scholarly journals Modelling transpiration of soilless greenhouse cucumber and its relationship with leaf temperature in a Mediterranean climate

2018 ◽  
pp. 911 ◽  
Author(s):  
Georgios Nikolaou ◽  
Damianos Neocleous ◽  
Nikolaos Katsoulas, Constantinos Kittas
Keyword(s):  
Water Resource Management ◽  
Correlation Coefficients ◽  
Prediction Equation ◽  
Climatic Conditions ◽  
Leaf Temperature ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Winter Crop ◽  
Greenhouse Cucumber

Three experiments (spring and autumn-winter seasons) with soilless cucumber crop (cv. Phenomeno) were conducted in order: (i) to calibrate the simplified Penman -Monteith model equation as affected by greenhouse microclimate (ii) to validate the prediction efficiency of the model at different climatic conditions and (iii) to establish a relationship between transpiration and leaf temperature. To determine Penman-Monteith model parameter variables related to the plants such as transpiration and leaf area index (LAI), so as environmental variables (i.e., radiation, temperature, humidity) were recorded. The results revealed that the determined model parameters were suitable for the whole cucumber cultivation cycle and a wide range of climatic conditions. However, parameterization of the model using autumn-winter crop data revealed superiority compared to spring data, as indicated by the correlation coefficients. Model validation showed a good fit between simulates and measures allowing implementation in commercial soilless practices. With respect to greenhouse microclimate, cooling affected daily mean air temperature and vapor pressure deficit, so as model coefficients. Leaf temperature indicated a good correlation with transpiration and the prediction equation was validated under different greenhouse climatic conditions. These results may be of value in Mediterranean greenhouses, enabling a more efficient water resource management without significant losses in agricultural productivity.   

scholarly journals Growth analysis of chickpea (Cicer arietinum L.)

1994 ◽  
Vol 51 (3) ◽  
pp. 430-435 ◽  
Author(s):  
S.S.S. Nogueira ◽  
V. Nagai ◽  
N.R. Braga ◽  
M. Do C.S.S. Novo ◽  
M.B.P. Camargo
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Growth Analysis ◽  
Climatic Conditions ◽  
Area Index ◽  
Experimental Station ◽  
Matter Production ◽  
Winter Crop ◽  
Quadratic Models

An experiment to study the growing pattern of a chickpea variety, IAC-Marrocos, was carried out at the Monte Alegre Experimental Station, SP, during 1987 and 1988. The dry matter production of all parts of the plant, as well the leaf area index, were weekly evaluated. Exponential quadratic models of regression were adjusted to total dry matter, leaf dry matter and leaf area index, and a linear model to dry matter of grain. Based on the growth analysis it was concluded that the chickpea is a rustic eatable plant that can be recommended as an alternative winter crop for similar climatic conditions as those of the experiment.

scholarly journals Annual evapotranspiration retrieved solely from satellites' vegetation indices for the Eastern Mediterranean

2015 ◽  
Vol 15 (11) ◽  
pp. 15397-15429 ◽  
Author(s):  
D. Helman ◽  
I. M. Lensky ◽  
A. Givati
Keyword(s):  
Land Surface ◽  
Water Resource Management ◽  
Eastern Mediterranean ◽  
Vegetation Indices ◽  
Correlation Coefficients ◽  
Empirical Relationships ◽  
Rainfall Gradient ◽  
Proposed Model ◽  
Wide Range ◽  
Highly Correlated

Abstract. We present a simple model to retrieve actual evapotranspiration (ET) solely from satellites (PaVI-E). The model is based on empirical relationships between vegetation indices (NDVI and EVI from MODIS) and total annual ET (ETAnnual) from 16 FLUXNET sites representing a wide range of plant functional types and ETAnnual. The model was applied separately for (a) annual vegetation systems (i.e., croplands and grasslands) and (b) systems with combined annual and perennial vegetation (i.e., woodlands, forests, savannah and shrublands). It explained most of the variance in ETAnnual in those systems (71% for annuals, and 88% for combined annuals and perennials systems) while multiple regression and modified Temperature and Greenness models using also land surface temperature did not improve its performance (p > 0.1). PaVI-E was used to retrieve ETAnnual at 250 m spatial resolution for the Eastern Mediterranean from 2000 to 2014. Models' estimates were highly correlated (R = 0.92, p < 0.01) with ETAnnual calculated from water catchments balances along rainfall gradient in the Eastern Mediterranean. They were also comparable to the coarser resolution ET products of MSG (LSA-SAF MSG ETa, 3.1 km) and MODIS (MOD16, 1 km) at 148 Eastern Mediterranean basins with correlation coefficients (R) of 0.75 and 0.77 and relative bias of 5.2 and −5.2%, respectively (p < 0.001 for both). The proposed model is expected to contribute to hydrological study in the Eastern Mediterranean assisting in water resource management, which is one of the most valuable resources of this region.

scholarly journals Inoculant, nitrogen and phosphorus improves photosynthesis and water-use efficiency in soybean production

2021 ◽  
pp. 1-14
Author(s):  
C. E. N. Savala ◽  
A. N. Wiredu ◽  
J. O. Okoth ◽  
S. Kyei-Boahen
Keyword(s):  
Water Use Efficiency ◽  
Water Use ◽  
Management Practices ◽  
Climatic Conditions ◽  
Growth Stages ◽  
Nitrogen And Phosphorus ◽  
Area Index ◽  
Physiological Processes ◽  
Wide Range ◽  
Use Efficiency

Abstract Soybean yield within the Southern Africa falls below its potential despite similar climatic conditions across some agroecologies, replicable agronomic management practices and introduced improved varieties. Understanding physiological processes and water-use efficiency (WUE) of soybean offer information on bridging this yield gap. A field study was conducted in 2017 and 2018 seasons in two agroecologies (Angonia and Ruace) in Mozambique to evaluate the effects of Bradyrhizobium diazoefficiens strain USDA110 formerly known as Bradyrhizobium japonicum inoculant, nitrogen and phosphorus on nodulation, physiology and yield of non-promiscuous (Safari) and promiscuous (TGx 1740-2F) soybean varieties. Data on transpiration, photosynthesis, leaf area index, radiation interception and WUE from the beginning of flowering to maturity were collected. Transpiration rate varied considerably with interaction between locations, growth stages, varieties and treatments. At podding, phosphorus-treated soybean at Angonia transpired less (6.3 mmol/m2/s) than check plants (6.6 mmol/m2/s). Photosynthesis rate and WUE were distinct with variety, growth stages and inputs within agroecologies. For instance, in Angonia 2018 season, phosphorus fertilized TGx 1740-2F photosynthesized more at flowering (25.3 μmol/m2/s) while the lowest was phosphorus-treated Safari at podding with 17.2 μmol/m2/s. At the same site in 2017, inoculated soybean photosynthesized more at 22.8 μmol/m2/s leading to better WUE of 3.6 that corresponded to 2894 kg/ha yield. Overall, soybean WUE was higher when inoculated than N-treated, while P application yielded better. Results from this study will complement breeders’ effort in developing phosphorus efficient varieties suited for a wide range of changing climatical conditions.

scholarly journals Model parameters of four important vegetable crops for improved water use and yield estimation

Water SA ◽  
2018 ◽  
Vol 44 (4 October) ◽  
Author(s):  
JT Vahrmeijer ◽  
JG Annandale ◽  
JM Steyn ◽  
KL Bristow
Keyword(s):  
Water Use ◽  
Growth Parameters ◽  
Water Productivity ◽  
Resource Planning ◽  
Crop Growth ◽  
Climatic Conditions ◽  
Model Parameters ◽  
Vegetable Production ◽  
Vegetable Crops ◽  
Wide Range

High-value vegetable crops are typically grown under irrigation to reduce production risk. For water resource planning it is essential to be able to accurately estimate water use of irrigated crops under a wide range of climatic conditions. Crop water use models provide a means to make water use and yield estimates, but need crop- and even cultivar-specific parameters. There is generally a lack of crop-specific model parameters for some important commercially grown vegetable crops, especially parameters determined over both summer and winter seasons. The experimental site used in this study was on the Steenkoppies Aquifer, a catchment under stress and an important vegetable production area in South Africa. Crop-specific growth parameters and water use for 4 selected high-value vegetable crops (beetroot, cabbage, carrots and broccoli) were measured over multiple seasons (two summers and one winter). These were used to parameterise the Soil Water Balance (SWB) generic crop growth model for both summer and winter seasons. In seasons where the same cultivar was planted, a single set of model parameters could be used to successfully simulate crop growth and water use. Results show that the amount of irrigation water required is dependent on season and rainfall, with broccoli having the lowest (1.8–2.7 kg m−3) and beetroot the highest (12.2–23.4 kg m−3) water productivity (WPFM), defined as fresh mass of marketable product per unit water consumed. The root crops had a greater harvest index (HIDM) than cabbage and broccoli. The parameters obtained expand the current database of SWB crop growth parameters for vegetables and can be used in a wide range of mechanistic simulation models to improve water management at field and catchment levels.

scholarly journals Modelling LAI at a regional scale with ISBA-A-gs: comparison with satellite-derived LAI over southwestern France

2009 ◽  
Vol 6 (8) ◽  
pp. 1389-1404 ◽  
Author(s):  
A. Brut ◽  
C. Rüdiger ◽  
S. Lafont ◽  
J.-L. Roujean ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Land Surface ◽  
Regional Scale ◽  
Land Surface Model ◽  
Temperature Response ◽  
Climatic Conditions ◽  
Surface Model ◽  
Model Parameters ◽  
Area Index ◽  
Satellite Signal

Abstract. A CO2-responsive land surface model (the ISBA-A-gs model of Météo-France) is used to simulate photosynthesis and Leaf Area Index (LAI) in southwestern France for a 3-year period (2001–2003). A domain of about 170 000 km2 is covered at a spatial resolution of 8 km. The capability of ISBA-A-gs to reproduce the seasonal and the interannual variability of LAI at a regional scale, is assessed with satellite-derived LAI products. One originates from the CYCLOPES programme using SPOT/VEGETATION data, and two products are based on MODIS data. The comparison reveals discrepancies between the satellite LAI estimates and between satellite and simulated LAI values, both in their intensity and in the timing of the leaf onset. The model simulates higher LAI values for the C3 crops than the satellite observations, which may be due to a saturation effect within the satellite signal or to uncertainties in model parameters. The simulated leaf onset presents a significant delay for C3 crops and mountainous grasslands. In-situ observations at a mid-altitude grassland site show that the generic temperature response of photosynthesis used in the model is not appropriate for plants adapted to the cold climatic conditions of the mountainous areas. This study demonstrates the potential of LAI remote sensing products for identifying and locating models' shortcomings at a regional scale.

scholarly journals CO<sub>2</sub> fluxes and ecosystem dynamics at five European treeless peatlands – merging data and process oriented modelling

2014 ◽  
Vol 11 (6) ◽  
pp. 9249-9297
Author(s):  
C. Metzger ◽  
P.-E. Jansson ◽  
A. Lohila ◽  
M. Aurela ◽  
T. Eickenscheidt ◽  
...  
Keyword(s):  
Water Table ◽  
Photosynthetic Efficiency ◽  
Heterotrophic Respiration ◽  
Soil Conditions ◽  
Model Parameters ◽  
Co2 Fluxes ◽  
Area Index ◽  
Wide Range ◽  
Process Oriented ◽  
Organic Decomposition

Abstract. The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

scholarly journals Pan-Arctic modelling of net ecosystem exchange of CO 2

2013 ◽  
Vol 368 (1624) ◽  
pp. 20120485 ◽  
Author(s):  
G. R. Shaver ◽  
E. B. Rastetter ◽  
V. Salmon ◽  
L. E. Street ◽  
M. J. van de Weg ◽  
...  
Keyword(s):  
Leaf Area ◽  
Air Temperature ◽  
Net Ecosystem Exchange ◽  
Light Response ◽  
The Arctic ◽  
Model Parameters ◽  
Arctic Ecosystems ◽  
Area Index ◽  
Wide Range ◽  
Single Regression

Net ecosystem exchange (NEE) of C varies greatly among Arctic ecosystems. Here, we show that approximately 75 per cent of this variation can be accounted for in a single regression model that predicts NEE as a function of leaf area index (LAI), air temperature and photosynthetically active radiation (PAR). The model was developed in concert with a survey of the light response of NEE in Arctic and subarctic tundras in Alaska, Greenland, Svalbard and Sweden. Model parametrizations based on data collected in one part of the Arctic can be used to predict NEE in other parts of the Arctic with accuracy similar to that of predictions based on data collected in the same site where NEE is predicted. The principal requirement for the dataset is that it should contain a sufficiently wide range of measurements of NEE at both high and low values of LAI, air temperature and PAR, to properly constrain the estimates of model parameters. Canopy N content can also be substituted for leaf area in predicting NEE, with equal or greater accuracy, but substitution of soil temperature for air temperature does not improve predictions. Overall, the results suggest a remarkable convergence in regulation of NEE in diverse ecosystem types throughout the Arctic.

scholarly journals How can the First ISLSCP Field Experiment contribute to present-day efforts to evaluate water stress in JULESv5.0?

2019 ◽  
Vol 12 (7) ◽  
pp. 3207-3240 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Now, 30 years on, we demonstrate how the wealth of data collected during FIFE and its subsequent in-depth analysis in the literature continue to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating “unstressed” vegetation parameters and thresholds for water stress. In particular, the responses to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Revisiting the First ISLSCP Field Experiment to evaluate water stress in JULESv5.0

2018 ◽  
Author(s):  
Karina E. Williams ◽  
Anna B. Harper ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Camilla T. Mathison ◽  
...  
Keyword(s):  
Water Stress ◽  
Field Experiment ◽  
Tallgrass Prairie ◽  
Land Surface ◽  
Carbon Assimilation ◽  
Model Parameters ◽  
Area Index ◽  
Wide Range ◽  
Dry Spell ◽  
Depth Analysis

Abstract. The First ISLSCP Field Experiment (FIFE), Kansas, US, 1987–1989, made important contributions to the understanding of energy and CO2 exchanges between the land-surface and the atmosphere, which heavily influenced the development of numerical land-surface modelling. Thirty years on, we demonstrate how the wealth of data collected at FIFE and its subsequent in-depth analysis in the literature continues to be a valuable resource for the current generation of land-surface models. To illustrate, we use the FIFE dataset to evaluate the representation of water stress on tallgrass prairie vegetation in the Joint UK Land Environment Simulator (JULES) and highlight areas for future development. We show that, while JULES is able to simulate a decrease in net carbon assimilation and evapotranspiration during a dry spell, the shape of the diurnal cycle is not well captured. Evaluating the model parameters and results against this dataset provides a case study on the assumptions in calibrating "unstressed" vegetation parameters and thresholds for water stress. In particular, the response to low water availability and high temperatures are calibrated separately. We also illustrate the effect of inherent uncertainties in key observables, such as leaf area index, soil moisture and soil properties. Given these valuable lessons, simulations for this site will be a key addition to a compilation of simulations covering a wide range of vegetation types and climate regimes, which will be used to improve the way that water stress is represented within JULES.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

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