Changing Weather Conditions Research Articles

IoT Based Weather Application

The purpose of this weather application using IOT is to provide real-time weather updates to users, based on data collected from various IoT devices installed in different locations. The application collects data from these devices, processes it, and presents it in a user-friendly format, allowing users to access accurate and reliable weather information. The application uses sensors such as temperature, humidity, air pressure, wind speed, and direction, to collect data from different locations. The data is transmitted to a central server, where it is processed and analyzed using various algorithms to determine the weather conditions. The processed data is then displayed in an intuitive graphical format, providing users with a clear understanding of the weather situation. The application also uses machine learning algorithms to predict weather patterns, based on historical data, allowing users to plan their activities accordingly. Users can also set up custom alerts to receive notifications when the weather conditions change, ensuring that they are always informed and prepared. One of the key benefits of this weather application is its accuracy and reliability, as it relies on real-time data collected from IoT devices, rather than relying solely on weather forecasts. This provides users with up-to-date information, allowing them to make informed decisions about their daily activities. In conclusion, this weather application using IoT provides users with real-time weather updates, accurate predictions, and customizable alerts, making it an essential tool for anyone looking to stay informed about the weather. Its intuitive user interface and reliable data collection ensure that users can plan their activities with confidence.

Algae's Promise to Sequester Carbon Sheds New Insight on Changing Climate

The addition of more greenhouse gases (GHG) to the earth’s atmosphere, which accounts for more than half of the planet’s warming potential, has resulted in changes in long-term average weather conditions, or climate change. In order to counter the increased concentration of carbon dioxide in the atmosphere, carbon sequestration is a newly developed strategy. Contrary to carbon emission reduction measures, carbon sequestration has a strong potential to lower carbon dioxide levels or mask carbon dioxide emission if the gas is trapped from several stationary sources and used effectively to produce chemical and energy. The implementation of carbon regulations has spread widely. The cost of air pollution is credited with a monetary value. Due to this, investments in the growth of microalgae for carbon sequestration have received attention from all around the world. With these systems, existing carbon mitigation strategies are shown to be a viable and promising alternative. In general, the microorganism groups that make up microalgae are extremely diverse and quick-growing, and they are very skilled in photoautotrophic, heterotrophic, and mixotrophic settings. With a unit carbon dioxide fixation capacity 10–50 times greater than terrestrial plants, these microalgae can be grown on non-fertile land. Describe in detail the most recent advancement in the effective use of microalgae for carbon dioxide in this article review.

Forecasting Biogas Formation in Landfills

Abstract The aim of the present research was to develop a mathematical model for estimating the amount of viscous gas generated as a function of weather conditions. Due to the lack of models for predicting gas formation caused by sudden changes in weather conditions in the literature, such a model was developed in this study using the parameters of landfills recorded for over a year. The effect of temperature on landfill gas production has proved to be of particular interest. We constructed an algorithm for calculating the amount of the produced gas. The model developed in this study could improve the power control of the landfill power plant.

Adaptive dynamic building envelope integrated with phase change material to enhance the heat storage and release efficiency: A state-of-the-art review

the research of PCMs in the field of building energy efficiency has developed rapidly over the past decade. The static PCM-built envelopes cannot flexibly adjust their heat storage and release according to the changes in weather conditions and occupants’ demands, resulting in low heat storage and release efficiency. The application of the adaptive dynamic building envelope integrated with PCM (ADBEIPCM) addresses this problem. This paper systematically reviewed the ADBEIPCMs for the first time, including their system configuration, working principles, control strategies, and system performance. The research methods and the PCM properties were also well summarized. The results show that the ADBEIPCM can store solar energy and release heat in time to reduce building load and improve comfort mainly by rotating, moving, flipping, and controlling the state of vents. This review divided the ADBEIPCMs into two categories: opaque envelopes and transparent envelopes. The experiment studies and simulation studies accounted for 15.28% and 84.62% of the research on opaque envelopes, and each accounted for 50% of the research on transparent envelopes. But onsite monitoring studies on transparent envelopes only accounted for 25%. In the design of ADBEIPCM, the main encapsulation method of PCM was macro-encapsulation, and the type of PCM was mainly organic. This review analyzed the shortcomings of existing studies and gave recommendations for engineers, architects, and scholars. Future research should focus on the development of novel PCMs with high strength and stability, the development of artificial intelligence-based short-term control strategies, and the development of ADBEIPCM based on bionic technology and powered by renewable energies.

A review of climatic impacts on water main deterioration

Watermains are both directly and indirectly affected by climatic conditions such as temperature and precipitation. Research has been conducted to understand and model the effects of climatic conditions on watermain breaks. However, review studies to map the knowledge development in this area, to identify key achievements and limitations of previous studies are missing, and are addressed in this study. This review uses a mixed systematic and scientometric analysis to establish the research trends, contributions, methods, and covariates employed by previous studies related to climatic impacts on watermain deterioration. Web of Science and Scopus database is primarily employed to identify 70 relevant studies on the subject matter. These studies have been mostly conducted by institutions based in Canada, USA, and Europe. There is a general lack of collaboration among different institutions conducting research in this area. Studies in the subject matter are published from 1982 onwards, however, significant number of studies per year can only be noticed from 2005 onwards. Previous studies have been mostly focused on the modelling of watermain failure and have used statistical methods, and data-driven and artificial intelligence (AI) approaches for failure modelling of watermains under climatic conditions. For testing and validation of research data, studies have employed correlation analysis, performance evaluation metrics, and descriptive statistics. Typically, climate-related variables used in studies include temperature, moisture, and precipitation. Reviewed studies have considered cold (66%), hot (31%), and dry (13%) climatic conditions. Studies have investigated watermains made of metal (56%), plastics (43%), and Concrete and Asbestos cement (31%). Future studies are recommended to consider Data-driven and AI approaches in research design; pay attention to watermains in climatically vulnerable and massively populated regions; and consider climate risk assessment and the impact of climate change and extreme weather conditions on watermains.

기후변화가 해안 관광목적지에 미치는 영향 분석 : 해수욕장의 활동선호일수 및 침수지역 변화를 중심으로

Coastal tourist destinations are highly vulnerable to climate change and its effects are seen in various parts of world. This study examines possible future changes in the costal tourist destinations of South Korea, focusing on changes in preferred weather conditions for beach activities and the expansion of flooding beaches due to sea level rise. The results show that days available for beach activities will be increased, but weather comfort for activity will be decreased. When it comes to the effects of sea level rise, beaches at the South Sea have high flooding potential, while beaches at the East Sea have low flooding probability. These findings suggest the need for location-specific adaption strategies to minimize climate change impacts.

Assessment of Rice Yield Sensitivity to Changing Weather Conditions in Prayagraj Using DSSAT V4.7.5 Crop Simulation Model

The Field experiments were conducted during 2012-19 to determine the effect of changing weather such as (Tmax, Tmin, Tavg, Solar radiation and CO2 concentration) on grain yield, LAI, Anthesis days and maturity days of four rice cultivars i.e (Swarna sub 1, Sarjoo 52, Pant Dhan 4 and NDR 359) at the college of forestry farm , SHUATS Prayagraj. The DSSAT-CERES rice model was calibrated and validated, for the cultivars under Prayagraj conditions and it was observed that the values i.e Percent error, RMSE, nRMSE and Pearson correlation coefficient (r) were good in agreement and within permissible limit. Among all the four varieties NDR 359 yields more followed by pant dhan 4, Swarna sub 1 and sarjoo-52. The result revealed that by increasing temperature (Tmax, Tmin, Tavg) for all the variety and phenophases the yield got reduced but under increased condition of Solar radiation and CO2 concentration the yield got increased. In case of LAI same result was observed but during the phenophase of flowering to maturity stage of the crop there was no effect found. During the interaction between changing weather with anthesis days and maturity days it was found that the anthesis days and maturity days got increased with increased in Tmax and Tavg. Other weather parameter has no effect on it. The interaction of weather parameter with the yield, LAI, anthesis days and aturity days were found significant at 5% or 1% level for all the four varieties and henophases. The research outcome indicates that, the future farming will be challengeable due to climate change, we must prepare with suitable varieties and crop management plan to tackle the situation.

Integration of Climate Smart Agro-Technologies and Efficient Post- Harvest Operations in Changing Weather Conditions in Nigeria

The purpose of this study was to examine the integration of climate-smart agro-technologies and efficient post-harvest operations in changing weather conditions in Nigeria. Agriculture, which is the mainstay of most rural families in Nigeria, has faced several problems in recent times as a result of variety of factors such as post-harvest losses, climate change fluctuations, and high poverty level resulting in poor agricultural outputs and low income. Empirical studies have indicated that food production and income growth of farming households would be worse-off, if climate change is not properly mitigated. The combination of climate-smart agro-technologies and effective post-harvest management operations in this era of unfavorable climatic condition and post-harvest losses has become imperative. Climate smart agriculture consists of a three-win approach; for long-term food supply and security. It also comprises of three important goals such as mitigation, adaptation, and increased production. Agro-climate smart technologies includes solar energy techniques for drying agricultural product, green house technology for cultivation, climate resilient storage structures for storing harvested grains, and climate smart waste usage for agricultural waste management. Efficient post-harvest management operations such as proper harvesting, sun-drying, threshing, processing, packaging, and transportations were also explored. This study advocated the adoption of climate smart agro- technologies and efficient post-harvest management operations as an alternative measures for increased food production and farm income in the face of changing weather and climatic conditions. How to Cite: Anosike F. C., Obasi I. O., Nwachukwu E. U., Obi J. N., Orji J. E., Inyang P., Chinaka I. C., Osang E. A., Iroegbu C. S., Nzeakor F. C., Onu S. E., 2023. "Integration of Climate Smart Agro-Technologies and Efficient Post- Harvest Operations in Changing Weather Conditions in Nigeria." Journal of Agriculture and Crops, vol. 9, pp. 281-292.

Pre-rut behavioural changes in farmed red deer with reference to atmospheric conditions

Red deer (Cervus elaphus) exhibit specific behaviour during the rutting season, which may have an impact on the safety on cervid farms, both due to aggressive interactions between animals and the safety of people staying there, such as staff and tourists. This issue applies especially to stags whose behaviour changes radically, and the correct interpretation of the observed changes is very important. Therefore, the aim of the study was to analyse the pre-rut behaviour of stags and to show the influence of atmospheric conditions on vocalization and other elements of their behaviour, which facilitate determination of the onset of the rutting season. The observations were conducted in August and September of 2017 and 2018. It was shown that lower temperatures, declines in air humidity, increasing atmospheric pressure, and transition of the moon phase towards the full moon resulted in intensification of the vocalization activity in the red deer in the pre-rutting season, which may accelerate the rutting period in the deer males. The number of vocalizations varied between the years and depended on the mean temperature, air humidity, atmospheric pressure, and moon phase in the prerutting and rutting seasons. Through observation of the changing weather conditions, it is possible to predict the time of increased activity of stags and the onset of the rutting period. Predicting the date of mating season in farm breeding, based on daily observations of changes in the behaviour of stags, can be helpful in planning veterinary treatments or selecting the composition of the hinds to be covered by specific stags, which can also contribute to the improvement of their welfare.

Harmful entomofauna in forestry and green infrastructure

The national invention of the forests of the Republic of Srpska established over 100 species, with the entire volume of wood mass being dominated by deciduous trees (beech 45%, oak 8%, other deciduous trees 7%, tribal deciduous trees 3%). Beech has the largest share in state forests in the supplies (43%), followed by fir about 20%, and spruce by 16%. Of the harmful endomofauna of fir, one third are gradeogenic species, which can cause great economic and environmental damage. Harmful endomofauna of beech number 32 species, of which economically significant primary species are prone to mass occurrences and trophical relations related to the leaf (15.75% of species). Harmful endomofauna of oak species represent 40 most common species. Outbreaking primary species make up one quarter, feed predominantly on leaves and cause defoliation (50%). Harmful for seeds or acorns are 15% of pests, which can have a detrimental effect on the reproduction and regeneration of oak forests. The most common pests in spruce forests are species that occur frequently and can only occasionally cause minor damage (56.25%). The most economically important are bark beetles and wood borers, which tend to outbreak (12.5%) and cause dammage on a hudge area. Outbreaking species are also pest of seed and cones, which participate in the spruce pest complex with 14.58%. Pests in nurseries are important for reproduction in forestry and for providing nursery stock for the establishment of green infrastructure. Of the 54 harmful species, almost a quarter are non-native species (24.07%). Often, non-native pests are transferred from nurseries to public green spaces, green corridors, and entrepreneurs are ofteen serving as a pathway for introduction of non-native harmful species into forest ecosystems. Therefore, ornamental plants are rightly considered the most important pathways for introduction of invasive alien species in mannaged and protective forests. Non-native and invasive species that are introduced in the Republic of Srpska e.g. emerging pests are folowing: Aproceros leucopoda, Cameraria ohridella, Corythucha arcuata, Corythucha ciliata, Cydalima perspectalis, Eopineus strobi, Gillettella cooleyi, Leptoglossus occidentalis, Metcalfa pruinosa, Obolodiplosis robiniae, Phyllonorycter platani, Pseudaulacaspis pentagona, Stictocephala bisonia etc. Most of these species are pests in nurseries and ongreen infrastructure. Some native insect species appear as emerging pests due to their increase of population , as an answer to changing weather conditions. One example is the ash wasp Tomostethus nigritus (F.) (Hymenoptera: Tenthredinidae), which in the last ten years appear in local outbreaks in tree lines or other green areas at the territory of Southeastern Europe from the Balkan Peninsula to the Nordic countries. Increased populations of Zeuzera pyrina (Lepidoptera: Cossidae) were also applied in nurseries and on elements of green infrastructure. Due to the climate change, the species Ovalisia (Palmar) festiva migrated from the Mediterranean area, setting a dangerous pest in nurseries, while the linden bug Oxycarenus lavaterae is common on lindens, building large colonies but so far with no significant damage on trees. In order to prevent introduction and stop the spread of alien invasive species, there is need to ensure the maintenance of a high level of health protection status in agriculture, green infrastrucrure and forestry.

The Effect of Local Weather Conditions on American Kestrel (Falco sparverius) Reproduction

ABSTRACT American Kestrel (Falco sparverius) populations have been declining in North America during recent decades and potential causes, including climate change, currently are under investigation. Many studies of migratory birds have demonstrated the effects of climate change, including changes in local weather conditions and the increase in extreme weather, but the relationship between local weather and kestrel ecology in the northeastern United States has received little attention. We examined the relationship of local weather conditions and kestrel breeding performance in northwestern New Jersey between 1996 and 2016. We also obtained temperature, rainfall, and snowfall data from weather stations within or adjacent to our study area. We did not detect significant changes in climate over the study period, but we did find significant associations between local weather conditions and kestrel breeding performance. Warmer temperatures during the breeding season were significantly correlated with earlier nesting, and early nesting had significant positive correlations with clutch size, hatching rate, nestling survival, and nesting success (raising at least one young to fledging). We did not detect a significant relationship between rainfall and nesting variables, but snowfall during autumn was strongly related to kestrel breeding performance the following year. Compared to years when there was no snowfall in our study area the preceding autumn, kestrels breeding in years following autumn snow had significantly smaller clutches, lower hatching rates, lower nestling survival rate, and lower nesting success. Kestrels in our region are partial migrants; first-year birds generally migrate to southern wintering grounds while older birds may remain in the region, presumably in response to local conditions. We suggest that substantial snow during autumn may drive a larger percentage of adults to migrate south, as indicated by the greater number of kestrels counted at representative autumn hawk watch sites during years with substantial autumn snow. Our study concludes that variations in local weather conditions throughout the year can affect the breeding performance of American Kestrels, whether or not they are associated with climate change.

Optimized hill climbing algorithm for an islanded solar photovoltaic system

Conventional energy generation technologies face unreliability due to the depletion of fossil fuels, soaring energy prices, greenhouse gas emissions, and continuously increasing energy demand. As a result, researchers are searching for reliable, cheap, and environmentally friendly renewable energy technologies. Solar photovoltaic (PV) technology, which directly converts sunlight into electricity, is the most attractive sustainable energy source due to the sun's ubiquitous presence. However, the non-linear behaviour of solar PV demands maximum power point tracking (MPPT) to ensure optimal power production. Although Hill Climbing (HC) is a simple, cheap, and efficient MPPT algorithm, it has a drawback of steady-state oscillations around MPP under uniform weather conditions. To overcome this weakness, we propose some modifications in the tracking structure of the HC algorithm. The proposed optimized HC (OHC) algorithm achieves zero steady-state oscillations without compromising the strength of the conventional HC algorithm. We applied both algorithms to an off-grid PV system under constant and changing weather conditions, and the results demonstrate the superiority of the proposed OHC algorithm over the conventional HC algorithm.

Research on the Improvement of Safety Navigation Based on the Shipmaster’s Control of Ship Navigational Parameters When Sailing in Different Sea State Conditions

Shipmasters must make several quick decisions with respect to the ship’s speed and heading when new sea conditions approach. The implications for ship stability and risky situations are known but there are no guides on how they should be addressed in this limited period of time. In the present paper, and from three points of view, the ship’s rolling motion in the long-term domain is analysed. Firstly, the ship’s behaviour after the influence of a single and external force was studied. Secondly, the influence of successive regular beam seas, with resistance and at zero-speed conditions, was analysed. Finally, the influence of wave direction on a ship sailing at non-zero speed was investigated. Results showed that once five minutes elapse, the rolling angle tends to be null regardless of the ship’s loading condition and that after a certain period of time, a coupling of the ship’s rolling frequency with the waves’ period and angle amplitude occurs. This circumstance was noted after three minutes for all of the ship loading conditions. Finally, novel guides for shipmasters in the form of 3D maps and polar diagrams were proposed to improve the ship’s behaviour-altering navigational parameters (heading and ship’s speed) when sailing in changing weather conditions. Therefore, for the three approaches, the relevant results and novel mathematical relations of linear factors were obtained which can be considered useful and applicable by the ship operators of most fishing and merchant fleets (regardless of their sizes) when they are operating under normal loading conditions.

Association of the Meteorological Parameters and Epileptic Seizures

Climate changes may be among the triggering factors in predicting epileptic seizures. In this study, we aimed to investigate the effects of changes in weather conditions and phases of the moon on epileptic seizures in epilepsy patients.

Relating storm-snow avalanche instabilities to data collected from the Differential Emissivity Imaging Disdrometer (DEID)

Storm-snow avalanches are challenging to forecast due to complex alpine terrain and during rapidly changing weather conditions. They can result in loss of lives and significant economic impact. We describe how a new device that continuously measures with high-frequency snowflake mass, size, density, and type, the Differential Emissivity Imaging Disdrometer (DEID), and show how the DEID can be used to aid avalanche forecasting when coupled with a storm-snow stability model. DEID measurements of snow accumulation, snow water equivalent (SWE), and snow density obtained during seventeen storms taken at the mid-Collins Snow-Study Plot at Alta Ski Area in Utah's Central Wasatch mountain range during winter 2020–2021 show excellent agreement with infrequent manual measurements. Additionally, two new variables, the Shape Density Index (SDI) and Complexity, are proposed and used to classify snowflake habit and estimate storm-snow shear strength. We illustrate how these DEID-derived data can be used to identify layers of concern in the storm snow such as density inversions, in real-time without digging snow pits. Furthermore, the DEID-data are used to run four variations of the SNOw Slope Stability model (SNOSS) for the storms investigated. The results are evaluated with data collected from tilt-board tests, infrasound measurements, and visual observations of avalanches. For a total fourteen storms analyzed, the DEID-driven SNOSS-modeled minimum stability index predicts the general stability of the storm-snow as indicated by observed avalanches, both natural and of unknown cause. The results provide a promising approach for nowcasting instabilities within storm-snow layers with a single instrument.

Online ship speed optimization based on BiLSTM encoder-decoder

Ship speed optimization can reduce fuel consumption and protect the environment. The existing offline speed optimization model cannot ensure the optimal ship speed due to the changing weather and sea condition during the voyage. We propose an online speed optimization model which consists of an offline speed optimization model and a fuel consumption prediction model. The online speed optimization model is to plan the average speed for each segment of the entire voyage. The fuel consumption prediction model is used to continuously monitor the fuel consumption during the voyage. For fuel consumption prediction, we propose a bidirectional long short-term memory (BiLSTM) based encoder-decoder with temporal attention mechanism. By the comparative experiments with three baseline models, the accuracy of the proposed prediction model is verified.

High regrowth of potato crop wild relative genotypes after cryogenic storage

Potatoes are consumed by millions of people and are the survival food in several countries. Cultivated varieties of potato (Solanum tubersosum L.) are results of selection and crossing of many wild species. Only 8–13% of wild potato species used for food are preserved by either in situ or ex situ methods. The U.S. National Potato Germplasm Collection maintains over 5900 accessions, of which 75% are crop wild relatives (CWR). The objective of the study was to investigate regrowth of cryogenically stored clonal propagules (shoot tips) of selected CWR accessions maintained in the collection. Sixty-nine accessions from 30 Solanum species and six accessions that are not yet assigned to a species were cryopreserved by a droplet vitrification method at the NLGRP. The post cryopreservation regrowth varied from 40 to 100% (average 68%) but was not significantly different between the tested accessions. Regrowth of six accessions tested after 10 years of cryogenic storage was between 35 and 90% (average 66%) and was significantly different from their initial regrowth (average 87%); the largest viability loss was in S. condolleanum; but for the other five accessions the regrowth was between 45 and 90% (average 72%) and suggested at least 10 years of successful storage in LN was possible. Twelve potato wild species cryopreserved in this study were reported in literature as important for developing cultivated varieties for changed weather conditions.

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

A new Maximum Power Point Tracking (MPPT) method, consisting in combining the Incremental Conductance (INC) algorithm with the Hysteresis control, was developed and applied to a standalone photovoltaic (PV) system to generate the maximum power of the PV array. The INC allows one to search for the Maximum Power Point (MPP). The hysteresis improves the accuracy of tracking the MPP very fast even after severe changes in weather conditions and has no oscillations around the MPP. The five-level S-Packed U Cells (SPUC5) inverter is used to transform the produced DC voltage to AC voltage; it generates five-level output voltage with a small number of switches and only DC source voltage. The capacitors of the SPUC5 are controlled by the Pulse Width Modulation (PWM) in order to balance their voltages. The proposed PV system was established and trained in the MATLAB/Simulink environment under various irradiation conditions. A comparison between different MPPT methods, INC-PWM and INC-PI, was investigated in order to examine the effectiveness of the developed MPPT technique in particular, and of all the PV system components. The results of the simulation validate the effectiveness of the suggested MPPT algorithm as well as the used SPUC5 inverter.

Climate Change in Jennifer Mills Dyschronia: An Eco-Social Critical Study

In the recent decades, the influence of the oblivious human actions has resulted in an environmental devastation and critical problems affecting both nature and human being existence. Climate changes entail a change in temperature and weather conditions, and these changes can lead to serious crisis such severe fires, droughts, rising sea levels, water scarcity, melting polar ice, floods, catastrophic storms, and declining biodiversity. The current paper tries to highlight the impact of capitalism and its practices upon the environment and how the economy plays an important role in depleting resource and destroying the whole environment. The study investigates Jennifer Mills Dyschronia to highlight the effect of climate change upon human lives through adapting ecosocialism theory. The study comes up that capitalist ideology, which seeks to achieve the ultimate gains, results in depleting the resources of the nations and thus creating deserted environments. The depletion of resources leads to displacing people from their environment.

Pathogenic complex and recovery of cereal agrocenoses in the Steppe of Ukraine

Topicality. Changes in weather and climatic conditions affect the formation of pathogenic complexes of grain agrocenoses and the species composition of pathogens, which are typical for the Steppe zone of Ukraine. At the same time, changes in cultivation technologies accompanying the transition to new forms of management also play a significant role in the formation of pathogenic complexes. It is necessary to find out the features of the pathogenic mycoflora formation and plant immunity in order to scientifically substantiate measures to stabilize the phytosanitary state of agro-cenoses at the current stage of grain production. Purpose. To divide into appropriate groups of grain crop diseases in the Steppe zone in terms of the nature of development, harmfulness and hy-drothermal dependence of their pathogens. Materials and Methods. In 1999–2019, we conducted surveys of wheat (winter and spring), rye, barley (winter and spring), oats and maize for disease in-festation in the Northern Steppe of Ukraine according to generally accepted methods of phytopathological research. Results. Over the years of research, we identified 123 pathogens, which caused 135 diseases in grain crops. The most diverse composition of pathogens was observed on wheat and maize, 64 and 55 pathogens, and, 33 and 41 diseases, respectively. It should be noted a wide range for specialization of the widespread pathogens in the Northern Steppe of Ukraine. The pathogens of smut infects generally a certain type of grain crops, rusts are somewhat less specialized. Less specialized parasites, such as fungi from the genera Fusarium, Helminthosporium, Alternaria cause the same type of diseases in several plant species, and some of them affect different plant organs. Thus, among the pathogens of Fusarium root rot of wheat, rye, barley and maize, the fungus Fusarium moniliforme Sheld. was identified. On the maize, in particular, this pathogen caused seedling mold, root and stem rot, cob rot, and grain mold. Conclusions. It was established that the hydrothermal regime can affect the development of diseases not only due to its compliance with the pathogen's requirements, but also affect the resistance of plants. The problem of agrocenosis recovery can be successfully solved by adapting modern intensive technologies of growing grain crops that aimed to optimally utilized ecological resources by plants in the Steppe of Ukraine, and prevent the spread of harmful organisms. Key words: winter wheat, maize, pathogens, diseases, hydrothermal conditions, harmfulness