Search results for: oil palm tree census

Authors: Masoud Soltanialvar, Ali Bagherpour

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Documented cases of human infection with H9N2 avian influenza viruses, first detected in 1999 in Hong Kong and China, indicate that these viruses can be directly transmitted from birds to humans. In this study, we characterized the mutation in the Hemagglutinin (HA) genes and proteins that correlates with a shift in affinity of the Hemagglutinin (HA) protein from the “avian” type sialic receptors to the “human” type in 10 Iranian isolates. We delineated the genomes and receptor binding profile of HA gene of some field isolates and established their phylogenetic relationship to the other Asian H9N2 sub lineages. A total of 1200 tissue samples collected from 40 farms located in various states of Iran during 2008 – 2010 as part of a program to monitor Avian Influenza Viruses (AIV) infection. To determine the genetic relationship of Iranian viruses, the Hemagglutinin (HA) genes from ten isolates were amplified and sequenced (by RT-PCR method). Nucleotide sequences (orf) of the (HA) genes were used for phylogenetic tree construction. Deduced amino acid sequences showed the presence of L226 (234 in H9 numbering) in all ten Iranian isolates which indicates a preference to binding of α (2–6) sialic acid receptors, so these Iranian H9N2 viruses have the potential to infect human beings. These isolates showed high degree of homology with 2 human H9N2 isolates A/HK/1073/99, A/HK/1074/99. Phylogenetic analysis of showed that all the HA genes of the Iranian H9N2 viruses fall into a single group within a G1-like sublineage which had contributed as donor of six internal genes to H5N1 highly pathogenic avian influenza. The results of this study indicated that all Iranian viruses have the potential to emerge as highly pathogenic influenza virus, and considering the homology of these isolates with human H9N2 strains, it seems that the potential of these avian influenza isolates to infect human should not be overlooked.

Keywords: influenza virus, hemagglutinin, neuraminidase, Iran

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Authors: Siddique Ullah Baig, Alisha Manzoor

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The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

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Authors: Sebaa H., Cherifi F., Djabeur Abderrezak M.

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Argania spinosa, Sapotaceae sole representative in Algeria and Morocco; hence it is endemic in these regions. However, it is a recognised oil, forage, and timber tree highly adapted to aridity. The exploitation of the argan fruits produces considerable amounts of under or related products. These products, such as the endocarps of a fruit, recuperated after the use of kernels to extract oil. This research studies in detail the contents of total phenolic content was determined by Folin Ciocalteu reagent and Flavonoids by aluminum chloride colorimetric assay). Antioxidant activity of extracts was expressed as the percentage of DPPH radical inhibition and IC50 values (μg/mL). Antimicrobial activity evaluated using agar disk diffusion method against reference Pseudomonas aeruginosa ATTC 27453, Escherichia coli ATCC 23922. Immature endocarps showed a higher polyphenol content than mature endocarps. The total phenolic content in immature endocarps was found to vary from 983,75+ /- 0.45 to 980,1 +/- 0.43 mg gallic acid equivalents/g dry weight, whereas in mature endocarps, the polyphenol content ranged from 100,58 mg/g +/- 0.42 to 105 +/- 0.55% mg gallic acid equivalent / g dry weight. The flavonoid content was 16.5 mg equivalent catechin/g dry weight and 9.81mg equivalent catechin /g dry weight for immature and mature endocarp fruits, respectively. DPPH assay of the endocarps extract yielded a half-maximal effective concentration (IC50) value in the immature endocarps (549.33 μg/mL) than in mature endocarps (322 μg/mL). This result can be attributed to the higher phenolics and flavonoid compounds in the immature endocarps. Methanol extract of immature endocarps exhibited antibacterial activity against E.colie (inhibition zone, 11mm).

Keywords: antioxidant activity, antimicrobial activity, total phenolic content, DPPH assay

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Authors: Abdullah Alaklabi, Ibrahim A. Arif, Sameera O. Bafeel, Ahmad H. Alfarhan, Anis Ahamed, Jacob Thomas, Mohammad A. Bakir

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Diospyros mespiliformis (Hochst. ex A.DC.; Ebenaceae) is a large deciduous medicinal plant. This plant species is currently listed as endangered in Saudi Arabia. Molecular identification of this plant species based on short sequence regions (571 and 664 bp) of plastid rbcL (ribulose-1, 5-biphosphate carboxylase) gene was investigated in this study. The endangered plant specimens were collected from Al-Baha, Saudi Arabia (GPS coordinate: 19.8543987, 41.3059349). Phylogenetic tree inferred from the rbcL gene sequences showed that this species is very closely related with D. brandisiana. The close relationship was also observed among D. bejaudii, D. Philippinensis and D. releyi (≥99.7% sequence homology). The partial rbcL gene sequence region (571 bp) that was amplified by rbcL primer-pair rbcLaF-rbcLaR failed to discriminate D. mespiliformis from the closely related plant species, D. brandisiana. In contrast, primer-pair rbcL1F-rbcL724R yielded longer amplicon, discriminated the species from D. brandisiana and demonstrated nucleotide variations in 3 different sites (645G>T; 663A>C; 710C>G). Although D. mespiliformis (EU980712) and D. brandisiana (EU980656) are very closely related species (99.4%); however, studied specimen showed 100% sequence homology with D. mespiliformis and 99.6% with D. brandisiana. The present findings showed that rbcL short sequence region (664 bp) of plastid rbcL gene, amplified by primer-pair rbcL1F-rbcL724R, can be used for authenticating samples of D. mespiliforformis and may provide help in authentic identification and management process of this medicinally valuable endangered plant species.

Keywords: Diospyros mespiliformis, endangered plant, identification partial rbcL

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Authors: Ezzat Abd El Lateef

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Agroforestry means combining the management of trees with productive agricultural activities, especially in semiarid regions where crop yield increases are limited in agroforestry systems due to the fertility and microclimate improvements and the large competitive effect of trees with crops for water and nutrients, in order to assess the effect of agroforestry of some field crops with citrus trees as an approach to establish biodiversity in fruit tree plantations. Three field crops, i.e., maize, soybean and sunflower, were inter-planted with seedless orange trees (4*4 m) or were planted as solid plantings. The results for the trees indicated a larger fruit yield was obtained when soybean and sunflowers were interplant with citrus. Statistically significant effects (P<0.05) were found for maize grain and biological yields, with increased yields when grown as solid planting. There were no differences in the yields of soya bean and sunflower, where the yields were very similar between the two cropping systems. It is evident from the trials that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Maize, unlike the other crops, was more sensitive to shade conditions under agroforestry practice and not preferred in the biodiversity system. The potential of agroforestry to improve or increase biodiversity is efficient as the understorey crops are usually C4 species, and the overstorey trees are invariably C3 species in agroforestry. Improvement in interplant species is most likely if the understorey crop is a C3 species, which are usually light saturated in the open, and partial shade may have little effect on assimilation or by a concurrent reduction in transpiration. It could be concluded that agroforestry is an efficient concept to increase biodiversity through the interaction of trees with the interplant field crop species. Some field crops could be employed successfully, like soybean or sunflowers, while others like maize are sensitive to incorporate in agroforestry system.

Keywords: agroforestry, field crops, C3 and C4 plants, yield

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

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Authors: Barış Ozluoymak, Emin Guzel, Ahmet İnce

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Since chemical fertilizers are used for meeting the deficiency of plant nutrients, its many harmful effects are not taken into consideration for the structure of the earth. These fertilizers are hampering the work of the organisms in the soil immediately after thrown to the ground. This interference is first started with a change of the soil pH and micro organismic balance is disrupted by reaction in the soil. Since there can be no fragmentation of plant residues, organic matter in the soil will be increasingly impoverished in the absence of micro organismic living. Biological activity reduction brings about a deterioration of the soil structure. If the chemical fertilization continues intensively, soils will get worse every year; plant growth will slow down and stop due to the intensity of chemical fertilizers, yield decline will be experienced and farmer will not receive an adequate return on his investment. In this research, a prototype of automatic farm manure spreading machine for orange orchards that not just manufactured in Turkey was designed, constructed, tested and eliminate the human drudgery involved in spreading of farm manure in the field. The machine comprised several components as a 5 m3 volume hopper, automatic controlled hydraulically driven chain conveyor device and side delivery conveyor belts. To spread the solid farm manure automatically, the machine was equipped with an electronic control system. The hopper and side delivery conveyor designs fitted between orange orchard tree row spacing. Test results showed that the control system has significant effects on reduction in the amount of unnecessary solid farm manure use and avoiding inefficient manual labor.

Keywords: automatic control system, conveyor belt application, orchard, solid farm manure

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Authors: Gulfam Hasan, Ijaz Ashraf, Saleem Ashraf, Muhammad Rafay Muzammil, Salman Asghar, Shafiq-Ur-Rehman Zia

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The word “climate change” has become the most popular term when anyone observes any uncertain climate variation in their respective region. Asian countries are more prone to the impact of this phenomenon, and Pakistan is the leading affected country. Last few years, governments all over the world have been trying to cater to this issue for the best entrust of their population, especially agriculture. Now the farmers in Pakistan are fully aware of the term “climate change” and are more concerned about its solutions. On the other hand, developed countries like the USA are setting a benchmark for developing countries in every sphere of life. Based on cultural and other variations, the research was carried out to identify the behavior of farmers regarding the same issue. Cross-sectional survey research was designed for an in-depth study of relevant research questions. Face-to-face interviews were conducted in Pakistan, while virtual and face-to-face interviews were conducted in the Indiana State of the USA. The results of the present study and the responses of farmers were very interesting. The common climate change mitigation strategies suggested by farmers of both countries were less use of motor vehicles (replacement with bicycles in the circle of 10 Km), less dependency on chemical fertilizers (increased use of Manure, Bio-fertilizer, Compost), and plantation of the tree. The difference of opinion was in less government interest, lack of farmers’ education, political instability (views of Pakistani farmers), awareness of local communities, self-satisfaction, and economic disparities (views of USA farmers). Based on the given evidence, it was recommended that there is a dire need to address the climate change issue all over the world without discrimination of race, color, region, or religion. Because it will affect not only agriculture but also the real effect will be on HUMANITY.

Keywords: climate change, mitigation strategies, forests, biodiversity

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Authors: P. J. Kagosi, M. Mndolwa, E. Japhate

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The study was conducted to communities adjacent MNR, Lushoto district, Tanzania. The MNR is one of the nine nature reserves in the Eastern Arc Mountains of Tanzania with an area of 8,700ha with high biological diversity. However, biodiversity in MNR have been threatened by increasing human activities for livelihood in 1970s. The AF systems in the study area was practised since 1980s however, no study was conducted on AF impacts. This paper presents the influence of AF on livelihood of communities adjacent MNR and biodiversity conservation. Qualitative and quantitative data were collected using socio-economic survey and botanical surveys. Data were analysed using Statistical Packages for Social Sciences and content analysis. The study found that in 1970s free livestock grazing caused considerable surface runoff, soil erosion and reduction of crop production. Since 1980s, the study area received various interventions based on the land conservations and improved livelihood through practising AF systems. It was further found that the AF farming improved crop productivity, reduced soil erosion, increased firewood (80.2%) and other forest products availability and AF encouraged community members practicing indoor livestock keeping.The dominant agroforestry tree found in the study area is grevillea reported by 74.1% of respondents planting an average of 40 trees. The study found that the AF reduced pressure to MNR as forest products and fodders were obtained from community's farms in turn, currently water flow from MNR has been increased. Thus AF products support livelihood needs and conserve biodiversity. The study recommends continuity education on new AF technology packages.

Keywords: impact of agroforestry, biodiversity management, communities’ livelihoods, Magamba nature reserve

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: B. Niez, B. Moulia, J. Dlouha, E. Badel

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Trees adjust their development to the environmental conditions they experience. Storms events of last decades showed that acclimation of trees to mechanical stresses due to wind is a very important process that allows the trees to sustain for long years. In the future, trees will experience new wind patterns, namely, more often strong winds and fewer daily moderate winds. Moreover, these patterns will go along with drought periods that may interact with the capacity of trees to adjust their growth to mechanical stresses due to wind. It is necessary to understand the mechanisms of wood functional acclimations to environmental conditions in order to predict their behaviour and in order to give foresters and breeders the relevant tools to adapt their forest management. This work aims to study how trees adjust the mechanical and hydraulic functions of their wood to environmental stresses and how this acclimation may be beneficial for the tree to resist to future stresses. In this work, young poplars were grown under controlled climatic conditions that include permanent environmental stress (daily mechanical stress of the stem by bending and/or hydric stress). Then, the properties of wood formed under these stressed conditions were characterized. First, hydraulic conductivity and sensibility to cavitation were measured at the tissue level in order to evaluate the changes in water transport capacity. Secondly, bending tests and Charpy impact tests were carried out at the millimetric scale to locally measure mechanical parameters such as elastic modulus, elastic limit or rupture energy. These experimental data allow evaluating the impacts of mechanical and water stress on the wood material. At the stem level, they will be merged in an integrative model in order to evaluate the beneficial aspect of wood acclimation for trees.

Keywords: acclimation, environmental stresses, hydraulics, mechanics, wood

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Authors: Svetlana S. Saveysheva, Victoria E. Vasilenko

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The purpose of the research was to study the emotional and personal characteristics of preschool children in relation to the characteristics of child-parent interaction and deviant parental attitudes. The study involved 172 mothers and 172 children (85 boys and 87 girls) aged 4,5 to 7 years (mean age 6 years) living in St. Petersburg, Russia. Methods used were, demographic questionnaire, projective drawing method 'House-Tree-Man', Test of anxiety (Temml, Dorki, Amen), technique of studying self-esteem 'Ladder', expert evaluation of sociability and aggressiveness, questionnaire for children-parent emotional interaction (E.I. Zaharova) and questionnaire 'Analysis of family relationships' (E.G. Eidemiller, V.V. Yustitsky). Results. The greatest number of links with personal characteristics have received such parental deviant attitudes as overprotection and characteristics of authoritarian style (prohibitions, sanctions). If the mother has such peculiarities of the parental relationship, the child is characterized by lower self-esteem, increased anxiety, distrust of themselves and hostility. Children have more pronounced manifestations of aggression in a conniving and unstable style of parenting. The sensitivity of the mother is positively associated with children’s self-esteem. Unconditional acceptance of the child, the predominance of a positive emotional background, orientation to the state of the child during interaction promote the development of communication skills and reduce of aggressiveness. But the excessive closeness of the mother with the child can make it difficult to develop the communicative skills. Conclusions. The greatest influence on emotional and personal characteristics is provided by such features of the parental relation as overprotection, characteristics of authoritarian style, underdevelopment of the sphere of parental feelings, sensitivity of mother and behavioral manifestations of emotional interaction. Research is supported by RFBR №18-013-00990.

Keywords: characteristics of personality, child-parent interaction, children, deviant parental attitudes

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Authors: Anele Horn, Amanda Van Eeden

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The emphasis on the challenges posed by continued urbanisation, especially in developing countries has resulted in urban sprawl often researched and analysed in metropolitan urban areas, but rarely in small and medium towns. Consequently, there exists no comparative instrument between the proportional extent of urban sprawl in metropolitan areas measured against that of small and medium towns. This research proposes an Urban Sprawl Index as a possible tool to comparatively analyse the extent of urban sprawl between cities and towns of different sizes. The index can also be used over the longer term by authorities developing spatial policy to track the success or failure of specific tools intended to curb urban sprawl. In South Africa, as elsewhere in the world, the last two decades witnessed a proliferation of legislation and spatial policies to limit urban sprawl and contain the physical expansion and development of urban areas, but the measurement of the successes or failures of these instruments intending to curb expansive land development has remained a largely unattainable goal, largely as a result of the absence of an appropriate measure of proportionate comparison. As a result of the spatial political history of Apartheid, urban areas acquired a spatial form that contributed to the formation of single-core cities with far reaching and wide-spreading peripheral development, either in the form of affluent suburbs or as a result of post-Apartheid programmes such as the Reconstruction and Development Programme (1995) which, in an attempt to assist the immediate housing shortage, favoured the establishment of single dwelling residential units for low income communities on single plots on affordable land at the urban periphery. This invariably contributed to urban sprawl and even though this programme has since been abandoned, the trend towards low density residential development continues. The research area is the Western Cape Province in South Africa, which in all aspects exhibit the spatial challenges described above. In academia and popular media the City of Cape Town (the only Metropolitan authority in the province) has received the lion’s share of focus in terms of critique on urban development and spatial planning, however, the smaller towns and cities in the Western Cape arguably received much less public attention and were spared the naming and shaming of being unsustainable urban areas in terms of land consumption and physical expansion. The Urban Sprawl Index for the Western Cape (USIWC) put forward by this research enables local authorities in the Western Cape Province to measure the extent of urban sprawl proportionately and comparatively to other cities in the province, thereby acquiring a means of measuring the success of the spatial instruments employed to limit urban expansion and inefficient land consumption. In development of the USIWC the research made use of satellite data for reference years 2001 and 2011 and population growth data extracted from the national census, also for base years 2001 and 2011.

Keywords: urban sprawl, index, Western Cape, South Africa

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Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

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Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Kherbache Mehdi

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Within the framework of the validation of the Master in business administration marketing and sales in INSIM institute international in management Blida, we get the opportunity to do a professional internship in Sonelgaz Enterprise and a thesis. The thesis deals with the integration of social networking in the communication strategy of a company. The problematic is: How communicate with social network can be a solution for companies? The challenges stressed by this thesis were to suggest limits and recommendations to Sonelgaz Enterprise concerning social networks. The whole social networks represent more than a billion people as a potential target for the companies. Thanks to research and a qualitative approach, we have identified tree valid hypothesis. The first hypothesis allows confirming that using social networks cannot be ignored by any company in its communication strategy. However, the second hypothesis demonstrates that it’s necessary to prepare a strategy that integrates social networks in the communication plan of the company. The risk of this strategy is very limited because failure on social networks is not a restraint for the enterprise, social networking is not expensive and, a bad image which could result from it is not as important in the long-term. Furthermore, the return on investment is difficult to evaluate. Finally, the last hypothesis shows that firms establish a new relation between consumers and brands thanks to the proximity allowed by social networks. After the validation of the hypothesis, we suggested some recommendations to Sonelgaz Enterprise regarding the communication through social networks. Firstly, the company must use the interactivity of social network in order to have fruitful exchanges with the community. We also recommended having a strategy to treat negative comments. The company must also suggest delivering resources to the community thanks to a community manager, in order to have a good relation with the community. Furthermore, we advised using social networks to do business intelligence. Sonelgaz Enterprise can have some creative and interactive contents with some amazing applications on Facebook for example. Finally, we recommended to the company to be not intrusive with “fans” or “followers” and to be open to all the platforms: Twitter, Facebook, Linked-In for example.

Keywords: social network, buzz, communication, consumer, return on investment, internet users, web 2.0, Facebook, Twitter, interaction

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Sirajo Abubakar, Ismail Ahmad Abir, Muhammad Sabiu Bala, Muhammad Mustapha Adejo, Aravind Shanmugaveloo

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Over the years, land subsidence has been a serious threat mostly to urban areas. Land subsidence is the sudden sinking or gradual downward settling of the ground’s surface with little or no horizontal motion. In most areas, land subsidence is a slow process that covers a large area; therefore, it is sometimes left unnoticed. South of Johor is the area of interest for this project because it is going through rapid urbanization. The objective of this research is to evaluate and identify potential deformations in the south of Johor using integrated remote sensing and 2D resistivity methods. Synthetic aperture radar interferometry (InSAR) which is a remote sensing technique has the potential to map coherent displacements at centimeter to millimeter resolutions. Persistent scatterer interferometry (PSI) stacking technique was applied to Sentinel-1 data to detect the earth deformation in the study area. A dipole-dipole configuration resistivity profiling was conducted in three areas to determine the subsurface features in that area. This subsurface features interpreted were then correlated with the remote sensing technique to predict the possible causes of subsidence and uplifts in the south of Johor. Based on the results obtained, West Johor Bahru (0.63mm/year) and Ulu Tiram (1.61mm/year) are going through uplift due to possible geological uplift. On the other end, East Johor Bahru (-0.26mm/year) and Senai (-1.16mm/year) undergo subsidence due to possible fracture and granitic boulders loading. Land subsidence must be taken seriously as it can cause serious damages to infrastructures and human life. Monitoring land subsidence and taking preventive actions must be done to prevent any disasters.

Keywords: interferometric synthetic aperture radar, persistent scatter, minimum spanning tree, resistivity, subsidence

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Ashik Sarder

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Bangladesh is a disaster-prone and one of the most vulnerable countries to climate change. The country has a long coastal area which is frequently being affected by several types of natural disasters due to climate change. The disasters have impacts on the life and livelihood of different natural resources depending on communities living in the coastal areas. The Malo is a Hindu religious traditional fishing community living at Sarafpur Union of Dumuria Upazila of Khulna district of south-west coastal Bangladesh. Fishing is the only means of their livelihood and the community has been engaged in fishing practices inherently in rivers, estuaries, and sea for more than 300 years. and they are totally dependent on this traditional occupation. But, in recent year’s climate change has negative impacts on their only livelihood option. The study aims to examine the impacts of climate change on the livelihood of Malo fishing community in south-west coastal Bangladesh, identify the adaptation strategies undertaken and practiced by Malo fishing community to cope with climate change and sustain their livelihood and explore the changing adaptation strategies undertaken by Malo fishing community and others. The study has been conducted from both qualitative and quantitative perspectives. Data has been collected from both primary and secondary sources. The primary data has been collected in the participatory observation approach following both qualitative and quantitative method. The primary source of data includes village census, face-to-face interview and in-depth case studies using structured questionnaire. The secondary source of the literature includes different national and international documents, policy papers, books and articles; related websites and peer-viewed documents on climate change, vulnerability, adaptation, livelihood, and fisheries. The study has identified different practices of adaption to climate change by Malo fishing community and others in the selected area. Three types of adaption practices have been identified. Firstly, the indigenous adaptation practices by Malo fishing community to cope with climate change have been identified. These identified adaptation practices by Malo fishing community include; ensuring drinking water and sanitation facilities, planting trees to tackle impacts of cyclone, excavating dumps to preserve the valuable assets, growing vegetables and rearing domestic livestock to earn surplus money, taking loans for ensuring continuation of present livelihood and migrating to near city or towns for better livelihood options. Secondly, adaptation initiatives undertaken by the government have provided limited facility to this vulnerable fishing community and made them benefited. And thirdly, some adaptation initiatives commenced by few non-government and community-based organizations have also made the Malo fishing community as beneficiaries. The study has suggested recommendations for Malo fishing community to overcome the challenges and impacts of climate change for retaining their traditional fishing livelihood. The accumulated recommendations would be very useful for the researchers, academicians, policy-makers of Government and non-government organizations to conduct more researches and take initiatives for Malo fishing community to make them more capable to sustain their fishing livelihood.

Keywords: climate change, livelihood, adaptation, anthropology, vulnerability

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Authors: Maria Francesca Scannone, Martina Bochicchio

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One of the major environmental problems today is hydrocarbon contamination. The promising sustainable technologies for the treatment of these contaminated sites involves the use of biological organisms. In Agri Valley (Basilicata Region) there is a living laboratory (natural oil seeps) where the selective pressure has enriched the environmental matrices with microorganisms, fungi and plant species able to use the hydrocarbons as a source of metabolic energy, to degrade or tolerate hydrocarbons. Observers visiting this area are fascinated by its unspoiled nature, and the condition of the ecosystem does not appear to has been damaged. The amazing resiliency observed in Tramutola site is of key importance to try to bring green remediation technologies, but no research has been done to identify high-performing native species. The aim of this research was to study how natural processes affect the fate of released oil or how individual species or communities of plants and animals are capable of dealing with the burden of otherwise toxic chemicals. The survey of vegetation was carried out, more than 60 species have been identified and divided into tree, shrub and herb layer. Plant data sheets have been completed only for the species that showed the most appropriate properties for phytoremediation. In general, members of the Salicales, Cyperales, Poales, Fagales, Cornales, Equisetales orders were the most commonly identified orders. They are pioneer plants with high adaptive capacity and vegetative propagation. The literature review has highlighted the existence of rhizosphere effect and a green liver model on selected plants. The study provides significant information on the environmental stress adaptation processes of many indigenous plants that are living and growing on a natural leak of crude oil and gas that migrates up through subsurface.

Keywords: green liver, hydrocarbon degradation, oil seeps, phytoremediation

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Authors: Makhosi Buthelezi

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Mitochondrial DNA cytochrome c oxidase I (COI) gene analyses linked the South African groundnut leaf miner (GLM) to the Australian soya bean moth Aproaerema simplexella (Walker) and Indian Aproaerema modicella (Deventer). Thus, the genetic relatedness of GLM, A. simplexela, and A. modicella was examined by performing mitochondrial and nuclear (COI, cytochrome oxidase subunit II (COII), mitochondrial cytochrome b (CYTB), nuclear ribosomal 28S (28S) and intergenic spacer elongation factor-1 alpha ( EF-1 ALPHA) on 44 specimens collected from South Africa, four from Mozambique, and three each from single locations in India and Australia. Phylogenetic analyses were conducted using the Maximum Parsimony (MP) and Neighbour-Joining (NJ) methods. All of the datasets of the five DNA gene regions that were sequenced were also analyzed using the Basic Local Alignment Search Tool (BLAST) to find the closest matches for inclusion in the phylogenetic trees as outgroups and for purposes of information. In the phylogenetic trees for COI, COII, cytb and EF-1 ALPHA, a similar pattern was observed in the way that the sequences assembled into different groups; i.e., some sequences of A. simplexella from Australia were grouped separately from the others, but some Australian sequences grouped with those of the GLM from South Africa, India, and Mozambique. In the phylogenetic tree for 28S, all sequences from South Africa, Australia, India, and Mozambique grouped together and formed one group. For COI, genetic pairwise distance ranged from 0.97 to 3.60 %, for COII it ranged from 0.19% to 2.32%, for cytb it ranged from 0.25 to 9.77% and for EF-1 ALPHA it ranged 0.48 to 6.99%. Results of this study indicate that these populations are genetically related and presumably constitute a single species. Thus, further molecular and morphological studies need to be undertaken in order to resolve this apparent conundrum on the taxonomy of these populations.

Keywords: aproaerema modicella, aproaerema simplexella, mitochondrial DNA, nuclear DNA

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Authors: Anukwu J. U., Nwamba H. O., Njom V. S., Achikanu C. E., Edoga C. O. Chiaha I. E.

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The major environmental crisis is the loss of biodiversity and the decline is predominant in the fish population. Although taxonomic history began 250 years ago, there are still undiscovered members of species and new species are waiting to be uncovered. The failure of the traditional taxonomic method to address this issue has resulted to the adoption of a molecular approach-DNA barcoding. It was proposed that DNA barcoding using the mitochondrion cytochrome oxidase subunit I (COI) gene has the capability to serve as a barcode for fish. The aim of this study was to use DNA barcoding in the identification of fish species in the New Calabar River, Rivers State. BLAST result showed the correlation between the sequence queried and the biological sequences with the NCBI database. The names of the samples, percentage ID, predicted organisms, and GenBank Accession numbers were clearly identified. A total of 18 sequences (all > 600bp) belonging to 8 species, 7 genera, 7 families, and 5 orders were validated and submitted to the NCBI database. Each nucleotide peak was represented by a single colour with various percentage occurrences. Two (22%) out of the 9 original samples analyzed corresponded with the predicted organisms from the BLAST result.) There were a total of 712 positions in the final dataset. Evolutionary analyses were conducted in MEGA11. Pairwise sequence alignment showed different consensus positions and a total of 30 mutations. There was one insertion from Polynemus dubius and 29 substitutions (transition-15 and transversion-14) mutations. No deletion and nonsense codons were detected in all the amplified sequences. This work will facilitate more research in other keys areas such as the identification of mislabeled fish products, illegal trading of endangered species, and effective tracking of fish biodiversity.

Keywords: DNA barcoding, Imo river, phylogenetic tree, mutation.

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Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

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Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

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Authors: Kahlouche Amal, Touzene F. Zohra, Betatache Fatihaet Nouani Abdelouahab

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The development of the world production of the cheese these last decades, as well as agents' greater request cheap coagulants, accentuated the search for new surrogates of the rennet. What about the interest to explore the vegetable biodiversity, the source well cheap of many naturals metabolites that the scientists today praise it (thistle, latex of fig tree, Cardoon, seeds of melon). Indeed, a big interest is concerned the search for surrogates of vegetable origin. The objective of the study is to show the possibility of extracting a protease coagulant the milk from the cake of Sunflower, available raw material and the potential source of surrogates of rennet. so, the determination of the proteolytic activity of raw extracts, the purification, the elimination of the pigments of tint of the enzymatic preparations, a better knowledge of the coagulative properties through study of the effect of certain factors (temperature, pH, concentration in CaCl2) are so many factors which contribute to value milk particularly those produced by the small ruminants of the Algerian dairy exploitations. Otherwise, extracts coagulants of vegetable origin allowed today to value traditional, in addition, although the extract coagulants of vegetable origin made it possible today to develop traditional cheeses whose Iberian peninsula is the promoter, but the test of 'pressed paste not cooked' cheese manufacturing led to the semi-scale pilot; and that, by using the enzymatic extract of sunflower (Helianthus annus) which gave satisfactory results as well to the level of outputs as on the sensory level,which, statistically,did not give any significant difference between studied cheeses. These results confirm the possibility of use of this coagulase as a substitute of rennet commercial on an industrial scale.

Keywords: characterization, cheese, Rennet, sunflower

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Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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Authors: Andrew Kanzunguze, Sopani Sichinga, Paston Simkoko, George Nxumayo, Cosmas, V. B. Dambo

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Early detection of plant invasions is a necessary prerequisite for effective invasive plant management in protected areas. This study was conducted to determine the distribution and abundance of alien invasive trees in Nyika National Park (NNP). Data on species' presence and abundance were collected from belt transects (n=31) in a 100 square kilometer area on the central plateau. The data were tested for normality using the Shapiro-Wilk test; Mann-Whitney test was carried out to compare frequencies and abundances between the species, and geographical information systems were used for spatial analyses. Results revealed that Black Wattle (Acacia mearnsii), Mexican Pine (Pinus patula) and Himalayan Raspberry (Rubus ellipticus) were the main alien invasive trees on the plateau. A. mearnsii was localized in the areas where it was first introduced, whereas P. patula and R. ellipticus were spread out beyond original points of introduction. R. ellipticus occurred as dense, extensive (up to 50 meters) thickets on the margins of forest patches and pine stands, whilst P. patula trees were frequent in the valleys, occurring most densely (up to 39 stems per 100 square meters) south-west of Chelinda camp on the central plateau with high variation in tree heights. Additionally, there were no significant differences in abundance between R. ellipticus (48) and P. patula (48) in the study area (p > 0.05) It was concluded that R. ellipticus and P. patula require more attention as compared to A. mearnsii. Howbeit, further studies into the invasion ecology of both P. patula and R. ellipticus on the Nyika plateau are highly recommended so as to assess the threat posed by the species on biodiversity, and recommend appropriate conservation measures in the national park.

Keywords: alien-invasive trees, Himalayan raspberry, Nyika National Park, Mexican pine

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Authors: Mohamed Aboelghar, Ayman Abou Hadid, Usama Albehairy, Asmaa Khater

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Sustainable agricultural development of the desert areas of Egypt under the pressure of irrigation water scarcity is a significant national challenge. Existing water harvesting techniques on the northwest coast of Egypt do not ensure the optimal use of rainfall for agricultural purposes. Basin-scale hydrology potentialities were studied to investigate how available annual rainfall could be used to increase agricultural production. All data related to agricultural production included in the form of geospatial layers. Thematic classification of Sentinal-2 imagery was carried out to produce the land cover and crop maps following the (FAO) system of land cover classification. Contour lines and spot height points were used to create a digital elevation model (DEM). Then, DEM was used to delineate basins, sub-basins, and water outlet points using the Soil and Water Assessment Tool (Arc SWAT). Main soil units of the study area identified from Land Master Plan maps. Climatic data collected from existing official sources. The amount of precipitation, surface water runoff, potential, and actual evapotranspiration for the years (2004 to 2017) shown as results of (Arc SWAT). The land cover map showed that the two tree crops (olive and fig) cover 195.8 km2 when herbaceous crops (barley and wheat) cover 154 km2. The maximum elevation was 250 meters above sea level when the lowest one was 3 meters below sea level. The study area receives a massive variable amount of precipitation; however, water harvesting methods are inappropriate to store water for purposes.

Keywords: water catchements, remote sensing, GIS, sustainable agricultural development

Procedia PDF Downloads 117

Authors: Debit Datta, Jeffrey J. Coleman, Scott A. Enebak, Lori G. Eckhardt

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Loblolly pine (Pinus taeda) is a leading productive timber species in the southeastern USA. Over the past three years, an emerging threat is expressed by successive needle defoliation followed by stunted growth and tree mortality in loblolly pine plantations. Considering economic significance, it has now become a rising concern among landowners, forest managers, and forest health state cooperators. However, the symptoms of the disease were perplexed somewhat with root disease(s) and recurrently attributed to invasive Phytophthora species due to the similarity of disease nature and devastation. Therefore, the study investigated the potential causal agent of this disease and characterized the fungi associated with loblolly pine needle defoliation in the southeastern USA. Besides, 70 trees were selected at seven long-term monitoring plots at Chatom, Alabama, to monitor and record the annual disease incidence and severity. Based on colony morphology and ITS-rDNA sequence data, a total of 28 species of fungi representing 17 families have been recovered from diseased loblolly pine needles. The native brown-spot pathogen, Lecanosticta acicola, was the species most frequently recovered from unhealthy loblolly pine needles in combination with some other common needle cast and rust pathogen(s). Identification was confirmed using morphological similarity and amplification of translation elongation factor 1-alpha gene region of interest. Tagged trees were consistently found chlorotic and defoliated from 2019 to 2020. The current emergence of the brown-spot pathogen causing loblolly pine mortality necessitates the investigation of the role of changing climatic conditions, which might be associated with increased pathogen pressure to loblolly pines in the southeastern USA.

Keywords: brown-spot needle blight, loblolly pine, needle defoliation, plantation forestry

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Authors: Maryam Beiranvand, Sajad Yaghoubi

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Background: Some microbes can colonize plants’ inner tissues without causing obvious damage and can even produce useful bioactive substances. In the present study, the diversity of the endophytic bacteria associated with medicinal plants from Iran was investigated by culturing techniques, molecular gene identification, as well as measuring them for antibacterial activity. Results: In the spring season from 2013 to 2014, 35 herb pharmacology samples were collected, sterilized, meshed, and then cultured on selective media culture. A total of 199 endophytic bacteria were successfully isolated from 35 tissue cultures of medical plants, and sixty-seven out of 199 bacterial isolates were subjected to identification by the 16S rRNA gene sequence analysis method. Based on the sequence similarity gene and phylogenetic analyses, these isolates were grouped into five classes, fourteen orders, seventeen families, twenty-one genera, and forty strains. The most abundant group of endophytic bacteria was actinobacterial, consisting of thirty-two (47%) out of 67 bacterial isolates. Ten (22.3%) out of 67 bacterial isolates remained unidentified and classified at the genus level. The signature of the 16S rRNA gene formed a distinct line in a phylogenetic tree showing that they might be new species of bacteria. One (5.2%) out of 67 bacterial isolates was still not well categorized. Forty-two out of 67 strains were candidates for antimicrobial activity tests. Nineteen (45%) out of 42 strains showed antimicrobial activity multidrug resistance (MDR); thirteen (68%) out of 19 strains were allocated to classes actinobacteria. Four (21%) out of 19 strains belonged to the Bacillaceae family, one (5.2%) out of 19 strains was the Paenibacillaceae family, and one (5.2%) out of 19 strains belonged to the Pseudomonadaceae family. The other twenty-three strains did not show inhibitory activities. Conclusions: Our research showed a high-level phylogenetic diversity and the intoxicating antibiotic activity of endophytic bacteria in the herb pharmacology of Iran.

Keywords: Antibacterial activity, endophytic bacteria, multidrug-resistant bacteria, whole genom sequencing

Procedia PDF Downloads 86