Physiological response of swine to cycling environmental conditions

1967 ◽  
Vol 9 (4) ◽  
pp. 453-462 ◽  
Author(s):  
T. E. Bond ◽  
C. F. Kelly ◽  
H. Heitman
Keyword(s):  
Constant Temperature ◽  
Air Temperature ◽  
Environmental Conditions ◽  
Physiological Response ◽  
Respiration Rates ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Group Averaging ◽  
Maximum Air Temperature

Rectal and surface temperatures, and respiration and pulse rates, were obtained for groups of Duroc pigs that were exposed to air temperatures that varied sinusoidally over a 24-hour period. Two groups averaging 37 and 108 kg were exposed to a constant temperature of 21·1°C and then to temperatures that cycled about a mean of 21·1°C (15·6–26·7°C, 10·0–32·2°C, and 4·4–37·8°C). For a third group averaging 53 kg, the minimum was always near 21·1°C, and the maximum air temperature of the cycle was 33·2, 42·5 or 48·8°C.The response of rectal and surface temperatures, and pulse and respiration rates, to the various 24-hour cycling air temperatures are discussed and com-pared with inherent daily fluctuations in these responses that are present even when there is no variation in air temperature.

CORRELATION COMMUNICATION BETWEEN METEOROLOGICAL PARAMETERS AT EXTREME VALUES OF MAXIMUM AIR TEMPERATURES

2020 ◽  
pp. 101-112
Author(s):  
S.V. Savchuk ◽  
V.E. Timofeev ◽  
O.A. Shcheglov ◽  
V.A. Artemenko ◽  
I.L. Kozlenko
Keyword(s):  
Air Temperature ◽  
Meteorological Parameters ◽  
Extreme Values ◽  
Daily Temperature ◽  
Sea Level Pressure ◽  
Maximum Daily Temperature ◽  
The North ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

The object of the study is the maximum daily air temperature during the months of the year over 1991-2016 by the data of 186 meteorological stations of Ukraine. Extreme values of the maximum daily temperature equal to or exceeded their 95th (Tmax95p and above, ºС) percentile were taken as extreme. The article sets the dates (137 cases) of extreme values of maximum air temperature on more than 60 % of the territory. For these dates, 13 meteorological parameters were selected: average, minimum, and maximum air temperatures; average, minimum and maximum relative humidity; station and sea-level pressure; average, maximum (from 8 synoptic hours) wind speed; rainfall; height of snow cover. The purpose of this work is to determine the correlation coefficient (K), in particular, statistically significant (K≤-0.6, K≥0.6), on these dates between selected meteorological parameters at 186 meteorological stations of Ukraine for 1991-2013. The density of the cases of statistically significant dependence between the meteorological parameters in extremely warm days in separate seasons is determined. In extremely warm days, meteorological parameters and areas with statistically significant correlations at K≤-0.6 were detected: T and F (focally in southern and some western regions with significant density) − in winter; T and F (with the highest density ubiquitous or almost ubiquitous), P and V (in a large number of regions, usually west or right-bank, but with less frequency) − in the transition seasons, and in the autumn between − T and F (in the south with smaller density) and P and F (in some areas of the north, northwest, west, lower east). In all seasons, such a correlation between other meteorological parameters had a focal distribution, usually with a smaller density. In these days, a focal distribution with a small frequency of dependencies at K≥0.6 was found between the meteorological parameters detected (F and V in transition seasons, T and F in winter), except for similar ones. However, such dependence is observed between T and V in some regions in winter and autumn and in some areas of south, southeast, east with a smaller density. The study of the maximum daily temperature is relevant, because from the level of natural hydrometeorological phenomena it is accompanied by dangerous phenomena, negatively affecting the weather dependent industries.

scholarly journals Variation of Frost Roughness on a Flat Plate Under Forced Convection

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Tongxin Zhang ◽  
Dennis L. O’Neal ◽  
Stephen T. McClain
Keyword(s):  
Relative Humidity ◽  
Surface Temperature ◽  
Air Temperature ◽  
Environmental Conditions ◽  
Mean Square ◽  
Empirical Correlations ◽  
Testing Conditions ◽  
Air Temperatures ◽  
Photogrammetric Method ◽  
Grain Roughness

Abstract Experiments were conducted on a cold flat aluminum plate to characterize the variation of frost roughness over both time and location on the surfaces. The testing conditions included air temperatures from 8 to 16 °C, wall temperatures from −20 to −10 °C, relative humidities from 60 to 80%, and air velocities from 0.5 to 2.5 m/s. Each test lasted 2 h. A 3D photogrammetric method was employed to measure the variation in frost root-mean-square height and skewness by location and time. These data were used to develop the equivalent sand-grain roughness for the frost at different locations and time. The experimental results showed that frost roughness varied by location and changed with time. For the environmental conditions in this study, relative humidity and air temperature were the most important factors determining changes in the peak frost roughness. For example, at an air temperature of 12 °C and a surface temperature of −15 °C, the frost roughness peaked at about 40 min for a relative humidity of 80% and 90 min for a relative humidity of 60%. Empirical correlations were provided to describe the relationships between the environmental conditions and the appearance of the peak frost roughness.

scholarly journals Trends of Changes of Maximum Air Temperature in Ukraine as an Impact Factor on Population Health

2020 ◽  
Keyword(s):  
Population Health ◽  
Air Temperature ◽  
Thermal Regime ◽  
Climate Changes ◽  
System Analysis ◽  
Global Climate ◽  
Maximum Temperature ◽  
Air Temperatures ◽  
Average Maximum ◽  
Maximum Air Temperature

Purpose. The aim of this research is detection of trends of changes (according to fact and scenario data) of extreme air temperature as a component of thermal regime in different regions of Ukraine because of global climate change. Methods. System analysis, statistical methods. Results. Time distribution of maximum air temperature regime characteristics based on results of observations on the stations located in different regions of Ukraine during certain available periods: Uzhgorod (1946-2018), Kharkiv (1936-2005), Оdessа (1894-2005), аnd also according to scenarios of low (RCP2.6), medium (RCP4.5) and high (RCP8.5) levels of greenhouse gases emissions. Meanwhile, air temperature ≥ 25°С was considered high (days with maximum temperature within 25,0-29,9°С are hot), ≥ 30°С was considered very high (days with such temperature are abnormaly hot). Trends of changes of extreme air temperatures were identified as a component of thermal regime in different regions of Ukraine within global climate changes. Dynamics of maximum air temperature and its characteristics in ХХ and beginning of ХХІ centuries were researched. Expected time changes of maximum air temperature and number of days with high temperature during 2021-2050 were analyzed by RCP2.6, RCP4.5 and RCP8.5 scenarios. There were identified the highest day air temperatures possible once in a century and also possibility of maximum day temperature more than 30°С by RCP4.5 scenario. Well-timed prediction of climate changes will help evaluate their impact on human and natural systems which will be useful for development and taking preventive measures towards minimization of negative influence of such changes. Conclusions. Processes of climate warming in Ukraine are activating. There was determined a strong trend on increasing of average maximum of air temperature in winter with speed 0.17-0,39 degrees centigrade/10 years. According to climatic norm this index mainly increased mostly (up to 3,3 degrees centigrade) in January in North-East of the country. In future such anomalies will grow. Determination of correlation between climate and health is the base for taking protective measures against perils for population health connected with climate.

scholarly journals (56) Transpiration and Photosynthesis of Grafted Watermelon Transplants as Affected by Environmental Factors during Graft Union Formation

HortScience ◽  
2005 ◽  
Vol 40 (4) ◽  
pp. 996D-996
Author(s):  
Sung Kyeom Kim ◽  
Duk Jun Yu ◽  
Ro Na Bae ◽  
Hee Jae Lee ◽  
Changhoo Chun
Keyword(s):  
Environmental Factors ◽  
Air Temperature ◽  
Environmental Conditions ◽  
Vapor Pressure Deficit ◽  
Photon Flux ◽  
Union Formation ◽  
Graft Union ◽  
Yield And Quality ◽  
Air Temperatures ◽  
Grafted Transplants

Grafted transplants are widely used for watermelon culture in Korea mainly to reduce the yield and quality losses caused by soil-borne diseases. It is normal practice to cure the grafted transplants under high relative humidity (RH) and low photosynthetic photon flux (PPF) conditions for a few days after grafting to prevent the wilting of the transplants. Transpiration rate (TR) and net photosynthetic rate (NPR), however, could be suppressed under those environmental conditions. In the present study, TR and NPR of the grafted watermelon transplants were compared during graft union formation under 18 environmental conditions combining two air temperatures (20 and 28 °C), three RHs (60%, 80%, and 100%), and three PPF s (0, 100, and 200 μmol·m-2·s-1). Percentages of graft union formation and survival were also evaluated. TR and NPR dramatically decreased just after grafting but slowly recovered 2 to 3 days after grafting at 28 °C. The recovery was clearer at higher PPF and lower RH. On the other hand, the recovery of TR and NPR was not observed in 7 days after grafting at 20 °C. Differences in TR and NPR affected by RH were nonsignificant. Percentage of graft union formation was 98% when air temperature, RH, and PPF were 28 °C, 100%, and 100 μmol·m-2·s-1, respectively, which was the highest among all the treatments. Percentage of survival was over 90% when air temperature was 28 °C and RH was higher than 80% (when vapor pressure deficit was lower than 0.76 kPa). In addition, higher PPF enhanced TR and NPR and promoted rooting and subsequent growth of grafted transplants. Results suggest that the acclimation process for grafted watermelon transplants can be omitted by properly manipulating environmental factors during graft union formation.

Impact of Environmental Conditions on Frost Crystal Structure

2020 ◽  
Vol 28 (02) ◽  
pp. 2050014
Author(s):  
Tongxin Zhang ◽  
Dennis L. O’Neal ◽  
Stephen T. McClain
Keyword(s):  
Crystal Structure ◽  
Air Temperature ◽  
Wall Temperature ◽  
Environmental Conditions ◽  
Strong Influence ◽  
Aluminum Surface ◽  
Air Velocity ◽  
Air Temperatures ◽  
Crystal Type ◽  
Frost Growth

Frost crystal type and distribution were characterized in the initial periods of frost growth on an aluminum surface. Experiments were carried out for a range of wall temperatures from [Formula: see text]C to [Formula: see text]C, air temperatures from [Formula: see text]C to [Formula: see text]C, relative humidities from 15% to 85%, and air velocities from 0.5 to 5.0[Formula: see text]m/s. The results showed that frost crystal type was strongly dependent on the wall temperature and humidity. Changing the air temperature shifted the region of some frost crystal types. Decreasing the air temperature from 22 down to either [Formula: see text]C or [Formula: see text]C led to the decrease of feather crystals but increased the region of scroll crystals. Air velocity had smaller impacts on frost crystal type but had a strong influence on the distance between the crystals, particularly at lower air velocities. The results were compared to prior researchers. The results should provide a better understanding of frost morphology during the early stages of frost growth on metal surfaces.

scholarly journals Daily Minimum and Maximum Air Temperature in Poland in the Years 1951–2005

2009 ◽  
Vol 2 (1) ◽  
pp. 35-56 ◽  
Author(s):  
Marek Kejna ◽  
Andrzej Araźny ◽  
Rafał Maszewski ◽  
Rajmund Przybylak ◽  
Joanna Uscka-Kowalkowska ◽  
...  
Keyword(s):  
Air Temperature ◽  
North Atlantic ◽  
Daily Maximum ◽  
Grid Data ◽  
The North ◽  
Nao Index ◽  
Air Temperatures ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
Maximum Air Temperature

Abstract In this study grid data of daily maximum and minimum air temperatures taken from the NCEP/NCAR reanalysis for the territory of Poland for the years 1951-2005 have been used as a basis for an analysis of the spatial distribution of daily maximum and minimum air temperature, the frequency of characteristic days and the variability of these parameters in the period analysed. The results obtained were then compared to the variability in atmospheric circulation in Europe, described by the North Atlantic Oscillation (NAO) index.

scholarly journals GPRChinaTemp1km: a high-resolution monthly air temperature dataset for China (1951–2020) based on machine learning

2021 ◽  
Author(s):  
Qian He ◽  
Ming Wang ◽  
Kai Liu ◽  
Kaiwen Li ◽  
Ziyu Jiang
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Air Temperature ◽  
Spatial Interpolation ◽  
Gaussian Process Regression ◽  
Temperature Data ◽  
Air Temperatures ◽  
Maximum Air Temperature ◽  
Maximum Minimum

Abstract. An accurate spatially continuous air temperature dataset is crucial for multiple applications in environmental and ecological sciences. Existing spatial interpolation methods have relatively low accuracy and the resolution of available long-term gridded products of air temperature for China is coarse. Point observations from meteorological stations can provide long-term air temperature data series but cannot represent spatially continuous information. Here, we devised a method for spatial interpolation of air temperature data from meteorological stations based on powerful machine learning tools. First, to determine the optimal method for interpolation of air temperature data, we employed three machine learning models: random forest, support vector machine, and Gaussian process regression. Comparison of the mean absolute error, root mean square error, coefficient of determination, and residuals revealed that Gaussian process regression had high accuracy and clearly outperformed the other two models regarding interpolation of monthly maximum, minimum, and mean air temperatures. The machine learning methods were compared with three traditional methods used frequently for spatial interpolation: inverse distance weighting, ordinary kriging, and ANUSPLIN. Results showed that the Gaussian process regression model had higher accuracy and greater robustness than the traditional methods regarding interpolation of monthly maximum, minimum, and mean air temperatures in each month. Comparison with the TerraClimate, FLDAS, and ERA5 datasets revealed that the accuracy of the temperature data generated using the Gaussian process regression model was higher. Finally, using the Gaussian process regression method, we produced a long-term (January 1951 to December 2020) gridded monthly air temperature dataset with 1 km resolution and high accuracy for China, which we named GPRChinaTemp1km. The dataset consists of three variables: monthly mean air temperature, monthly maximum air temperature, and monthly minimum air temperature. The obtained GPRChinaTemp1km data were used to analyse the spatiotemporal variations of air temperature using Theil–Sen median trend analysis in combination with the Mann–Kendall test. It was found that the monthly mean and minimum air temperatures across China were characterized by a significant trend of increase in each month, whereas monthly maximum air temperature showed a more spatially heterogeneous pattern with significant increase, non-significant increase, and non-significant decrease. The GPRChinaTemp1km dataset is publicly available at https://doi.org/10.5281/zenodo.5112122 (He et al., 2021a) for monthly maximum air temperature, at https://doi.org/10.5281/zenodo.5111989 (He et al., 2021b) for monthly mean air temperature and at https://doi.org/10.5281/zenodo.5112232 (He et al., 2021c) for monthly minimum air temperature.

scholarly journals A New Model to Downscale Urban and Rural Surface and Air Temperatures Evaluated in Shanghai, China

2018 ◽  
Vol 57 (10) ◽  
pp. 2267-2283 ◽  
Author(s):  
Dongwei Liu ◽  
C. S. B. Grimmond ◽  
Jianguo Tan ◽  
Xiangyu Ao ◽  
Jie Peng ◽  
...  
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Wave Radiation ◽  
Climate Services ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures

AbstractA simple model, the Surface Temperature and Near-Surface Air Temperature (at 2 m) Model (TsT2m), is developed to downscale numerical model output (such as from ECMWF) to obtain higher-temporal- and higher-spatial-resolution surface and near-surface air temperature. It is evaluated in Shanghai, China. Surface temperature (Ts) and near-surface air temperature (Ta) submodels account for variations in land cover and their different thermal properties, resulting in spatial variations of surface and air temperature. The net all-wave radiation parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature submodel, the objective hysteresis model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near-surface air temperature submodel considers the horizontal and vertical energy changes for a column of well-mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land-cover types, values are more similar. Downscaled, higher-temporal- and higher-spatial-resolution air temperatures are compared to observations at 110 automatic weather stations across Shanghai. After downscaling with TsT2m, the average forecast accuracy of near-surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress.

scholarly journals Improving node number simulation in soybean

2009 ◽  
Vol 44 (7) ◽  
pp. 661-668 ◽  
Author(s):  
Nereu Augusto Streck ◽  
Gizelli Moiano de Paula ◽  
Felipe Brendler Oliveira ◽  
Ana Paula Schwantes ◽  
Nilson Lemos de Menezes
Keyword(s):  
Air Temperature ◽  
Temperature Response ◽  
Node Number ◽  
Arithmetic Average ◽  
Soybean Cultivars ◽  
Daily Minimum ◽  
Air Temperatures ◽  
Nonlinear Temperature ◽  
Santa Maria ◽  
Maximum Air Temperature

The objective of this study was to improve the simulation of node number in soybean cultivars with determinate stem habits. A nonlinear model considering two approaches to input daily air temperature data (daily mean temperature and daily minimum/maximum air temperatures) was used. The node number on the main stem data of ten soybean cultivars was collected in a three-year field experiment (from 2004/2005 to 2006/2007) at Santa Maria, RS, Brazil. Node number was simulated using the Soydev model, which has a nonlinear temperature response function [f(T)]. The f(T) was calculated using two methods: using daily mean air temperature calculated as the arithmetic average among daily minimum and maximum air temperatures (Soydev tmean); and calculating an f(T) using minimum air temperature and other using maximum air temperature and then averaging the two f(T)s (Soydev tmm). Root mean square error (RMSE) and deviations (simulated minus observed) were used as statistics to evaluate the performance of the two versions of Soydev. Simulations of node number in soybean were better with the Soydev tmm version, with a 0.5 to 1.4 node RMSE. Node number can be simulated for several soybean cultivars using only one set of model coefficients, with a 0.8 to 2.4 node RMSE.

scholarly journals Comparison Air Temperature under Global Climate Change Issue in Gifu city and Ogaki city, Japan

2016 ◽  
Vol 1 (1) ◽  
pp. 37 ◽  
Author(s):  
Ali Rahmat ◽  
Abdul Mutolib
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Global Climate Change ◽  
Global Climate ◽  
Regional Scale ◽  
Climate Change Issue ◽  
Air Temperatures ◽  
Maximum Air Temperature ◽  
Gifu Prefecture ◽  
Global Data

Increases in air temperature indicate a global climate change. Thus, information in the change of temperature regional scale is important to support global data. The present research was conducted in Gifu city and Ogaki city located in Gifu prefecture, Japan. The results showed that, average air temperatures in both cities are quite similar with a difference value of under 1<sup>o</sup>C. Maximum air temperature in Gifu city is significantly higher than Ogaki city, whereas minimum air temperature in Gifu city is significantly lower than in Ogaki city. Daily range of air temperature in Gifu city significantly higher than in Ogaki city. In both cities, air temperature relatively increased in three decades. This is because of different in land characteristics in both cities.

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