Dry Weather Research Articles

Aflatoxins in maize, milk and dairy products from Serbia.

This study presents data on the occurrence of aflatoxins B1, B2, G1 and G2 in maize and aflatoxin M1 (AFM1) in milk and dairy products from Serbia in 2022. A total of 100 maize samples were analysed using liquid chromatography tandem mass spectrometry, while 107 cow and goat milk, besides dairy products were tested with an ELISA method. Aflatoxins contaminated 78% of the maize samples, with aflatoxin B1 as the most prevalent aflatoxin, also at the highest determined level. All milk samples tested positive for AFM1, while contamination in dairy products ranged from 14% to 100%. The hot and dry weather during the 2022 maize growing season, characterised by moderate to extreme drought conditions, significantly increased maize contamination with aflatoxins, impacting subsequent milk and dairy products contamination. The findings of this study confirm the continuous trend and persistent challenge in Serbia concerning the prevalence of aflatoxins in maize and milk, closely linked to climate change.

Nitrogen dynamics as a function of soil types, compaction, and moisture.

In this study, the complex interactions between soil types, compaction, and moisture on nitrogen (N) transformation processes such as ammonia (NH3) volatilization, ammonification, nitrification, and denitrification were examined over a 30-day period using a simulated column approach. Two soil types: loam, and sandy loam, were subjected to three compaction treatments-control, surface, and sub-surface compaction-and two moisture regimes, dry and wet. Liquid urea ammonium nitrate (32-0-0) was used as the N fertilizer source at a rate of 200 kg N ha-1. Key indicators of N transformations were measured, including residual concentrations of ammonium (NH4-N) and nitrate (NO3-N), NO3-N leaching, NH3 volatilization, and nitrous oxide (N2O) emissions. Findings revealed that compaction significantly increased residual NH4-N concentrations in deeper soil profiles, with the highest 190.80 mg kg-1 recorded in loam soil under sub-surface compaction and dry conditions. Nitrification rates decreased across both soil types due to compaction, evidenced by elevated residual NH4-N levels. Increased NO3-N leaching was observed in loam soil (178.06 mg L-1), greater than sandy loam (81.11 mg L-1), due to initial higher residual NO3- in loam soil. The interaction of compaction and moisture most affected N2O emissions, with the highest emissions in control treatments during dry weather at 2.88 kg ha -1. Additionally, higher NH3 volatilization was noted in moist sandy loam soil under control conditions at 19.64 kg ha -1. These results highlight the necessity of considering soil texture, moisture, and compaction in implementing sustainable N management strategies in agriculture and suggest recommendations such as avoiding broadcast application in moist sandy loam and loam soil to mitigate NH3 volatilization and enhance N use efficiency, as well as advocating for readjustment of fertilizer rate based on organic matter content to reduce potential NO3-N leaching and N2O emissions, particularly in loam soil.

Prediction of the Hydrological Drought Index (HDI) based on Rain Simulation Data using an Artificial Neural Network (ANN) in the Randugunting Watershed, Rembang Regency

Randugunting Watershed, with the main river Randugunting River, originates from the North Limestone Mountains of Rembang Regency. Because of its cyclical nature, the river flow discharge is continually subject to change. The discharge rises during rainy weather and falls during dry weather. Due to this issue, Rembang will likely experience drought throughout the dry season. The objectives of this study are to: (1) determine the drought index and its sharpness based on the Hydrological Drought Index Method (HDI) and (2) make drought predictions using the HDI based on discharge for the years 2023–2026 using simulated rain data with Artificial Neural Networks (ANN). Calculation of regional rainfall using the Thiessen Polygon Method. To find simulated rain and drought prediction based on the ANN with Backpropagation algorithm using Mathlab software. From the analysis indicate that the number of months that would experience wet conditions are decreasing from 7 months in 2023 and 2024 to 6 months in 2025 and only 3 months in 2026. In the anticipated drought from 2023 to 2026, there will be 14 dry months, 8 very dry months, and 3 extremely dry months. The examination of the hydrological drought’s duration revealed that the typical drought period fell between May and November.

Operation Risk Simulation and Interaction Impact of Stormwater and Sewage Systems Based on Storm Water Management Model

With the increasing urbanization rate, higher demand is placed on drainage systems, necessitating analysis of their risk profiles. While many studies focus on the individual hydraulic modeling of stormwater and wastewater systems when considering operational risks, they often overlook the exacerbating effects of combined stormwater and wastewater flows on each other’s risks. In this study, we constructed a model of the combined stormwater and wastewater drainage system in Lijiao, Guangdong Province. We analyzed the operational risks of both stormwater and sewage networks in different scenarios, focusing on full-load pipes, overload pipes, node overflows, and minimum flow velocities. Furthermore, we compared the exacerbating effects of sewage and stormwater on each other’s network operational risks. Simulation results indicated that, for sewage networks with combined sewer sections, the lengths of full-load pipes and overload pipes increased by an average of 27.4% and 16.3%, respectively, during rainy weather scenarios compared to dry weather. After considering the inflow of sewage into combined sewer sections, the average length of full-load pipes increased by 3.8 km, overload pipe length increased by 1.1 km, and overflow volume increased by 2.26 × 104 m3. As the return period of rainfall events increases, these inter-system impacts gradually diminish. Therefore, when modeling drainage systems and assessing operational risks, particularly during low return period rainfall events, the inclusion of both stormwater and sewage in combined sewer networks should be comprehensively considered.

The estimation of infiltration and inflow in a sewage network by combining continuous monitoring of hydrological parameters, flow and temperature with stable isotopes of oxygen and hydrogen

The failure of sewage network systems can lead to the introduction of external water, impacting the capacity, performance, and environmental sustainability of urban infrastructures. This study examined methods for identifying and quantifying external water in a sewage system in cold climate conditions through the analysis of stable isotope of oxygen (δ18O) and hydrogen (δ2H) from samples, and continuous temperature monitoring, followed by the simulation of the network's hydraulics and temperature profile. The assessment was conducted during periods of low and high groundwater levels, specifically during dry weather flow. In comparison, the yearly trends of infiltration and inflow rates were assessed utilizing the moving minimum method. Using δ18O as a tracer, daily infiltration rates of 5.8 % and 35 % were estimated for periods of low and high groundwater levels, respectively. Using the outputs of the thermodynamic model, temperature was used as a tracer and the daily infiltration rates were found to be 1.5 % and 21.9 % for the same periods. The infiltration and inflow rate for the year in question was estimated to be 23 % using the moving minimum method. The findings of this study demonstrate the temporal variability of infiltration in networks and highlight the need for, as well as the potential of, a multi-faceted approach and continuous monitoring for the accurate estimation of external water before sewage network renovations are carried out.

Investigating First Flush Occurrence in Agro-Urban Environments in Northern Italy

The first flush (FF) phenomenon is commonly associated with a relevant load of pollutants, raising concerns about water quality and environmental management in agro-urban areas. An FF event can potentially transport contaminated water into a receiving water body by activating combined sewer overflow (CSO) systems present in the drainage urban network. Therefore, accurately characterizing FF events is crucial for the effective management of sewer systems and for limiting environmental degradation. Given the ongoing controversy in the literature regarding the delineation of FF event occurrences, there is an unavoidable necessity for further investigations, especially experimental-based ones. This study presents the outcomes of an almost two-year field campaign focused on assessing the water quantity and quality of two combined sewer systems in Northern Italy. For this purpose, various hydro-meteorological variables, including precipitation, flow rate, temperature, and solar radiation, in addition to water quality analytics, were measured continuously to capture stormwater events. Throughout the monitoring period, sixteen stormwater events were identified and analyzed using five indices usually adopted in the literature to identify FF occurrences. The results indicate that there is a strong positive correlation between the mass first flush ratios calculated for nutrients and three factors, including maximum rainfall intensity, maximum flow rate, and antecedent dry weather period. Furthermore, rainfall duration was found to possess a strong negative correlation with the mass first flush ratios calculated for nutrients. However, for the same rainfall event, the occurrence of FF has never been unanimously confirmed by the indices examined in this study. Moreover, different macro-groups of pollutants can behave differently. Thus, it becomes apparent that relying solely on a priori analyses, without the support of data from experimental monitoring campaigns, poses a risk when designing actions for the mitigation of FF occurrences.

Foliar nitrogen uptake in broadleaf evergreen Mediterranean forests: Fertilisation experiment with labelled nitrogen

Atmospheric nitrogen (N) deposition in Mediterranean sclerophyllous forests of Holm oak (Quercus rotundifolia, Q. ilex) in Spain often exceeds empirical critical loads established for ecosystem conservation. There are still uncertainties on the capacity of canopy retention and uptake of the atmospheric N deposited of these forests. Studying and analysing all the forest nitrogen-cycle processes is essential to understand the potential effect of N deposition in these ecosystems. This study conducted a year-long short-term fertilisation experiment with labelled ammonium (15N-NH4) and nitrate (15N-NO3) to estimate foliar N absorption rates and assess the influence of leaf phenology and meteorological seasonal variations. Fertilising solutions were prepared to simulate low and high wet N deposition concentration, based on data reported from previous studies. Additionally, ecophysiological and meteorological measurements were collected to explore potential relationships between absorption rates, plant activity, and weather conditions. The results showed that Holm oak leaves were able to absorb both oxidised and reduced N compounds, with higher rates of NH4+ absorption. N recovery of both NH4+ and NO3− was higher in the low concentration treatments, suggesting reduced effectiveness of absorption as concentration increases. Foliar absorption rates were leaf-age dependent, with the highest values observed in young developing leaves. Foliar uptake showed seasonal changes with a clear reduction during the summer, linked to drought and dry weather conditions, and showing also smaller leaf net assimilation and stomatal conductance. During the rest of the year, foliar N absorption was not clearly associated to plant physiological activity but with environmental conditions. Our findings suggest that Holm oak canopies could absorb an important part of the incoming N deposition, but this process is compound, season and leaf phenology dependent. Further research is therefore needed to better understand and model this part of the N cycle.

Study on the relationship between structure and moisturizing performance of seamless knitted fabrics of protein fibers for autumn and winter

Abstract With dry weather and low humidity in autumn and winter, human skin is usually prone to dryness, even leading to itchy skin and other problems, so it is important to do a good job of skin moisturizing. The fabrics produced by using protein fiber have a certain moisturizing effect on human skin. Five types of yarn including collagen fiber, cheese protein fiber, silkworm pupa protein fiber, cashmere protein fiber, and viscose are chosen as veil materials, while nylon/spandex composite fiber is chosen as inner yarn material. Three fabric structures including the weft plain stitch, 1 + 1 mock rib, and 1 + 3 mock rib are selected for the study. Based on the full factorial experimental design method, 15 samples of seamless knitted fabrics are produced using a circular knitting machine. In order to investigate the effects of different veil materials and fabric structure of seamless knitted fabric on skin moisturizing performance, the skin moisture content test and the trans-epidermal water loss test were carried out before and after the fabric samples were wrapped around the skin of 20 participants. The results show that both the veil materials and the fabric structure have significant effects on the skin moisture content. The use of collagen yarn as the veil material and 1 + 1 mock rib as the fabric structure results in better moisturizing effects on human skin. In terms of the trans-epidermal water loss test, the fabric structure has significant effects on the results, while the veil material has no significant effect on it. However, the value of trans-epidermal water loss of the fabric with protein yarn is smaller than that of the fabric with ordinary viscose. Therefore, using cheese protein yarn as the veil material and 1 + 1 mock rib as the fabric structure results in a smaller trans-epidermal water loss value.

Enhancement of energy and cost efficiency in wastewater treatment plants using hybrid bio-inspired machine learning control techniques

Global population growth drives demand for clean water, energy, and wastewater production in urban areas. Most existing wastewater treatment plants (WWTPs) are energy- and cost-intensive. To achieve the UN Sustainable Development Goals (SDGs) by 2030, many regions have implemented strict policies for energy consumption and contaminated water discharge, promoting environmental sustainability. This paper attempts to enhance the achievement of SDGs in the wastewater treatment industry by proposing a novel method for hierarchical control of wastewater treatment plants to ensure energy and cost efficiency with less knowledge of the process model, fewer measurements, and fewer control loops. This controller is the combination of a machine learning control technique with a bio-inspired computational algorithm. To evaluate and validate the performance of the proposed controller on the WWTP, the benchmark simulation model no. 1 (BSM1) has been used. The most significant contributions of this paper show that 488.96 KWh/d, 3620.08 Kg/d, and 3454.55 KWh/d of aeration energy cost index, sludge production cost index, and operational cost index are respectively saved when compared to the default control strategy (DCS). Also, 893.69 Kg pollution units per day of effluent fine-related costs have been successfully recovered when compared to the DCS. The experimental results illustrate that the proposed control yields significant amelioration of the energy and cost profile of the WWTP with no effluent violation in dry, rain, and storm weather conditions.

European summer weather linked to North Atlantic freshwater anomalies in preceding years

Abstract. Amplified Arctic ice loss in recent decades has been linked to the increased occurrence of extreme mid-latitude weather. The underlying mechanisms remain elusive, however. One potential link occurs through the ocean as the loss of sea ice and glacial ice leads to increased freshwater fluxes into the ocean. Thus, in this study, we examine the link between North Atlantic freshwater anomalies and European summer weather. Combining a comprehensive set of observational products, we show that stronger freshwater anomalies are associated with a sharper sea surface temperature front between the subpolar and the subtropical North Atlantic in winter, an increased atmospheric instability above the sea surface temperature front, and a large-scale atmospheric circulation that induces a northward shift in the North Atlantic Current, strengthening the sea surface temperature front. In the following summer, the lower-tropospheric winds are deflected northward along the enhanced sea surface temperature front and the European coastline, forming part of a large-scale atmospheric circulation anomaly that is associated with warmer and drier weather over Europe. The identified statistical links are significant on timescales from years to decades and indicate an enhanced predictability of European summer weather at least a winter in advance, with the exact regions and amplitudes of the warm and dry weather anomalies over Europe being sensitive to the location, strength, and extent of North Atlantic freshwater anomalies in the preceding winter.

Wastewater generation model to predict impacts of urine separation on wastewater treatment plants.

Wastewater treatment plants (WWTPs) are under increasing pressure to enhance resource efficiency and reduce emissions into water bodies. The separation of urine within the catchment area may be an alternative to mitigate the need for costly expansions of central WWTPs. While previous investigations assumed a spatially uniform implementation of urine separation across the catchment area, the present study focuses on an adapted stochastic wastewater generation model, which allows the simulation of various wastewater streams (e.g., urine) on a household level. This enables the non-uniform separation of urine across a catchment area. The model is part of a holistic modelling framework to determine the influence of targeted urine separation in catchments on the operation and emissions of central WWTPs, which will be briefly introduced. The wastewater generation model is validated through an extensive sampling and measurement series. Results based on observed and simulated wastewater quantity and quality for a catchment area of 366 residents for two dry weather days indicate the suitability of the model for wastewater generation and transport modelling. Based on this, four scenarios for urine separation were defined. The results indicate a potential influence of spatial distribution on the peaks of total nitrogen and total phosphorus.

Hybrid supervised hierarchical control of a biological wastewater treatment plant.

In wastewater treatment intensification, hierarchical control structures are developed to improve the plant's performance. This paper proposes two novel hybrid supervised hierarchical control structures for specifying the dissolved oxygen concentration in the last aerobic reactor of the wastewater treatment plant (WWTP) based on the nitrification rate and the ammonia level in this reactor. These structures combine the optimum disturbance rejection PI control (OPI), adaptive neuro-fuzzy inference system (ANFIS), and genetic algorithms (GA) to reduce energy consumption and operational costs, improve effluent quality, and reduce the number and percentage of times the established maximum concentration of pollutants in the effluent of the WWTP is violated. The proposed control strategy is implemented and evaluated using benchmark simulation model no. 1 (BSM1). The OPI-ANFIS-GA configuration significantly enhances effluent quality in dry, rainy, and stormy weather conditions, reducing total nitrogen violations by 50.17%, 63.35%, and 47.35%, respectively. Then, 6.79% and 7.12% of aeration energy and 1.44% and 1.46% of operational costs are reduced in dry and rain weather conditions. The OPI-ANFIS configuration enhanced significant energy savings and a cost reduction in storm weather conditions. Both configurations led to a 49.89% decrease in total suspended sludge (TSS) during stormy weather conditions. The proposed controller significantly improves the performance of the WWTP in all weather scenarios compared to the default controller and similar controllers found in the literature.

Seed production of spring cereals at the Federal Agrarian Scientific Center of the North-East named after N.V. Rudnitsky

Seed production of spring grain crops is the foundation of food security of a modern state. Together with breeding, seed production provides high quality products in the required volume. In the Kirov region, the main producers of original seeds are the Federal Agrarian Scientific Center of the NorthEast named after N.V. Rudnitsky (FASC of the North-East) and Vyatka State Agrotechnological University. FASC of the North-East was reorganized in 2017 to include the North-East Regional Agrarian Research Center, Falyonskaya Breeding Station, Nizhny Novgorod, Mari, Mordovian and Chuvash Agricultural Research Institutes. The FASC of the North-East in Kirov has been producing original seeds of spring grain crops since 1974 by the method of individual-family selection. Original seeds are sold annually to the farms of the Kirov region and other regions of the Russian Federation for use in the nurseries of propagation and super elite. The article analyzes the work of the seed production department for 2019–2021, displays the methodology of obtaining original seeds of spring cereals (oats, wheat, barley), describes the varieties most in demand in the Kirov region. The area of sowing original seeds of spring cereals in the experimental fields of the FASC of the North-East increased by 23.4% during the period under review, reaching 49 ha in 2021. Due to dry weather in 2021, the gross harvest of conditioned spring cereal seed remained at the same level as in 2019 at 60.9 tons. The revenue of the seed division of the FASC of the North-East from the sale of original seeds increased by 47.53% in 2021 compared to 2019 to reach 2.5 million rubles. Original seeds are usually sold to the enterprises that have their own seed production units: AO Agrofirma "Doronichi", APC "Plemzavod "Krasny Oktyabr", APC "Agricultural Artel "Krasnaya Talitsa", OOO "Zurinsky Agrocomplex", OOO "Preduralye". Thus, the Seed Production Department of the FASC of the North-East is an important link in ensuring food security in the region.

Effect of integrated use of Zircon and Siliplant on productivity of <i>Echinacea purpurea</i> roots in Western Caucasus

Echinacea purpurea L. – is a perennial medicinal plant, from the herb of which dozens of preparations have been created that are used to strengthen the immune system, in the treatment of inflammatory diseases. At present, oxyconic acids and alkamides have been found in the plant’s root system, and the preparations «Anginol» and «Prostanov» have been created on their basis. The production and creation of new medicinal products from the roots and rhizomes of the Echinacea purpurea depends on a stable raw material base, which can be ensured by obtaining maximum yields of roots. As a result of studies to determine the timing of harvesting, methods to increase the yield of the underground mass in the conditions of the Krasnodar Territory, it was revealed that the high yield of roots and rhizomes of Echinacea purpurea was determined on plantations III-IV years of growing, which averaged 10 c/ha, they had an oxyconic acid content of 3,9%. In the future, there is a decrease in yield to 8 c/ha, and active substances to 2.1%. Dual treatments treatments Zircon (0.04 l/ha) and Siliplant (0.5 l/ha) both separately and in the mixture gave the opportunity to increase the yield for III and IV years to 28–30% and improve the quality of raw materials, the content of active substances increased by 5–7%. The complex use of these drugs in the V year of vegetation allows to increase the yield of roots to 10.3 c/ha with a high content of oxidic acids – 2.55%. It was revealed that foliar fertilization of vegetative plants with two-component system Siliplant + Zircon promotes the adaptation of Echinacea purpurea to dry weather conditions and makes it possible to obtain stable yields of medicinal raw materials with high quality regardless of weather conditions.

Spatial and remote sensing monitoring shows the end of the bark beetle outbreak on Belgian and north-eastern France Norway spruce (Picea abies) stands.

In 2022, Europe emerged from eight of the hottest years on record, leading to significant spruce mortality across Europe. The particularly dry weather conditions of 2018 triggered an outbreak of bark beetles (Ips typographus), causing the loss of thousands of hectares of Norway spruce stands, including in Wallonia and North-eastern France. A methodology for detecting the health status of spruce was developed based on a dense time series of satellite imagery (Sentinel-2). The time series of satellite images allowed the modelling of the spectral response of healthy spruce forests over the seasons: a decrease in photosynthetic activity of the forest canopy causes deviations from this normal seasonal vegetation index trajectory. These anomalies are caused by a bark beetle attack and are detected automatically. The method leads in the production of an annual spruce health map of Wallonia and Grand-Est. The goal of this paper is to assess the damage caused by bark beetle using the resulting spruce health maps. A second objective was to compare the influence of basic variables on the mortality of spruce trees in these two regions. Lasted 6years (2017-2022), bark beetle has destroyed 12.2% (23,674ha) of the spruce area in Wallonia and Grand-Est of France. This study area is composed of three bioclimatic areas: Plains, Ardennes and Vosges, which have not been equally affected by bark beetle attacks. The plains were the most affected, with 50% of spruce forests destroyed, followed by the Ardennes, which lost 11.3% of its spruce stands. The Vosges was the least affected bioclimatic area, with 5.6% of spruce stands lost. For the most problematic sites, Norway spruce forestry should no longer be considered.

Response of arabica coffee populations on coffee leaf rust in two weather conditions in North Sumatra, Indonesia

Coffee leaf rust (CLR) disease is seriously threatening the sustainability of coffee production in many countries. The incidence and severity as CLR parameters generally depend on the coffee plant, pathogen, and environment. Therefore, this study aimed to determine the effect of arabica coffee populations and weather conditions on CLR parameters. The study was carried out using a field experiment with seven groups of arabica coffee populations in different weathers in North Sumatra Province, Indonesia. The results showed that the arabica coffee population P7 from District Toba had high resistance to wet weather. Furthermore, all the population groups showed higher degree of CLR parameters in dry than wet weather, while a significant interaction between the population and the weather was observed on branch rust incidence, leaf rust incidence, and severity. Moreover, H. vastatrix races were probably varied and had different adaptability to weather changes, which was the most decisive factor for the dispersal and severity of CLR. The CLR parameters in the dry weather did not correlate with the parameters in the wet weather and vice versa. The total rainfall and the number of the rainy day reduced the CLR dispersal and severity.

Precipitation impacts the physicochemical water quality and abundance of microbial source tracking markers in urban Texas watersheds

This study investigated the sources of fecal pollution in surface and groundwaters collected from three urban watersheds in Texas during dry and wet weather and identified the impact of precipitation on water quality. Water samples (n = 316 and 107 for dry and wet events, respectively) were collected biweekly from eight sampling sites (6 sites from creeks and ponds, and 2 well sites) during two-year monitoring and analyzed for six physico-chemical parameters and ten qPCR-based assays targeting general (E. coli, Enterococcus, and universal Bacteroidales), human (BacHum and HF183), animal (Rum2Bac, BacCow, BacCan), and avian (Chicken/Duck-Bac and GFD) fecal markers. Elevated concentrations of NO3-N and NO2-N were observed in ponds and creeks sites during wet weather. Fecal markers analysis indicated higher concentrations of Rum2Bac, BacCow, and BacCan markers in most of pond and creek sites under wet weather, suggesting stormwater runoff contributed to non-point sources of fecal contamination by animal sources. Furthermore, sporadically higher concentrations of these markers were detected at groundwater sampling sites, demonstrating the significant human health risk. Multivariate statistical analysis such as cluster analysis (CA) and principal coordinate analysis (PCoA) was performed to identify relationship between sampling sites; while CA majorly classified ponds, creeks, and well sites separately, PCoA identified similarities in water quality characteristics between waters of wells with ponds and creeks. Overall, results indicate ruminant and dog fecal contamination is a major concern during storm events, consequently impacting surface and groundwater quality of the study.

Dust captured by a canopy and individual leaves of trees in the tropical mixed deciduous forest: Magnitude and influencing factors

Forest tree leaves play a significant role in air purification, but forest fires could offset the dust sink role. This study aims to assess the functions of the forest in atmospheric dust sink and source and assess the dust capturing capacity of individual leaves of various tree species in the tropical mixed deciduous forest in the dry season (November 21, 2021, to January 23, 2022), along with its influencing factors—climatic variables, environmental variables, and leaf morphology. The result shows that the downward flux or the forest dust sink role was predominant midday when air–mass turbulence played a role. Nonetheless, net mass PM1 and PM10 concentration trapped by the forest canopy was low, 0.79 and 2.24 µg m−3, respectively. For PM2.5, forest fires could outrun the PM2.5 sink role for the entire dry season. Considering the individual tree leave, maximum dust capturing capacities for the forest trees ranged from 0.95 to 5.197 g m−2. Leaf dust capturing capacity was enhanced under cold and dry weather, strong winds, and for trees with defoliated or irregular shape. Leaf/leaflet enhancing the dust capturing capacity exhibited large size; either thick and leathery texture (Coriaceous) or thin, semi-translucent, membrane-like texture (Membranaceous); indumentum top being short, stiff trichomes (Scabrous); or indumentum bottom surface being densely short, soft trichomes (Tomentose). The various dust capturing dynamics among tree species could benefit dust capturing by the forests in the dry season.

Seasonal dynamics of hydration of shoots of resource species of shrubs in the mediterranean subarid subtropics

   An attractive region for tourism - the Southern Coast of Crimea, including the vicinity of the Nikitsky Botanical Garden – is experiencing a high year-round anthropogenic load. This has a negative impact on the conservation and renewal of woody and herbaceous resource species, many of which are ornamental, food and medicinal. As part of the study of the possibilities of renewing the resources of ornamental shrubs and assessing their adaptive potential in the conditions of the Mediterranean subtropics, the article characterizes the water content in buds and shoots based on the methodology for determining the percentage of water per dry mass. The dynamics of the hydration of shoots in winter, spring and autumn is shown. A comparative analysis of the saturation of shoots with water in unstable and stable species at different times of the year is carried out. Species with minimum and maximum water saturation of buds and shoots have been identified. The difference is indicated in the studied species in terms of water content before saturation in natural conditions and after, already in thelaboratory. Attention is drawn to the dependence of species stability on the month of saturation. The characteristic of saturation of plant tissues with water is given when weather conditions change in spring (rainy and dry weather, thaw) when modeling climatic conditions in the laboratory. The species in which the maximum saturation with water occurs both during imitation of rainy weather and during a thaw are highlighted. These studies were conducted for the first time on the described species in the conditions of the Mediterranean subtropics.

Unusual outbreaks of curly top disease in processing tomato fields in northern California in 2021 and 2022 were caused by a rare strain of beet curly top virus and facilitated by extreme weather events

In the western United States, curly top disease (CTD) is caused by beet curly top virus (BCTV). In California, CTD causes economic loss to processing tomato production in central and southern areas but, historically, not in the north. Here, we document unusual CTD outbreaks in processing tomato fields in the northern production area in 2021 and 2022, and show that these were caused by the rare spinach curly top strain (BCTV-SpCT). These outbreaks were associated with proximity of fields to foothills and unusually hot, dry, and windy spring weather conditions, possibly by altering migrations of the beet leafhopper (BLH) vector from locations with BCTV-SpCT reservoirs. Support for this hypothesis came from the failure to observe CTD outbreaks and BLH migrations in 2023, when spring weather conditions were cool and wet. Our results show the climate-induced emergence of a rare plant virus strain to cause an economically important disease in a new crop and location.