Hourly Relationship between Reference Evapotranspiration and Shoot Shrinkage in Walnut Trees and Pomegranate under Deficit Irrigation.
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ABSTRACT:
SUBMITTER: Salgado E
PROVIDER: S-EPMC8747659 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Alternative models for the estimation of reference evapotranspiration (ETo) are typically assessed using traditional error metrics, such as root mean square error (RMSE), which may not be sufficient to select the best model for irrigation scheduling purposes. Thus, this study analyzes the performance of the original and calibrated Hargreaves-Samani (HS), Romanenko (ROM) and Jensen-Haise (JH) equations, initially assessed using traditional error metrics, for use in irrigation scheduling, considering the simulation of different irrigation intervals/time scales. Irrigation scheduling was simulated using meteorological data collected in Viçosa-MG and Mocambinho-MG, Brazil. The Penman-Monteith FAO-56 equation was used as benchmark. In general, the original equations did not perform well to estimate ETo, except the ROM and HS equations used at Viçosa and Mocambinho, respectively. Calibration and the increase in the time scale provided performance gains. When applied in irrigation scheduling, the calibrated HS and JH equations showed the best performances. Even with greater errors in estimating ETo, the calibrated HS equation performed similarly or better than the calibrated JH equation, as it had errors with greater potential to be canceled during the soil water balance. Finally, in addition to using error metrics, the performance of the models throughout the year should be considered in their assessment. Furthermore, simulating the application of ETo models in irrigation scheduling can provide valuable information for choosing the most suitable model.
| S-EPMC7799801 | biostudies-literature
Project description:This study addresses the interactive effects of deficit irrigation and huanglongbing (HLB) infection on the physiological, biochemical, and oxidative stress responses of sweet orange trees. We sought to answer: (i) What are the causes for the reduction in water uptake in HLB infected plants? (ii) Is the water status of plants negatively affected by HLB infection? (iii) What are the key physiological traits impaired in HLB-infected plants? and (iv) What conditions can mitigate both disease severity and physiological/biochemical impairments in HLB-infected plants? Two water management treatments were applied for 11 weeks to 1-year-old-trees that were either healthy (HLB-) or infected with HLB (+) and grown in 12-L pots. Half of the trees were fully irrigated (FI) to saturation, whereas half were deficit-irrigated (DI) using 40% of the water required to saturate the substrate. Our results demonstrated that: reduced water uptake capacity in HLB+ plants was associated with reduced root growth, leaf area, stomatal conductance, and transpiration. Leaf water potential was not negatively affected by HLB infection. HLB increased leaf respiration rates (ca. 41%) and starch synthesis, downregulated starch breakdown, blocked electron transport, improved oxidative stress, and reduced leaf photosynthesis (ca. 57%) and photorespiration (ca.57%). Deficit irrigation reduced both leaf respiration (ca. 45%) and accumulation of starch (ca.53%) by increasing maltose (ca. 20%), sucrose, glucose, and fructose contents in the leaves, decreasing bacterial population (ca. 9%) and triggering a series of protective measures against further impairments in the physiology and biochemistry of HLB-infected plants. Such results provide a more complete physiological and biochemical overview of HLB-infected plants and can guide future studies to screen genetic tolerance to HLB and improve management strategies under field orchard conditions.
| S-EPMC8554030 | biostudies-literature
Project description:The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation water use efficiency, it is necessary to predict the water requirements for crops in advance. Reference evapotranspiration (ETo) is a hypothetical standard reference crop evapotranspiration, many types of artificial intelligence models have been applied to predict ETo; However, there are still few in the literature regarding the application of hybrid models for deep learning model parameters optimization. This paper proposes two hybrid models based on particle swarm optimization (PSO) and long-short-term memory (LSTM) neural network, used to predict ETo at the four climate stations, Shaanxi province, China. These two hybrid models were trained using 40 years of historical data, and the PSO was used to optimize the hyperparameters in the LSTM network. We applied the optimized model to predict the daily ETo in 2019 under different datasets, the result showed that the optimized model has good prediction accuracy. The optimized hybrid models can help farmers and irrigation planners to make plan earlier and precisely, and can provide valuable information to improve tasks such as irrigation planning.
| S-EPMC10112815 | biostudies-literature
Project description:BackgroundThe aim of this study was to determine the individual and interactive effects of various irrigation regimes and fertilizer treatments on the quality of the Wonderful pomegranate cultivar.MethodsTwo field experiments were conducted over two consecutive growing seasons (2018 and 2019) to determine the individual and interactive effects of various organic and mineral fertilizer treatments on the fruit quality of the Wonderful pomegranate under various irrigation conditions. A split-plot experimental design was used, in which the main plots included three levels of irrigation (100%, 80%, and 60% of evapotranspiration) while the subplots included five fertilizer treatments with different co-application ratios of mineral and organic fertilizers.ResultsAll tested physicochemical properties of the fruit were significantly affected by the irrigation treatment, with irrigation at 80% of evapotranspiration representing the best strategy for reducing water use and improving fruit quality. Moreover, the co-application of mineral and organic fertilizers had a significant effect on fruit quality, with 75% mineral + 25% organic fertilizer improving all of the physical and chemical properties of the fruit in both experimental seasons. Irrigation and the co-application of mineral and organic fertilizers also had a significant interaction effect on the physicochemical attributes of fruit, which further increased fruit quality.ConclusionsThe co-application of organic and mineral fertilizers produced better quality pomegranate fruit than mineral fertilizer alone under deficit irrigation conditions. This technique could therefore be applied to improve the fruiting of horticultural trees in arid growing regions.
| S-EPMC8139271 | biostudies-literature
Project description:Challenges exist for assessing the impacts of climate and climate change on the hydrological cycle on local and regional scales, and in turn on water resources, food, energy, and natural hazards. Potential evapotranspiration (PET) represents atmospheric demand for water, which is required at high spatial and temporal resolutions to compute actual evapotranspiration and thus close the water balance near the land surface for many such applications, but there are currently no available high-resolution datasets of PET. Here we develop an hourly PET dataset (hPET) for the global land surface at 0.1° spatial resolution, based on output from the recently developed ERA5-Land reanalysis dataset, over the period 1981 to present. We show how hPET compares to other available global PET datasets, over common spatiotemporal resolutions and time frames, with respect to spatial patterns of climatology and seasonal variations for selected humid and arid locations across the globe. We provide the data for users to employ for multiple applications to explore diurnal and seasonal variations in evaporative demand for water.
| S-EPMC8385079 | biostudies-literature
Project description:The study investigates the potential of two new machine learning methods, least-square support vector regression with a gravitational search algorithm (LSSVR-GSA) and the dynamic evolving neural-fuzzy inference system (DENFIS), for modeling reference evapotranspiration (ETo) using limited data. The results of the new methods are compared with the M5 model tree (M5RT) approach. Previous values of temperature data and extraterrestrial radiation information obtained from three stations, in China, are used as inputs to the models. The estimation exactness of the models is measured by three statistics: root mean square error, mean absolute error, and determination coefficient. According to the results, the temperature or extraterrestrial radiation-based LSSVR-GSA models perform superiorly to the DENFIS and M5RT models in terms of estimating monthly ETo. However, in some cases, a slight difference was found between the LSSVR-GSA and DENFIS methods. The results indicate that better prediction accuracy may be obtained using only extraterrestrial radiation information for all three methods. The prediction accuracy of the models is not generally improved by including periodicity information in the inputs. Using optimum air temperature and extraterrestrial radiation inputs together generally does not increase the accuracy of the applied methods in the estimation of monthly ETo.
| S-EPMC7517042 | biostudies-literature
Project description:Increasing vapor pressure deficit (VPD) increases atmospheric demand for water. While increased evapotranspiration (ET) in response to increased atmospheric demand seems intuitive, plants are capable of reducing ET in response to increased VPD by closing their stomata. We examine which effect dominates the response to increasing VPD: atmospheric demand and increases in ET or plant response (stomata closure) and decreases in ET. We use Penman-Monteith, combined with semiempirical optimal stomatal regulation theory and underlying water use efficiency, to develop a theoretical framework for assessing ET response to VPD. The theory suggests that depending on the environment and plant characteristics, ET response to increasing VPD can vary from strongly decreasing to increasing, highlighting the diversity of plant water regulation strategies. The ET response varies due to (1) climate, with tropical and temperate climates more likely to exhibit a positive ET response to increasing VPD than boreal and arctic climates; (2) photosynthesis strategy, with C3 plants more likely to exhibit a positive ET response than C4 plants; and (3) plant type, with crops more likely to exhibit a positive ET response, and shrubs and gymniosperm trees more likely to exhibit a negative ET response. These results, derived from previous literature connecting plant parameters to plant and climate characteristics, highlight the utility of our simplified framework for understanding complex land-atmosphere systems in terms of idealized scenarios in which ET responds to VPD only. This response is otherwise challenging to assess in an environment where many processes coevolve together.
| S-EPMC6919419 | biostudies-literature
Project description:Background and aimsShoot characteristics differ depending on the meristem tissue that they originate from and environmental conditions during their development. This study focused on the effects of plant water status on axillary meristem fate and flowering patterns along proleptic and epicormic shoots, as well as on shoot growth rates on 'Nonpareil' almond trees (Prunus dulcis). The aims were (1) to characterize the structural differences between proleptic and epicormic shoots, (2) to determine whether water deficits modify shoot structures differently depending on shoot type, and (3) to determine whether shoot structures are related to shoot growth rates.MethodsA hidden semi-Markov model of the axillary meristem fate and number of flower buds per node was built for two shoot types growing on trees exposed to three plant water status treatments. The models segmented observed shoots into successive homogeneous zones, which were compared between treatments. Shoot growth rates were calculated from shoot extension measurements made during the growing season.Key resultsProleptic shoots had seven successive homogeneous zones while epicormic shoots had five zones. Shoot structures were associated with changes in growth rate over the season. Water deficit (1) affected the occurrence and lengths of the first zones of proleptic shoots, but only the occurrence of the third zone was reduced in epicormic shoots; (2) had a minor effect on zone flowering patterns and did not modify shoot or zone composition of axillary meristem fates; and (3) reduced growth rates, although patterns over the season were similar among treatments.ConclusionsTwo meristem types, with different latency durations, produced shoots with different growth rates and distinct structures. Differences between shoot type structure responses to water deficit appeared to reflect their ontogenetic characteristics and/or resource availability for their development. Tree water deficit appeared to stimulate a more rapid progression through ontogenetic states.
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Project description:We investigated whether leaching fraction (LF) is able to modify the effects of irrigation water salinity (ECiw) on evapotranspiration (ET). We conducted an experiment with a completely randomized block design using five levels of ECiw and two LFs. Results showed that the electrical conductivity of drainage water (ECdw) in an LF of 0.29 was considerably higher during the 21-36 days after transplanting (DAT), and considerably lower after 50 DAT than in an LF of 0.17. The hourly, nighttime, daily, cumulative and seasonal ET all decreased considerably as a result of an increase in the ECiw. The daily ET started to be considerably higher in the LF of 0.29 than in the LF of 0.17 from 65 DAT. Compared with the LF of 0.17, the seasonal ET in the LF of 0.29 under various ECiw levels increased by 4.8%-8.7%. The Maas and Hoffman and van Genuchten and Hoffman models both corresponded well with the measured relative seasonal ET and the LF had no marked effects on these model parameters. Collectively, an increase in the level of ECiw always decreased the ET substantially. An increase in the LF increased the ET considerably, but there was a time lag.
| S-EPMC5543072 | biostudies-other
Project description:Accurate estimation of the reference evapotranspiration (ETo) is crucial for determining crop water requirements. However, the lack of appropriate weather stations representing croplands, particularly in drylands, may adversely influence the accuracy of ETo estimates. To overcome this issue, a promising approach is to use meteorological stations in cropland areas to collect weather data that are representative of actual conditions. However, the number of agrometeorological stations in these areas is limited. Therefore, this study aims to assess the effectiveness of three datasets, including ERA5 and ERA5-Land, and WaPOR (Water Productivity Open-access portal), for estimating ETo in cropland areas on a basin scale. The land use/land cover (LULC) of the European Space Agency (ESA) was used to identify the sites resembling agrometeorological stations. Data were collected from 2009 to 2022, and the FAO-Penman-Monteith method was used to estimate daily and monthly ETo. The accuracy and reliability of ETo estimates with the three datasets were evaluated by comparing them with ETo estimated by ground measurements. Statistical analysis metrics, normalized root mean squared error (nRMSE), and relative mean bias error (rMBE) were used to assess the performance of the datasets. This study highlights that ERA5 exhibited superior overall performance compared to other datasets in estimating ETo. However, WaPOR performed better at high-altitude stations with inhomogeneous topography than ECMWF reanalysis (i.e., ERA5 and ERA5-L). Thus, none of the datasets could provide accurate ETo estimates for all the stations within the basin. Therefore, applying the best-performing data source yielded better results than using a single dataset. These findings are valuable for improving irrigation scheduling and water management practices on a large scale, particularly in regions facing data scarcity challenges.
| S-EPMC10901012 | biostudies-literature