Fusarium head blight (FHB) caused by Fusarium pathogens is one of the most devastating fungal diseases of small grain cereals worldwide, substantially reducing yield quality and food safety. Its severity is increasing due to the climate change caused by weather fluctuations. Intensive research on FHB control methods has been initiated more than a decade ago. Since then, the environment has been rapidly changing at regional to global scales due to increasing anthropogenic emissions enhanced fertilizer application and substantial changes in land use. It is known that environmental factors affect both the pathogen virulence as well as plant resistance mechanisms. Changes in CO2 concentration, temperature, and water availability can have positive, neutral, or negative effects on pathogen spread depending on the environmental optima of the pathosystem. Hence, there is a need for studies of plant–pathogen interactions in current and future environmental context. Long-term monitoring data are needed in order to understand the complex nature of plants and its microbiome interactions. We suggest an holobiotic approach, integrating plant phyllosphere microbiome research on the ecological background. This will enable the development of efficient strategies based on ecological know-how to fight Fusarium pathogens and maintain sustainable agricultural systems.

14In coming decades drought is expected to expand globally owing to increased 15 evaporation and reduced rainfall. In order to reduce the vulnerability of agricultural 16 systems we need to understand the crop plant growth environment. Understanding, 17 predicting and controlling the rhizosphere has potential to harness plant microbe 18 interactions, improve plant responses to environmental stress and mitigate effects of 19 climate change. Our plant growth-promoting rhizobacteria (PGPR) are isolated from 20 the natural laboratory 'Evolution Canyon' Israel (EC). The endophytic rhizobacteria 21 from the wild progenitors of cereals have been co-habituated with their hosts for long 22 periods of time. The study revealed that silica particles (SN) triggered the PGPR 23 production of exopolysaccharides (EPS) containing D-glucuronate (D-GA). This leads 24 to increased plant biomass accumulation in drought-stressed growth environments. 25The PGPR increased EPS content increases the water holding capacity (WHC) and 26 osmotic pressure of the biofilm matrix. Light-and electron-microscopic studies show 27 that in the presence of SN particles, bacterial morphology is changed, indicating that 28 SNs are associated with significant reprogramming in bacteria. 29The results here show that the production of EPS containing D-GA is induced by SN 30 treatment. The findings encourage formulation of cells considering microencapsulation 31 with materials that ensure higher WHC and hyperosmolarity under field conditions. 32Our results illustrate the importance of considering natural soil nanoparticles in the 33 application of PGPR. Osmotic pressure involvement of holobiont cohabitation is 34 discussed. 35 36 65 keeper for the bacterial drought tolerance enhancement (Timmusk, Kim et al. 2015).66 EC is a well described natural laboratory where microbes have co-habituated with 67 the hosts over a long period of time (Nevo 2012). Reciprocity between the organisms 68 is generally accepted (Gilbert, Bosch et al. 2015, Gilbert 2016, Rice, Kallonen et al. 69 2016, Gilbert 2019) and organisms that have co-evolved within the environment are 70 more robust to environmental stress situations (Robinson, Klein et al. 2018, Vega 71 2019). Microbes found in extreme habitats developed a different strategy to adapt to 72 such conditions through evolution. Holobiotic complex relationships in the given 73 framework, not robotic associations of genes, are becoming more and more accepted 74 in developmental and evolutionary biology (Gilbert, Bosch et al. 2015, Gilbert 2016, 75 Rice, Kallonen et al. 2016, Gilbert 2019). Hence, understanding the framework of 76 adaptation to extreme environments is gaining interest in a period of environment 77 change (Robinson, Klein et al. 2018, Vega 2019) . 78 Our recent plant nanointerface interaction research focusing on native soil particles 79 shows that silica nanoparticles (SN) promote PGPR attachment and plant 80 colonization, and this effect is translated into crop yield enhancement under stress 81 condit...

The Law enforcement agencies like that of police today are faced with large volume of data that must be processed and transformed into useful information and hence data mining can greatly improve crime analysis and aid in reducing and preventing crime. The purpose of this study is to construct predictive models that could help in the effort of crime pattern analysis with the aim of supporting the crime prevention activities at the Hossaena town police office. For this study, a six-step hybrid knowledge discovery process model is followed, due to the nature of the problem and attributes in the dataset. The classification technique such as J48 decision tree and Naive Bayes used to build the models. Performance of the models is compared using accuracy, True Positive Rate, False Positives Rate, and the area under the Relative Optical character curve. J48 decision tree registers better performance with 96.34% accuracy. Lastly for extracting the knowledge the researcher develop the prototype for the user for support the decision which crime is assigned under the serious, medium or low for this purpose the researcher generate the prototypes.

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