Influence Of Weather Conditions Research Articles

Influence of Weather Conditions on Contamination of Grain Fodder by Micromycetes in the Northwestern Black Sea Region of Ukraine

Influence of Weather Conditions on Contamination of Grain Fodder by Micromycetes in the Northwestern Black Sea Region of Ukraine

METHODS OF FORECASTING GRAIN CROP YIELD INDICATORS TAKING INTO ACCOUNT THE INFLUENCE OF METEOROLOGICAL CONDITIONS IN THE INFORMATION-ANALYTICAL SUBSYSTEM

Forecasting crop yields is one of the key challenges for the agricultural sector, especially in the context of a changing climate and unstable weather conditions. Kazakhstan, possessing significant territories suitable for growing grain crops, faces many challenges related to the effective management of agricultural activities. In this regard, yield forecasting becomes an integral part of planning and decision-making processes in agriculture. Information and analytical subsystems that integrate yield forecasting methods allow agribusinesses to estimate future production more accurately, minimise risks associated with climate change and optimise resource use. An important component of such systems is the consideration of weather conditions, as weather factors have a direct impact on crop growth and development. The purpose of this article is to develop and evaluate modern methods of forecasting grain yields taking into account the influence of weather conditions, as well as their integration into information-analytical subsystems to improve the accuracy of agricultural forecasting. To achieve this goal, the article addresses the following tasks: to analyse existing methods of yield forecasting and identify their advantages and disadvantages, to develop forecasting models, including machine learning methods such as gradient bousting and recurrent neural networks, to validate the developed models on the basis of historical data using cross-validation methods, to evaluate the effectiveness of the proposed methods and compare them with basic models such as linear regression and simple average, to evaluate the effectiveness of the proposed methods and to compare them with the basic models such as linear regression and simple average. This article reviews modern methods of forecasting grain crop yields in Kazakhstan, as well as technologies used in information-analytical subsystems. Particular attention is paid to the analysis of the influence of meteorological conditions on yields and the development of models that take this factor into account. The presented review and research results are aimed at improving the existing approaches to the management of agricultural processes under conditions of growing uncertainty caused by climate change. The article explores an important scientific task related to the development of methods for step-by-step forecasting of agrometeorological factors and grain yields, relying on the principle of analogy.

Development and Assessment of the Performance of a Novel Parabolic Trough Solar Collector-Driven Three-Stage Cooling Cycle

Abstract A gaseous flow is employed as heat transfer fluid (HTF) in a parabolic trough solar collector (PTSC) for simultaneous production of cooling at three different levels of temperature to meet the demands of air conditioning, refrigeration, and ultra-low-temperature refrigeration required to ensure the efficacy of some special vaccines. The combined system consists of five subsystems including PTSC, Kalina cycle (KC), ejector refrigeration cycle (ERC), cascaded refrigeration cycle (CRC), and absorption refrigeration cycle (ARC). A simulation through an engineering equation solver (EES) is conducted to assess the impact of internal tube diameter of absorber and solar irradiation on rise of HTF temperature and mass flowrate of Kalina cycle fluid. It is determined that for given solar irradiation, the temperature of HTF goes down when internal diameter of absorber tube is enlarged. The influence of weather conditions; solar irradiation and ambient temperature, type of HTF, and concentration of ammonia–water basic solution on thermal and exergy efficiencies of three-stage cooling cycle (TSC) are examined. The TSC with helium-operated PTSC delivers better results than air and CO2. Exergy analysis shows that solar collector (30.26%) dissipates the highest exergy, followed by the ejector (12.5%) and vapor generator subsystem (7.61%). The type of CRC fluid pair affects TSC cycle refrigeration capacity and cooling exergy efficiency. The promotion of solar irradiation from 850 to 1200 W/m2 increases the cooling exergy efficiency of the three-stage cycle from 6.72% to 9.52% when the evaporator temperature is set at −45 °C and CRC employs NH3-propylene.

Influence of weather conditions on the duration of the growing season and economically valuable traits and properties of soybean varieties of domestic and foreign selection

The influence of meteorological conditions of the region on the duration of the vegetation period and production process of domestic and foreign soybean breeding was determined. The research was conducted in the period 2021–2023 in the Bryansk region. 18 soybean varieties included in the Register of breeding achievements admitted to use were taken as an object of research. According to the duration of the vegetation period varieties are divided into three groups of ripeness: fast-ripening – Vita, Lira, Leader 10, Amadea, Lisbon, Vera, early-maturing – Protina, Volma, Kora, Zusha, Mezenka, Osmon, Sultana, medium-maturing – Sculptor, Pripyat, Puma, Sirelia, Ros. It was revealed that, on average, plant height increased with the increasing vegetation period: fast-ripening – 75.8 cm, early-maturing – 77.3, medium-maturing – 83.0 cm. It was revealed that, on average, with an increase in the growing season, the height of plants increased: precocious – 75.8 cm, early-maturing – 77.3 cm, middle-maturing – 83.0 cm. 4 genotypes (22 %) with low attachment of the lower beans were identified: Vera, Kora, Pripyat, Sirelia, 11 varieties (61 %) with medium attachment of the lower beans: Vita, Lira, Leader 10, Amadea, Lisbon, Volma, Zusha, Osmon, Sultana, Sculptor, Puma, 3 varieties (17 %) with a high attachment: Protina, Mezenka, Ros. The weight of 1000 seeds was calculated – varieties with larger filled seeds: Sultana (176), Ros (177), Lisbon (162), Vita (158), Vera (158), Sirelia (158). Varieties with the highest seed yield were identified: Ros (25.3 c/ha), Zusha (22.8), Sculptor (22.2), Pripyat (22.2), Lisbon (22.1 c/ha). Crude protein was determined by the Kjeldahl method, crude fat by the Soxhlet. The high content of crude protein was formed by the varieties of domestic breeding: Puma (36.66%), Mezenka (35.95%), Osmon (35.75%), Vera (35.34%); foreign varieties: Sirelia (39.05%), Sultana (38.27%), Pripyat (36.17%). The crude fat content in the seeds varied both by year and by variety. The maximum fat value was noted in the genotypes: Ros (23.78%), Mezenka (23.72%), Sculptor (23.18%), Zusha (22.45 %), Sultana (22.36%).

Improving Pedestrian Safety with Head-Up Display Warning in a Connected Environment

In this paper, the potential of using a head-up display (HUD) in the connected environment to improve a vehicle’s running comfort and pedestrian safety is tested, by providing warning information to drivers in advance. To achieve this objective, driving simulation technology is used to construct the connected environment and develop the HUD, and the effectiveness of the system is then tested. Specifically, thirty-four participants were recruited to conduct driving simulation experiments in six scenarios: three warning display types (Baseline/Head-down display/Head-up display) combined with two weather conditions (clear weather/foggy weather). The effects of the three different warning display types on braking risk-avoidance strategy were studied by comparing the drivers’ performance during the perception and decision stage (position of accelerator-pedal release, position of first braking), the risk-avoidance manipulation stage (maximum deceleration, braking distance) and the risk-avoidance result stage (minimum collision distance, position of minimum speed). The influences of weather conditions and driver attributes were also considered. When the HUD warnings were activated, drivers started to decelerate further away from pedestrians, with a more stable and moderate deceleration process and a greater safety margin between the vehicle and the pedestrians. Using HUD warnings in foggy conditions improved drivers’ perception and decision abilities, this study confirmed the great benefits that HUD warnings in the connected environment can bring to traffic safety, especially under risky situations and inclement weathers. The research results provide a reference for the more humanized and rationalized optimization design of these warning systems.

Correlation between perennial grass productivity and landscape and climatic conditions

The yield monitoring (1998–2023) of cloverothymothy grass stands of 1 year of use within the moraine hill was carried out in order to find patterns in the influence of weather conditions on it. The grass stands were operated in the conditions of the Tver region without fertilizers in a single-cut mode on a field divided into 120 plots. Using regression analysis, we determined the influence of temporal variability of average monthly values: average daily temperatures, their amplitude, amount of precipitation and hydrothermal coefficient on the hay yield of perennial grasses. It was revealed that in total these parameters determine about 43% of the variability in grass productivity, but fluctuations in temperature amplitudes are responsible for 32% of the temporal variability of the yield. The yield of herbs is affected by the variability of growing conditions not only in time, but also in space. The negative impact on the yield of air temperature changes is observed in all parts of the landscape, except for the flat top, where productivity responds positively to the growth of the hydrothermal coefficient and negatively to the increase in air temperatures in the pre-harvest period. The following have a negative impact on product yield: temperature changes in late summer and early autumn, especially on southern slopes, which can make it difficult for plants to overwinter; thaws in March, causing the formation of an ice crust on the soil surface and damaging the tillering nodes of plants; hot days in the pre-harvest period, accelerating the ripening of grasses and reducing the intensity of biomass accumulation. February thaws, promoting the accumulation of moisture in the soil, lead to an increase in grass yield. Measures that reduce the negative impact of temperature changes on the grass harvest include: autumn mowing of young grass, snow retention in meadows, and sprinkling of grass on the hottest days of the pre-harvest period.

The Influence of Weather Conditions on the Immortelle Volatile Constituents from Essential oil and Hydrosol with a Focus on Italidiones and Its Molecular Docking Anti-Inflammatory Potential

Objectives Immortelle has garnered global attention for its cosmetic, medicinal, and culinary applications worldwide. Apart from neryl acetate, α-pinene and γ-curcumene as the most important components for the estimation of the essential oil quality, in recent years a group of β-diketones, known as italidiones, appear as significant quality parameters. However, it is unknown how weather conditions (temperature and precipitation) influence their accumulation in essential oil and hydrosol, nor their anti-inflammatory potential. Methods This study investigates the chemical composition of immortelle essential oil and hydrosol over three successive years (2019/20, 2020/21, and 2021/22), by GC-FID and GC-MS analysis. In silico molecular docking model with Vascular Adhesion Protein-1 (VAP-1) was used for the simulation of the anti-inflammatory potential of italidiones, as well as other β-diketones present in immortelle essential oil and hydrosol. Results During the three-year trial, it was established that essential oil compounds such as α-pinene, neryl acetate, and italicene were positively correlated with temperature and negatively correlated with precipitation, as well as β-diketones and total italidiones. Moreover, trans-caryophyllene, γ-curcumene, and ar-curcumene were in negative correlation with temperature, and a slight positive correlation with precipitation. On the other side, in the hydrosol the content of both total β-diketones and total italidiones was strongly negatively correlated with temperatures, and positively correlated with precipitation, which was the opposite of essential oil. Additionally, findings indicated that italidiones could bind the human VAP-1 protein in the vicinity of the topiquinone and block its function. Conclusion Weather conditions affect variations in the accumulation of volatile compounds in essential oil and hydrosol, which in some cases can affect changes in olfactory characteristics, as well as criteria prescribed by standards, and even changes in biological activities. These results indicate that italidiones, as well as other β-diketones present in immortelle, may be responsible for its anti-inflammatory activity.

Brooding duration does not depend on cat predation risk but is related to weather and phenology in the wandering albatross (Diomedea exulans).

Parental investment increases offspring fitness at the expense of the parent's ability to invest in other offspring. In many animal species, parents guard their offspring after birth. The parental decision over the duration of this period is expected to be triggered by the associated fitness costs and benefits for both offspring and parents. Here, we evaluated the relevance of several intrinsic and environmental variables in determining brooding period duration in the wandering albatross (Diomedea exulans) and questioned whether brooding duration was related to chick subsequent survival and biometry prior to fledging. We used a semi-experimental design to increase the variance in cat abundance, a recent predator of albatross chicks, and predicted that an increased predation risk at the nest scale would trigger longer chick brooding and thus, protection. In addition, we questioned the influence of weather conditions, hatching date, and characteristics of chicks (sex and biometry) and parents (sex and age) on brooding duration. We report no effect of predation risk or parental characteristics on brooding duration. However, the probability for a parent to end brooding decreased with forthcoming unfavorable weather. Our data also revealed reduced brooding duration for late-hatched chicks and a positive association between brooding duration and chick structural size, and between the frequency of shifts between parents and chick structural size. Finally, brooding duration was not associated with chick survival or with chick biometry prior to fledging. We discuss these results in light of pre-existing hypotheses on fitness costs and benefits associated with brooding duration for chicks and parents.

The influence of weather conditions on the formation of the winter wheat harvest according to various precursors in the arid zone of Stavropol

Relevance. The identification of agro meteorological factors that have the greatest impact on the formation of grain yields and their consideration in the improvement of agricultural technologies is an urgent task of agriculture.Methods. The research was carried out in 1972–2023 in the fields of the Prikumsk experimental breeding station in a 6-pole grain-and-grass crop rotation. The purpose of the research is to study the influence of agro meteorological conditions on the formation of the winter wheat harvest according to various precursors for the correction and adaptation of applied agricultural technologies in the arid zone of the Stavropol Territory.Results. The yield of winter wheat significantly depended on precipitation in September — October, moisture reserves by spring, total moisture availability of crops, temperature in May and was determined by the density of plants and the weight of 1000 grains. The maximum yield was formed with precipitation in September — October >117 mm, the highest density of standing (294–392 pcs/m2), spring moisture reserves in the meter soil layer and average total moisture supply for pure steam, respectively, 129–145 mm and 382 mm, occupied steam 115–135 mm and 378 mm and winter wheat 105–125 mm and 342 mm. The minimum duration of the sowing — germination period and the maximum density of standing accounted for a clean and occupied pair for the amount of precipitation for September — October (59–87), and a half-pair >117 mm. Compared with pure steam, the density of standing decreased by an average of 12,2%, the yield by 19,2%, the duration of germination increased 1.4 times, and in repeated crops by 22,6%, 45,3% and 2,7 times, respectively. The mass of 1000 grains had a significant positive relationship with the density of standing by half-steam and a negative one with the average temperature for May — June by pure steam. For half-steam and pure steam, yield is more closely related to the mass of 1000 grains (r = 0.52–0.66) than to the density of standing (r = 0.45–0.50).

Improving Soybean Gross Primary Productivity Modeling Using Solar-Induced Chlorophyll Fluorescence and the Photochemical Reflectance Index by Accounting for the Clearness Index

Solar-induced chlorophyll fluorescence (SIF) has been widely utilized to track the dynamics of gross primary productivity (GPP). It has been shown that the photochemical reflectance index (PRI), which may be utilized as an indicator of non-photochemical quenching (NPQ), improves SIF-based GPP estimation. However, the influence of weather conditions on GPP estimation using SIF and PRI has not been well explored. In this study, using an open-access dataset, we examined the impact of the clearness index (CI), which is associated with the proportional intensity of solar incident radiation and can represent weather conditions, on soybean GPP estimation using SIF and PRI. The midday PRI (xanthophyll de-epoxidation state) minus the early morning PRI (xanthophyll epoxidation state) yielded the corrected PRI (ΔPRI), which described the amplitude of xanthophyll pigment interconversion during the day. The observed canopy SIF at 760 nm (SIFTOC_760) was downscaled to the broadband photosystem-level SIF for photosystem II (SIFTOT_FULL_PSII). Our results show that GPP can be accurately estimated using a multi-linear model with SIFTOT_FULL_PSII and ΔPRI. The ratio of GPP measured using the eddy covariance (EC) method (GPPEC) to GPP estimated using SIFTOT_FULL_PSII and ΔPRI exhibited a non-linear correlation with the CI along both the half-hourly (R2 = 0.21) and daily scales (R2 = 0.25). The GPP estimates using SIFTOT_FULL_PSII and ΔPRI were significantly improved by the addition of the CI (for the half-hourly data, R2 improved from 0.64 to 0.71 and the RMSE decreased from 8.28 to 7.42 μmol•m−2•s−1; for the daily data, R2 improved from 0.71 to 0.81 and the RMSE decreased from 6.69 to 5.34 μmol•m−2•s−1). This was confirmed by the validation results. In addition, the GPP estimated using the Random Forest method was also largely improved by considering the influences of the CI. Therefore, our findings demonstrate that GPP can be well estimated using SIFTOT_FULL_PSII and ΔPRI, and it can be significantly enhanced by accounting for the CI. These results will be beneficial to vegetation GPP estimation using different remote sensing platforms, especially under various weather conditions.

Influence of Weather Conditions and the Aphid Population on the Potato Virus Y Infection of Tobacco in the Field

Potato virus Y (PVY) is a major tobacco (Nicotiana tabacum L.) pathogen that causes severe crop losses. We studied the influence of meteorological factors and a population of twelve aphid species on the development of PVY in field-grown tobacco from 1996 to 2010 in Poland. Three PVY-susceptible tobacco varieties were used in the study. The mean virus incidence ranged from 18% in 2010 to almost 99% in 1996, 2004, and 2009. For determining the relationship between tobacco plant infection and meteorological conditions and aphid populations, logistic regression analysis was used. It was found that the probability of PVY infection is significantly dependent on the average air temperature, relative humidity, number of days with an average temperature of at least 25 °C, and the abundance of Aphis fabae and Brachycaudus helichrysi. The probability of infection of tobacco plants with potato virus Y decreased with increasing air temperature and relative humidity. In addition, with each subsequent day with a temperature of at least 25 °C, the risk of infection decreased by 24%. Furthermore, it was often observed that high populations of Aphis fabae and Brachycaudus helichrysi were associated with a high incidence of virus infection in tobacco plants.

Research on spatial patterns of soil erosion in wind erosion region based on the revised wind erosion equation and partial least squares regression

Understanding the complex influencing factors of soil erosion is critical for maintaining regional ecological security. The revised wind erosion equation (RWEQ) and partial least squares regression (PLSR) model were used to reveal the primary factors affecting soil erosion. Based on the results of the RWEQ model, the wind erosion area was 8,439.3 km2 in 2018, accounting for 54.3% of the total planning area, and mild erosion, moderate erosion, intense erosion, very intense erosion, and fierce erosion accounted for 18.22%, 11.43%, 11.78%, 10.16%, and 2.74% of the total planning area, respectively. Based on the results of the PLSR model, the results indicate that the proportion of mining land, meteorological indicators, and mean square deviation of slope difference were positively correlated with the soil erosion area, intensity, and severity, respectively. The proportion of grassland and forest land was negatively correlated with the soil erosion area, intensity, and severity. The mean square deviation of slope difference, the mean square deviation of difference in elevation, and the proportion of urban land use contributed the most to the soil erosion severity index, with variable importance in projection (VIP) scores of 1.55, 1.44 and 1.43, respectively. The mean square deviation of slope difference, the proportion of urban land, and the mean square deviation of difference in elevation contributed the most to the soil erosion area, with VIP scores of 1.53, 1.26 and 1.24, respectively. The results provide new insights into wind erosion and the influences of weather conditions and human influences, which can guide regional soil and water conservation planning in wind erosion regions.

Influence of Wind and Rainfall on the Performance of a Photovoltaic Module in a Dusty Environment

This study presents an analysis of the influence of weather conditions on the performance of a multicrystalline silicon photovoltaic module, which operates under constant resistive load and is situated near a limestone quarry. The quarry is a significant source of dust, and hence the focus of the study is on the weather factors influencing the presence of soiling on the module’s surface. The analysis encompasses a three-week period, during which the global horizontal irradiance and wind speed were recorded at 10-min intervals by an on-site weather station. The current, voltage, and back temperature of the module were also measured. Supplementary weather data were obtained from the Copernicus Atmosphere Monitoring Service and the NASA POWER databases. The primary objective is to assess whether any influence of the observed weather conditions on the presence of soiling can be inferred from the recorded data. The contribution is in part intended to test how different techniques can be used to extract useful information on the weather-related effects from somewhat limited data, assembled from various sources, while dealing with the underlying uncertainties. The analysis indicates a persistent deterioration of the module’s performance because of soiling and its subsequent improvement due to a favourable weather event.

Optimal electric bus scheduling method under hybrid energy supply mode of photovoltaic-energy storage system-power grid

Currently, the charging energy of electric buses (EBs) primarily relies on the power grid (PG), and the production of the electricity for the power grid still results in carbon emissions. In recent years, a remarkable development has been observed in the photovoltaic (PV) technology. If EBs can be charged using electricity generated from PV, it has great potential to significantly reduce carbon emissions for EB systems at the source. Considering the inherent output power fluctuations from PV source, we propose a hybrid electricity supply mode named “Photovoltaic-Energy Storage System-Power Grid” (PV-ESS-PG). Firstly, considering the characteristics of different electricity supply modes, we introduce charging strategies tailored to different scenarios and formulate a cooperative optimization model for EB dispatching and charging plans. Secondly, we decompose this model into two sub-problems: bus dispatching and charging scheduling. To solve these two sub-problems, we employ the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to obtain the optimization results of bus dispatching plan, charging mode, charging start time, and charging duration. Finally, we validate the proposed method using real-world data of EB operation and PV output power. We further analyze the influences of weather conditions, ESS capacity, and EB rated battery capacity on the optimization results. We find that, compared to the conventional unitary power grid electricity supply mode, the proposed method reduces daily charging costs by 25.48% and carbon emissions by 68.71% of the whole bus route.

ВПЛИВ ПОГОДНИХ УМОВ НА ЧИСЕЛЬНІСТЬ АМФІБІЙ ТА РЕПТИЛІЙ В УМОВАХ ПРИРОДНОГО ЗАПОВІДНИКА «МЕДОБОРИ» ЗА ПЕРІОД 2016–2020 РОКІВ

Based on the results of long-term observations, the influence of weather conditions on the dynamics of the number and biodiversity of amphibians and reptiles over five years in the "Medobory" nature reserve was analyzed. The number, reproduction, metamorphosis stages, and distribution of amphibians and reptiles depend significantly on climatic conditions. Low temperatures in spring inhibit spawning and larval development. During critical periods, a low amount of precipitation (e.g., 15.7 mm in May 2016, 9.1 mm in April 2018, and 12.1 mm in April 2019, compared to the norm of 45 mm) also negatively affects amphibian populations. This factor led to the disappearance of Triturus cristatus Laur., Lissotriton vulgaris L. (an outbreak was noted in 2014), and Bufo viridis Laur. from the reserve (last observed at MG-1 in 2013), as well as the less common Hyla orientalis Bedriaga. Amphibians and reptiles were recorded during the active period along two regular herpetological routes, MG-1 and MG-2, and observations were made during field research, covering all areas suitable for the reproduction and habitat of amphibians. Eleven species of amphibians have been confirmed in the reserve, belonging to six families: Salamandridae, Bombinatoridae, Pelobatidae, Bufonidae, Hylidae, and Ranidae. Among these amphibians, five species are listed in Appendix II of the Berne Convention, and one species (T. cristatus Laur.) is included in the Red Book of Ukraine. The most common amphibian species are Rana temporaria L., Rana arvalis Nilsson, and Bufo bufo L. Frogs such as Pelophylax lessonae Camerano and Pelophylax ridibundus Pallas occasionally occur within the reserve, as they require an aquatic environment even after reproduction. There are seven species of reptiles in the reserve and one in the immediate vicinity, out of the ten recorded in the Ternopil region. These reptiles occupy the most suitable habitats for their survival. The species represent five families: Emydidae (freshwater turtles), Anguidae (spindly lizards), Lacertidae (true lizards), Colubridae (snakes), and Viperidae (vipers). Common species include Lacerta agilis Andrz., Natrix natrix L., and Anguis fragilis L. Six species of reptiles are included in Appendix II of the Berne Convention, and the common copperhead (Coronella austriaca Laur.) is included in the Red Book of Ukraine.

COMPONENT COMPOSITION OF ARTEMISIA SANTOLINIFOLIA TURCZ EX BESS. ESSENTIAL OIL

Purpose. To conduct a comparative analysis of the qualitative composition and quantitative content of components of essential oils isolated from different organs of Artemisia santolinofolia, and also to study the influence of weather conditions on the accumulation and composition of essential oils. Material and methods. The object of the study is the aerial part of A. santolinifolia, collected in the Okinsky district of the Republic of Buryatia during the flowering phase, in August 2016, 2017, 2019. Essential oils were isolated by hydrodistillation. The component composition was determined by chromatography-mass spectrometry with an Agilent Packard HP 6890 gas chromatograph with a quadrupole mass spectrometer (HP MSD 5973N). Results. The highest content of essential oils is in inflorescences (0.7%) and leaves (0.7%), less in the aerial parts (0.5%) and stems (0.4%). Monoterpenoids mainly accumulate in inflorescences, sesquiterpenoids are mostly found in leaves and stems. Dominant components characteristic of all parts of the plant: 1,8-cineole (1.5–9.1%), terpineol-4 (0.7–2.8%), bornyl-2-methylbutonoate (1.5–1.8), camphor (0.4–39.5%), borneol (0.7–6.4%), bornyl acetate (3.1–5.0%), davana ether (isomer 1) (1.9–5.3%), davana ester (isomer 2) (1.1–3.2%), davanone (0.6–12.4%), caryophiollene (0.5–2.0%), bicyclogermacrene ( 0.7–6.2%), spatulenol (0.8–19.9%). The hydrothermal coefficient (HTC) was calculated and a positive correlation between HTC and the content of essential oil in the raw material was shown. Conclusions. For the first time, the component composition of essential oils isolated from the inflorescences, leaves, and stems of Artemisia santolinofolia was studied; 60 compounds related to mono- and sesquiterpene compounds were identified. The dominant components of essential oils were identified. A study of the dynamics of accumulation showed that oils are contained in all organs of the plant, therefore the entire above-ground part of the plant is collected; the optimal period for collecting raw materials is the flowering phase. The content of essential oils depends more on the amount of precipitation than on the average monthly temperature.

Influence of weather conditions in Central Polissia, Ukraine, on the expression of quality indicators in potato cultivars of different maturity groups

For Ukrainians, potatoes are a key foodstuff and the most important strategic crop in the vegetable segment, and therefore it is vital to investigate the quality characteristics of potato tubers. The purpose of this study was to investigate the influence of various meteorological factors on the taste and starch content of tubers of different potato cultivars. The study employed laboratory, analytical, mathematical, and statistical methods. Both positive and negative correlation between starch content in tubers, taste, average monthly temperature, and precipitation were found in cultivars of different ripeness groups. For some potato cultivars, the positive effect on the starch content in tubers was due to the synergistic interaction of temperatures in August and precipitation in July, while for other cultivars this effect was determined by temperature and precipitation in August. It was found that an increase in temperature in August contributed to the improvement of the taste characteristics of early-ripening cultivars, while for middle early and mid-ripening genotypes, increased temperatures in June and August were key factors, and middle-late cultivars responded to increased precipitation in August. For each of the 19 cultivars studied, periods with a positive effect of average monthly temperature and precipitation on the improvement of taste were identified. The cluster analysis helped to identify potato cultivars with high starch content – Lietana, Opillia, Vzirets, and Oleksandryt, with high taste qualities – Lietana, Mezhyrichka 11, Vzirets, Avanhard, Partner, Oleksandryt, Fanatka, Rostavytsia, and Opillia. The findings of this study can serve as a scientific basis for the formulation of policies aimed at mitigating the effects of climate change and adapting existing cultivars to support sustainable potato production in a particular region and creating new plastic potato genotypes with sustainable quality characteristics

Analyzing energy consumption due to occupant interaction with manual and automatic window blinds in multiple climates

Proper daylight management through automated or manual blind systems can enhance user comfort and energy conservation. Furthermore, the influence of weather conditions, coupled with occupant behavior, significantly impacts energy consumption, rendering weather forecasts invaluable in conducting individual building energy simulations to identify energy-efficient strategies for the future. Also, I wonder if it is possible to move some items from room 308 until you can provide items from other resources. Future weather conditions and their impact on building performance can be evaluated using Representative Concentration Pathways (RCP) scenarios provided by the Intergovernmental Panel on Climate Change (IPCC). This research aimed to compare the energy usage of manual and automated window blinds with internal blinds in mid-size office buildings across four main climate zones (2B Hot-Dry; 2A Hot-Humid; 7 Very Cold; 4A Mixed-Humid) in the USA under current and future climate change scenarios (RCP 4.5, 8.5). Utilizing simulation as the methodology and comparing the energy use resulting from the RCP 4.5 and 8.5 scenarios revealed that the most significant decrease in heating energy usage was happening in the Hot-Humid zone with Automated blinds, which is a more efficient alternative than manual Blinds. In contrast, the Very Cold zone experienced almost no changes in either heating or cooling energy consumption. In Climate Zones 2B Hot-Dry and 7 Very Cold, rising temperatures lead to increased cooling energy requirements and reduced heating demands due to climate changes. Climate Zone 4A Mixed-Humid saw reduced energy consumption for cooling but increased usage for heating, particularly under RCP 8.5. In Zone 2A Hot-Humid, a high demand for heating energy was found.

Design of proactive management system for residential buildings by using smart equipment

This study's object is an energy efficiency of residential sector. The work is aimed at solving the task to improve the energy efficiency of the housing sector by devising technical solutions for monitoring and managing energy consumption and microclimate parameters of buildings. The proposed proactive management system for residential buildings consists of multi-sensors measuring CO2, temperature and humidity, smart meters of heat and electricity consumption, and smart plugs. The equipment is combined into single system through an integration controller with remote user access through an interactive web interface. A feature of the technical solution is the ability to collect, process, visualize, and archive data on the consumption of energy, as well as on the key parameters of the microclimate of residential premises. The advantages of the system are its flexibility due to the possibility of integrating additional devices during operation, as well as the use of standard communication protocols, which enables the interchangeability of component elements. The implementation and testing were carried out under the conditions of a real pilot site. The use of the system in practice confirmed the efficiency and stability of the operation, making it possible to obtain data on the parameters of energy consumption and microclimate and devising recommendations for reducing energy consumption at the pilot site. It was established that the microclimate meets the requirements of the standards (air temperature is about 22 °С while relative humidity does not exceed 60 %). Decrease in energy consumption can be achieved by reducing the temperature of the heat carrier in the absence of residents, as well as by considering the influence of weather conditions. During periods of residents activity, an excess of the permissible level of CO2 was recorded, therefore, automatic ventilation systems should be provided in the apartments

A deep hybrid network for significant wave height estimation

The influence of weather conditions on sea state, and in particular on the dynamic evolution of waves, is an important issue that affects several areas, including maritime traffic and the planning of coastal works. To collect relevant data, buoys are used to set up distributed sensor networks along coastal areas. However, unfavourable weather conditions can lead to downtime, which can be extended due to maintenance issues. The ability to improve the robustness of these sensor systems using predictive models, i.e. digital twins, to interpolate and extrapolate missing data is an important and growing area of research. To accomplish such a task, models must be found that can account for both the spatial and temporal dynamics of the input data to correctly estimate the variables of interest. In this work, a deep learning architecture is proposed to realize a digital twin for the monitoring buoy for significant wave height estimation using spatial and temporal information about the wind field in the area of interest. The proposed methodology was applied to a case study using wave height data from an Italian Sea Monitoring Network buoy installed near the coast of Sicily and wind field data from the Copernicus Climate Change Service ERA5 reanalysis. The reported results show that the use of a multi-block hybrid deep neural network consisting of convolutional layers for spatial feature extraction and short-term memory layers for modelling the involved dynamics, which takes into account the buoy surrounding area, outperforms other empirical, numerical, machine learning and deep learning methods used in the literature.