A multi-scale "soil water structure" model based on the pedostructure concept

International audienceCurrent soil water models do not take into account the internal organization of the soil medium and, consequently, ignore the physical interaction between the water film at the surface of solids making the soil structure, and this structure. In that sense they empirically deal with the physical soil properties that are all generated from this soil water – structure interaction. As a result, the thermodynamic state of the soil water medium, which constitutes the local physical conditions, namely the pedo-climate, for biological and geo-chemical processes in soil, is not defined in these models. The omission of soil structure from soil characterization and modeling does not allow for coupling disciplinary models for these processes with soil water models. The objective of the article is to present a soil water structure model, Kamel®, which should be liable to open the deadlocks above-mentioned. This computer model was developed based on a new paradigm in soil physics where the hierarchical soil structure is taken into account allowing for defining its thermodynamic properties. After a review of soil physics principles which forms the basis of the paradigm, we describe the basic relationships and functionality of the model. Kamel® runs with a set of 15 soil input parameters, the pedohydral parameters, which are parameters of the physically-based equations of four soil characteristic curves that can be measured in the laboratory. For cases where some of these parameters are not available, we show how to estimate these parameters from commonly available soil information using published pedotransfer functions. A published field experimental study on the dynamics of the soil moisture profile following a pounding infiltration rainfall event was used as an example to demonstrate soil characterization and Kamel® simulations. The simulated soil moisture profile for a period of 60 days showed very good agreement with experimental field data. Simulations using input data calculated from soil texture and pedotransfer functions were also generated and compared to simulations of the more ideal characterization. The later comparison illustrates how Kamel® can be used and adapt to any case of soil data availability. As physically based model on soil structure, it may be used as a standard reference to evaluate other soil-water models and also pedotransfer functions at a given location or agronomical situation

The development of automated spatial and temporal measurement system for lab-scale local scour

The spatial and temporal measurements of local scour around bridge piers provide the quantification of local scouring process. Most studies on a laboratory scale faced difficulties in obtaining a holistic local spatial variability around bridge pier, especially for continuous small time interval. Long experimental period, which could take up to few days, does not permit a consistent time interval spatial scour measurement due in particular to the physical constraints that exist under laboratory conditions. This study proposed an automated, cost-effective system which is capable of detecting changes in both spatial and temporal local scour. The system allows measurement to be made by using data recorder at an adjustable distance (± 0.1 mm) and angle (± 0.1˚) from the original position, which is programmed and controlled with an Arduino, which is an open source microcontroller with multiple capability of controlling electrical components such as motors and sensors. When the data recorder is in position, data is automatically captured and sequentially saved at a particular spatial interval. In this study, a web camera was used as a data recorder to capture images in the azimuthal plane for a one-hour interval. Images were captured for 30 seconds per measurement per position. The system was set up to monitor and measure the temporal and spatial local scour continuously in an 80-hour experiment. Results show that the location of maximum scour depth varied for different time intervals, and migrated from downstream to upstream of the pier. The rate of scour decreased as duration of experiment was increased. The system was able to provide a holistic view of both spatial and temporal variability in the development of local scour on a laboratory scale

A Viral Protein Mediates Superinfection Exclusion at the Whole-Organism Level but Is Not Required for Exclusion at the Cellular Level

Superinfection exclusion (SIE), the ability of an established virus infection to interfere with a secondary infection by the same or a closely related virus, has been described for different viruses, including important pathogens of humans, animals, and plants. Citrus tristeza virus (CTV), a positive-sense RNA virus, represents a valuable model system for studying SIE due to the existence of several phylogenetically distinct strains. Furthermore, CTV allows SIE to be examined at the whole-organism level. Previously, we demonstrated that SIE by CTV is a virus-controlled function that requires the viral protein p33. In this study, we show that p33 mediates SIE at the whole-organism level, while it is not required for exclusion at the cellular level. Primary infection of a host with a fluorescent protein-tagged CTV variant lacking p33 did not interfere with the establishment of a secondary infection by the same virus labeled with a different fluorescent protein. However, cellular coinfection by both viruses was rare. The obtained observations, along with estimates of the cellular multiplicity of infection (MOI) and MOI model selection, suggested that low levels of cellular coinfection appear to be best explained by exclusion at the cellular level. Based on these results, we propose that SIE by CTV is operated at two levels-the cellular and the whole-organism levels-by two distinct mechanisms that could function independently. This novel aspect of viral SIE highlights the intriguing complexity of this phenomenon, further understanding of which may open up new avenues to manage virus diseases.Peer reviewe

Agroinoculation of Citrus tristeza virus Causes Systemic Infection and Symptoms in the Presumed Nonhost Nicotiana benthamiana

Citrus tristeza virus (CTV) naturally infects only some citrus species and relatives and within these it only invades phloem tissues. Failure to agroinfect citrus plants and the lack of an experimental herbaceous host hindered development of a workable genetic system. A full-genome cDNA of CTV isolate T36 was cloned in binary plasmids and was used to agroinfiltrate Nicotiana benthamiana leaves, with or without coinfiltration with plasmids expressing different silencing-suppressor proteins. A time course analysis in agroinfiltrated leaves indicated that CTV accumulates and moves cell-to-cell for at least three weeks postinoculation (wpi), and then, it moves systemically and infects the upper leaves with symptom expression. Silencing suppressors expedited systemic infection and often increased infectivity. In systemically infected Nicotiana benthamiana plants, CTV invaded first the phloem, but after 7 wpi, it was also found in other tissues and reached a high viral titer in upper leaves, thus allowing efficient transmission to citrus by stem-slash inoculation. Infected citrus plants showed the symptoms, virion morphology, and phloem restriction characteristic of the wild T36 isolate. Therefore, agroinfiltration of Nicotiana benthamiana provided the first experimental herbaceous host for CTV and an easy and efficient genetic system for this closterovirus

Survey of Leafhopper Species in Almond Orchards Infected with Almond Witches'-Broom Phytoplasma in Lebanon

Leafhoppers (Hemiptera: Auchenorrhyncha: Cicadellidae) account for more than 80% of all “Auchenorrhynchous” vectors that transmit phytoplasmas. The leafhopper populations in two almond witches'-broom phytoplasma (AlmWB) infected sites: Tanboureet (south of Lebanon) and Bourj El Yahoudieh (north of Lebanon) were surveyed using yellow sticky traps. The survey revealed that the most abundant species was Asymmetrasca decedens, which represented 82.4% of all the leafhoppers sampled. Potential phytoplasma vectors in members of the subfamilies Aphrodinae, Deltocephalinae, and Megophthalminae were present in very low numbers including: Aphrodes makarovi, Cicadulina bipunctella, Euscelidius mundus, Fieberiella macchiae, Allygus theryi, Circulifer haematoceps, Neoaliturus transversalis, and Megophthalmus scabripennis. Allygus theryi (Horváth) (Deltocephalinae) was reported for the first time in Lebanon. Nested PCR analysis and sequencing showed that Asymmetrasca decedens, Empoasca decipiens, Fieberiella macchiae, Euscelidius mundus, Thamnottetix seclusis, Balclutha sp., Lylatina inexpectata, Allygus sp., and Annoplotettix danutae were nine potential carriers of AlmWB phytoplasma. Although the detection of phytoplasmas in an insect does not prove a definite vector relationship, the technique is useful in narrowing the search for potential vectors. The importance of this information for management of AlmWB is discussed

Towards an end-to-end analysis and prediction system for weather, climate, and Marine applications in the Red Sea

AbstractThe Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.</jats:p

Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the Red Sea

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(1), (2021): E99-E122, https://doi.org/10.1175/BAMS-D-19-0005.1.The Red Sea, home to the second-longest coral reef system in the world, is a vital resource for the Kingdom of Saudi Arabia. The Red Sea provides 90% of the Kingdom’s potable water by desalinization, supporting tourism, shipping, aquaculture, and fishing industries, which together contribute about 10%–20% of the country’s GDP. All these activities, and those elsewhere in the Red Sea region, critically depend on oceanic and atmospheric conditions. At a time of mega-development projects along the Red Sea coast, and global warming, authorities are working on optimizing the harnessing of environmental resources, including renewable energy and rainwater harvesting. All these require high-resolution weather and climate information. Toward this end, we have undertaken a multipronged research and development activity in which we are developing an integrated data-driven regional coupled modeling system. The telescopically nested components include 5-km- to 600-m-resolution atmospheric models to address weather and climate challenges, 4-km- to 50-m-resolution ocean models with regional and coastal configurations to simulate and predict the general and mesoscale circulation, 4-km- to 100-m-resolution ecosystem models to simulate the biogeochemistry, and 1-km- to 50-m-resolution wave models. In addition, a complementary probabilistic transport modeling system predicts dispersion of contaminant plumes, oil spill, and marine ecosystem connectivity. Advanced ensemble data assimilation capabilities have also been implemented for accurate forecasting. Resulting achievements include significant advancement in our understanding of the regional circulation and its connection to the global climate, development, and validation of long-term Red Sea regional atmospheric–oceanic–wave reanalyses and forecasting capacities. These products are being extensively used by academia, government, and industry in various weather and marine studies and operations, environmental policies, renewable energy applications, impact assessment, flood forecasting, and more.The development of the Red Sea modeling system is being supported by the Virtual Red Sea Initiative and the Competitive Research Grants (CRG) program from the Office of Sponsored Research at KAUST, Saudi Aramco Company through the Saudi ARAMCO Marine Environmental Center at KAUST, and by funds from KAEC, NEOM, and RSP through Beacon Development Company at KAUST

Evaluation of commercial soy sauce koji strains of Aspergillus oryzae for γ-aminobutyric acid (GABA) production

In this study, four selected commercial strains of Aspergillus oryzae were collected from soy sauce koji. These A. oryzae strains designated as NSK, NSZ, NSJ and NST shared similar morphological characteristics with the reference strain (A. oryzae FRR 1675) which confirmed them as A. oryzae species. They were further evaluated for their ability to produce γ-aminobutyric acid (GABA) by cultivating the spore suspension in a broth medium containing 0.4 % (w/v) of glutamic acid as a substrate for GABA production. The results showed that these strains were capable of producing GABA; however, the concentrations differed significantly (P < 0.05) among themselves. Based on the A. oryzae strains, highest GABA concentration was obtained from NSK (194 mg/L) followed by NSZ (63 mg/L), NSJ (51.53 mg/L) and NST (31.66 mg/L). Therefore, A. oryzae NSK was characterized and the sequence was found to be similar to A. oryzae and A. flavus with 99 % similarity. The evolutionary distance (K nuc) between sequences of identical fungal species was calculated and a phylogenetic tree prepared from the K nuc data showed that the isolate belonged to the A. oryzae species. This finding may allow the development of GABA-rich ingredients using A. oryzae NSK as a starter culture for soy sauce production