Influence Of Weather Conditions Research Articles

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.

Species-Specific Responses of Insectivorous Bats to Weather Conditions in Central Chile.

Insectivorous bats play a crucial role in agroecosystems by providing invaluable pest control services. With the escalating impacts of climate change, a comprehensive understanding of the environmental factors influencing bat activity becomes imperative for their conservation in agricultural landscapes. This study investigates the influence of weather conditions, specifically air temperature and relative humidity, on the timing activity and the relative abundance of five insectivorous bat species in central Chile. Data from automatic bat detectors and climatological stations are utilized for analysis. Our results unveil species-specific behaviors, with Tadarida brasiliensis exhibiting early emergence and extended activity periods compared to other bat species. Histiotus montanus and Lasiurus villosissimus display delayed onsets on more humid evenings, whereas Lasiurus varius and T. brasiliensis initiate activity earlier on colder nights compared to warmer ones. Relative humidity emerges as a key factor influencing relative abundance for all species, with more minutes with bat passes detected on drier nights. These findings suggest that global warming may influence observed bat behaviors, potentially altering foraging patterns and activity levels of these bat species. Moreover, as climate change continues, understanding the long-term impact on bat populations and their adaptive strategies is crucial for effective conservation measures. Further studies exploring these dynamics can provide valuable insights for shaping conservation efforts in the face of evolving environmental challenges.

Influence of Weather Conditions in the Northwestern Russian Federation on Flax Fiber Characters According to the Results of a 30-Year Study.

Weather has significant impact on plant growth and development. It is important to analyze the influence of changing climate conditions on the expression of plant agronomic characters. Two flax varieties were grown from 1987 to 2018 in the Northwest of Russia. Weather conditions and their influence on flax agronomic characters were analyzed using the variance and correlations analyses. Significant influence of conditions of a particular year on the manifestation of all evaluated characters was revealed. Starting from June, high temperatures accelerate plant development at all stages. Prolongation of the germination-flowering period is most important for improving fiber productivity, while fast ripening in hot weather after flowering is preferable for the formation of high-quality fiber. Such data give a possibility to predict the yield amount and quality. The use of weather conditions data also makes possible a comparison of the results obtained in different years. The suggested method of classifying meteorological conditions of a year can be used in other genebanks for systematizing and analyzing the results of crop evaluation in the field. The correlation analysis revealed 3 correlated pleiades, namely (1) of productivity, (2) of fiber quality and yield, and (3) of the growing season phase durations, the sums of active temperatures and precipitation during each period. The great influence of growing conditions on the economically valuable traits indicates the necessity of searching for genotypes with stable character manifestations for breeding new varieties with stable yields and good fiber quality.

Weed infestation of narrow-leaved lupine crops in grain-grass-rowed crop rotation in the North-West of Russia

The results of the long term (2012–2018) study of weed infestation of green fallow fields with narrow-leaved lupin in the crop rotation including cereals, grasses and row crops in the North-West region of Russia (Leningrad region) are presented. The assessment of weediness in the narrow-leaved lupine variety Oligarch crops was carried out annually at 24 permanent survey sites (0.1 square meter). Based on the results of the surveys, the formation of a diverse and constant species composition of weeds (from 15 to 25 species), mainly of medium and severe degree of weediness (141–593 specimens per square meter), with the proportion of young plants ranging from 90.4 to 99.7 %. The mass species of weeds were lamb’s quarters, field pansy, corn spurry, hemp-nettles, fumitory, shepherd’s purse, prevalent perennial weeds were field sowthistle, coltsfoot, red sorrel, couch grass, marsh woundwort. The prevailing influence of weather conditions and individual characteristics on the weed infestation of narrow-leaved lupine crop has been determined. The combined effect of two factors was expressed by 47.7, 57.8 and 47.1 % in terms of species abundance, initial abundance and final phytomass of weeds, respectively. Long term application of mineral fertilizers led to an increase in the number of annuals (by 1.5–1.6 times) and a decrease in the density of growth of perennial weed species (by 1.6–1.9 times). The influence of the integrated plant protection system used in the crop rotation was manifested in a significant decrease in the density of perennial weed species (by 4.6 times) in narrow-leaved lupine crop.

Open Dataset for Testing of Visual SLAM Algorithms under Different Weather Conditions

Existing datasets for testing SLAM algorithms in outdoor environments are not suitable for assessing the influence of weather conditions on localization accuracy. Obtaining a suitable dataset from the real world is difficult due to the long data collection period and the inability to exclude dynamic environmental factors. Artificially generated datasets make it possible to bypass the described limitations, but up to date, researchers have not identified testing SLAM algorithms under different weather conditions as a stand-alone task, despite the fact that it is one of the main aspects of the difference between outdoor and indoor environments. This work presents a new open dataset that consists of 36 sequences of robot movement in an urban environment or rough terrain, in the form of images from a stereo camera and the ground truth position of the robot, collected at a frequency of 30 Hz. Movement within one area occurs along a fixed route; the sequences are distinguished only by whether conditions, which can make it possible to correctly assess the influence of weather phenomena on the accuracy of localization.

Chemical Composition of Healthy and Raspberry Leaf Blotch Emaravirus-Infected Red Raspberry ‘Willamette’ Fruits

The aim of this study was to determine the changes in chemical composition of fresh red raspberry ‘Willamette’ fruits caused by the presence of raspberry leaf blotch emaravirus (RLBV). In three experimental orchards of ‘Willamette’ raspberry, fruits were harvested from RLBV-free and RLBV-infected plants in 2019 and 2020. Fruits were collected at appropriate maturity stages and further analyzed in terms of total phenolics, total anthocyanins, and selected individual phenolics. In all three experimental orchards, the phenolic profiles of the infected and uninfected fruit samples were considerably different during both studied years. Nonetheless, the intensity of the modifications varied greatly depending on the location and harvest year. Statistical analysis revealed that the influence of RLBV infection on the studied features was undeniable, although the influences of weather conditions and soil composition outweighed the influence of RLBV. Taking into consideration all the experimental and statistical data, it can be concluded that RLBV had an impact on the phenolic profile of raspberry ‘Willamette’ fruits, while sensitivity to environmental conditions and soil composition is emphasized.

Influence of weather conditions and elements of harvest structure on yield of spring triticale cultivated in organic agriculture on southern chernozem of northern Kazakhstan

The article presents the results of research on the influence of weather conditions and organic fertilizers on the elements of the crop structure and the productivity of spring triticale. The studies were carried out in the LLP " SPCGF named after A. Barayev" on southern carbonate chernozems in 2018-2021. Triticale was cultivated according to the falow. Dry above-ground mass of sweet clover, sainfoin, alfalfa, brome and wheatgrass was introduced into the fallow field as organic fertilizers. An annual decrease in the grain yield of spring triticale was noted over the years of research from 1.95 t/ha in 2018 to 1.01 t/ha in 2021. The weight of 1000 grains did not change significantly over the years of the study and ranged from 37.0-45.7 g. The number of triticale grains per unit area gradually decreased over the years of the study from a maximum in 2018 of 6951 pieces/m2 to a minimum in 2021 of 2739 pcs/m2. Variants of application of aboveground biomass of various perennial grasses as organic fertilizers had an equivalent effect on the yield of triticale and crop structure elements in comparison with the control (aboveground biomass of sweet clover). A positive correlation was obtained between the yield of triticale and HTC (according to Selyaninov) for the months of June and August, where the dependence on the variants of the experiment changed from medium to high (with June r=0.62 ... 0.94, with August r=0.64 ... 0.80). A moderate correlation was obtained between the grain yield and the HTC (according to Selyaninov) for the period June-August (r=0.59…0.78). The influence of the mass of 1000 grains on the yield was ambiguous, in some cases the relationship was weak (r=-0.21 ... -0.27) in others - medium (r=0.33 ... 0.36). A positive correlation was established between the grain yield and the number of grains per 1 m2 (r=0.61…0.94).

Influence of weather conditions on the dynamics of summer phytoplankton in the Kuibyshev reservoir

Based on observation data in the summer of 2019 and 2021, an assessment was made of changes in abiotic characteristics and chlorophyll (Chl) content in the Kuibyshev Reservoir. Regular observations were carried out at the outlet section of the reservoir (Zhigulevsky hydroelectric complex) under conditions of complete mixing of water masses. The main goal of the study is to assess the influence of abiotic factors on the chlorophyll content and the mass development of cyanobacteria. It has been established that the main influencing factors are thermal regime and weather conditions. 2019 is characterized as “cold”. The total number of days with water temperatures above 22 °C was only 11. The degree of favorability was low (23 °C ˃ t ˃ 22 °C). 2021 characterized as “warm”. The total number of days with water temperatures above 22 °C was 72. The degree of favorability varied widely: from low (23 °C ˃ t ˃ 22 °C) to extreme high (t ˃ 26 °C). The most favorable year for the mass development of cyanobacteria was 2021, when the Chl content over the summer period was 7.2 μg/dm3. The least favorable year was 2019, when the Chl content was 1.4 μg/dm3. Seasonally, the temperature optimum was observed annually in July. The Chl content in July 2021 was 12.6 μg/dm3, and in July 2019 – 1.8 μg/dm3. Significant variability in chlorophyll content is due to synoptic cyclicity and changing weather conditions. The established influence of thermal regime and weather conditions on the content of chlorophyll suggests that in conditions of global warming, the process of mass development of cyanobacteria is expected to intensify, which will negatively affect the ecological state and water quality of the Kuibyshev Reservoir.

The Influence of Weather Conditions on the Diurnal Variation in Range of Motion in Older Adults with Knee Osteoarthritis.

(1) Background: This study investigated the relationship between weather conditions, diurnal patterns, and total knee range of motion (ROM), as well as the severity of symptoms (pain and stiffness) in older adults with knee osteoarthritis. (2) Methods: An exploratory longitudinal study was conducted on 28 older adults with knee osteoarthritis (mean age 71.86 ± 4.49 years; 46.4% men, 53.6% women). We used as assessment tools the Visual Analog Scales (VAS) for self-reported local knee pain and stiffness, and goniometry for ROM. Measurements were taken twice, six months apart, in winter and summer, in the morning and evening of each selected day. Recorded weather factors comprised temperature, relative humidity, barometric pressure, and maximum wind speed. (3) Results: The study revealed significant effects of season and time of day on pain and stiffness, respectively (p < 0.001). Additionally, a significant interaction between season and time influenced total knee ROM (p < 0.001). Moreover, there was a statistically significant relationship between time and total knee ROM (p < 0.001). (4) Conclusions: This research underscores the complex link between seasonal fluctuations and daily variations in some symptomatic and functional aspects of knee osteoarthritis in older adults.

Agrobiological and phenological characteristics of Dagestan aboriginal grape varieties in the conditions of the Krasnodar region

Native varieties have a number of positive characteristics that are widely used in the breeding process. Among them are varieties of very early ripening (Yay izyum white and Yay izyum pink), medium ripening (Ag izyum, Khatmi), late ripening (Agadai, Koz izyum), etc. The purpose of the research is to study the influence of weather conditions on agrobiological indicators and the onset of phenological phases of the grape plant. The experiment included 14 Dagestan native grape varieties of different ripening periods and directions for using the crop in the conditions of the Anapa zonal experimental station of viticulture and winemaking. The research has established: one variety of very early ripening (Ag emchek); 5 early ripening varieties (Khotsa tsibil, Budai Shuli, Chaush novyy, Khatmi); 7 early-medium varieties (Ag chakrak, Ag raisin, Gimra, Dagestan, Dzhagar, Dokur, Dubut) and 1 late-ripening variety (Chil Gulyabi). Agrobiological indicators and indicators of crop quality were also determined. The number of inflorescences per one developed shoot (K1 - fruiting coefficient) is the lowest in the Budai Shuli variety - 0.55, and the highest in the Gimra variety - 1.74. For other varieties it ranges from 0.61 to 1.56. According to the fruiting coefficient (K2), the varieties Gimra and Khotsa tsibil are also distinguished (1.90 and 1.71, respectively). For other varieties of oats, this indicator ranges from 1.23-1.68.

Model of the influence of weather conditions on car traffic (using the example of weather conditions in Siberia)

The purpose of the study is to build a model of the influence of weather and climatic factors on the throughput of various types of roads and intersections. Weather conditions affect the acceleration, braking and stability of a vehicle on the road. The results show that the weather affects traffic intersections of streets, which need to be optimized depending on the current road and transport situation. As a result, a model of the influence of rain, snow and ice on road situations was simulated and built.

METHOD OF CONDUCTING TESTS FOR VERIFYING THE MAIN FUNCTIONS OF COMBAT MEANS OF THE PORTABLE AIRCRAFT MISSILE COMPLEX USING STANDARD EQUIPMENT

In recent years, researchers have been actively working on the development of bench testing methods for anti- aircraft systems, in particular, using the latest technologies, materials, design, and operating principles. One of the most recent studies on this topic is devoted to the use of information technology to solve the problems of testing anti- aircraft missile systems. The authors argue that the use of virtual models and bench tests can reduce development costs and provide a more accurate assessment of the performance parameters of air defence missile systems.&#x0D; Other studies focus on analysing the impact of various factors on the operation of anti-aircraft missile systems, including the influence of weather conditions, magnetic field and other factors. Studies on this topic have shown that consideration of such factors is important for planning and conducting bench tests.&#x0D; Studies have also been conducted on safety and reliability issues during bench tests of anti-aircraft missile systems. Particular attention was paid to the detection and elimination of malfunctions, as well as ensuring safety during testing.&#x0D; In general, recent research and publications show that the development of bench testing methods for air defence missile systems is a relevant and promising topic that contributes to improving the reliability and efficiency of their operation.&#x0D; In order to increase the efficiency, reliability and reduce the cost of research and development work on the development of MANPADS, the article proposes a method for testing the main functions, including the function of missile guidance and launch, as well as the functions of power and control systems. The bench test method is an effective tool for testing the functions of a complex in conditions that are as close as possible to the actual conditions of its operation. However, it is necessary to investigate the effectiveness of this method for testing the functions of a man-portable anti-aircraft missile system and identify possible shortcomings and limitations that may affect the accuracy of test results and the reliability of the system as a whole.

Computer vision systems and deep learning for the recognition of athlete's movement: A review article

The process of detecting people in videos and then tracking their movement is one of the very important topics. The process of tracking people and studying their behaviour could result in a large set of information that can help researchers in studying reactions. The techniques of detection and tracking the movement of people are used in the sports field, where the athlete's movement is studied and analyzed within the game. Based on the information obtained from the process of tracking the athlete's movement, it is possible to improve the playing performance as well as avoid injuries and choose the best playing strategy. In some games, the accuracy of athlete's performance is a measure of the points given to the athlete's like gymnastics. This study reviews a set of articles that relied on computer vision as well as deep learning in the process of distinguishing and analysing the athlete's movement. The articles are confined to the years from 2015 to 2022, dealing with different indoor and outdoor sports. Certainly, the study of indoor games is better because the influence of weather conditions is less than that of outdoor ones. Reviewing the articles demonstrates that relying on computer vision systems is more effective than relying on human rulers, as humans are more prone to error. As for relying on the deep learning techniques for detecting the object, the results are very positive, due to the correct detection of the object. The results of the analysis of this object will be more accurate.

Influence of weather conditions on the productive potential of pasture ecosystems in the south of Russia (Based on artificially created models)

For the rational use of degraded pastures and the fight against desertification, it is necessary to apply phytomelioration of territories more widely. The most effective will be the use of communities consisting of shrubs, semi-shrubs and perennial grasses. To identify on this further, the study was conducted at the experimental sites of the Agroecology Research Center of the Russian Academy of Sciences in the period from 2019 to 2022. In this study, artificially created models of long-term pasture ecosystems were utilized. In the arid conditions of the south of Russia, weather conditions had the greatest impact on the productivity of the created pasture models (share of influence is 81-85%), while the yield of dry fodder mass of the herbaceous-semi-shrub layer varied from 1.2 to 3.9 t/ha, depending on the seasonality of the pasture and the composition of the soil substrate. The highest yield of phytomass is formed on pastures created on a chernozem-like sandy loam substrate (humus horizon of chernozem-like sandy loam soil) on spring-summer pastures, the yield increase is 33% higher compared to spring-summer pastures on a light chestnut sandy substrate (a product of Aeolian processing of light chestnut soil). On all types of pastures, groups of cereals were leading in terms of biomass. Analysis of the multiple regression equation between the phytomass yield of model pastures (y3), temperature (x1) and precipitation of the warm period (x2) on pastures with a chernozem–like soil substrate showed that the multiple correlation coefficient R = 0.96 - this states a close relationship between the effective indicator and two factors. The multiple determination coefficient R2 = 0.98 means that 98% of the variation in the phytomass yield level is taken into account by the regression equation and 2% is accounted for by unaccounted factors on a light chestnut sandy substrate. The moderate correlation dependence of the yield of the fodder mass of model pastures (y3) on a plot with a light chestnut sandy substrate on the temperature in the warm period (x1), the component (r=0.52) indicates a significant effect on the yield of precipitation of the warm period (x2) with r=0.94.

Preservation of the quality of flax by using a self-propelled baler wrapper

The article analyzes the influence of weather conditions on the quality of the obtained flax. The relevance of the use of a baler-wrapper in the cultivation of long-flax to obtain a long fiber of high quality is proved. The reasons for not carrying out the wrapping operation in flax-growing farms in Russia are named. A brief overview of the currently produced self-propelled wrapper pickers is given and a small excursion into the history of the beginning of their production is given. The necessity of developing a domestic self-propelled wrapper as more high-performance in contrast to trailed and mounted units is substantiated. The design and technological scheme of the projected self-propelled baler-wrapper for flax ribbons is given.

Golf and Science

Golf is often seen as a leisurely sport and is considered to be the most popular outdoor sport. Most importantly, Golf is a remarkable fusion of art and science. This research explores the profound scientific understandings that govern the dynamics of golf, from the physics of ball flight to the biomechanics of the swing. It delves into the intricacies of golf equipment design, the influence of weather conditions, and the impact of golf on physical and mental well-being. Through a comprehensive analysis of existing literature and empirical studies, this research signifies the fusion of golf and science, offering a holistic understanding of this age-old game's modern facets. The paper concludes by shedding light on the potential of golf as a platform for understanding the dynamics behind the sport and its contributions to the wider domain of sports science.

Influence of varietal characteristics of winter wheat and weather conditions on lodging resistance and productivity

Growing technologies and variety selection are crucial for increasing yields and improving the quality of winter wheat grain. The area under winter wheat is the largest in Ukraine, which is associated with the production of high-quality grain. The aim of the study was to determine the influence of weather conditions and variety characteristics on winter wheat plant height, internode length, lodging resistance, productivity factor and yield during the years under study. In the course of the study, the following generally accepted methods were used: systematic approach, system analysis approach, analytical synthesis approach, field approach and statistical approach. The article presents data on the results of research with 20 varieties of soft winter wheat in the conditions of the Training and Practical Centre of Mykolaiv National Agrarian University from 2017 to 2023. Agricultural technology for growing winter wheat varieties is widespread in the steppes of southern Ukraine. The influence of weather conditions and varietal characteristics on lodging resistance and productivity of winter wheat was investigated. The results showed that the optimum plant height of winter wheat varieties ranged from 82.1 to 84.5 cm, and the highest yield was 6.32 t/ha in Staleva and 6.68 t/ha in Duma Odeska. A significant effect of varietal traits on stem length, second and last internode, number of stems formed per 1 m2 , grain weight in the ear and lodging resistance of winter bread wheat was established. Plants of the tested winter soft wheat varieties Staleva, Dyvo, Katarina, Felix, Ozerna, PONTICUS, Faust, Glaucus have a very high (9.0 points) resistance to lodging regardless of the weather conditions of the year. Ukrainian varieties Duma Odeska (6.68 t/ha) and Staleva (6.32 t/ha) achieved higher productivity. The obtained scientific results of the research contribute to the widespread use of the studied winter wheat varieties of this reasonably climatic zone and contribute to further improvement of grain production

Influence of weather conditions on yield and protein content in winter wheat grain

The results of three-year studies (2020–2022) conducted in the forest-steppe zone of the Samara region in the agrocenosis of winter wheat are presented. The purpose of the work was to study the influence of natural and climatic conditions of the research area on the formation of yield indicators, protein content in winter wheat grain. The material was 10 varieties from the Vavilov All-Russian Institute of Plant Genetic Resources (VIR) collection and 5 varieties of selection of the Povolzhsky Scientific Research Institute of Selection and Seed Growing named after P.N. Konstantinov. Yield, grain protein content and protein yield per hectare were determined. Varieties characterized by high yield and high amount of protein in grain, showing maximum protein yield in different weather conditions of the years were identified. Over the years of research, the year 2022 was the most favorable for the formation of high yields (between 6 and 8.5 t/ha were harvested in the indicated year), where a large amount of precipitation was observed in May – the first ten-day period of June. The protein content in grain was the highest in 2021 (14–19%), when high temperatures were observed during the grain filling period in the absence of precipitation. For each variety, the correlation dependence of the sum of active temperatures and the amount of precipitation during the spring-summer vegetation period with the studied indicators was established. There was a negative correlation between the sum of active temperatures and yield (from –0.553 to –0.981) and a positive correlation with the protein content indicator (from 0.605 to 0.984) depending on the variety. The amount of precipitation was in a positive correlation with the yield index, the dependence on the protein content in the grain was ambiguous and depended on the variety. The studied indicators were influenced not only by natural and climatic conditions, but also by the genotypic features of the studied varieties, which explains the diverse correlation dependence.