Diversification of Vascular Occlusions and Crystal Deposits in the Xylem Sap Flow of Five Tunisian Grapevines

Bouamama-Gzara, Badra; Zemni, Hassène; Sleimi, Noomène; Ghorbel, Abdelwahed; Gzara, Lassâad; Mahfoudhi, N.

doi:10.3390/plants11162177

Cited by 4 publications

(4 citation statements)

References 49 publications

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“…When the annular width changed from 2.0 to 2.6 μm, the Δp changed from 15.49 to 15.09 Pa, the q remained constant, and the ξ changed from 2.80×10 5 to 2.71×10 5 , which decreased by 3.21%. When the annular height changed from 2.0 to 2.6 μm, the Δp changed from 12.71 to 16.71 Pa, the q remained constant, and the ξ changed from 2.18×10 5 to 3.07×10 5 , which increased by 40.83%. When the annular spacing changed from 2.0 to 2.6 μm, the Δp changed from 15.47 to 15.10 Pa, the q remained constant, and the ξ changed from 2.79×10 5 to 2.71×10 5 , which decreased by 2.87%.…”

Section: The Vessel Structure Parameters On Flow Resistance Coefficientmentioning

confidence: 99%

“…It can be seen in Fig 11 that the ξ decreased with the increase of pitted inscribed circle diameter and pitted spacing, and increased with the increase of pitted width and pitted height. When the pitted inscribed circle diameter changed from 18 to 24 μm, the Δp changed from 7.92 to 4.62 Pa, the q changed from 8.40×10 −14 to 1.49×10 −13 m 3 /s, and the ξ changed from 1.69×10 5 to 0.18×10 5 , which decreased by 89.35%. When the pitted width changed from 2.0 to 5.0 μm, the Δp changed from 6.69 to 6.45 Pa, the q remained constant, and the ξ changed from 8.36×10 4 to 7.81×10 4 , which decreased by 6.58%.…”

Section: The Vessel Structure Parameters On Flow Resistance Coefficientmentioning

confidence: 99%

“…The growth of Panax notoginseng has strict requirements on temperature and humidity conditions [ 3 ]. The limitation of the hydraulic pathway is considered to be the major constraint on the growth of Panax notoginseng [ 4 , 5 ]. Water transport from the roots to the leaves depends on the xylem, and the vessel is the main water transport channel of xylem [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

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Xylem vessel type and structure influence the water transport characteristics of Panax notoginseng

Bao

et al. 2023

PLoS ONE

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Panax notoginseng plays a very important role in medicinal and economic value. The restriction imposed by the hydraulic pathway is considered to be the main limitation on the optimal growth state of Panax notoginseng. The flow resistance and water transport efficiency of vessel were affected by vessel type and secondary thickening structure. The vessel structure parameters of Panax notoginseng were obtained by experimental anatomy, and the flow resistance characteristics were analyzed by numerical simulation. The results showed that the xylem vessels had annular thickening and pit thickening walls. The flow resistance coefficient (ξ) of the pitted thickening vessel was significantly lower than that of annular thickening vessel in four cross-sectional types. The ξ of the circular cross-sectional vessel was the largest, followed by the hexagon, pentagon cross-sectional vessel and the lowest was the quadrilateral cross-sectional vessel, and the structure coefficient (S) was just the opposite. The ξ of the vessel model was positively correlated with the annular height, pitted width and pitted height, and negatively correlated with the annular inscribed circle diameter, annular width, annular spacing, pitted inscribed circle diameter and pitted spacing. Among them, annular (pitted) height and the annular (pitted) inscribed circle diameter had a great influence on the ξ. The increasing and decreasing trend of the S and ξ were opposite in the change of annular (pitted) inscribed circle diameter, and consistent in the change of in other structural parameters, indicating that the secondary wall thickening structure limited the inner diameter of the vessel to maintain a balance between flow resistance and transport efficiency.

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Section: The Vessel Structure Parameters On Flow Resistance Coefficientmentioning

confidence: 99%

Section: The Vessel Structure Parameters On Flow Resistance Coefficientmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Xylem vessel type and structure influence the water transport characteristics of Panax notoginseng

Bao

et al. 2023

PLoS ONE

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“…Liu et al investigated the transpiration and the water sources of T. ramosissima by using heat balance and oxygen isotopic analysis and found that daily sap flow was positively correlated with air temperature (Ta), photosynthetically active radiation (PAR), and the vapor pressure deficit (VPD) [28]. Bouamama-Gzara et al used the xylem sap flow of five Tunisian grapevine cultivars to investigate the xylem morphological dynamics, and the results showed that Hencha and Khamri were sensitive to environmental constraints, while the other three cultivars presented higher tolerance [29]. Ouyang et al investigated the impact of urbanization on sap flow of common evergreen tree species, and results show that the impact of pollutant discharge on average sap flux density was greater than that of climatic factors [30].…”

Section: Introductionmentioning

confidence: 99%

An Improved Sap Flow Prediction Model Based on CNN-GRU-BiLSTM and Factor Analysis of Historical Environmental Variables

Guo

Wang

et al. 2023

Forests

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Sap flow is widely used to estimate the transpiration and water consumption of canopies and to manage water resources. In this paper, an improved time series prediction model was proposed by integrating three basic networks—CNN, GRU and BiLSTM—to assess sap flow with historical environment variables. A dataset with 17,569 records of each, including 9 environment variables and 1 sap flow, was applied from a public database of SAPFLUXNET. After normalization, the environment variables were analyzed and composed with the factor analysis method. After the CNN-GRU-BiLSTM structure was designed, N records of three main factors were computed from environment variables, which were measured at N previous moments, and the sap flow was measured at the current moment, and they were applied for each training, validation, and testing cycle. To improve and compare the CNN-GRU-BiLSTM-based model, nine other models, using the methods of multiple linear regression, support vector regression, random forest, LSTM, GRU, BiLSTM, CNN-GRU, CNN-BiLSTM, and CNN-GRU-LSTM, were constructed in this study, respectively. Results show that the performance of the CNN-GRU-BiLSTM-based model has more accuracy than the other nine models we built in this paper, with the mean absolute error, mean squared error, mean absolute percentage error, and coefficient of determination (R2) being 0.0410, 0.0029, 0.2708 and 0.9329, respectively. Furthermore, for a comparison of the descending dimension method of factor analysis, principal component analysis (PCA) and singular value decomposition (SVD) methods were applied and compared, respectively. Results show that the performance of the factor analysis-based model is better than the PCA- or SVD-based model, with the R2 results of the factor analysis-based model being higher than the PCA- and SVD-based models by 5.06% and 10.63%, respectively. This study indicates that the CNN-GRU-BiLSTM-based sap flow prediction model established with a factor analysis of historical environmental variables has optimistic applications for analyzing the transpiration of trees and evaluating water consumption.

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An Improved Transformer Model for Sap Flow Prediction that Efficiently Utilizes Environmental Information

Yu,

Yao,

Yang

et al. 2024

Agric Res

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As an important reference for assessing plant water consumption and estimating plant transpiration, it is of great significance to achieve accurate prediction of plant sap flow. A number of deep learning models were established and compared using approximately 3 years of continuous eucalyptus flow time series data collected from the SAPFLUXNET open dataset and 6 environmental factors, including shortwave solar incident radiation, air temperature, air relative humidity, net radiation, vapor pressure deficit, and photosynthetic photon flux density. The experimental results show that the improved Transformer model, with the introduction of a two-step self-attention mechanism and simplified design, maintains significant predictive performance advantages compared to the original Transformer model, long short-term memory, gated recurrent unit, and temporal convolutional neural network models. In the shorter 1-h forecast, the mean squared error and coefficient of determination (R2) of the improved Transformer model are 0.0191 and 0.965, respectively. Compared to the suboptimal typical Transformer model, the MSE is reduced by 22.9%, and R2 is increased by 1.0%. Additionally, the improved model maintains stable predictive performance advantages in long-term plant flow prediction. In the longest 8-h advance prediction, the MSE is reduced by 14.9% compared to the suboptimal Transformer model, and R2 increases by 3.0% compared to the Transformer model. The comprehensive experimental results show that the improved Transformer model makes more effective use of environmental information to achieve more accurate and long-term plant flow prediction. This study emphasizes the basic principle and validity of the two-step self-attention network structure and provides a valuable basis for developing more effective methods for predicting plant sap flow.

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Diversification of Vascular Occlusions and Crystal Deposits in the Xylem Sap Flow of Five Tunisian Grapevines

Cited by 4 publications

References 49 publications

Xylem vessel type and structure influence the water transport characteristics of Panax notoginseng

Xylem vessel type and structure influence the water transport characteristics of Panax notoginseng

An Improved Sap Flow Prediction Model Based on CNN-GRU-BiLSTM and Factor Analysis of Historical Environmental Variables

An Improved Transformer Model for Sap Flow Prediction that Efficiently Utilizes Environmental Information

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