GRAIN YIELD OF SOYBEAN VARIETIES OF DIFFERENT MATURITY GROUPS IN THE FOREST-STEPPE ZONE OF THE MIDDLE VOLGA REGION

The experiments were carried out in non-watering conditions of the forest-steppe of the middle Volga region in the fields of Samara Research Institute in 2016-2018. The purpose of the research is to study the features of grain yield formation in soybean varieties of different maturity groups in order to create new varieties of Volga ecotype with high and stable grain yield. The material for the study was 29 soybean varieties of different agroecotypes and maturity groups. Standard is Samer 3. Observations and records were carried out according to the generally accepted methodology. Meteorological conditions in 2016-2018 characterized as arid, the hydrothermal coefficient varied from 0.5 to 0.7. On average, over the years of testing, the studied varieties were classified as very early – with a vegetation period of 86…90 days (8 varieties) and early 91…109 days (21 varieties), including the Samer 3 standard, ripeness groups. The high grain yield over the years of testing was in the early ripeness group - 1.95 t/ha. The sum of active temperatures above 10°C (r=+0.993…+0.999) and the amount of precipitation (r=+0.845…+0.939) had a significant impact on the duration of vegetation of both groups of ripeness in all years. A significant influence of the hydrothermal coefficient and the average daily temperature on the duration of vegetation was, revealed in 2017 and 2018. The correlation of vegetation duration with the hydrothermal coefficient was r=-0.767…-0.977, and with an average daily temperature of r=-0.902…-0.970. Among the varieties of different groups of ripeness, high seed yields (2.00…2.21 t/ha) on average over the years of testing had: Oressa, Swapa, Samer 1, Lira, Cordoba, Lisbon, Malaga

GRAIN YIELD OF SOYBEAN VARIETIES OF DIFFERENT MATURITY GROUPS IN THE FOREST-STEPPE ZONE OF THE MIDDLE VOLGA REGION

The experiments were carried out in non-watering conditions of the forest-steppe of the middle Volga region in the fields of Samara Research Institute in 2016-2018. The purpose of the research is to study the features of grain yield formation in soybean varieties of different maturity groups in order to create new varieties of Volga ecotype with high and stable grain yield. The material for the study was 29 soybean varieties of different agroecotypes and maturity groups. Standard is Samer 3. Observations and records were carried out according to the generally accepted methodology. Meteorological conditions in 2016-2018 characterized as arid, the hydrothermal coefficient varied from 0.5 to 0.7. On average, over the years of testing, the studied varieties were classified as very early – with a vegetation period of 86…90 days (8 varieties) and early 91…109 days (21 varieties), including the Samer 3 standard, ripeness groups. The high grain yield over the years of testing was in the early ripeness group - 1.95 t/ha. The sum of active temperatures above 10°C (r=+0.993…+0.999) and the amount of precipitation (r=+0.845…+0.939) had a significant impact on the duration of vegetation of both groups of ripeness in all years. A significant influence of the hydrothermal coefficient and the average daily temperature on the duration of vegetation was, revealed in 2017 and 2018. The correlation of vegetation duration with the hydrothermal coefficient was r=-0.767…-0.977, and with an average daily temperature of r=-0.902…-0.970. Among the varieties of different groups of ripeness, high seed yields (2.00…2.21 t/ha) on average over the years of testing had: Oressa, Swapa, Samer 1, Lira, Cordoba, Lisbon, Malaga

Impact of weather factors on hospital admission of hand, foot and mouth disease under climate change scenarios in Ho Chi Minh City.

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in Vietnam. The present study aims to examine the association between weather factors and HFMD in association with hospitalisation. Daily and weekly weather and HFMD data from 2013 to 2018 in Ho Chi Minh City were deployed. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the Global Climate Model (GCM) and Yasushi Honda model. The result showed that the average daily temperature induces an increase in the risk of HFDM hospitalisation was 26°C- 30.1°C. The average daily humidity also caused increasing the risk of hospitalisation of HFMD was 75% - 85%. However, the average daily humidity <60% reduced the risk of getting HFMD. The study provides quantitative evidence that the incidence of HFMD cases was associated with meteorological variables including average daily temperature and daily humidity in Ho Chi Minh City. This findings implies that there is a need for building a public health policy for eliminating and mitigating climate change impact on community health in a resilient approach.

Investigating the Co-movement Nexus Between Air Quality, Temperature, and COVID-19 in California: Implications for Public Health

This research aims to look at the link between environmental pollutants and the coronavirus disease (COVID-19) outbreak in California. To illustrate the COVID-19 outbreak, weather, and environmental pollution, we used daily confirmed cases of COVID-19 patients, average daily temperature, and air quality Index, respectively. To evaluate the data from March 1 to May 24, 2020, we used continuous wavelet transform and then applied partial wavelet coherence (PWC), wavelet transform coherence (WTC), and multiple wavelet coherence (MWC). Empirical estimates disclose a significant association between these series at different time-frequency spaces. The COVID-19 outbreak in California and average daily temperature show a negative (out phase) coherence. Similarly, the air quality index and COVID-19 also show a negative association circle during the second week of the observed period. Our findings will serve as policy implications for state and health officials and regulators to combat the COVID-19 outbreak.

New Regression models for Estimation daily temperature of Karachi and its Neural Network analysis

<p>This study presents the determination of the average daily temperature distribution for Karachi city. Artificial Neural Network (ANN) has been used to predict the average daily temperature of 2018, 2019, and 2020. Two regression models (linear and non-linear) were also developed. These models are based on relative humidity and dew points. Karachi's six-year environmental datasets were used for the case study location and to establish temperature distribution models. In ANN three years, temperature data (2015-2017) was used to train and validate the NN model. The same data was used to find the regression coefficients of each model. Both models and NN are then used to estimate the average daily temperature of years 2018-2020. The statistical errors are also calculated for comparison and to evaluate the performance of both models; an excellent agreement was found between recorded and ANN estimates. Both regression models predict average daily temperature with reasonable uncertainties. However, the non-linear regression model predictions are better. The results show that the models provide a good prediction of temperature distribution.</p>

Influence of low temperatures on heat balance in easily assembled premises of different types

The purpose of this work was to analyze the thermal balance of easily assembled premises of different types and sizes during the periods of low average daily temperatures. The research was conducted during the winter period of 2020–2021 in the Kyiv region. The used material was easily assembled premises of different types and sizes: easily assembled ones without insulation elements; with elements of warming and premises with deep-litter. In each of the studied premises were kept 400 dairy cows. The studies were performed during two periods: the first period had ambient temperatures from -10 to -14.9 °C and the second one from -15.0 °C and below. In our studies, the average daily temperature (during the ambient temperature from -10 to 14.9 °C) in easily assembled premises with the use of insulation elements was 6.20 and 5.31 °C higher than in premises without insulation and deep-litter. A similar trend was observed during the period of lowering the ambient temperature up to 15 °C and below. Thus, the advantage of the premises without insulation constituted 6.28 °C, and of the premises with deep-litter per 5.84 °C, respectively. It was found that keeping in easy-to-assemble premises with insulation elements, the consumption of free thermal energy from the whole herd during the experimental periods was lower compared to the keeping in a boxing cowshed and a cowshed with deep litter. This is due to the smaller range of fluctuations in the average daily temperature in a room with insulation elements. A similar trend was observed for energy consumption through enclosing structures and for moisture evaporation and, accordingly, total heat consumption. In general, heat deficiency was observed during the keeping of cows in the investigated premises of easily assembled type at negative temperatures (-10–14.9 and -15 °С and above). Accordingly, the thermal balance of the premises was negative. The highest values of heat balance among easily assembled premises in both research periods were observed for keeping in rooms that used insulation elements.

Sunshine, temperature and suicidal behaviour in patients treated with antidepressants: an explorative nested case–control study

Our aim was to explore if different exposure windows for sunshine or temperature are associated with increased suicidal behaviour among people starting antidepressant treatment. 307 completed and 1674 attempted suicides were included as cases in the conditional logistic regression analyses, while controlling for potential confounders, including season, as well as temperature and hours of sunshine when these variables were not the main exposure variable. Ten controls were matched to each case using risk-set sampling. The role of season, age, and sex was examined with likelihood ratio tests (LRTs) with and without the respective interaction terms and with stratified analyses. There was no overall association between temperature or sunshine with suicidal behaviour. Age was a significant effect modifier for suicide and suicide attempt for both sunshine and temperature exposure. In stratified analyses, an increase of one degree Celsius in the average daily temperature during the last 4 weeks was associated, in the unadjusted model, with a 3% increase in the rate of suicide (p = 0.023) amongst older patients (65+). In the same age group, an increase of 1 h in the average daily sunshine during the last 4 weeks was associated with an 8% increase in the rate of suicide attempt (p = 0.002), while the respective increase for the exposure period of 5–8 weeks was 7% (p = 0.007). An increase of one degree Celsius in the average daily temperature during the last 4 weeks was associated with a 3% increase in the rate of suicide attempt (p = 0.007). These associations did not retain statistical significance in the adjusted models. No associations were found in the other age groups. Our results point to a possible effect modification by age, with higher risk of suicidal behavior associated with an increase in sunshine and temperature found in the older age groups.

Stability and Variability of Camelina sativa (L.) Crantz Economically Valuable Traits in Various Eco-Geographical Conditions of the Russian Federation

C. sativa is a valuable oilseed; it has a wide nutritional and technical use. The purpose of this study is a comprehensive study of C. sativa collection accessions in various ecological and geographical conditions to determine the environmental stability parameters. C. sativa All-Russian Institute of Plant Genetic Resources (VIR) collection accessions served as a material source for the study. The study was conducted in four different ecological and geographical regions of the Russian Federation. In the factor structure of the environmental parameters variability two factors are identified covering 94.8% of the variability. The first factor is associated with the precipitation sum (PS) and the temperatures sum (TS) for the vegetation period (68.7%), the second factor is associated with the average daily temperature (TM) for the same period (26.1%). Analysis of the system of correlations between the parameters of stability and plasticity and the value of regression coefficients for meteorological indicators showed that for all the studied features, indicator b closely correlates with regression coefficients for the temperatures sum (TS) and average daily temperature (TM) for the vegetation period. Indicator Sd—with coefficients for the precipitation sum (PS) and average daily precipitation (PM). The result of the study made it possible to identify collection accessions of C. sativa with a high stable adaptability to the contrasting climatic conditions of the studied regions.

Research long-term fluctuations in winter temperatures. Methods for analyzing the intensities and synchronicities of fluctuations in fuel consumption

The article deals with the problem of assessing the deviations of the meteorological characteristics of the heating season. The usual method of calculating the relative deviations of indicators from the arithmetic mean is not suitable. A requirement is imposed on the “new” averages and estimates of deviations of meteorological characteristics, which follows from their properties: the duration multiplied by the average daily temperature difference for the heating period should be equal to the integral temperature difference. The application of this property to the means and to the very estimates of the deviations of meteorological characteristics makes it difficult to determine the latter. A method is being developed to determine the intensities of fluctuations in the meteorological characteristics of the heating season. Intensities show how much, on average, the duration, average daily and integral temperature differences for the heating period can deviate from the average expected level. A technique is being developed for reflecting synchronous and asynchronous fluctuations in deviations of meteorological characteristics, and the contributions of these fluctuations are determined.