scholarly journals Artificial solar radiation protection of raspberry plantation

2020 ◽  
Author(s):  
K. Szalay ◽  
B. Keller ◽  
R. Rák ◽  
N. Péterfalvi ◽  
L. Kovács ◽  
...  
Keyword(s):  
Climate Change ◽  
High Temperature ◽  
Biological Indicators ◽  
Solar Irradiation ◽  
Light Use Efficiency ◽  
Proximal Sensing ◽  
Direct Radiation ◽  
Wide Range ◽  
Imaging Camera ◽  
Use Efficiency

AbstractOne of the biggest challenges of raspberry production in Hungary nowadays is reducing the unfavorable effects of climate change. The maturation phase of main varieties within this region falls in a period of extremely high temperature and atmospheric drought detaining desirable fruit growth. Dedicated plant breeding alone is not enough. An immediate action is required. There has been a need for physical protection against excessive direct radiation. In order to restore, or even save the domestic raspberry production and market, introducing of greenhouse or polytunnel solutions are needed. Experimental plantations of three different raspberry varieties were set in two repetitions: covered and uncovered versions. Each cover has characteristic interaction with light which can generate different environmental conditions and also differences in plant growth and fruit quality. Besides the monitoring of elementary biological indicators, a wide range of sensors (temperature, humidity, solar irradiation) was used to identify differences and to find the optimal tunnel material for maximal plant productivity. Within the framework of the project we also tested a portable spectroradiometer and a snapshot imaging camera to study the practical value of proximal sensing in water- and photosynthetic light use efficiency and vitality mapping.

scholarly journals Remote sensing of ecosystem light use efficiency with MODIS-based PRI

2011 ◽  
Vol 8 (1) ◽  
pp. 189-202 ◽  
Author(s):  
A. Goerner ◽  
M. Reichstein ◽  
E. Tomelleri ◽  
N. Hanan ◽  
S. Rambal ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Vapour Pressure Deficit ◽  
Ground Truth ◽  
Light Use Efficiency ◽  
Wide Range ◽  
Evaluation Exercise ◽  
Use Efficiency ◽  
Study Sites ◽  
Absorbed Photosynthetically Active Radiation

Abstract. Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the effectiveness with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependence on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well.

scholarly journals P-model v1.0: An optimality-based light use efficiency model for simulating ecosystem gross primary production

2019 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Primary Production ◽  
Satellite Data ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth System Model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a gross primary production (GPP, photosynthesis per unit ground area) model, the P-model, that combines the Farquhar-von Caemmerer-Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation-transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model is forced here with satellite data for the fraction of absorbed photosynthetically active radiation and site-specific meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs and prescribed parameters, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8-day mean, 131 sites) – better than some state-of-the-art satellite data-driven light use efficiency models. The R2 is reduced to 0.69 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.37 (means by site) and 0.53 (means by vegetation type). The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosythesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

2020 ◽  
Vol 13 (3) ◽  
pp. 1545-1581 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Quantum Yield ◽  
Primary Production ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr−1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals Optimization of forest age-dependent light-use efficiency and its implications on climate-vegetation interactions in china

2015 ◽  
Vol XL-7/W3 ◽  
pp. 449-454 ◽  
Author(s):  
Z. Li ◽  
T. Zhou
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Forest Stand ◽  
Stand Age ◽  
Light Use Efficiency ◽  
Forest Age ◽  
Middle Aged ◽  
Broadleaf Forest ◽  
Age Dependent ◽  
Use Efficiency

Forest’s net primary productivity (NPP) is a key index in studying interactions of climate and vegetation, and accurate prediction of NPP is essential to understand the forests’ response to climate change. The magnitude and trends of forest NPP not only depend on climate factors (e.g., temperature and precipitation), but also on the succession stages (i.e., forest stand age). Although forest stand age plays a significant role on NPP, it is usually ignored by remote sensing-based models. In this study, we used remote sensing data and meteorological data to estimate forest NPP in China based on CASA model, and then employed field observations to inversely estimate the parameter of maximum light-use efficiency (ε<sub>max</sub>) of forests in different stand ages. We further developed functions to describe the relationship between maximum light-use efficiency (ε<sub>max</sub>) and forest stand age, and estimated forest age-dependent NPP based on these functions. The results showed that ε<sub>max</sub> has changed according to forest types and the forest stand age. For deciduous broadleaf forest, the average ε<sub>max</sub> of young, middle-aged and mature forest are 0.68, 0.65 and 0.60 gC MJ<sup>-1</sup>. For evergreen broadleaf forest, the average εmax of young, middle-aged and mature forests are 1.05, 1.01 and 0.99 gC MJ<sup>-1</sup>. For evergreen needleleaf forest, the average ε<sub>max</sub> of young, middle-aged and mature forests are 0.72, 0.57 and 0.52 gC MJ<sup>-1</sup>.The NPP of young and middle-aged forests were underestimated based on a constant ε<sub>max</sub>. Young forests and middle-aged forests had higher ε<sub>max</sub>, and they were more sensitive to trends and fluctuations of climate change, so they led to greater annual fluctuations of NPP. These findings confirm the importance of considering forest stand age to the estimation of NPP and they are significant to study the response of forests to climate change.

scholarly journals Evaluation and Comparison of Light Use Efficiency and Gross Primary Productivity Using Three Different Approaches

2020 ◽  
Vol 12 (6) ◽  
pp. 1003 ◽  
Author(s):  
Mengjia Wang ◽  
Rui Sun ◽  
Anran Zhu ◽  
Zhiqiang Xiao
Keyword(s):  
Primary Productivity ◽  
Regression Tree ◽  
Gross Primary Productivity ◽  
Light Use Efficiency ◽  
Validation Data ◽  
Direct Radiation ◽  
Lower Accuracy ◽  
Use Efficiency ◽  
Tree Approach ◽  
Better Than

Light use efficiency (LUE), which characterizes the efficiency with which vegetation converts captured/absorbed radiation into organic dry matter through photosynthesis, is a key parameter for estimating vegetation gross primary productivity (GPP). Studies suggest that diffuse radiation induces a higher LUE than direct radiation in short-term and site-scale experiments. The clearness index (CI), described as the fraction of solar incident radiation on the surface of the earth to the extraterrestrial radiation at the top of the atmosphere, is added to the parameterization approach to explain the conditions of diffuse and direct radiation in this study. Machine learning methods—such as the Cubist regression tree approach—are also popular approaches for studying vegetation carbon uptake. This paper aims to compare and analyze the performances of three different approaches for estimating global LUE and GPP. The methods for collecting LUE were based on the following: (1) parameterization approach without CI; (2) parameterization approach with CI; and (3) Cubist regression tree approach. We collected GPP and meteorological data from 180 FLUXNET sites as calibration and validation data and the Global Land Surface Satellite (GLASS) products and ERA-interim data as input data to estimate the global LUE and GPP in 2014. Site-scale validation with FLUXNET measurements indicated that the Cubist regression approach performed better than the parameterization approaches. However, when applying the approaches to global LUE and GPP, the parameterization approach with the CI became the most reliable approach, then closely followed by the parameterization approach without the CI. Spatial analysis showed that the addition of the CI improved the LUE and GPP, especially in high-value zones. The results of the Cubist regression tree approach illustrate more fluctuations than the parameterization approaches. Although the distributions of LUE presented variations over different seasons, vegetation had the highest LUE, at approximately 1.5 gC/MJ, during the whole year in equatorial regions (e.g., South America, middle Africa and Southeast Asia). The three approaches produced roughly consistent global annual GPPs ranging from 109.23 to 120.65 Pg/yr. Our results suggest the parameterization approaches are robust when extrapolating to the global scale, of which the parameterization approach with CI performs slightly better than that without CI. By contrast, the Cubist regression tree produced LUE and GPP with lower accuracy even though it performed the best for model validation at the site scale.

scholarly journals Remote sensing of ecosystem light use efficiency with MODIS-based PRI – the DOs and DON'Ts

2010 ◽  
Vol 7 (5) ◽  
pp. 6935-6969 ◽  
Author(s):  
A. Goerner ◽  
M. Reichstein ◽  
E. Tomelleri ◽  
N. Hanan ◽  
S. Rambal ◽  
...  
Keyword(s):  
Meteorological Data ◽  
Vapour Pressure Deficit ◽  
Ground Truth ◽  
Light Use Efficiency ◽  
Wide Range ◽  
Evaluation Exercise ◽  
Use Efficiency ◽  
Study Sites ◽  
Absorbed Photosynthetically Active Radiation

Abstract. Several studies sustained the possibility that a photochemical reflectance index (PRI) directly obtained from satellite data can be used as a proxy for ecosystem light use efficiency (LUE) in diagnostic models of gross primary productivity. This modelling approach would avoid the complications that are involved in using meteorological data as constraints for a fixed maximum LUE. However, no unifying model predicting LUE across climate zones and time based on MODIS PRI has been published to date. In this study, we evaluate the efficiency with which MODIS-based PRI can be used to estimate ecosystem light use efficiency at study sites of different plant functional types and vegetation densities. Our objective is to examine if known limitations such as dependance on viewing and illumination geometry can be overcome and a single PRI-based model of LUE (i.e. based on the same reference band) can be applied under a wide range of conditions. Furthermore, we were interested in the effect of using different faPAR (fraction of absorbed photosynthetically active radiation) products on the in-situ LUE used as ground truth and thus on the whole evaluation exercise. We found that estimating LUE at site-level based on PRI reduces uncertainty compared to the approaches relying on a maximum LUE reduced by minimum temperature and vapour pressure deficit. Despite the advantages of using PRI to estimate LUE at site-level, we could not establish an universally applicable light use efficiency model based on MODIS PRI. Models that were optimised for a pool of data from several sites did not perform well.

Application of TEM to Deformation, Wear, and Fracture of Ceramics

1974 ◽  
Vol 32 ◽  
pp. 472-473
Author(s):  
B. J. Hockey
Keyword(s):  
Wear Resistance ◽  
High Temperature ◽  
Mechanical Behavior ◽  
Brittle Materials ◽  
High Temperature Strength ◽  
Wide Range ◽  
Corrosive Environments ◽  
Further Development

Ceramics, such as Al2O3 and SiC have numerous current and potential uses in applications where high temperature strength, hardness, and wear resistance are required often in corrosive environments. These materials are, however, highly anisotropic and brittle, so that their mechanical behavior is often unpredictable. The further development of these materials will require a better understanding of the basic mechanisms controlling deformation, wear, and fracture.The purpose of this talk is to describe applications of TEM to the study of the deformation, wear, and fracture of Al2O3. Similar studies are currently being conducted on SiC and the techniques involved should be applicable to a wide range of hard, brittle materials.

TEM study of boron additions to cobalt aluminide

1988 ◽  
Vol 46 ◽  
pp. 546-547
Author(s):  
Gerald B. Feldewerth
Keyword(s):  
High Temperature ◽  
Turbine Engines ◽  
Major Drawback ◽  
University Of Missouri ◽  
Specific Strength ◽  
Aerospace Applications ◽  
Wide Range ◽  
Ordered Alloys ◽  
The University ◽  
Very High

In recent years an increasing emphasis has been placed on the study of high temperature intermetallic compounds for possible aerospace applications. One group of interest is the B2 aiuminides. This group of intermetaliics has a very high melting temperature, good high temperature, and excellent specific strength. These qualities make it a candidate for applications such as turbine engines. The B2 aiuminides exist over a wide range of compositions and also have a large solubility for third element substitutional additions, which may allow alloying additions to overcome their major drawback, their brittle nature.One B2 aluminide currently being studied is cobalt aluminide. Optical microscopy of CoAl alloys produced at the University of Missouri-Rolla showed a dramatic decrease in the grain size which affects the yield strength and flow stress of long range ordered alloys, and a change in the grain shape with the addition of 0.5 % boron.

PLATINUM

Alloy Digest ◽  
1970 ◽  
Vol 19 (11) ◽  
Keyword(s):  
Corrosion Resistance ◽  
High Temperature ◽  
Heat Treating ◽  
Industrial Applications ◽  
High Melting ◽  
High Melting Point ◽  
White Metal ◽  
Temperature Performance ◽  
Wide Range ◽  
Corrosion And Oxidation

Abstract PLATINUM is a soft, ductile, white metal which can be readily worked either hot or cold. It has a wide range of industrial applications because of its excellent corrosion and oxidation resistance and its high melting point. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties. It also includes information on high temperature performance and corrosion resistance as well as forming, heat treating, machining, and joining. Filing Code: Pt-1. Producer or source: Matthey Bishop Inc..

ACI TYPE HN

Alloy Digest ◽  
1982 ◽  
Vol 31 (6) ◽  
Keyword(s):  
Stainless Steel ◽  
Corrosion Resistance ◽  
High Temperature ◽  
Steel Casting ◽  
Nickel Content ◽  
Heat Treating ◽  
High Temperature Corrosion ◽  
Temperature Performance ◽  
Wide Range ◽  
Iron Chromium

Abstract Type HN is an iron-chromium-nickel alloy containing sufficient chromium for good high-temperature corrosion resistance and with nickel content in excess of the chromium. This alloy has properties somewhat similar to the more widely used ACI Type HT alloy but with better ductility. Type HN is used for highly stressed components in the 1800-2000 F temperature range. It is used in the aircraft, automotive, petroleum, petrochemical and power industries for a wide range of components and parts. This datasheet provides information on composition, physical properties, hardness, elasticity, and tensile properties as well as creep. It also includes information on high temperature performance and corrosion resistance as well as casting, heat treating, machining, and joining. Filing Code: SS-410. Producer or source: Various stainless steel casting companies.

Sign in / Sign up

Export Citation Format

Share Document