Experimental Field Site Research Articles

First Report of Dalbulus maidis (DeLong and Wolcott) (Hemiptera: Cicadellidae) in Oklahoma.

The corn leafhopper, Dalbulus maidis (DeLong and Wolcott) (Hemiptera: Cicadellidae), is an invasive insect that can cause damage to maize (Zea mays L.) in two ways: by direct feeding and the transmission of several plant pathogens. Dalbulus maidis is an invasive and serious economic pest of maize that has spread from its center of origin in Mexico to the southernmost parts of the United States. Prior to 2024, corn leafhoppers had not been documented in Oklahoma, and their spread northward toward the United States corn belt is of significant concern. Here, we provide the first reports of the insect in maize in several Oklahoma counties. Insect specimens were collected at various commercial and experimental field sites by Oklahoma State University research and extension personnel. The identity of the insect species was validated through morphological and molecular taxonomy. The presence records for the corn leafhopper presented here provide valuable information for future monitoring and management efforts of this economically important pest and disease.

Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm

AbstractSoil water content (SWC) estimation is important for many areas including hydrology, agriculture, soil science, and environmental science. Ground penetrating radar (GPR) is a promising geophysical method for SWC estimation. However, at present, most of the studies are based on partial information of GPR, like travel time or amplitude information, to invert the SWC. Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. The proposed scheme includes a petrophysical relationship to link the SWC with the relative dielectric permittivity, 1D GPR forward modeling, and a GWO optimization algorithm. First, numerical modeling was carried out, and the proposed scheme was applied to both noise‐free and noisy data to verify its applicability. Then, the proposed method was applied to data collected from a field experimental site. These results, derived from both synthetic and real datasets, show that the proposed inversion scheme resulted in a good match between the observed and calculated GPR data. In the numerical modeling, it was observed that the SWC could be inverted accurately, even when noise was present in the data. These demonstrate that the GWO method can be applied for the quantitative interpretation of GPR data. The proposed scheme shows potential for SWC estimation by using GPR full waveform data.

Physical and chemical characterization of remote coastal aquifers and submarine groundwater discharge from a glacierized watershed

AbstractCoastal aquifers play an important role in marine ecosystems by providing high fluxes of nutrients and solutes via submarine groundwater discharge pathways. The physical and chemical characterization of these dynamic systems is foundational to understanding the extent and magnitude of hydrogeologic processes and their subsequent contributions to the marine environment. We describe a km‐scale experimental field site located in a glaciofluvial delta entering Kachemak Bay, Alaska. Our characterization applies geophysical (ERT and HVSR), hydrogeologic (grain size analyses, slug tests and tidal response analyses) and geochemical (major ions and stable water isotopes) methods to describe the complexity of coastal aquifers in proglacial environments currently experiencing rapid transformations. The hydrogeologic and geophysical techniques revealed thick (20–84 m) sediments dominated by sands and gravels and delineated zones of freshwater, brackish water and saltwater at both high and low tides within the subterranean estuary. Estimates of hydraulic conductivities via multiple approaches ranged from 2 to 250 m d−1, with means across the four methods within the same order of magnitude. Tidal response analyses highlighted a coastal aquifer in strong connection with the sea as evidenced by clear spring‐ and neap‐tidal signals within a proximal piezometric hydrograph. Geochemical sampling revealed coastal groundwaters as substantially enriched in solutes compared to proximal river samples with limited variability across seasons. A clear connection between the Wosnesenski River and the adjacent aquifer was also observed, with concentrated recharge from the river corridor during the meltwater season. This combination of approaches provides the basis for a conceptual model for coastal aquifer systems within the Gulf of Alaska and an upscaled mean daily yield of freshwater and solutes from the delta subsurface. Our findings are critical for subsequent numerical simulations of groundwater flow, tidal pumping and chemical reactions and transport in these understudied environments. This approach may be applied for low‐cost, large‐scale hydrogeologic investigations in coastal areas and may be particularly useful for remote sites where access and mobility are challenging.

LABORATORY DETERMINATION OF THE MAXIMUM DENSITY AND OPTIMAL HUMIDITY OF LARGE-BLOCK SOILS

he purpose of our field research was to develop and select a method of work on laying and compacting the material of large-block soils, ensuring the receipt and determination of maximum density and optimal soil moisture. On the basis of these studies, technical conditions for the construction of thrust prisms are further drawn up. This article presents the results of the work performed with a brief methodology of field and laboratory research. The article provides data characterizing the material intended for installation in the body of the dam. The currently existing methods for determining the control parameters of laying large-block soils are contradictory and require experimental work. A number of parameters are taken into account: grain composition, humidity, density. Therefore, the article considers a laboratory method for determining the maximum density and optimal humidity of stone material when laying in the body of the dam. The results of the research carried out on the development of our quarry area, the thickness of the uncompacted layer was determined, the choice of a sealing mechanism, the number of passes along one track, the determination of the density of dry soil in experimental field sites intended for use in filling the body of the dam, graphs of the required densities for full-scale grain composition are presented. The strength properties of the stone material were determined experimentally for the average grain composition and for the upper curve of the accepted “fish”

Predictive monitoring of soil organic carbon using multispectral UAV imagery: a case study on a long-term experimental field

Effective monitoring of the soil organic carbon (SOC) content at the field scale is crucial for supporting sustainable agricultural practices. This study evaluates the utility of multispectral data acquired by an unmanned aerial vehicles (UAV) during bare soil conditions for predicting the SOC content of a long-term experimental field site (LTE) in Saxony-Anhalt, Germany. Our methodology involves constructing predictive models using multiple algorithms (CUBIST, MARS, linear regression) and applying image correction techniques to enhance prediction accuracy by mitigating the influence of confounding factors such as crop residuals. Among the tested models, the CUBIST algorithm, combined with a pixel selection strategy employing a 2 m radius and stratified image correction, demonstrates the most promising results, achieving an R-squared value of 0.54 and an RMSE of 1.9 g kg−1. Spatial distribution maps generated by this optimized model effectively depict the impact of organic fertilization on the SOC content, although the clarity of these patterns varies depending on the image processing method and algorithm used. Our findings highlight the potential of utilizing UAV-derived multispectral data for SOC monitoring at the LTE scale. However, further research is warranted to assess the generalizability of this approach to agricultural fields with lower SOC variability.

Behavior and mechanisms of Doppler wind lidar error in complex terrain: stable flow case study at Perdigão

A numerical experiment is carried out investigating the magnitude of biases in ground-based lidar measurements in complex flow conditions. Biases assessed include those arising from flow curvature and from the interaction of turbulence with the wind field reconstruction (WFR) algorithms used by a WindCube lidars and anemometers. RANS-CFD and WRF-LES simulations were performed for the Perdig˜ao Field Experiment site for a range of atmospheric conditions. Virtual anemometer and lidar data were generated for four locations: two near exposed ridge tops and two in low-speed regions in the valley. The LES data at these four locations show that the scalar inflation terms (the relation between scalar and vector averaged wind speed) for virtual lidar and virtual cups agree very well with predictions using perturbation theory. While the lidar errors vary greatly with location and height, the contribution from the flow curvature tends to be larger than the differences arising from scalar inflation. For one lidar/mast pair near the ridge top, comparisons between simulations and measurements are carried out for a resonant mountain wave event on June 14th, 2017, and for the whole duration of the Perdig˜ao campaign for winds perpendicular to the ridges. The lidar error during the mountain wave, a period of strong stability and low inversion height, is significantly larger than the campaign average. The sensitivity of the lidar error to atmospheric stability is confirmed by the RANS simulations, which suggests strong sensitivity of flow curvature error to stability conditions and to the shape of the wind speed profile near the top of the boundary layer.

Reducing the fatal attraction of nocturnal insects using tailored and shielded road lights

The attraction of insects to artificial light is a global environmental problem with far-reaching implications for ecosystems. Since light pollution is rarely integrated into conservation approaches, effective mitigation strategies towards environmentally friendly lighting that drastically reduce insect attraction are urgently needed. Here, we tested novel luminaires in two experiments (i) at a controlled experimental field site and (ii) on streets within three municipalities. The luminaires are individually tailored to only emit light onto the target area and to reduce spill light. In addition, a customized shielding renders the light source nearly invisible beyond the lit area. We show that these novel luminaires significantly reduce the attraction effect on flying insects compared to different conventional luminaires with the same illuminance on the ground. This underlines the huge potential of spatially optimized lighting to help to bend the curve of global insect decline without compromising human safety aspects. A customized light distribution should therefore be part of sustainable future lighting concepts, most relevant in the vicinity of protected areas.

Early Detection of Rubber Tree Powdery Mildew by Combining Spectral and Physicochemical Parameter Features

Powdery mildew significantly impacts the yield of natural rubber by being one of the predominant diseases that affect rubber trees. Accurate, non-destructive recognition of powdery mildew in the early stage is essential for the cultivation management of rubber trees. The objective of this study is to establish a technique for the early detection of powdery mildew in rubber trees by combining spectral and physicochemical parameter features. At three field experiment sites and in the laboratory, a spectroradiometer and a hand-held optical leaf-clip meter were utilized, respectively, to measure the hyperspectral reflectance data (350–2500 nm) and physicochemical parameter data of both healthy and early-stage powdery-mildew-infected leaves. Initially, vegetation indices were extracted from hyperspectral reflectance data, and wavelet energy coefficients were obtained through continuous wavelet transform (CWT). Subsequently, significant vegetation indices (VIs) were selected using the ReliefF algorithm, and the optimal wavelengths (OWs) were chosen via competitive adaptive reweighted sampling. Principal component analysis was used for the dimensionality reduction of significant wavelet energy coefficients, resulting in wavelet features (WFs). To evaluate the detection capability of the aforementioned features, the three spectral features extracted above, along with their combinations with physicochemical parameter features (PFs) (VIs + PFs, OWs + PFs, WFs + PFs), were used to construct six classes of features. In turn, these features were input into support vector machine (SVM), random forest (RF), and logistic regression (LR), respectively, to build early detection models for powdery mildew in rubber trees. The results revealed that models based on WFs perform well, markedly outperforming those constructed using VIs and OWs as inputs. Moreover, models incorporating combined features surpass those relying on single features, with an overall accuracy (OA) improvement of over 1.9% and an increase in F1-Score of over 0.012. The model that combines WFs and PFs shows superior performance over all the other models, achieving OAs of 94.3%, 90.6%, and 93.4%, and F1-Scores of 0.952, 0.917, and 0.941 on SVM, RF, and LR, respectively. Compared to using WFs alone, the OAs improved by 1.9%, 2.8%, and 1.9%, and the F1-Scores increased by 0.017, 0.017, and 0.016, respectively. This study showcases the viability of early detection of powdery mildew in rubber trees.

Sulfur dynamics in saline sodic soils: The role of paddy cultivation and organic amendments

The phenomenon of sulfur (S) deficiency in Chinese soil is becoming increasingly severe, especially in the northeastern saline-sodic wasteland (WL). To determine the bioavailability of S in long-term cultivated paddy soil with or without organic amendment addition, the long-term field experiment site was established and incubation experiments were conducted. Compared to WL, soil properties have been continuously improved during the 15-year paddy field (PF) cultivation, ultimately enhancing the content of soil organic carbon (by 242.62 %), total nitrogen (by 126.49 %) and alkali-hydrolyzed nitrogen (by 28.07 %). Additionally, soil salinization has been decreasing, and the stock of total sulfur (TS) and available sulfur (AS) in the 0–60 cm soil layer have increased by 32.09 % and 293.52 % respectively. In contrast, organically-amended soil (OA) manifested superior TS and AS levels vs. PF. Additionally, water-soluble sulfur (WSS) was markedly elevated, registering post-annual increments of 227.31 % and 268.36 % in PF and OA, respectively, relative to WL. The key mechanistic impetus for the application of organic amendments was the enhancement of the soil's adsorptive and mineralization capabilities. As observed in our soil culture experiment, the maximum adsorption of sulfate ions and the cumulative mineralization of sulfur in the soil follow the pattern of OA > PF > WL. The Partial Least Squares Path Model (PLSPM) corroborated that both organic amendments and years of cultivation indirectly influenced total inorganic sulfur fractions. This influence is primarily mediated via structural soil enhancements and salinization amelioration, thereby elevating available quantities of sulfur in saline-sodic soil environments. In conclusion, from the perspective of soil sulfur biogeochemical cycling, we have confirmed that reclaiming saline-sodic wasteland for paddy field could be a beneficial and sustainable approach for soil management. These findings of this study can also provide an in-depth understanding of the bioavailability and influencing mechanism of sulfur in long-term saline-sodic paddy fields.

The physical and chemical properties of the technosols in the pot experiment with waste and groundwater irrigation


 
 
 Mediterranean areas are characterized by a strong spatial variability that makes the soil hydrogeological logical response highly complicated. Some seasons provoke dramatic changes in soil properties determining the runoff rates, such as soil water content or soil water repellency. In recent years, important progress has been made in adapting water needs to local conditions through the use of various parameters to assess soil water status. Estimation of the water status of the soil has been widely used in soil science as a tool for quantitative analysis. The main objective of this case study was to analyze technosol and irrigation water physical and chemical properties in the pot experiment with lysimeters. A pot experiment with Avocado rootstocks was equipped with lysimeters in the facilites of the «La Mayora Experimental Field site» of the Higher Council for Scientific Research (Spain). The scheme of the pot experiment included three sources of irrigation: a) groundwater; b) regenerated municipal wastewater (100%); c) a mix of ground and regenerated municipal wastewater (50 / 50%). Chemical analysis data indicate that the reclaimed wastewater does not meet irrigation requirements in terms of pH, EC and due to the significant content of sodium and chlorine. Even groundwater satisfies irrigation water qualitative requirements partially. The suitability of irrigation water on pH level can be characterized mainly as unsuitable and doubtful. Diluting regenerated wastewater with groundwater following the 50% principle led to a decrease in the potential risks for salinization of groundwater connected with leaching of the leachate. The dynamics of the change in the volume of leachate are related to precipitation, the frequency of irrigation, and different manifestations of the physical, mineralogical, and chemical properties of technosols.
 
 

Fate of fluoroquinolones in field soil environment after incorporation of poultry litter from a farm with enrofloxacin administration via drinking water

The practice of incorporating animal manure into soil is supported within the European Circular economy as a possible substitute for mineral fertilizers and will become crucial for the sustainability of agriculture. However, this practice may indirectly contribute to the dissemination of antibiotics, resistance bacteria, and resistance genes. In this study, medicated drinking water and poultry litter samples were obtained from a broiler-chick farm. The obtained poultry litter was incorporated into the soil at the experimental field site. The objectives of this research project were first to develop analytical methods able to quantify fluoroquinolones (FQs) in medicated drinking water, poultry litter, and soil samples by LC–MS; second to study the fate of these FQs in the soil environment after incorporation of poultry litter from flock medicated by enrofloxacin (ENR); and third to screen the occurrence of selected fluoroquinolone resistance encoding genes in poultry litter and soil samples (PCR analysis). FQs were quantified in the broiler farm’s medicated drinking water (41.0 ± 0.3 mg∙L−1 of ENR) and poultry litter (up to 70 mg∙kg−1 of FQs). The persistence of FQs in the soil environment over 112 days was monitored and evaluated (ENR concentrations ranged from 36 μg∙kg−1 to 9 μg∙kg−1 after 100 days). The presence of resistance genes was confirmed in both poultry litter and soil samples, in agreement with the risk assessment for the selection of AMR in soil based on ENR concentrations. This work provides a new, comprehensive perspective on the entry and long-term fate of antimicrobials in the terrestrial environment and their consequences after the incorporation of poultry litter into agricultural fields.Graphical

Optimized NPK fertilizer recommendations based on topsoil available nutrient criteria for wheat in drylands of China

The optimized management of crop fertilization is very important for improving crop yield and reducing the consumption of chemical fertilizers. Critical nutrient values can be used for evaluating the nutritional status of a crop, and they reflect the nutrient concentrations above which the plant is sufficiently supplied for achieving the maximum potential yield. Based on on-farm surveys of 504 farmers and 60 field experimental sites in the drylands of China, we proposed a recommended fertilization method to determine nitrogen (N), phosphorus (P), and potassium (K) fertilizer input rates for wheat production, and then validated the method by a field experiment at 66 different sites in northern China. The results showed that wheat grain yield varied from 1.1 to 9.2 t ha−1, averaging 4.6 t ha−1, and it had a quadratic relationship with the topsoil (0−20 cm) nitrate N and soil available P contents at harvest. However, yield was not correlated with the inputs of N, P, and K fertilizers. Based on the relationship (exponential decay model) between 95–105% of the relative yield and topsoil nitrate N, available P, and available K contents at wheat harvest from 60 field experiments, the topsoil critical nutrient values were determined as 34.6, 15.6, and 150 mg kg−1 for soil nitrate N, available P, and available K, respectively. Then, based on five groups of relative yield (>125%, 115–125%, 105–115%, 95–105%, and <95%) and the model, the five groups of topsoil critical nutrient levels and fertilization coefficients (Fc) were determined. Finally, we proposed a new method for calculating the recommended fertilizer input rate as: Fr=Gy×Nr×Fc, where Fr is the recommended fertilizer (N/P/K) input rate; Gy is the potential grain yield; Nr is the N(NrN), P(NrP), and K(NrK) nutrient requirements for wheat to produce 1,000 kg of grain; and Fc is a coefficient for N(Nc)/P(Pc)/K(Kc) fertilizer. A 2-year validated experiment confirmed that the new method reduced N fertilizer input by 17.5% (38.5 kg N ha−1) and P fertilizer input by 43.5% (57.5 kg P2O5 ha−1) in northern China and did not reduce the wheat yield. This outcome can significantly increase the farmers’ benefits (by 7.58%, or 139 US$ ha−1). Therefore, this new recommended fertilization method can be used as a tool to guide N, P, and K fertilizer application rates for dryland wheat production.

Comparative field studies of biochemical and agro-physiological parameters in semi-arid zone with rainfall Moroccan climate of durum wheat

Durum wheat production is highly unpredictable throughout the year because of uncertain rainfall and frequent dry spells and it is absolutely necessary to characterize the impact of drought on grain yield. The objective in this research is to carry out a comparative analysis of biochemical and physiological responses and production parameters of durum wheat (Triticum durum) in semi-arid zone with rainfall in Morocco's climates. Thirteen durum wheat genotypes selected at INRA-Morocco and three control varieties were evaluated under Moroccan rainfed conditions for two growing seasons (2019/20 and 2020/21). The INRA-Morocco-Douyet Fez experimental field site was where the trials were conducted (34°2 N, 5°W, 416 m). Different parameters were studied. Five physiological, four agronomical and one biochemical trait are measured in this study: leaf area, leaf temperature, relative water content, chlorophyll content, proline, yield and yield components. Decreased rainfall significantly increased proline content, leaf temperature and decreased leaf area, grain yield, chlorophyll and relative water content (P < 0.01). Based on these results, field-induced rainfall variations resulted in inconsistencies in the response of the assessed traits to drought-related interactions between both growing seasons (2020–2021) in order to identify stable, high-yielding genotypes in the presence and absence of rainfall, which requires a strong association of drought-related traits.

Precipitation seasonality and soil pH drive the large-scale distribution of soil invertebrate communities in agricultural ecosystems.

Soil invertebrates contribute significantly to vital ecosystem functions such as the breakdown of organic matter and cycling of essential nutrients, but our knowledge of their large-scale distribution in agricultural systems is limited, which hinders our ability to robustly predict how they will respond to future global change scenarios. Here, we employed metabarcoding analysis of eukaryotic 18S rRNA genes to examine the diversity and community composition of invertebrates in 528 sorghum rhizosphere and bulk soils, collected from 53 experimental field sites across China. Our results revealed that Nematoda, Arthropoda, and Annelida were the dominant soil invertebrate groups in agroecosystems. Among all climatic and soil parameters we examined, precipitation seasonality (i.e. the irregular distribution of precipitation during a normal year) had the strongest relationship with the richness of soil invertebrates, with an increase in soil invertebrate richness predicted with increasing precipitation seasonality. Mean annual precipitation and soil pH were the most important predictors of soil invertebrate community structure, with numerous invertebrate phylotypes showing either significantly positive or negative relationships with these two variables. Our findings suggest that shifts in precipitation patterns and soil pH, induced by future climate change and agricultural practices, will have important consequences for the distribution of soil invertebrate communities, with implications for agricultural ecosystem sustainability.

Straw return plus zinc fertilization increased the accumulations and changed the chemical compositions of mineral-associated soil organic carbon

Agricultural zinc (Zn) fertilization can markedly promote organo-Zn complex formation, especially when combined with straw. However, how soil organic carbon (SOC) conversion responds to Zn and/or straw plus Zn has received little attention. Here, we explored the SOC, particulate organic carbon (POC), mineral-associated organic carbon (MAOC), as well as the OC chemical compositions’ responses in a field experiment site created in 2016. The following treatments were control (CK, no straw return and no Zn fertilization), straw return (St), Zn fertilization (Zn), and straw return combined with Zn fertilization (St+Zn). The results of our three-year study indicated that MAOC content under St+Zn increased by 4.4–6.4%, which led to a slight SOC accumulation (3.7–7.4%) compared to that of St alone. After including straw return with Zn fertilization, the Zn content of particulate organic matter and that of mineral-associated organic matter (ZnMAOM) both increased and thus helped MAOC formation. The chemical compositions of POC and MAOC were affected mainly by straw return and Zn fertilization, respectively. Both the Zn and St+Zn treatments had increased relative hydroxyl C contents and reduced O-alkyl C contents in MAOC, compared to that of CK and St, and the ZnMAOM content best explained the changes. In both the POC and MAOC fractions, the aromatic C to aliphatic C ratio decreased in Zn treatments compared to those in CK. Altogether, Zn’s effects on SOC and its fractions were closely linked to straw return, and Zn aids in MAOC and SOC accumulations when applied with straw.

High Ammonium Addition Changes the Diversity and Structure of Bacterial Communities in Temperate Wetland Soils of Northeastern China.

The soil microbiome is an important component of wetland ecosystems and plays a pivotal role in nutrient cycling and climate regulation. Nitrogen (N) addition influences the soil's microbial diversity, composition, and function by affecting the soil's nutrient status. The change in soil bacterial diversity and composition in temperate wetland ecosystems in response to high ammonium nitrogen additions remains unclear. In this study, we used high-throughput sequencing technology to study the changes of soil bacterial diversity and community structure with increasing ammonium concentrations [CK (control, 0 kg ha-1 a-1), LN (low nitrogen addition, 40 kg ha-1 a-1), and HN (high nitrogen addition, 80 kg ha-1 a-1)] at a field experimental site in the Sanjiang Plain wetland, China. Our results showed that except for soil organic carbon (SOC), other soil physicochemical parameters, i.e., soil moisture content (SMC), dissolved organic nitrogen (DON), total nitrogen (TN), pH, ammonium nitrogen (NH4+), and dissolved organic carbon (DOC), changed significantly among three ammonium nitrogen addition concentrations (p < 0.05). Compared to CK, LN did not change soil bacterial α-diversity (p > 0.05), and HN only decreased the Shannon (p < 0.05) and did not change the Chao (p > 0.05) indices of soil bacterial community. Ammonium nitrogen addition did not significantly affect the soil's bacterial community structure based on non-metric multidimensional scaling (NMDS) and PERMANOVA (ADONIS) analyses. Acidobacteriota (24.96-31.11%), Proteobacteria (16.82-26.78%), Chloroflexi (10.34-18.09%), Verrucomicrobiota (5.23-11.56%), and Actinobacteriota (5.63-8.75%) were the most abundant bacterial phyla in the soils. Nitrogen addition changed the complexity and stability of the bacterial network. SMC, NO3-, and pH were the main drivers of the bacterial community structure. These findings indicate that enhanced atmospheric nitrogen addition may have an impact on bacterial communities in soil, and this study will allow us to better understand the response of the soil microbiome in wetland ecosystems in the framework of increasing nitrogen deposition.

Chamomile essential oils exert anti-inflammatory effects involving human and murine macrophages: Evidence to support a therapeutic action.

Chamomile (M. chamomilla L.) is an herbaceous plant from family Astereaceae, that has a long history of use in traditional medicine. It has been used as herbal remedies for thousands of years to treat several diseases, including infections, neuropsychiatric, respiratory, gastrointestinal, and liver disorders. Chronic inflammation is involved in the pathogenesis of most infectious and non-infectious diseases and macrophages are considered the major cellular players that drive disease initiation and maintenance. The aim of this study was to evaluate the variation in the chemical profile of the essential oil of M. chamomilla plants collected in three experimental field sites in the Molise region. Additionally, we evaluated the pharmacological mechanism behind the anti-inflammatory effect of M. chamomilla essential oils. Three essential oils (called GC1, GC2 and GC3) were extracted from aerial parts of M. chamomilla by hydrodistillation and chemical composition was analyzed by gas chromatography-mass spectrometry (GC-MS). The essential oils were tested for their ability to modulate pro-inflammatory murine macrophages and human peripheral blood mononuclear cells (PBMCs) functions. The chemical analysis of the samples revealed the presence of a high content of the oxygenated sesquiterpenes that represented more than the half of the entire oils. GC1, GC2 and GC3 essential oils significantly attenuated LPS/IFN-γ-induced inflammation by reducing M1 polarization. In details, they showed significant anti-inflammatory property by inhibiting NO, TNF-α and IL-6 production. These effects were correlated to a suppression of LPS-mediated p65 activation, the critical transactivation subunit for NF-κB transcription factor. Oxidative stress may trigger macrophages activation and elicit strong immune responses. Our study demonstrated that GC1, GC2 and GC3 were highly effective at increasing GCL and HMOX-1 anti-oxidant enzymes expression leading to the rapid scavenging of ROS. The antioxidant activity of these oils was explained throughout the activation of NRF2 signaling pathway. Next, we demonstrated that essential oils were able to reduce CD4+ T cell activation which are also involved in inflammatory processes. Our data describe for the first time that chamomile essential oils exerted their anti-inflammatory and antioxidant activity by modulating macrophages and CD4+ T cells-mediate immune response.

Derivation and validation of soil total and extractable cadmium criteria for safe vegetable production

Determining the appropriate soil cadmium (Cd) criteria for vegetable production is important for ensuring that the Cd concentrations of the vegetables meet food safety standards. The soil extractable Cd criteria for vegetable production are also essential for both food safety and environmental management, especially in areas with a high natural background level. In the present study, soil total and extractable Cd criteria were derived using the approach of species sensitivity distribution integrated with soil aging and bioavailability as affected by soil properties. A dataset of 90 vegetable species planted in different soils was compiled by screening the published in literature in five bibliographic databases using designated search strings. The empirical soil–plant transfer model was applied to normalize the bioaccumulation data. After normalization, the intra-species variability was reduced by 18.3 to 84.4%. The soil Cd concentration that would protect 95% (HC5) of the species was estimated by species sensitivity distribution curves that were fitted by the Burr III function. The soil Cd criteria derived from the added approach for risk assessment were proposed as continuous criteria based on a combination of organic carbon and pH in the soil. Criteria for total Cd and EDTA-extractable Cd in the soil ranged from 0.23 to 0.61 mg kg−1 and from 0.09 to 0.25 mg kg−1, respectively. Field experimental data were used to validate the applicability and validity of these criteria. Most of the predicted HC5 values in the field experimental sites were below the 1:1 line. These results provide a scientific basis for soil Cd criteria for vegetable production that will ensure food safety.

The main factors that drive plant dieback under extreme drought differ among Mediterranean shrubland plant biotypes

AbstractQuestionsKnowledge of how extreme drought events induce plant dieback and, eventually, plant mortality, may improve our forecasting of ecosystem change according to future climate projections, especially in Mediterranean drylands. In them, shrublands are the main vegetation communities in transition areas from a subhumid to semi‐arid climate. This study analyzed differences in plant dieback after an unusual drought in 2014 and identified their main underlying factors in relation to three groups of explanatory variables: water availability, soil properties and vegetation structure attributes.LocationFour Mediterranean shrublands along a climatic gradient in SE Spain.MethodsAt each experimental field site, we sampled a pool of vegetation structure characteristics, soil depth and soil surface properties, and we also determined water availability by continuously monitoring soil moisture and the microclimate conditions.ResultsThe climatic analysis showed that there was an extreme drought event in 2014, which was below the first percentile of the driest years. Under such conditions, vegetation dieback occurred at all the study sites. However, plant dieback differed between sites and plant biotypes. Subshrubs were the main affected biotype, with diebacks close to 60% at the driest sites, and up to 40% dieback for shrubs depending on their vertical development. Relative extractable water and bare soil surface cover were the best explanatory variables of plant community dieback but changed between plant biotypes. Vegetation structure variables related to plant vertical development (leaf area index [LAI], plant height, phytovolume) were significant explanatory variables of plant dieback in shrubs, subshrubs and grasses. Consecutive dry days fitted the best model to explain subshrub dieback.ConclusionsWe found that rainfall pattern rather than total annual rainfall was the climatic factor that best determined water availability for plants in Mediterranean drylands. These results also pointed out the relevance of plant structure and soil properties for explaining ecosystem responses to extreme drought.

Assessing long-term impacts of cover crops on soil organic carbon in the central US Midwestern agroecosystems.

Cover crops have been reported as one of the most effective practices to increase soil organic carbon (SOC) for agroecosystems. Impacts of cover crops on SOC change vary depending on soil properties, climate, and management practices, but it remains unclear how these control factors affect SOC benefits from cover crops, as well as which management practices can maximize SOC benefits. To address these questions, we used an advanced process-based agroecosystem model, ecosys, to assess the impacts of winter cover cropping on SOC accumulation under different environmental and management conditions. We aimed to answer the following questions: (1) To what extent do cover crops benefit SOC accumulation, and how do SOC benefits from cover crops vary with different factors (i.e., initial soil properties, cover crop types, climate during the cover crop growth period, and cover crop planting and terminating time)? (2) How can we enhance SOC benefits from cover crops under different cover crop management options? Specifically, we first calibrated and validated the ecosys model at two long-term field experiment sites with SOC measurements in Illinois. We then applied the ecosys model to six cover crop field experiment sites spanning across Illinois to assess the impacts of different factors on SOC accumulation. Our modeling results revealed the following findings: (1) Growing cover crops can bring SOC benefits by 0.33 ± 0.06 MgC ha-1 year-1 in six cover crop field experiment sites across Illinois, and the SOC benefits are species specific to legume and non-legume cover crops. (2) Initial SOC stocks and clay contents had overall small influences on SOC benefits from cover crops. During the cover crop growth period (i.e., winter and spring in the US Midwest), high temperature increased SOC benefits from cover crops, while the impacts from larger precipitation on SOC benefits varied field by field. (3) The SOC benefits from cover crops can be maximized by optimizing cover crop management practices (e.g., selecting cover crop types and controlling cover crop growth period) for the US Midwestern maize-soybean rotation system. Finally, we discussed the economic and policy implications of adopting cover crops in the US Midwest, including that current economic incentives to grow cover crops may not be sufficient to cover costs. This study systematically assessed cover crop impacts for SOC change in the US Midwest context, while also demonstrating that the ecosys model, with rigorous validation using field experiment data, can be an effective tool to guide the adaptive management of cover crops and quantify SOC benefits from cover crops. The study thus provides practical tools and insights for practitioners and policy-makers to design cover crop related government agricultural policies and incentive programs for farmers and agri-food related industries.