Plant Temperature and Its Simulation Model of Thermo-Sensitive Genic Male Sterile Rice

Chuangen, Lu; Shi-jian, Xia; Chen, Jing; Hu, Ning; Yao, Ke-min

doi:10.1016/s1672-6308(08)60046-3

Cited by 7 publications

(6 citation statements)

References 8 publications

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“…Specifically, Rn showed a clear four-stage distribution: stable (0:00~6:00), increasing (6:00~13:00), decreasing (13:00~19:00), and stable (19:00~24:00). On the other hand, Tc, Ta, and SHF decreased continuously before 7:00, increased from 7:00 to 14:00, and then decreased continuously after 14:00, which is consistent with the research findings of Lu (2008). Rn directly affects the underlying surface thermal conditions and microclimate formation as an energy source (Gao and Zhuang, 1986).…”

Section: Discussionsupporting

confidence: 85%

“…The canopy, having absorbed net solar radiation, releases energy through longwave radiation, which in turn increases the surrounding temperature. This time lag between Tc and the atmospheric temperature (Ta) has been observed (Lu et al, 2008). Furthermore, Deng et al (2020) found Tc shows more intensified changes and a forward phase compared to Ta.…”

Section: Introductionmentioning

confidence: 79%

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Diurnal-Scale Time Lag between Canopy Temperature and Environmental Factors of Winter Wheat

Xu,

Wu,

Zhang

et al. 2024

Preprint

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Exploring and quantifying the lag effect between environment factors and canopy temperature can improve the accuracy of using environmental factors to predict canopy temperature. In order to quantitatively analyze the lag relationship, we continuously monitored the canopy temperature (Tc) of winter wheat, and simultaneously collected the data of such environmental factors as net radiation (Rn), atmospheric temperature (Ta), relative humidity (RH) and soil heat flux (SHF). With the synchronous diurnal time series, we analyzed the lag relationships between Tc-Rn, Tc-Ta, Tc-RH and Tc-SHF using the bivariate plot; calculated the lag time at jointing stage, heading stage and filling stage using time-lagged correlation analysis; established the Tc lag response model based on Rn, Ta, RH and SHF respectively using the least square. The results indicated that: in sunny days, (1) the hysteresis loops of Tc-Rn, Tc-Ta, Tc-RH were approximately bow-shaped, Tc-SHF was approximately “figure-8”-shaped, and their directions were anticlockwise, clockwise, anticlockwise and clockwise; (2) in the jointing, heading and filling stages of wheat, Tc was 50 min behind Rn; Ta 40, 30 and 30 min behind Tc respectively; RH 30, 40 and 10 min behind Tc respectively; and no lag was found between Tc and SHF; (3) lag effect could improve the accuracy of the Tc response model, because in the jointing, heading and filling stages, the Radj2(adjusted coefficient of determination) of Tc response model based on Rn (Rn-Tc) had increased 13.46%, 13.64% and 12.32% respectively; the Radj2 of Ta-Tc increased 9.02%, 6.31% and 5.56%; and the Radj2 of RH-Tc increased 6.53%, 9.33% and 1.61%. This study may provide some reference for the research on mechanism influencing canopy temperature change.

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Section: Discussionsupporting

confidence: 85%

Section: Introductionmentioning

confidence: 79%

Diurnal-Scale Time Lag between Canopy Temperature and Environmental Factors of Winter Wheat

Xu,

Wu,

Zhang

et al. 2024

Preprint

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“…However, numerous studies indicate differences in the response of Tp when Ta changes by only a few degrees Celsius [ 6 ]. When plants grow under conditions of strong solar and thermal radiation exchange, they are often warmer than the air during the day and cooler than the air at night [ 7 ]. The adaptations for species’ survival in environments of intense heat and water stress are closely related to its accommodative responses.…”

Section: Introductionmentioning

confidence: 99%

How the Plant Temperature Links to the Air Temperature in the Desert Plant Artemisia ordosica

Ding

Gao

et al. 2015

PLoS ONE

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Plant temperature (Tp) is an important indicator of plant health. To determine the dynamics of plant temperature and self-cooling ability of the plant, we measured Tp in Artemisia ordosica in July, in the Mu Us Desert of Northwest China. Related factors were also monitored to investigate their effects on Tp, including environmental factors, such as air temperature (Ta), relative humidity, wind speed; and physiological factors, such as leaf water potential, sap flow, and water content. The results indicate that: 1) Tp generally changes in conjunction with Ta mainly, and varies with height and among the plant organs. Tp in the young branches is most constant, while it is the most sensitive in the leaves. 2) Correlations between Tp and environmental factors show that Tp is affected mainly by Ta. 3) The self-cooling ability of the plant was effective by midday, with Tp being lower than Ta. 4) Increasing sap flow and leaf water potential showed that transpiration formed part of the mechanism that supported self-cooling. Increased in water conductance and specific heat at midday may be additional factors that contribute to plant cooling ability. Therefore, our results confirmed plant self-cooling ability. The response to high temperatures is regulated by both transpiration speed and an increase in stem water conductance. This study provides quantitative data for plant management in terms of temperature control. Moreover, our findings will assist species selection with taking plant temperature as an index.

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“…The absortion of net solar radiation warms up the canopy, which releases energy to increase the surrounding temperature via long-wave radiation. In consequence, the peaks of Tc and Ta are not synchronized (Lu et al, 2008). This phenomenon is a certain hysteresis (Zhang et al, 2018b).…”

Section: Introductionmentioning

confidence: 95%

Hysteresis Between Canopy Temperature and Atmospheric Temperature and Their Drivers on Winter Wheat

Huang¹,

Wang²,

Guo³

et al. 2022

Preprint

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Quantitative characterization of the time-lag effect between canopy temperature and atmospheric temperature and its controlling factors in the agricultural ecosystem may contribute to a higher inversion accuracy of soil water content using canopy-air temperature information. For this end, the canopy temperature (Tc) of winter wheat at four irrigation levels, W1 (field capacity of 95%), W2 (field capacity of 80%), W3 (field capacity of 65%) and W4 (field capacity of 50%), were continuously monitored, and the data of such environmental factors as solar radiation (Rs), atmospheric temperature (Ta), relative humidity (RH) and soil water content (SWC) were simultaneously collected. With the synchronous diurnal time series, the lag relationship between Tc and Ta was analyzed, and the lag time (LT) was calculated using time-lagged correlation analysis; multiple linear regression model was used to construct the time lag model based on factors of Rs, Ta, RH and SWC, and path analysis was used to study the interaction among the factors. The results showed: (1) hysteresis existed between Tc and Ta over the diel cycles, and different weather and irrigation levels did not change the direction of the time lag loop. (2) the key driver regulating the diel hysteresis pattern between Tc and Ta varied under different weather: on rainy days, key driver was Rs while on cloudy and sunny days, the key driver was RH. Meanwhile, SWC had some effect on hysteresis under a certain threshold.(3) the multiple regression model indicated that together Rs, Ta, RH, and SWC explained 68 ± 3, 48 ± 8, and 64 ± 3% of the variation of time-lag effect on rainy, cloudy, and sunny days, respectively. Path analysis showed that the key driver could enhance the time-lag effect through other indirect factors. These findings clearly indicated a dynamic process of time-lag effect between Tc and Ta with different weather and different irrigation levels. This study contributes to the understanding of the time-lag effect and its driving factors and this analysis provides the basis for further improvement on monitoring crop water deficit.

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Plant Temperature and Its Simulation Model of Thermo-Sensitive Genic Male Sterile Rice

Cited by 7 publications

References 8 publications

Diurnal-Scale Time Lag between Canopy Temperature and Environmental Factors of Winter Wheat

Diurnal-Scale Time Lag between Canopy Temperature and Environmental Factors of Winter Wheat

How the Plant Temperature Links to the Air Temperature in the Desert Plant Artemisia ordosica

Hysteresis Between Canopy Temperature and Atmospheric Temperature and Their Drivers on Winter Wheat

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