Mycoplasma capricolum subsp. capricolum (Mcc) is an important etiological agent of contagious agalactia (CA). CA affects small ruminants and is characterized by inducing mastitis, arthritis, kerato-conjunctivitis and respiratory symptoms. The aim of this study was to isolate and characterize Mcc from Moroccan goats with contagious agalactia. A total of 300 Alpine goats were monitored. Serology analysis, molecular identification, and isolation of Mcc were realized from suspected goats. An experimental study was conducted for isolated Mcc to determine their pathogenicity. Thus, clinical observation showed that respiratory symptoms were predominant in young animals, and other symptoms, such as mastitis, keratoconjunctivitis and lameness, were more frequently detected in adult goats. Of the 80 tested blood samples, 28 sera were seropositive for Mcc antibodies. Mcc was identified by polymerase chain reaction (PCR) in milk, lung tissue and synovial liquid samples. The isolation of Mcc was successful through bacterial culture from lung tissue. LppA gene sequence of this strain revealed 98.1% similarity with the reference strain (ATCC 27343), with 11 missense variants. Experimental infection resulted in severe and generalized CA disease in sheep and goats, confirming the high pathogenicity of the Moroccan Mcc isolate.
Small ruminant sinus adenocarcinoma (ENA) is a contagious disease caused by a beta retrovirus called Enzootic Nasal Tumor Virus or ENTV. The first cases were sporadically diagnosed in Morocco in 2018. However, in the last two years, ENTV has appeared enzootic in three herds of the Sardi breed. The annual incidence varied between 5 and 20 %. Most cases involved female animals aged 15 to 42 months. The disease developed within 2 to a maximum of 6 months. Diseased animals presented with progressive weight loss and increased mortality or needed to be slaughtered. The condition associated mainly with unilateral skull deformation, serous or seromucous nasal discharge with dyspnea, and in some individuals an exophthalmos. During pathology tumor-like masses were found in the paranasal sinuses, which showed the growth of an expansive and organized epithelial neoplasm on histopathology. After an overview of the differential diagnoses that can lead to confusion with ANE, the authors investigate why the disease occurs more frequently in Morocco and particularly in the Sardi breed.
Literature on the drivers of environmental technology has been increasing in recent years. However, few studies analyze the issue in developing countries. The main goals of understanding the drivers of, and obstacles to the ecological decisions made by firms, are to design efficient environmental regulatory instruments to achieve the environmental targets. This article analyzes the determinants, including the effects of environmental regulations, of the environmental technology adoption and improvement of environmental performance in the olive oil industry in managing the olive mills wastewater (OMWW). To meet our research objective, we applied a two-stage Heckman probit model to the data collected from 156 olive oil producers in three Moroccan provinces known by a high concentration of olive oil production activity. Our results showed that the environmental regulation is one main determinant of the adoption of environmental technology by olive oil producers. However, our findings indicate that the environmental regulation, as currently designed, is not strict enough to encourage producers to improve their environmental performance in the developmental context of this particular country. The conclusions of this research also suggest that the environmental performance of oil mills, while not explained by the severity of the environmental regulation, are influenced by other external and internal factors. On the one hand, the influence of the external environment of firms via the effect of external collaboration and international market orientation, and, on the other hand by internal factors related to environmental awareness of the producer and the firm’s technical competency. In the light of our findings, we recommend to the policy makers to carry out a reform of the regulatory measures through: (i) the implementation of the current legislation, (ii) designing an effective incentive system, combining better targeted green subsidy with an optimal tax on industrial wastewater discharge (iii) setting up programs to raise awareness and reinforce technical capacities.
Bluetongue is an arthropod-borne viral disease transmitted by Culicoides biting midges, affecting domestic and wild ruminants. The current study aims to assess the seroprevalence of the bluetongue virus (BTV) and confirm its active circulation among sheep and goats populations in Morocco, as well as study the risk factors associated with BTV infection. To this end, a total of 1651 samples were randomly collected from 1376 sheep and 275 goats in eight (out of 12) regions of the country between March 2018 and July 2021.These samples were primarily tested using competitive ELISA (c-ELISA). Subsequently, 65% of c-ELISA positives (n = 452) were analyzed by real-time reverse transcription-polymerase chain reaction (RT-qPCR). The results revealed an overall BTV seroprevalence in small ruminants in Morocco of 41.7%, including 42.6% in sheep and 37.5% in goats. The RT-qPCR results showed that the overall BTV viropositivity rate was 46.7%, including 48.1% in sheep and 41.8% in goats. These viro-serological rates varied significantly by age, sex, and breed of the tested animals, husbandry method, season, and geographic origin. This indicates that these parameters constitute risk factors for BTV transmission routes in Morocco. The findings also indicate that goats play a role as reservoirs in maintaining the BTV in Morocco. It appears from this study that bluetongue is endemic in Morocco. The environmental and climate conditions as well as the husbandry methods adopted in the country are particularly favorable for the virus transmission throughout the country.
Dry leaves of date palms (DPs) are by-products of date cultivation that are often mismanaged in oasis agroecosystems. Ideally, they should be upcycled in a circular agriculture model before producing and exporting high-value products. Compost inputs enhance soil organic matter and conserve soil. This study investigated composting of four mixtures based on farming system requirements and the availability of organic resources. The DPs were used alone or combined with sheep manure and rock phosphate. We experimented with farm-scale windrow composting to improve understanding and support decision-making. The results showed that temperature increased rapidly to 70 °C at the beginning of composting in the mixtures with manure. Organic matter content decreased by 40% in all windrows during composting, which indicated organic matter mineralisation and loss of volatile solids. Composting DP with or without sheep manure for 136 days with two turnings conserved nitrogen and increased the nitrogen content of compost. Mixing DP with sheep manure and rock phosphate increased the final total phosphorus content of compost to 0.52% (dry matter basis). Our results highlight that composting DP is a feasible alternative to improve circularity in oasis agroecosystems, by increasing organic matter content and fertiliser value, thus paving the way for sustainable production of high-value products from DP.
Agriculture drought is a recurrent phenomenon that affects most parts of Sahel regions. With the advent of various satellite data, drought risk assessment has become more accessible, but the challenge lies in choosing a well-defined time scale. This study aims to contribute to agricultural drought monitoring, based on the calculation of composite indices using the MODIS sensor in the Senegalese Groundnut basin. The approach is based upon vegetation condition and health (VCI, VHI) and temperature (TCI) indices. Subsequently, those indices were evaluated based upon crop yield data, and a Holt-Winter forecasting was performed to determine the driest month in 2020-2021. Here we show that all investigated communes are sensitive to drought, especially Keur Samba Gueye (in July, September, and October). Based on its significant correlation with VCI and TCI (R²>0.57), VHI was proven to be a reliable water stress indicator. Our approach demonstrates the Groundnut basin’s vulnerability to climate change.
The southern and Eastern Mediterranean countries are facing rapid demographic growth, swift urbanization and significant socioeconomic development which requires new and growing needs for energy. At the same time, these countries have a high potential for utilizing renewable energy resources, especially wind and solar, as well as improving their energy use and efficiency. The Southern Mediterranean countries (limited to Algeria, Morocco, Tunisia, Libya and Egypt in our study) have implemented policies, programs, regulations, infrastructures and dedicated important funding to the renewable energy application. However, the region still needs to go beyond several limits that require in-depth scientific studies to come up with technical, political or managerial solutions. This chapter provides an examination of the cooperation in the field of Science, Technology and Innovation between the European Union and the Southern Mediterranean Countries in the domain of renewable energy. A review of the participation of these countries in programs such ERANETMED, H2020, and PRIMA highlighted the existence of research centers of excellence, individual expertise and large networks of collaboration. Our results draw attention to the need for implementation of more transnational collaborative research and innovation programs in the field renewable energy as a driver to the southern Mediterranean countries energy transition.KeywordsRenewable energySouth Mediterranean countriesScience and technology collaborationEU-MED research and innovation programsKnowledge based economy
Sidi Mohamed Ben Abdellah dam watershed is one of the most vulnerable areas of the risk of soil degradation due to its wide exposure, lithological heterogeneity and varying climatic factors. In this sense, the qualitative study of the spatial-temporal evaluation of ground-level occupancy from satellite visualisation data (acquired by the Landsat TM 5 and Landsat TM 8) device derives a land-use map that shows the areas at risk degradation after the integration of a combination of multiple factors into a GIS geographic information system (climate, terrain, pedology, vegetation cover and human intervention (anti-erosive practice); The results require adaptive vision to better control the phenomenon, toreduce its severity in areas at high risk of soil degradation.
Unmanned aerial vehicles (UAVs) with on-board camera have the advantages of providing a Bird-view images (Aerial images). This type of image is considered as a rich source of information specially for intelligent agriculture. A dataset of more than 984 images of avocado threes is made publicly available with a ground resolution of 2.7 cm per pixel. It has been collected over 113 Hectares of avocado farm in ALLAL TAZI region of Morocco using a DJI Phantom 4 Pro UAV. It comprises original bird view and annotated images. The dataset is available at https://data.mendeley.com/datasets/tvhh83r3hj/2
Augmented reality (AR) is a relevant technology, which has demonstrated to be efficient for several applications, especially in the architecture, engineering, construction and operation (AECO) domain, where the integration of building information modeling (BIM) and AR has proved to be optimal in handling construction projects. However, the main challenge when integrating a virtual 3D model in an AR environment is the lack of precision and accuracy of placement that can occur between the real and the virtual environments. Although methods for placement via AR have been reported in the literature, there is a lack of investigations addressing their evaluation. Therefore, this paper proposes a methodology to perform a quantitative and qualitative assessment of several AR placement methods and a discussion about their usability in the specific context of AECO. We adopt root mean square error (RMSE) to quantify the placement accuracy of a 3D model and standard deviation to examine its stability (jittering). The results revealed that the AR placement error range is extremely wide (from a few centimeters up to meters). In marker-based methods, the results showed centimeter-range in both indoor and outdoor environments, compared to other methods (Inertial, Marker-less, etc.), while marker-less methods have widely varying error range from centimeters to a few meters. Other commercial solutions based on placement-sensors (GNSS and IMU), such as Trimble SiteVision, have proven placement performance in manual mode with centimeter order, while for the automatic mode, the order of placement and stability is metric, due to the low coverage of RTX (real time extended) in the study area.
Building Information Modeling (BIM) is one of the most promising advances in the Architecture, Engineering and Construction (AEC) industry. Even though BIM models are rich and very structured, they are not suitable for extracting information quickly and efficiently to respond to some specific queries required for making decisions. Hence, extracting information from BIM models is a very important and challenging issue. This motivated us to propose an integrated solution based on Dynamo and Power BI to allow extraction and visualization of BIM data according four relevant use cases in the AEC domain: cost extraction, clash detection, change detection and plan extraction. The research presented in this paper is based on programming algorithms on Dynamo for information extraction and creating dashboards on Power BI for the visualization of the extracted results. Additionally, we used a Revit plug-in which automates the execution of Dynamo scripts through customized buttons that correspond to each of the analyses treated in this research.
This article reviews the main recent applications of multi-sensor remote sensing and Artificial Intelligence techniques in multivariate modelling of agricultural drought. The study focused mainly on three fundamental aspects, namely descriptive modelling, predictive modelling, and spatial modelling of expected risks and vulnerability to drought. Thus, out of 417 articles across all studies on drought, 226 articles published from 2010 to 2022 were analyzed to provide a global overview of the current state of knowledge on multivariate drought modelling using the inclusion criteria. The main objective is to review the recent available scientific evidence regarding multivariate drought modelling based on the joint use of geospatial technologies and artificial intelligence. The analysis focused on the different methods used, the choice of algorithms and the most relevant variables depending on whether they are descriptive or predictive models. Criteria such as the skill score, the given game complexity used, and the nature of validation data were considered to draw the main conclusions. The results highlight the very heterogeneous nature of studies on multivariate modelling of agricultural drought, and the very original nature of studies on multivariate modelling of agricultural drought in the recent literature. For future studies, in addition to scientific advances in prospects, case studies and comparative studies appear necessary for an in-depth analysis of the reproducibility and operational applicability of the different approaches proposed for spatial and temporal modelling of agricultural drought. HIGHLIGHTS : The components and fundamentals of multivariate modelling of agricultural drought were discussed. ARTICLE HISTORY The importance of hybrid artificial intelligence models is widely discussed in improving the performance of traditional machine learning models. Quantum machine learning algorithms are weakly explored in multivariate drought modelling. Therefore, future studies should explore this approach. The major challenge of multivariate modelling of drought frequency is mainly related to the difference in the return periods of the different variables (time-shifted and spatially effects).
Camel pox (CML) is a widespread infectious viral disease of camels that causes huge economic losses to the camel industry. In this study, a local strain of Camel pox virus (CMLV) was attenuated by 175 serial passages in Vero cells and the residual pathogenicity and infectivity were tested in naïve camels at 120, 150 and 175 passage levels. Also, the safety and immunogenicity of the 175th passage were evaluated in camels using a dose of 104.0 Tissue Culture Dose 50% (TCID50) and monitored for up to one-year post vaccination (pv) for neutralizing antibody. Seroconversion was noted at day 14 pv with neutralizing antibody titers ranging from 0.5 and 1.6 logs over the one-year of the study. Among 8 camels inoculated with the P175 strain, 4 were challenged at 12-month pv with 105.7 TCID50/ml of the original virulent CMLV and complete protection was recorded in all animals. Whole genome sequencing detected six mutations in the original CMLV strain that were not present in the attenuated 175th passage of this strain. Overall, the findings of this study indicated that the 175th passage of the CMLV was attenuated, safe and afforded protection to camels against virulent CMLV, and is therefore, a promising vaccine candidate for the prevention of CML in camels.
In horses, demographic patterns are complex due to historical migrations and eventful breeding histories. Particularly puzzling is the ancestry of the North African horse, a founding horse breed, shaped by numerous influences throughout history. A genetic marker particularly suitable to investigate the paternal demographic history of populations is the non-recombining male-specific region of the Y chromosome (MSY). Using a recently established horse MSY haplotype (HT) topology and KASP™ genotyping, we illustrate MSY HT spectra of 119 Barb and Arab-Barb males, collected from the Maghreb region and European subpopulations. All detected HTs belonged to the Crown haplogroup, and the broad MSY spectrum reflects the wide variety of influential stallions throughout the breed’s history. Distinct HTs and regional disparities were characterized and a remarkable number of early introduced lineages were observed. The data indicate recent refinement with Thoroughbred and Arabian patrilines, while 57% of the dataset supports historical migrations between North Africa and the Iberian Peninsula. In the Barb horse, we detected the HT linked to Godolphin Arabian, one of the Thoroughbred founders. Hence, we shed new light on the question of the ancestry of one Thoroughbred patriline. We show the strength of the horse Y chromosome as a genealogical tool, enlighten recent paternal history of North African horses, and set the foundation for future studies on the breed and the formation of conservation breeding programs.
Eggs constitute an important part of the Moroccan diet. However, contaminated eggs can cause a serious public health problem if consumed undercooked, uncooked, or used in unpasteurized egg foodstuffs. This study was carried out to evaluate the microbial contents of eggs according to their sales sector in Morocco. For that, a total of 1770 eggs were collected from January to September 2021 from formal markets (refrigerated eggs from large shopping centers) and informal markets (eggs at ambient temperature from ambulatory sellers, street vendors, kiosks, and neighborhood stores) and transferred to the Avian Pathology Unit at Hassan II Agronomic and Veterinary Institute. The eggshells and their contents were tested separately; swabs of eggshells were used to inoculate Mac-Conkey agar, while the egg contents were cultured on Mac-Conkey and Mannitol salt agar, then standard microbiological tests were performed to identify the isolated organisms. The results showed that informal eggs were more contaminated (87%) than formal eggs (48) (p
Forest cover in the Rherhaya watershed of the Moroccan High Atlas region, char- acterized by its critical natural conditions, faces strong human pressure, leading to the fragmentation of the landscape. To improve natural capital management, to sup- port stakeholders in their decision-making process and to sustain ecosystem services provided by the watershed, this work aims at developing a long-term vision of the local landscape. Land-use/land-cover change dynamics have been analyzed at 1984, 2000 and 2017 timestamps, and prospective modeling based on the Land Change Modeler (LCM) model has been used to develop a future vision of forest landscapes. LCM modeling approaches rely on two types of input maps: (1) maps of land cover at times before the calibration period and (2) maps of explanatory variables (that precludes land-use or land-cover change over time such as slope, altitude and acces- sibility: distance to roads or human settlement). The model is validated through the juxtaposition of the 2017 observed map and the predicted map for the same year using the trained model. The result shows an overall accuracy of 64.58 per cent. Based on the hypothesis of human pressures intensification in the future, the fore- casted land-cover map by 2040 has been derived as a result of the explanatory vari- ables. This prospective modeling, therefore, predicts by 2040 an expansion of build- ings that will be made at the expense of bare soil surfaces. Indeed, this expansion will be linked to population growth stemming mainly due to a strong migration of populations from neighboring regions in search of better living conditions.
Heavy metals in mine tailings induce severe environmental contamination of terrestrial ecosystems. They are hazardous to human health and must be cleaned up. However, ex-situ procedures are costly and soil-destroying. Phytoremediation approaches might be a cost-effective and environmentally friendly option. Phytostabilization of mine tailings, which employs plants, is a commonly used technique for preventing the spread of contaminants and particles from the site. Nutrient-deficient mine tailings must be amended to increase plant growth and phytoremediation performance. This study aims to investigate the tolerance of Atriplex nummularia to high heavy metal levels (Pb, Zn, and Cu) and the effects of compost and chemical fertilizer on biomass generation and heavy metal uptake. Halophyte species have been commonly employed for the phytoremediation of soil polluted with heavy metals. A pot experiment was undertaken with four treatments: T1 (agricultural soil), T2 (mine tailings), T3 (mine tailings mixed with compost), and T4 (mine tailings with chemical fertilizer). Results showed that both amendments demonstrated a significant beneficial effect on growth and biomass production. For all treatments, metals mostly accumulated in the roots, with only a small amount transferred to the shoots. Compost application resulted in a higher Pb concentration in roots than chemical fertilizer. The results of this study suggest that Atriplex nummularia can be used in phytostabilization for these types of mine tailings. However, long-term field data is needed to improve understanding of the Atriplex nummularia tolerance to high concentrations of heavy metals, as well as their uptake and translocation to aerial components. Keywords: amendments, Atriplex nummularia, mine tailings, phytoremediation.
The objective of this study was to evaluate the effect of mixtures of the phosphate industry’s by-products and sewage sludge on some heavy metals (Pb, Zn and Cd) in the soil–plant system and the microbial load (bacteria, fungi and actinobacteria) in the soil. The experimental layout was a completely randomized design with ten treatments and four replications. The treatments consist of a combination of five substrates: phosphogypsum (PG), phosphate sludge (PS), sewage sludge (SS), phosphate waste rocks (PWR) and original mine topsoil (TS). Heavy metals analysis, phytoextraction efficiency (PEE) and bioconcentration factor (BCF) were carried out for three Ryegrass cuts. The microbial load of each treatment was determined at the end of the experiment. The results showed that the Pb, Zn and Cd contents of the treatments were well below the permissible limits given in the literature. The highest BCF and PEE were with treatment T4. Furthermore, bacteria, fungi and actinobacteria were significantly influenced by the different proportions of by-products used in the treatments, with the highest richness observed for the T4 treatment. For a successful reclamation of mine sites, it would be useful to determine the speciation of metals in the soil solution and the microbial genetic diversity.
Scenarios serve science by testing the sensitivity of a system and/or society to adapt to the future. In this study, we present a new land use scenario methodology called ScenaLand. This methodology aims to develop plausible and contrasting land use and management (LUM) scenarios, useful to explore how LUM (e.g. soil and water conservation techniques) may affect ecosystem services under global change in a wide range of environments. ScenaLand is a method for constructing narrative and spatially explicit land use scenarios that are useful for end-users and impact modellers. This method is innovative because it merges literature and expert knowledge, and its low data requirement makes it easy to be implemented in the context of inter-site comparison, including global change projections. ScenaLand was developed and tested on six different Mediterranean agroecological and socio-economic contexts during the MASCC research project (Mediterranean agricultural soil conservation under global change). The method first highlights the socioeconomic trends of each study site including emerging trends such as new government laws, LUM techniques through a qualitative survey addressed to local experts. Then, the method includes a ranking of driving factors, a matrix about land use evolution, and soil and water conservation techniques. ScenaLand also includes a framework to develop narratives along with two priority axes (contextualized to environmental protection vs. land productivity in this study). In the context of this research project, four contrasting scenarios are proposed: S1 (business-as-usual), S2 (market-oriented), S3 (environmental protection), and S4 (sustainable). Land use maps are then built with the creation of LUM allocation rules based on agroecological zoning. ScenaLand resulted in a robust and easy method to apply with the creation of 24 contrasted scenarios. These scenarios come not only with narratives but also with spatially explicit maps that are potentially used by impact modellers and other end-users. The last part of our study discusses the way the method can be implemented including a comparison between sites and the possibilities to implement ScenaLand in other contexts.
The dromedary camel (Camelus dromedarius) is a short-day desert breeder in which female ovulation is induced by mating. Current data indicate that male-induced ovulation is triggered by its seminal plasma nerve growth factor beta (β-NGF), but the exact mechanisms involved in the induction of ovulation are still unknown. In this study, we report that an intramuscular injection of β-NGF in sexually active short day-adapted female camels induces an ovulation attested by a surge of circulating LH (2 h to 6 h after treatment) followed by an oocyte release with its cumulus oophorus (confirmed by ultrasonography 72 h after treatment) and a large and progressive increase in circulating progesterone (significant from the 2nd to the 10th days after β-NGF injection). Additionally, this β-NGF treatment induces a broad nuclear c-Fos activation in cells located in various hypothalamic areas, notably the preoptic area, the arcuate nucleus, the dorso- and ventro-medial hypothalamus, the paraventricular nucleus, and the supraoptic nucleus. A double immunostaining with neuropeptides known to be involved in the central control of reproduction indicates that approximately 28% kisspeptin neurons and 43% GnRH neurons in the proptic area, and about 10% RFRP-3 neurons in the dorso- and ventro-medial hypothalamus are activated following β-NGF injection. In conclusion, our study demonstrates that systemic β-NGF induces ovulation in the female dromedary camel and indicates that this effect involves the central activation of hypothalamic neurons, notably the Kp neurons.
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