The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform
M. V. Cuevas - One of the best experts on this subject based on the ideXlab platform.
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Irrigation Scheduling from stem diameter variations a review
Agricultural and Forest Meteorology, 2010Co-Authors: J E Fernandez, M. V. CuevasAbstract:Precise Irrigation is essential in arid and semi-arid areas where water is scarce. This has impelled the scientific community to develop new technologies for Scheduling Irrigation. Of these, the ones relying on plant-based water-stress indicators have been found to have the greatest potential. Thus, measurements of stem water content, canopy temperature, sap flow, and stem diameter variation (SDV), among other variables, have proved useful not only for research purposes, but also for precise Irrigation Scheduling in commercial orchards. In this work we focus on the use of SDV records for Irrigation Scheduling. Of those mentioned above, this is the water-stress indicator that has received most attention from the scientific community, in terms of its potential for irrigating commercial orchards. Apart from being capable of an early detection of water stress, even if this is mild, SDV can be continuously and automatically recorded. This is a clear advantage over conventional indicators such as stem water potential (Ψstem). Among the SDV-derived indices that are useful for Scheduling Irrigation, the maximum daily shrinkage (MDS) and stem growth rate (SGR) are the most widely used. For young trees, and in periods of rapid stem growth, SGR could be a better indicator than MDS. In periods of negligible growth, however, SGR cannot be used as an indicator of plant water stress. Considerable differences in both MDS and SGR as a function of crop load have been reported for some species. It has been found, that SDV outputs are affected by seasonal growth patterns, crop load, plant age and size, and other factors, apart from water stress. Thus, expert interpretation of SDV records is required before using them for Scheduling Irrigation, which limits their potential for automating the calculation of the Irrigation dose. For some species, the MDS vs Ψstem relationships show diurnal hysteresis and seasonal changes. Some relationships also shown an increase of MDS as the plant water potential fell to a certain value, after which MDS decreases as the plant water potential became more negative. This has been reported for peach, lemon, grapevine and olive, among other species. Although SDV-derived indices show a high plant-to-plant variability, in most cases the signal intensity is high enough to achieve an acceptable sensitivity, which, for peach, lemon and pepper has been found to greater than that of Ψstem and leaf conductance (gl). In plum, apple and grapevine, however, Ψstem is more sensitive than MDS and SGR. In any case, the usefulness of an SDV-derived index for Irrigation Scheduling must be evaluated for the orchard conditions. In this work we describe the qualities that must be considered in such evaluation. One of them, the signal intensity, is being successfully used to schedule low-frequency Irrigation in orchards of a variety of species, for both full- and deficit-Irrigation treatments. When combined with aerial or satellite imaging, SDV measurements are useful for Scheduling Irrigation in large orchards with high crop-water-stress variability.
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Irrigation Scheduling from stem diameter variations: A review
Agricultural and Forest Meteorology, 2010Co-Authors: J E Fernandez, M. V. CuevasAbstract:Precise Irrigation is essential in arid and semi-arid areas where water is scarce. This has impelled the scientific community to develop new technologies for Scheduling Irrigation. Of these, the ones relying on plant-based water-stress indicators have been found to have the greatest potential. Thus, measurements of stem water content, canopy temperature, sap flow, and stem diameter variation (SDV), among other variables, have proved useful not only for research purposes, but also for precise Irrigation Scheduling in commercial orchards. In this work we focus on the use of SDV records for Irrigation Scheduling. Of those mentioned above, this is the water-stress indicator that has received most attention from the scientific community, in terms of its potential for irrigating commercial orchards. Apart from being capable of an early detection of water stress, even if this is mild, SDV can be continuously and automatically recorded. This is a clear advantage over conventional indicators such as stem water potential (Ψstem). Among the SDV-derived indices that are useful for Scheduling Irrigation, the maximum daily shrinkage (MDS) and stem growth rate (SGR) are the most widely used. For young trees, and in periods of rapid stem growth, SGR could be a better indicator than MDS. In periods of negligible growth, however, SGR cannot be used as an indicator of plant water stress. Considerable differences in both MDS and SGR as a function of crop load have been reported for some species. It has been found, that SDV outputs are affected by seasonal growth patterns, crop load, plant age and size, and other factors, apart from water stress. Thus, expert interpretation of SDV records is required before using them for Scheduling Irrigation, which limits their potential for automating the calculation of the Irrigation dose. For some species, the MDS vs Ψstemrelationships show diurnal hysteresis and seasonal changes. Some relationships also shown an increase of MDS as the plant water potential fell to a certain value, after which MDS decreases as the plant water potential became more negative. This has been reported for peach, lemon, grapevine and olive, among other species. Although SDV-derived indices show a high plant-to-plant variability, in most cases the signal intensity is high enough to achieve an acceptable sensitivity, which, for peach, lemon and pepper has been found to greater than that of Ψstemand leaf conductance (gl). In plum, apple and grapevine, however, Ψstemis more sensitive than MDS and SGR. In any case, the usefulness of an SDV-derived index for Irrigation Scheduling must be evaluated for the orchard conditions. In this work we describe the qualities that must be considered in such evaluation. One of them, the signal intensity, is being successfully used to schedule low-frequency Irrigation in orchards of a variety of species, for both full- and deficit-Irrigation treatments. When combined with aerial or satellite imaging, SDV measurements are useful for Scheduling Irrigation in large orchards with high crop-water-stress variability. © 2009 Elsevier B.V. All rights reserved.
J E Fernandez - One of the best experts on this subject based on the ideXlab platform.
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Irrigation Scheduling from stem diameter variations a review
Agricultural and Forest Meteorology, 2010Co-Authors: J E Fernandez, M. V. CuevasAbstract:Precise Irrigation is essential in arid and semi-arid areas where water is scarce. This has impelled the scientific community to develop new technologies for Scheduling Irrigation. Of these, the ones relying on plant-based water-stress indicators have been found to have the greatest potential. Thus, measurements of stem water content, canopy temperature, sap flow, and stem diameter variation (SDV), among other variables, have proved useful not only for research purposes, but also for precise Irrigation Scheduling in commercial orchards. In this work we focus on the use of SDV records for Irrigation Scheduling. Of those mentioned above, this is the water-stress indicator that has received most attention from the scientific community, in terms of its potential for irrigating commercial orchards. Apart from being capable of an early detection of water stress, even if this is mild, SDV can be continuously and automatically recorded. This is a clear advantage over conventional indicators such as stem water potential (Ψstem). Among the SDV-derived indices that are useful for Scheduling Irrigation, the maximum daily shrinkage (MDS) and stem growth rate (SGR) are the most widely used. For young trees, and in periods of rapid stem growth, SGR could be a better indicator than MDS. In periods of negligible growth, however, SGR cannot be used as an indicator of plant water stress. Considerable differences in both MDS and SGR as a function of crop load have been reported for some species. It has been found, that SDV outputs are affected by seasonal growth patterns, crop load, plant age and size, and other factors, apart from water stress. Thus, expert interpretation of SDV records is required before using them for Scheduling Irrigation, which limits their potential for automating the calculation of the Irrigation dose. For some species, the MDS vs Ψstem relationships show diurnal hysteresis and seasonal changes. Some relationships also shown an increase of MDS as the plant water potential fell to a certain value, after which MDS decreases as the plant water potential became more negative. This has been reported for peach, lemon, grapevine and olive, among other species. Although SDV-derived indices show a high plant-to-plant variability, in most cases the signal intensity is high enough to achieve an acceptable sensitivity, which, for peach, lemon and pepper has been found to greater than that of Ψstem and leaf conductance (gl). In plum, apple and grapevine, however, Ψstem is more sensitive than MDS and SGR. In any case, the usefulness of an SDV-derived index for Irrigation Scheduling must be evaluated for the orchard conditions. In this work we describe the qualities that must be considered in such evaluation. One of them, the signal intensity, is being successfully used to schedule low-frequency Irrigation in orchards of a variety of species, for both full- and deficit-Irrigation treatments. When combined with aerial or satellite imaging, SDV measurements are useful for Scheduling Irrigation in large orchards with high crop-water-stress variability.
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Irrigation Scheduling from stem diameter variations: A review
Agricultural and Forest Meteorology, 2010Co-Authors: J E Fernandez, M. V. CuevasAbstract:Precise Irrigation is essential in arid and semi-arid areas where water is scarce. This has impelled the scientific community to develop new technologies for Scheduling Irrigation. Of these, the ones relying on plant-based water-stress indicators have been found to have the greatest potential. Thus, measurements of stem water content, canopy temperature, sap flow, and stem diameter variation (SDV), among other variables, have proved useful not only for research purposes, but also for precise Irrigation Scheduling in commercial orchards. In this work we focus on the use of SDV records for Irrigation Scheduling. Of those mentioned above, this is the water-stress indicator that has received most attention from the scientific community, in terms of its potential for irrigating commercial orchards. Apart from being capable of an early detection of water stress, even if this is mild, SDV can be continuously and automatically recorded. This is a clear advantage over conventional indicators such as stem water potential (Ψstem). Among the SDV-derived indices that are useful for Scheduling Irrigation, the maximum daily shrinkage (MDS) and stem growth rate (SGR) are the most widely used. For young trees, and in periods of rapid stem growth, SGR could be a better indicator than MDS. In periods of negligible growth, however, SGR cannot be used as an indicator of plant water stress. Considerable differences in both MDS and SGR as a function of crop load have been reported for some species. It has been found, that SDV outputs are affected by seasonal growth patterns, crop load, plant age and size, and other factors, apart from water stress. Thus, expert interpretation of SDV records is required before using them for Scheduling Irrigation, which limits their potential for automating the calculation of the Irrigation dose. For some species, the MDS vs Ψstemrelationships show diurnal hysteresis and seasonal changes. Some relationships also shown an increase of MDS as the plant water potential fell to a certain value, after which MDS decreases as the plant water potential became more negative. This has been reported for peach, lemon, grapevine and olive, among other species. Although SDV-derived indices show a high plant-to-plant variability, in most cases the signal intensity is high enough to achieve an acceptable sensitivity, which, for peach, lemon and pepper has been found to greater than that of Ψstemand leaf conductance (gl). In plum, apple and grapevine, however, Ψstemis more sensitive than MDS and SGR. In any case, the usefulness of an SDV-derived index for Irrigation Scheduling must be evaluated for the orchard conditions. In this work we describe the qualities that must be considered in such evaluation. One of them, the signal intensity, is being successfully used to schedule low-frequency Irrigation in orchards of a variety of species, for both full- and deficit-Irrigation treatments. When combined with aerial or satellite imaging, SDV measurements are useful for Scheduling Irrigation in large orchards with high crop-water-stress variability. © 2009 Elsevier B.V. All rights reserved.
L S Pereira - One of the best experts on this subject based on the ideXlab platform.
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Irrigation Scheduling strategies for cotton to cope with water scarcity in the fergana valley central asia
Agricultural Water Management, 2009Co-Authors: L S Pereira, P R Teodoro, Paula Paredes, E D сholpankulov, O P Inchenkova, M G HorstAbstract:The Central Asian countries face high water scarcity due to aridity and desertification but excess water is often applied to the main irrigated crops. This over-Irrigation contributes to aggravate water scarcity problems. Improved water saving Irrigation is therefore required, mainly through appropriate Irrigation Scheduling. To provide for it, after being previously calibrated and validated for cotton in the Fergana region, the Irrigation Scheduling simulation model ISAREG was explored to simulate improved Irrigation Scheduling alternatives. Results show that using the present Irrigation Scheduling a large part of the applied water, averaging 20%, percolates out of the root zone. Several Irrigation strategies were analyzed, including full Irrigation and various levels of deficit Irrigation. The analysis focused a three-year period when experiments for calibration and validation of the model were carried out, and a longer period of 33 years that provided for an analysis considering the probabilities of the demand for Irrigation water. The first concerned a wet period while the second includes a variety of climatic demand conditions that provided for analyzing alternative schedules for average, high and very high climatic demand. Results have shown the importance of the groundwater contribution, mainly when deficit Irrigation is applied. Analyzing several deficit Irrigation strategies through the respective potential water saving, relative yield losses, water productivity and economic water productivity, it could be concluded that relative mild deficits may be adopted. Contrarily, the adoption of high water deficit that produce high water savings would lead to yield losses that may be economically not acceptable.
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gisareg a gis based Irrigation Scheduling simulation model to support improved water use
Agricultural Water Management, 2005Co-Authors: P S Fortes, A E Platonov, L S PereiraAbstract:Abstract To support improved Irrigation Scheduling in the Syr Darya basin, Uzbekistan, the ISAREG model was selected due to previous applications in similar climates. It is a conceptual non-distributed water balance model for simulating crop Irrigation schedules at field level and to compute Irrigation requirements under optimal and/or water stressed conditions. To provide for the use of the model at the project scale, a new version of the model, integrated with a Geographical Information System (GIS), was developed. This GIS based application is aimed at supporting the implementation of improved farm Irrigation management and, in a later phase, to also help project management. The integration concerns the creation of spatial and weather GIS databases usable by ISAREG, the models operation for different water management scenarios, and the production of crop Irrigation maps and time dependent Irrigation depths at selected aggregation modes, including the farm scale. The resulting information on alternative Irrigation schedules is, therefore, spatially distributed and shall be used both to support Irrigation Scheduling advising and to help in the identification of practices that may lead to water saving and provide for salinity control. The paper includes brief descriptions of the models, the databases and the integration of the models, as well as main features of the GISAREG application. Results relative to the comparative analysis of Irrigation Scheduling scenarios show the capabilities of the model to support the selection of water saving alternatives. The appropriateness of implementing 15–20-day time intervals between Irrigations is shown. In addition, results relative to compare net Irrigation requirements for wet and dry years show the usefulness of the model in handling time series of weather data.
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Irrigation Scheduling simulation the model isareg
2003Co-Authors: L S Pereira, P R Teodoro, P N Rodrigues, J L TeixeiraAbstract:This paper presents the new Windows version of the Irrigation Scheduling simulation model ISAREG. It describes the main features of the model, data requirements, simulation options, basic calculation procedures, and approaches used to Scheduling Irrigations for drought water scarcity. The main windows for handling the model are shown. including those for presentation of results.
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model validation and crop coefficients for Irrigation Scheduling in the north china plain
Agricultural Water Management, 1998Co-Authors: J L Teixeira, H J Zhang, L S PereiraAbstract:ISAREG is a model for simulation and evaluation of Irrigation Scheduling. The model performs the soil water balance and evaluates impacts of water stress on yields for different crops. It is now being used to support a water saving Irrigation Scheduling program in a pilot area in the North China plain. This paper reports on the calibration and validation of the model using independent data sets relative to winter wheat and summer maize. Data are originated from the Wangdu experimental station and concern a set of drainage lysimeters where diverse Irrigation treatments were applied representing different strategies of deficit Irrigation. The calibration of the model was performed by deriving the crop coefficients adapted to the local climatic conditions, and considering the soil freezing during winter. The validation of the model was performed using different data sets. Results show that the relative errors to estimate the soil water content averaged 5.3% for summer maize and 7.3% for the winter wheat. These results support the use of the model in the practice.
F Moreno - One of the best experts on this subject based on the ideXlab platform.
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new approach for olive trees Irrigation Scheduling using trunk diameter sensors
Agricultural Water Management, 2010Co-Authors: A Moriana, I F Giron, M J Martinpalomo, W Conejero, M F Ortuno, A Torrecillas, F MorenoAbstract:Trunk diameter fluctuations (TDFs) have been suggested as an Irrigation-Scheduling tool for several fruit trees, but the works in olive trees has not obtained successful results with any of the indicators (maximum daily shrinkage (MDS) and trunk growth rate (TGR)) that are calculated from the daily TDF curves. No studies of olive trees have ever used reference trees to reduce the influence of the environment, as in work for other fruit trees. In this work, we compare different continuous and discrete water status measurements in a drought cycle. We suggest the calculation of a new and related indicator (DTGR), the difference between the TGR of stressed trees, and the TGR of reference trees. Negative DTGR values always indicate water stress conditions. The current work describes the variations of this new indicator (DTGR) in relation to water stress, and compares DTRG to the midday stem water potential, maximum leaf conductance and to the MDS. The midday stem water potential and the maximum leaf conductance describe the stress cycle clearer than the trunk diameter fluctuation indicators. No significant differences were found in the values of MDS between stressed and reference trees. On the other hand, the DTGR pattern values were near that of the stem water potential, though positive values were recorded in some dates during the water stress cycle. These variations indicate that DTGR is not a cumulative water stress indicators, as is water potential. Therefore, according to our data, water potential is a better indicator than the TDF parameters when no deficit Irrigation Scheduling is performed in olive trees. DTGR seems to be a good indicator of water stress from a threshold value around -1.4Â MPa in olive trees. In addition, higher variability of DTGR than stem water potential may also be reduced with the increase in the number of sensors.
Raoul Lemeur - One of the best experts on this subject based on the ideXlab platform.
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A step towards new Irrigation Scheduling strategies using plant-based measurements and mathematical modelling
Irrigation Science, 2008Co-Authors: Kathy Steppe, Dirk J. W. De Pauw, Raoul LemeurAbstract:Because of the increasing worldwide shortage of freshwater and costs of Irrigation, a new plant-based Irrigation Scheduling method is proposed. In this method, two real-time plant-based measurements (sap flow and stem diameter variations) are used in combination with a mathematical water flow and storage model in order to predict the stem water potential. The amount of required Irrigation water is derived from a time integration of the sap flow profile, while the timing of the Irrigation is controlled based on a reference value for the predicted stem water potential. This reference value is derived from the relationship between midday values of maximum photosynthesis rates and stem water potential. Since modelling is an important part of the proposed methodology, a thorough mathematical analysis (identifiability analysis) of the model was performed. This analysis showed that an initial (offline) model calibration was needed based on measurements of sap flow, stem diameter variation and stem water potential. Regarding Irrigation Scheduling, however, only sap flow and stem diameter variation measurements are needed for online simulation and daily model calibration. Model calibration is performed using a moving window of 4 days of past data of stem diameter variations. The research tool STACI (Software Tool for Automatic Control of Irrigation) was used to optimally combine the continuous measurements, the mathematical modelling and the real-time Irrigation Scheduling. The new methodology was successfully tested in a pilot-scale setup with young potted apple trees ( Malus domestica Borkh) and its performance was critically evaluated.
