration of 99.27 t ha−1. Prescribed fire had the lowest carbon stocks at 19.39 t ha−1, with a CO2e sequestration of 71.16 t ha−1. The study also found that different traditional rangeland management practices significantly influenced the diversity, richness, and density of woody species in soil seed banks. The highest Shannon diversity was recorded in enclosures (3.56 ± 0.09), followed by communal grazing (2.87 ± 0.14) and prescribed fire (1.27 ± 0.08). As a result, enclosure promotes the storage of carbon in woody plants and increases the diversity, density, and richness of woody species seeds in the soil, while prescribed fire reduces it. Therefore, it recommend for pastoralists to expand the use of enclosures as it improves the potential for conserving carbon stocks and soil seed banks of woody species.

Phylogenetic and Morphological Analysis of a Novel Tolypocladium Species Isolated from Soil in South Korea

A fungal strain designated KNUF-22-014, belonging to the family Ophiocordycipitaceae, was isolated from a soil sample collected in Sobaeksan National Park, South Korea. Phylogenetic trees based on the combined sequences of internal transcribed spacer (ITS) regions and the large subunit of 28S rRNA (LSU) gene, as well as on five concatenated loci (LSU, ITS, translation elongation factor 1α, β-tubulin, and subunit 1 of RNA polymerase II), revealed that the isolate falls within the clade containing the genus Tolypocladium but occupies a distinct phylogenetic position. Its closest relative is T. tropicale. Morphologically, strain KNUF-22-014 can be distinguished from T. tropicale by the shape of its phialides (subcylindrical vs. lageniform), its conidiophore type (arborescent or unbranched vs. trichodermatoid), and its larger conidia size (2.1 ± 0.1 µm vs. 1.5 ± 0.1 µm). Phylogenetic analysis and morphological observations indicate that KNUF-22-014 represents a novel species in the genus Tolypocladium, for which the name Tolypocladium sobaeksanense sp. nov. is proposed.

Differential recruitment of plant growth-promoting bacteria community by soybean rhizosphere in no-tillage and integrated crop-livestock

Agricultural practices influence plant-microbe interactions in the rhizosphere and, particularly can drive the recruitment of plant growth-promoting bacteria (PGPB). This study assessed the PGPB community in soil under no-tillage (NT) and in the rhizosphere of maize and grass under integrated cro-livestock (ICL) to evaluate their influence on the recruitment of PGPB in the rhizosphere of soybean. Soil samples from the soybean rhizosphere under NT and ICL were collected and compared to samples collected from bulk soil and the rhizosphere of maize and grass in ICL, using the 16 S rRNA approach. The structure of the PGPB community differed (21.8% of variation) when comparing the rhizosphere of soybean in NT and ICL. The soybean rhizosphere in NT enriched distinct PGPB compared to those observed in ICL. The proportion of specialist PGPB was higher in the rhizosphere of soybean in ICL (33.8%) than in NT (26.5%). Regardless of the agricultural system, the rhizosphere of soybean showed a similar number of nodes, but ICL promoted a higher number of edges in the soybean rhizosphere. Bacillus and Mycobacterium were identified as the main keystone taxa in the rhizosphere of soybean in NT. In contrast, Streptomyces and Sphingomonas were keystone taxa in the rhizosphere of soybean in ICL. This study demonstrated distinct recruitment of PGPB by the rhizosphere of soybean based on agricultural systems, i.e., NT and ICL.

Exchangeable acidity characteristics of farmland black soil in northeast China

Exchangeable aluminum (Exc-Al), an often overlooked yet indispensable soil parameter, predominantly contributes to soil exchangeable acidity. In this study, we utilized data from 53 sets of surface and subsurface black soil characteristics, including Exc-Al, exchangeable acid (Exc-acid), pH, soil organic matter (SOM), and available and total nutrient levels, to develop a neural network prediction model for estimating Exc-Al and Exc-acid in the black soil area of northeast China. The deterministic neural network model (NNM) was employed to predict Exc-Al and Exc-acid contents in 690 sets of surface and subsurface farmland soil samples with unknown Exc-Al and Exc-acid values. Subsequently, a black soil exchangeable acidity map for northeast China was generated through spatial interpolation. Our results revealed that the average Exc-Al and Exc-acid contents in the 53 surface soils were 0.82 and 0.93 cmol kg−1, respectively, while those in the corresponding subsurface soils were 0.58 and 0.70 cmol kg−1, respectively. Multi-layer perceptron (MLP) neural networks effectively simulated Exc-Al and Exc-acid contents in the surface and subsurface black soils, with calibrated determination coefficients (Radj2) of 0.95–0.96, relative root mean square errors (rRMSE) of 17.3%–24.8%, and statistical significance α at 0.001. The MLP estimations and spatial interpolations revealed that 2.0% and 17.6% of the surface black soil area, and 0% and 3.7% of the subsurface soil area exhibited Exc-Al content exceeding 2.0 and 1.0 cmol kg−1, respectively. Furthermore, 6.7% and 24.9% of the surface black soil area, and 0% and 6.3% of the subsurface soil area showed Exc-acid content exceeding 2.0 and 1.0 cmol kg−1, respectively. These findings break the limitation of relying solely on soil pH as the unique indicator, enrich our knowledge of black soil exchangeable acidity, and enhance our understanding of the black soil acidity status in northeast China.

Experimental research on shear strength characteristics of cement-stabilized dredged silty clay reinforced with alginate fiber

In order to avoid uneven dispersion or agglomeration of traditional fibers after mechanical mixing, alginate fibers as natural fibers were selected in this study to reinforce the cement-stabilized dredged silty clay, forming alginate fiber-reinforced cement-stabilized dredged silty clay. The shear strength of cement-stabilized dredged silty clay reinforced with alginate fibers with the same cement content (9 % by wet weight) and cured for 7 and 28 days was investigated. Consolidated undrained (CU) triaxial compression tests were carried out on reinforced soil samples with varying fiber lengths (3 mm, 6 mm, and 9 mm) and fiber contents (0 %, 0.3 %, 0.6 %, and 0.9 % by weight of wet soil) to assess the shear strength characteristics. The results showed that, on average, the shear strength increased by 18.30 % and 18.56 % with the increasing content and length of alginate fibers, respectively. The variation in deviator stress and axial strain exhibited a shift from strain-softening to strain-hardening with increased confining pressure, alginate fiber content, and length. Hence, a double exponential curve model with different fiber content and length in three confined pressures was proposed, and the correlation coefficient of the fitting results was above 0.90. The secant modulus E50 increased and subsequently decreased with the length of fibers, with the largest secant modulus E50 observed for 6 mm fiber length. The strength parameters (cohesion c and internal friction angle φ) exhibited contrasting responses to variations in alginate fiber length and content. The cohesion of the fiber-reinforced soil specimens increased by 29.0 % and 13.1 %, respectively, for increased fiber content and length. Nevertheless, the angle of internal friction remained relatively unchanged. The findings of this study can serve as a reference guide for related engineering projects.

The distribution of particulate organic matter in the heterogeneous soil matrix - Balancing between aerobic respiration and denitrification

Denitrification, a key process in soil nitrogen cycling, occurs predominantly within microbial hotspots, such as those around particulate organic matter (POM), where denitrifiers use nitrate as an alternative electron acceptor. For accurate prediction of dinitrogen (N2) and nitrous oxide (N2O) emissions from denitrification, a precise quantification of these microscale hotspots is required. The distribution of POM is of crucial importance in this context, as the local oxygen (O2) balance is governed not only by its high O2 demand but also by the local O2 availability.Employing a unique combination of X-ray CT imaging, microscale O2 measurements, and 15N labeling, we were able to quantify hotspots of aerobic respiration and denitrification. We analyzed greenhouse gas (GHG) fluxes, soil oxygen supply, and the distribution of POM in intact soil samples from grassland and cropland under different moisture conditions. Our findings reveal that both proximal and distal POM, identified through X-ray CT imaging, contribute to GHG emissions. The distal POM, i.e. POM at distant locations to air-filled pores, emerged as a primary driver of denitrification within structured soils of both land uses. Thus, the higher denitrification rates in the grassland could be attributed to the higher content of distal POM. Conversely, despite possessing compacted areas that could favor denitrification, the cropland had only small amounts of distal POM to stimulate denitrification in it. This underlines the complex interaction between soil structural heterogeneity, organic carbon supply, and microbial hotspot formation and thus contributes to a better understanding of soil-related GHG emissions.In summary, our study provides a holistic understanding of soil-borne greenhouse gas emissions and emphasizes the need to refine predictive models for soil denitrification and N2O emissions by incorporating the microscale distribution of POM.

Ag nanoparticle-embedded fish scales as SERS substrates for sensitive detection of forever chemical in real samples

Biological materials with unique surface properties provide a new avenue for fabricating green and sensitive SERS-active substrates. Herein, we present a simple but efficient method to prepare surface-enhanced Raman scattering (SERS) substrates by depositing silver nanoparticles (AgNPs) on fish scale substrates using an evaporation-induced self-assembly method (EISA). Characterization of the formed flexible Ag-impregnated substrate proved outstanding SERS sensitivity, uniformity, and reproducibility properties, with a Raman enhancement factor of 1.3 × 106 and a relative standard deviation of 6.4 %. Using this powerful fish scale substrate, a toxic environmental pollutant perfluorooctane sulfonamide (PFOSA) was indirectly detected in lake water, soil, and human urine samples. Due to its chemical structure, it is difficult to detect low concentrations of PFOSA in real samples. Interestingly, malachite green (MG) was smartly used as the Raman label for PFOSA detection in real samples. One of the main appeals is that the concentration of PFOSA can be correlated with a decrease in the SERS signal of MG in real samples. In conclusion, the strategy employed and reproducible SERS substrates may have diverse applications in clinical and environmental analyses.

A modified methodology for extraction and quantification of microplastics in soil

The ubiquitousness of microplastics (<5 mm) has become a pressing environmental concern globally due to the extensive use of plastics. Microplastics have been well-studied in aquatic environments but not well-characterized in soils. Present analytical processes to quantify microplastics accurately in soil samples are quite challenging and require improved and validated analytical steps to eliminate the obscurities and biases. We aimed to develop an effective method for the extraction and quantification of microplastics from soil samples. Different ratios of low-(NaCl) and high-density solutions (ZnCl2/ NaBr) were tested to determine the most efficient combination for density-dependent separation of microplastics from soil. The combination of low- (1:6) and high-density (1:3) solutions {as weight of soil(g)/volume of density solution(ml)} accounted for 95% recovery of the spiked microplastic particles from soil samples. Likewise, different soil-to-solution ratios of H2O2 were tested for the removal of soil organic matter with heating and non-heating steps. Prior removal of organic matter from soil samples achieved a clear supernatant that facilitated 99% recovery of microplastic particles. The validation of individually spiked microplastic particles of small (10-100 μm) and large scale (100-5000 μm) resulted in recovery ranging from 88 to 99%. A validated modified method with prior digestion followed by density-dependent separation was further tested using the field samples with microplastic contamination. The microplastics of different shapes, sizes, colours and polymeric compositions were reported efficiently and well characterized in the field-collected soil samples using this method.

Determination of tetracycline residues in potatoes and soil by LC-MS/MS: Method development, validation, and risk assessment

A method utilizing liquid-liquid extraction (LLE) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed and validated according to the Commission Implementing Regulation (CIR) EU 2021/808 for quantifying four tetracyclines (TCs) in potatoes and soil. The method demonstrated recovery values ranging from 70 to 121% and precision (repeatability and within-laboratory reproducibility), with coefficient of variation (CV) values below 18% for all TCs in both matrices. The limits of quantification (LOQs) for the TCs ranged from 0.90 to 1.87 μg/kg in potatoes and from 0.68 to 1.25 μg/kg in soil. The decision limit (CCα) and detection capability (CCβ) ranged from 10.4 to 12.3 μg/kg and 11.9 to 14.3 μg/kg, respectively. Analysis of 538 potato and soil samples from Egyptian farms revealed a 13.2% occurrence of TC residues, with a higher frequency in soil (19.33%) than in potatoes (7.06%). Target hazard quotient (THQ) values indicated that TC residues in potatoes do not pose a health risk to Egyptian consumers.

Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation

Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing’s central urban area. Results indicated that Cd was the primary pollutant, with 28.33 % of soil samples exceeding the screening value. Amaranth was particularly problematic, exceeding thresholds for Cd, Hg, and Cr, and both amaranth and celery showed significantly higher HM accumulation (p < 0.05). The HM pollution level in the soil-vegetable system was moderate or above. The sources of HMs identified via Positive matrix factorization (PMF) model included agricultural activities (18.19 %), natural soil parent material (25.88 %), mixed metal smelting and transportation (30.72 %), and coal combustion (25.21 %). Furthermore, evaluations using the Random Forest (RF) model revealed an intricate interaction of factors influencing the presence of HMs, where enterprise density, population density, and road density played significant roles in HMs accumulation. Monte Carlo assessments revealed higher non-carcinogenic risks for children (Pb, As) and greater carcinogenic risks for adults (Cd). Therefore, the issue of HM pollution in soils and vegetables from fragmented fields in industrial urban areas need attention, given the potential for elevated health risks with long-term vegetable consumption.

Long-Term Effect of Crop Succession Systems on Soil Chemical and Physical Attributes and Soybean Yield.

Most soybean producers in the Cerrado biome use the direct seeding system, making it essential to cultivate cash or cover crops in the off-season, to promote soil protection, as well as increase organic matter, which is directly related to improvements in the chemical and physical characteristics of these soils. In this sense, this work was conducted in Jataí, state of Goias, Brazil, to evaluate the physical-chemical attributes of the soil and the performance of soybeans cultivated in different crop succession systems cultivated for 6 years in the region of Jataí, GO. The experimental design was randomized blocks with four plots and four replications; the crops that followed soybeans were arranged as follows: T1-corn (Zea mays); T2-pearl millet (Pennisetum glaucum); T3-Urochloa ruziziensis; and T4-corn + Urochloa ruziziensis. Soybean yield components and grain yield were evaluated in two harvests (2020/2021 and 2021/2022). Deformed and undisturbed soil samples were collected in 2022 to assess soil fertility and for physical analysis. The data were subjected to analysis of variance (F test) and the means were compared using the Tukey test at 5% probability. The soybean-millet succession system stood out for the chemical and physical attributes of the soil: calcium, magnesium, base saturation, hydrogen + aluminum, and total porosity. The crop succession system did not affect yield for the two years analyzed, but the accumulated grain yields were higher in the crop succession soybean/corn intercropped. The results highlight the importance of using cover crops in improving the physical and chemical qualities of the soil in the long term. However, in the Cerrado, there is a predominance of the soybean/corn succession system motivated by financial issues to the detriment of the qualitative aspects of the soil, in which the introduction of Urochloa ruziziensis in intercropping with corn would improve the chemical attributes of the soil and have a long-term impact on the accumulated grain production.

Experimental characterization of contact resistance of desert soil with waste-enhancement materials in grounding systems

This study aims to investigate how the electrical-resistivity of different soils and grounding enhancement-materials is influenced by water-content and the dehydration under ambient and high-constant temperatures. The used enhancement-materials were extracted from surrounding wastes in Egyptian desert. First, waste enhancement-materials, their developed-mixture and soil samples were prepared for experimental testing. The contact-resistance between soil and enhancement-material was measured by using a designed soil-box. It was observed that adding a wood-ash as an interface-layer between the soil and enhancement-materials decreased significantly the contact-resistance. The developed-mixture and wood-ash demonstrated highest water-content retention when compared against the other enhancement-materials. This maintains their resistivity values low to serve for grounding purpose. The wood-ash has the smallest grain–size diameter among the enhancement-materials. This is why it ensures effective contact between the soil and enhancement-materials in grounding systems. The effect of varying injected-current through the soil-box on the resistance values of soils and enhancement-materials is also investigated. Finally, the effectiveness of using of these materials in reducing the resistance-to-ground of a practical copper rod buried into desert soil is evaluated.

From Farm to Fork: Enhancing Agricultural and Food Safety Monitoring with Laser-Engineered Graphene Sensors

In the critical fields of precision agriculture and food safety, the demand for accurate and sensitive monitoring tools for fertilizers, pesticides, and food-borne pathogens cannot be overstated. Our collaborative research with commercial entities seeks to overcome the challenges faced by current electrochemical ion-selective, enzymatic, and immunosensors, which often fall short in selectivity, stability, and sensitivity, particularly under field conditions. We showcase the tunable properties of Laser-Induced Graphene (LIG) – such as surface wettability, roughness/area, and electrical conductivity – and their instrumental role in enhancing the commercial viability of these sensor technologies.We demonstrate the conversion of hydrophilic Laser-Induced Graphene (LIG) to a near-superhydrophobic state using an innovative dual-laser process in ambient conditions. This method intricately sculpts the surface into micro and nanoscale structures reminiscent of a lotus leaf, resulting in nearly superhydrophobic characteristics. By modifying the laser's power, speed, and fluence, we can also fine-tune the electroactive surface area and electrical conductivity, significantly impacting sensor functionality. For solid contact ion-selective electrodes (SC-ISEs), enhancing the LIG surface with high hydrophobicity prevents water layer accumulation at the ion-selective membrane and electrode interface. This design expels water from within the membrane, fosters stronger membrane-electrode adhesion, and consequently, diminishes signal interference. Such improvements are instrumental in boosting the sensor's accuracy and extending its operational lifespan. In contrast, a hydrophilic LIG with a large surface area enhances catalytic efficiency and allows more biorecognition agents to adhere to its surface, thereby amplifying the sensitivity of enzymatic pesticide sensors. Lastly, a flat, hydrophilic LIG surface ensures an even distribution of antibodies, which enhances the performance of sensors detecting foodborne pathogens.These modifications to LIG and the resulting sensors have substantial commercial potential. We have developed ions sensors for nitrate, ammonium, potassium, calcium, and magnesium have demonstrated near-Nernstian sensitivities, extensive sensing ranges across four orders of magnitude, and the ability to detect concentrations as low as 1 ppm in soil and water samples. These sensors are currently being integrated into commercial soil moisture and temperature probes for monitoring in farm fields. The pesticide sensing capability of the sensor can reach an extremely low picomolar detect limit for organophosphates, the nanomolar regime for neonicotinoids, and micromolar regime for glyphosate in surface waters. These sensors are currently being interfaced with LIG-based mist/fog harvesting devices to monitor pesticide and spray drift in farm fields. Finally, the LIG-based Salmonella sensors are capable of monitoring bacteria such as Salmonella to about 10 CFU/mL in actual food matrices such as chicken broth without the need for sample preconcentration or costly lab analyses.This research forges innovative avenues in agriculture and food safety monitoring, laying the groundwork for mass production of efficient and economical sensors. We believe this technology will revolutionize field monitoring, significantly advancing sustainable agriculture and improving public health safety. Figure 1

Printed and Laser Induced Graphene Electrochemical Biosensors for Rapid Environmental and Biomedical Monitoring

This presentation will demonstrate how low-cost printed and flexible graphene circuits can overcome the challenges associated with conventional electrical circuits to open the door to a highly sensitive monitoring of biochemical threats and toxins including nerve agents/pesticides. The use of inkjet and aerosol printing; spin coating; and laser writing (i.e., laser induced graphene) can be used to create such circuits with high resolution (line widths as low as 20 µm). Moreover, the use of rapid-pulse laser annealing of the printed graphene and/or salt porogens added into graphene inks before printing can be used to further improve the electrical conductivity (< 10 ohms/sq.) and electroactive surface area (nano/micro structuring) of the graphene circuits as well as be used to tune the surface of the printed graphene from one that is hydrophilic (water contact angle (WCA) = 48°) to one that is superhydrophobic (WCA = 158°). More recently we demonstrate how graphene synthesis, patterning and surface wettability can all be controlled through a laser induced graphene (LIG) process that creates a high surface area graphene surface directly from polyimide. Such LIG circumvents the need to create solution-phase graphene inks for printing. These printing and laser fabrication techniques are also amenable for use on flexible and chemically/thermally sensitive surfaces including polymers and paper.Moreover, the laser etched printed graphene and LIG exhibits an inherent 3D morphology that significantly increases the electrode electroactive surface over traditional 2D planar graphene electrodes. This large increase in surface area significantly improves the loading of enzyme onto the electrode surface and subsequently increases the heterogenous charge transport during catalytic pesticide sensing. Such ion sensors displayed near-Nernstian sensitivities, wide sensing ranges over four orders of magnitude extending from the 10–2 M down to detection limits in the 10–6 M range or for fertilizer ions (nitrate, ammonium, potassium, calcium, and magnesium) reaching down to detection limits less than 1 ppm in some cases in soil and water samples. The pesticide sensing capability of the sensor is able to reach an extremely low picomolar detect limit for organophosphates (paraoxon) and to the nanomolar regime for neonicotinoids in surface waters. We also demonstrate how this flexible LIG electrodes can be coupled with polymeric microfluidics and adhered to the body for continuous monitoring of lactate, glucose, and sodium in the sweat. Finally, we demonstrate how such surface wettability patterning of the printed graphene and LIG itself through laser etching can be used to make hydrophilic LIG tracks surrounded by near superhydrophic sidewalls for open microfluidic fluid transport without the need for polymeric microfluidics. Such open microfluidic tracks enable the splitting and transport of fluid samples to distinct electrochemical sensors for multiplexed biosensing of both fertilizer ion and pesticide monitoring from water samples and assist in harvesting sprayed pesticides in the field. Figure 1

Comprehensive analysis of correlations between soil electrical resistivity and index geotechnical properties

This study investigates the relationships between soil electrical resistivity and key geotechnical properties to develop predictive models for designing grounding systems in electrical substations. Conducted on 30 soil samples from various different regions of Thailand, the research evaluates resistivity in relation to soil water content, plasticity index, and dry density. Using a comprehensive laboratory setup, the soil samples were evaluated under controlled conditions, including temperature, humidity, and salt content of the soil samples, to establish robust correlations between the measured resistivity and the index geotechnical parameters. The results reveal a significant inverse relationship between soil resistivity and water content, confirming that water content is a dominant factor influencing resistivity. Further analysis using multiple non-linear regression demonstrated strong correlations, indicating that a combination of water content, soil dry density, and plasticity index can predict soil resistivity with high reliability. This approach enables optimization of substation grounding designs to ensure operational safety and regulatory compliance. The study suggests that integrating these geotechnical assessments into standard grounding system design procedures can significantly improve the effectiveness and safety of electrical infrastructure. Recommendations for future research include expanding the dataset to encompass a broader range of soil types and investigating the effects of particle size and electrolyte content on soil resistivity. These enhancements aim to refine the predictive models and address the broader applicability of the results in diverse geological settings.

Mesoplastic and Microplastic Pollution in the Soil of Small-Scale Agricultural Areas in Iligan, Mindanao, Philippines

ABSTRACT The Philippines is primarily an agricultural country in which most Filipinos depend on the health of the soil for livelihood. Plastic pollution adversely affects agriculture by degrading soil quality, fertility, and crop growth. However, the prevalence of plastic particles such as mesoplastics (>5 mm to 25 mm) and microplastics (<5 mm) in agricultural soils in the Philippines remains poorly understood. This study investigated the prevalence of mesoplastics and microplastics in agricultural soils in Iligan City, Philippines. We collected soil samples from the six sampling stations in high-elevation and low-elevation sites. Mesoplastics and microplastics were examined through manual sorting, categorized based on color, shape, and size, and identified using Fourier-transform infrared spectroscopy (FTIR). Mesoplastics were found to be more prevalent, averaging 2.22 items/kg compared to microplastics 0.83 items/kg. Mesoplastics were mainly white-colored (42%), mostly fragmented (55%), 5–10 mm in size (55%), and were predominantly polypropylene (85%). Microplastics were mainly transparent (40%), composed of fragments and film shapes(46%), and 3–4 mm (93%) in size. Polyethylene was the abundant microplastic polymer type (47%). It was observed that the low-elevation sites had a higher abundance of plastic particles, stressing the need to address local factors in tackling plastic pollution.

Machine Learning-Based Classification of Soil Parent Materials Using Elemental Concentration and Vis-NIR Data.

In soil science, the allocation of soil samples to their respective origins holds paramount significance, as it serves as a crucial investigative tool. In recent times, with the increasing use of proximal sensing and advancements in machine-learning techniques, new approaches have accompanied these developments, enhancing the effectiveness of soil utilization in soil science. This study investigates soil classification based on four parent materials. For this purpose, a total of 59 soil samples were collected from 12 profiles and the vicinity of each profile at a depth of 0-30 cm. Surface soil samples were analyzed for elemental concentrations using X-Ray fluorescence (XRF) and inductively coupled plasma-optical emission spectrometry (ICP-OES) and soil spectra using a visible near-infrared (Vis-NIR) spectrometer. Soil samples collected from soil profiles (12 soil samples) and surface (47 soil samples) were used to classify parent materials using machine learning-based algorithms such as Support Vector Machine (SVM), Ensemble Subspace k-Near Neighbor (ESKNN), and Ensemble Bagged Trees (EBTs). Additionally, as a validation of the classification techniques, the dataset was subjected to five-fold cross-validation and independent sample set splitting (80% calibration and 20% validation). Evaluation metrics such as accuracy, F score, and G mean were used to evaluate prediction performance. Depending on the dataset and algorithm used, the classification success rates varied between 70% and 100%. Overall, the ESKNN (99%) produced better results than other classification methods. Additionally, Relief algorithms were employed to identify key variables for each dataset (ICP-OES: CaO, Fe2O3, Al2O3, MgO, and MnO; XRF: SiO2, CaO, Fe2O3, Al2O, and MnO; Vis-NIR: 567, 571, 572, 573, and 574 nm). Subsequent soil reclassification using these reduced variables revealed reduced accuracies using Vis-NIR data, with ESKNN still yielding the best results.

First Report of Phytophthora cinnamomi causing root rot of avocado trees in Greece.

In September 2023, thirty declining 30-year-old avocado (Persea americana) trees ('Hass' grafted on 'Zutano' seedlings) were detected in a 1.5-ha orchard in the island of Crete (Chania region). Crown symptoms encompassed wilting and leaf chlorosis, advancing to defoliation and extensive dieback. Tap and feeder roots decayed and brown discoloration of root tissues was evident on heavily infected trees. The disease was severe and widespread, resulting in a 5% mortality rate among 300 trees. The pathogen was isolated with a modified soil baiting technique (Ferguson and Jeffers, 1999). Surface disinfected avocado fruits were immersed in water containing soil samples. Following a period of 2 to 8 days, tissue fragments from the resulting necrotic lesions on the fruit surface were transferred on ΡΑRP medium and subsequently incubated at 20°C (Ferguson and Jeffers, 1999). Three isolates (AV2, AV12 and AV11a) were obtained by transferring single hyphal tips to new Petri dishes containing V8 juice agar. They were grown at 20˚C and used for identification after 10 days. Isolates formed coralloid colonies with abundant clustered spherical hyphal swellings and terminal or intercalary (ratio 1:5) thick-walled chlamydospores measuring 20 to 36 μm (avg 29±0.8 μm) with characteristic thick walls (avg 1.2±0.2 μm). Sporangia, produced in non-sterile soil-extract water, were ovoid to obpyriform, persistent, non-papillate, 32 to 81 μm (avg 56±4.8 μm) long and 20 to 42 μm (avg 31±3.2 μm) wide (n=100). Isolates were heterothallic as they did not produce oospores in single cultures. Based on the morphological traits the isolates were identified as Phytophthora cinnamomi (Erwin and Ribeiro 1996). The internal transcribe spacer region (ITS) including ITS1, 5.8S rDNA region, and ITS2 as well as the cytochrome c oxidase subunit I (coxI) gene of the three representative isolates wereamplified with ITS1/ITS4 and FM83/FM84 primers, respectively (White et al. 1990; Martin and Tooley 2003), and sequenced (GenBank acc. PP506613 to PP506615 and PQ063867 to PQ063869, respectively). BLAST search revealed almost 100% identity with the sequences of P. cinnamomi ex-isotype isolate (KC478663 and KU899315 respectively). Pathogenicity tests using isolate AV2 were conducted following the soil infestation method (Jung et al. 1996) using six-year-old avocado 'Zutano' seedlings. Six non-inoculated plants treated with vermiculite-multivitamin juice mixture were used as controls. Plants (1 m tall) were grown in pots under greenhouse conditions and watered regularly. Six weeks post inoculation, all inoculated trees showed chlorosis, wilting and root rot, while control plants remained symptomless. Symptoms were similar to those observed in the field and the pathogen was re-isolated and molecularly identified as previously described. This study presents the first documented occurrence of P. cinnamomi, widely regarded as the most destructive avocado pathogen globally, on avocado crops in Greece (Rodger et al. 2019). Additionally, this marks the first recorded presence of this pathogen on the island of Crete, regardless of the host species. The accurate identification of Phytophthora species associated with avocado root rot is essential for implementing an effective disease management strategy, particularly in the selection of appropriate disease-resistant rootstocks.