• Journal of Bio-Environment Control
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• v.6 no.3
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• pp.205-215
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• 1997

An accurate transpiration model for greenhouse tomato crop, which is liable to transpiration depression and yield loss because of low solar radiation and high humidity, could be an efficient tool for the optimum control of greenhouse climate and for the optimization of Irrigation scheduling. The purpose of this study was to develop transpiration model of greenhouse tomato and to carry out the experimental verification. The formulas to calculate the canopy transpiration and temperature simultaneously were derived from the energy balance of canopy. Transpiration and microclimate variables such as net radiation, solar radiation, humidity, canopy and air temperature, etc. were simultaneously measured to estimate parameters of model equations and to verify the suggested model. Leaf boundary layer resistance was calculated as a function of Nusselt number and stomatal diffusive resistance was parameterized by solar radiation and leaf-air vapor pressure deficit. The equation for stomatal diffusive resistance could explain more than 80％ of its variation and the calculated stomatal diffusive resistance showed good agreements with the measured values in situations independent of which the constants of the equation were estimated. The canopy net radiation calculated by Stanghellini's model with slight modification agreed well with the measured values. The present transpiration model, into which afore-mentioned component equations were assembled, was found to predict the canopy temperature, instantaneous and daily transpiration with considerable accuracy in greenhouse climates.

• Food Science and Preservation
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• v.9 no.3
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• pp.261-266
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• 2002

A transpiration model was selected and tested experimentally to predict transpiration into of Fuji apple stored in a normal air and controlled atmospheres (l∼3% O$_2$+ l∼3% CO$_2$) at 0$\^{C}$ and 98% RH for 6weeks. CA storage decreased the respiration rate of Fuji apple by 50% when compared with normal air storage. The transpiration rates of apple showed 50∼70% higher in normal air storage than those in CA storage and were decreased by increasing CO$_2$concentration under same concentration of O$_2$. The transpiration rates estimated by the selected model were in good agreement with experimental data for Fuji apples under controlled atmosphere conditions and normal air. When the respiratory heat generation rate u of Fuji apple increased with storage conditions, the evaporating surface temperature and transpiration rate also increased. But since some portion of respiratory heat was used as latent heat in the evaporating surface, the change of u value had a little effect on the determination of the evaporation temperature and the transpiration rate.

• Journal of Bio-Environment Control
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• v.24 no.1
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• pp.1-7
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• 2015

Irrigation control plays an important role in improving productivity of paprika which is very sensitive to moisture condition. Among environmental factors, light intensity and distribution are not easily controlled and showed a big difference depending on season and region. For adequate irrigation control, therefore, transpiration and irrigation amounts considering light environmental data should be estimated. In current study, modified transpiration model was used for more precise estimation of transpiration. Seasonal transpiration and irrigation amounts at different regions were compared by using light environmental data provided from Korea Meteorological Administration. The transpiration amount in summer was rather smaller than those in spring and autumn seasons in Korea due to large deviations in light intensity as well as rainy period in summer. Irrigation system capacities at various regions could be recommended by using the transpiration amount in the spring having the longest photoperiod in the year. These results will be useful to the design of irrigation system and optimization of input energy in greenhouse.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.52-59
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• 2001

Methods to measure and estimate transpiration of a forest composed of evergreen broad-leaved trees (Pasania edulis Makino) are studied. Heat pulse velocity has been measured along with soil moisture and micrometeorological factors at the Fukuoka Experimental Forest, the Research Institute of Kyushu University Forests in Fukuoka, Japan (33$^{\circ}$38'N, 130$^{\circ}$31'E, alt. 75m). Tree cutting measurement was conducted to convert the heat pulse velocity into sap flow and transpiration. A big leaf model to calculate transpiration and Interception loss is examined and the estimated values are compared with the measured values obtained from the heat pulse measurement. The results show that 1) Pasania edulis Makino posessing radial pore structure had relatively high water content and high heat pulse velocity even within the central part of the stem near the pith, 2) the heat pulse velocity was well correspond to the water uptake in the tree cutting measurement, 3) the estimation of sap flow based on the heat pulse velocity is accurate, and 4) the big leaf model using the parameters obtained from measurement of a portable photosynthesis system in one day in summer gives reasonable estimation of transpiration independent of seasons and weather.

• The Korean Journal of Ecology
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• v.2 no.1
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• pp.31-37
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• 1978

The salt accumulation on the soil surface can be mathematically described. Although the movement of salts in soil solution is expressed in terms of mathematical model, which has certain limitations in practical application, except the exchangeable and absorbable state salts in soil solution. This model is illustrated by analyticl experiments in which evaporation from the bare soils, transpiration of plants and rainfall are required. Agreement between the model and the measured data was satisfactory, which validating the salt accumulation theory on the soil surface.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.3
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• pp.20-35
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• 1998

Characteristics of turbulent flow with wall transpiration is analyzed. The wall transpiration includes both of suction and injection and extends their range to 0~160 of absolute magnitude of Re$_{w}$ . Reynolds number based on inlet velocity also covers wide range of 3${\times}$$10^3$~8${\times}$$10^4$. The turbulent flow with wall transpiration induces change of wall boundary layer and rapid change of turbulent field. This, in turn, leads the change of whole flow field. For predicting this complicated flow field properly, newly modified $\kappa$-$\varepsilon$ model is utilized, which is formed by modifying dissipation rate equation. The modified $\kappa$-$\varepsilon$ model of Chien is also adopted for the comparison of model performance. Analysis shows the newly modified $\kappa$-$\varepsilon$ model is successfully able to reflect the characteristics of turbulent flow field with wall transpiration.ion.

• The KSFM Journal of Fluid Machinery
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• v.10 no.5
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• pp.27-33
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• 2007

Rarefied gas flows through two-dimensional micro channels are studied numerically for the performance optimization of a nanomembrane-based Knudsen compressor. The effects of the wall temperature distributions on the thermal transpiration flow patterns are examined. The flow has a pumping effect, and the mass flow rates through the channel are calculated. The results show that a steady one-way flow is induced for a wide range of the Knudsen number. The DSMC(direct simulation Monte Carlo) method with VHS(variable hard sphere) model and NTC(no time counter) techniques has been applied in this work to obtain numerical solutions. A critical element that drives Knudsen compressor Is the thermal transpiration membrane. The membranes are based on aerosol or machined aerogel. The aerogel is modeled as a single micro flow channel.

• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.411-417
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• 2017

Environmental and growth factors such as light intensity, vapor pressure deficit, and leaf area index are important variables that can change the transpiration rate of plants. The objective of this study was to compare the transpiration rates estimated by modified Penman-Monteith model and artificial neural network. The transpiration rate of paprika (Capsicum annuum L. cv. Fiesta) was obtained by using the change in substrate weight measured by load cells. Radiation, temperature, relative humidity, and substrate weight were collected every min for 2 months. Since the transpiration rate cannot be accurately estimated with linear equations, a modified Penman-Monteith equation using compensated radiation (Shin et al., 2014) was used. On the other hand, ANN was applied to estimating the transpiration rate. For this purpose, an ANN composed of an input layer using radiation, temperature, relative humidity, leaf area index, and time as input factors and five hidden layers was constructed. The number of perceptons in each hidden layer was 512, which showed the highest accuracy. As a result of validation, $R^2$ values of the modified model and ANN were 0.82 and 0.94, respectively. Therefore, it is concluded that the ANN can estimate the transpiration rate more accurately than the modified model and can be applied to the efficient irrigation strategy in soilless cultures.

• Journal of Bio-Environment Control
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• v.32 no.4
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• pp.384-395
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• 2023

Since transpiration plays a key role in optimal irrigation management, knowledge of the irrigation demand of crops like tomatoes, which are highly susceptible to water stress, is necessary. One way to determine irrigation demand is to measure transpiration, which is affected by environmental factor or growth stage. This study aimed to estimate the transpiration amount of tomatoes and find a suitable model using mathematical and deep learning models using minute-by-minute data. Pearson correlation revealed that observed environmental variables significantly correlate with crop transpiration. Inside air temperature and outside radiation positively correlated with transpiration, while humidity showed a negative correlation. Multiple Linear Regression (MLR), Polynomial Regression model, Artificial Neural Network (ANN), Long short-term Memory (LSTM), and Gated Recurrent Unit (GRU) models were built and compared their accuracies. All models showed potential in estimating transpiration with R² values ranging from 0.770 to 0.948 and RMSE of 0.495 mm/min to 1.038 mm/min in the test dataset. Deep learning models outperformed the mathematical models; the GRU demonstrated the best performance in the test data with 0.948 R² and 0.495 mm/min RMSE. The LSTM and ANN closely followed with R² values of 0.946 and 0.944, respectively, and RMSE of 0.504 m/min and 0.511, respectively. The GRU model exhibited superior performance in short-term forecasts while LSTM for long-term but requires verification using a large dataset. Compared to the FAO56 Penman-Monteith (PM) equation, PM has a lower RMSE of 0.598 mm/min than MLR and Polynomial models degrees 2 and 3 but performed least among all models in capturing variability in transpiration. Therefore, this study recommended GRU and LSTM models for short-term estimation of tomato transpiration in greenhouses.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.5
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• pp.29-43
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• 2020

Thermal environment of city is getting worse due to severe urban heat island caused by climate change and urbanization. The cooling effect of street tree is regarded as a effective way to ameliorate the urban heat environment. The effect is largely made up of shadow formation and transpiration. This study aims to identify how the transpiration affects the discomfort index by analyzing comprehensive impact of the transpiration on the air temperature and relative humidity. The changes in the amount of transpiration, air temperature, and relative humidity were estimated for Seogyo-dong area which has a lot of floating population in Seoul, at 2 p.m. in dry day in July and August. On average, the transpiration of the street tree decreased the temperature 0.3℃ and increased the relative humidity 2.6% in an hour. As a result of these changes in temperature and humidity, the discomfort index rose mostly(0.036 on average). It was always get rise especially on the day when the discomfort index was above 80(0.05 on average). However, compared with the significant change in temperature and humidity, the variation of the discomfort index itself was very slight(up to 0.107). Therefore, the effect of transpiration by the street trees might not be effective in the planning to improve the thermal environment(especially on the day when the discomfort index is high). It is necessary to select the species of trees and planting location considering the cooling effect of shade formation synthetically.