Biological Control of Three Fungal Diseases in Strawberry (Fragaria X ananassa) with Arbuscular Mycorrhizal Fungi

[EN] Similar to many other plant-based products, strawberries are susceptible to fungal diseases caused by various pathogen groups. In recent years, efforts have been made to combat these diseases using biological control methods, particularly the application of arbuscular mycorrhizal fungi (AMF). This study aimed to determine the effects of AMF (Funneliformis mosseae (Fm) and Gigaspora margarita (Gm)) on Rhizoctonia fragariae (Rf), Fusarium oxysporum (Fo), and Alternaria alternata (Aa), which are major pathogens for strawberry. The results showed that the effects of AMF on disease severity and plant growth varied depending on the pathogens involved. Rf caused the highest disease severity, followed by Fo and Aa, but all AMF treatments significantly reduced the disease severity compared to control treatments. The study also found that the specific AMF species and their combinations influenced plant growth responses under different pathogenic conditions. Different AMF treatments resulted in varying increases in plant fresh weight, dry weight, and length, depending on the pathogen. Moreover, the application of AMF led to increased levels of total phenolic content, antioxidant activity, and phosphorus content in pathogen-infected plants compared to control treatments. Fm was more efficient than Gm in increasing these biochemical parameters. The levels of root colonization by AMF were similar among different AMF treatments, but the effects on fungal spore density varied depending on the pathogen. Some AMF treatments increased fungal spore density, while others did not show significant differences. In conclusion, our research sheds light on the differential effects of AMF species on disease severity, plant growth, and biochemical parameters in strawberry plants facing diverse pathogens. These findings underscore the potential benefits of AMF in disease management, as they reduce disease severity and bolster plant growth and defense mechanisms.This research study was financially supported by the Scientific Research Projects Coordination Unit of Van Yuzuncu Yil University. Project number: FBA-2019-7833.Demir, S.; Durak, ED.; Günes, H.; Boyno, G.; Mulet, JM.; Danesh, YR.; Porcel, R. (2023). Biological Control of Three Fungal Diseases in Strawberry (Fragaria X ananassa) with Arbuscular Mycorrhizal Fungi. Agronomy. 13(9). https://doi.org/10.3390/agronomy1309243913

Region prioritization for the development carbon capture and utilization technologies

In recent years several strategies have been developed and adopted to reduce the levels of the Greenhouse Gas Emissions emitted to the atmosphere. The adoption of Carbon Capture and Utilization (CCU) technologies may contribute towards carbon sequestration as well as to the creation of high value products. This study presents a methodology to assess the potential of CO2utilization across Europe, and to identify the European regions with the greater potential to deploy nine selected carbon dioxide utilization technologies. The results show that Germany, UK and France at the first level followed by Spain, Italy and Poland are the countries where the larger quantities of available CO2 could be found but also where the majority of the potential receiving processes are located, and therefore with the greatest potential for CO2 utilization. The study has also revealed several specific regions where reuse schemes based on CO2 could be developed both in Central Europe (Dusseldorf and Cologne – Germany, Antwerp Province and East Flanders –Belgium and Śląskie – Poland) and in Scandinavia (Etelä-Suomi and Helsinki-Uusimaa –Finland). Finally, among all the selected technologies, concrete curing and horticulture production are the technologies with the higher potential for CO2 utilization in Europe

Method to identify opportunities for CCU at regional level — Matching sources and receivers

Carbon Capture and Utilization is an attractive strategy not only due to its potential for CO2 emissions reduction but also because it enables the creation of valuable products. The development of CO2-based industrial symbiosis partnerships can contribute significantly towards achieving the goals of GHG emissions reduction on a European level by 2030, while at the same time it leads to an increased added value through the development of new production lines and carbon neutral products. The presented article focuses on identifying potential partnerships between companies that produce CO2 and companies that may reuse CO2 as input for their industrial process. A novel methodological framework is presented based on developing generic matrices for CO2 sources and receivers and matching the industrial units based on geographical and technical criteria. Moreover, the paper provides the technical requirements of 17 CO2 utilization technologies with relatively high technology readiness level, including the CO2-to-product ratio, the required purity, pressure, temperature and the presence of a catalyst, as well as potential synergies and additional requirements. The methodology has been applied to the Västra Götaland region in West Sweden and the most promising CCU symbiosis have been identified. These include mineral carbonation (annual uptake: 59,600 tCO2), greenhouses (26,000 tCO2), algae production, methanol production (85,500 tCO2), power to gas (66,500 tCO2), pH control, lignin production, polymers synthesis and concrete curing (96,000 tCO2). If all of them could be applied, the total annual CO2 reduction would exceed 250,000 tCO2 per year

The Slogan Effect: The Power Of Brand Discourse In Liking And Purchasing Behaviour

Discourses have been a determiner effect through human history. However, only with the development of communication technologies and globalization of trade the strategic importance of discourse has increased. Especially establishments comprehending the importance of branding have been searching for a strong discourse. The most effective and catchy of those discourses are called slogans. Slogans present the power of brand discourse while determining the superiority of the brand in commercial wars. Especially global brands are aware of the powerful effect of slogans. Based on this awareness, while they conduct their communication efforts, they endeavour to have strong slogans. When the literature is inspected it is seen that there are not enough studies regarding slogans which have a strong effect on both commercial and social life. This study is conducted both with the aim of satisfying this need and revealing the power of brand discourse in liking and purchasing behavior. Within this aim, an experimental study is applied, and it is tried to measure the effect of slogan liking to slogan purchasing behaviour, brand liking, brand purchasing behaviour, brand and slogan relationship liking and purchasing behaviour. In this study, a quantitative research method is applied, and the data is collected through questionnaires; the gathered data were analyzed in terms of frequency, regression and correlation. According to the results slogan liking greatly affects all the variables presented in the research model. Thus, it is concluded that brand discourse has a very powerful effect

The evaluation of central macular and choroidal thickness in myopic subjects with spectral-domain optical coherence tomography Miyopik olgularda santral makÜla ve koroid kalinliǧinin spektral domain optik kohorens tomografi yöntemiyle deǧ erlendirilmesi

Purpose: The evaluation of choroid becomes possible after the developments in the technology of optic coherence tomography (OCT). In this study we aimed to evaluate central macular and choroidal thickness in myopic subjects with spectraldomain optical coherence tomography (SD-OCT). Materials and Methods: After complete ophthalmological examination, a hundred and seventy six eyes of 88 subjects with no retinal or choroidal disease except myopia, underwent scanning with SD-OCT for the measurements of central macular and choroidal thickness. Five groups were formed according to the spherical equivalent calculations of the refraction as follows: Group 1 (Controls): Between 0.00 and -0.75 D; Group 2: -1.00 and -3.00 D; Group 3: -3.25 and -6.00 D; Group 4: -6.25 and -10.00 D and Group 5: over -10.25 D. Results: The evaluation of anterior segment and the measurement of intraocular pressure were within normal limits in all of the subjects. When the mean central macular thickness measurements were analysed, there was a statistically significant difference between group 5 compared with the other four groups. However, when the mean central choroidal thickness measurements were analysed, we found a statistically significant difference between all of the groups (p<0.05). Conclusion: Central macular and choroidal thickness may vary in some ocular pathologies. In this study, the thickness of the macula and choroid were found to be decreased with the increasing degree of myopia. The degree of myopia should be considered when evaluating macular and choroidal thickness in the studies

Automatic Hidden Sadness Detection Using Micro-Expressions

3dMD;Baidu;DI4D;et al.;Mitsubishi Electric Research Laboratories, Inc;NSF12th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2017 -- 30 May 2017 through 3 June 2017 -- -- 128713Micro-expressions (MEs) are very short, rapid, difficult to control and subtle which reveal hidden emotions. Spotting and recognition of MEs are very difficult for humans. Lately, researchers have tried to develop automatically MEs detection and recognition algorithms, however the biggest obstacle is the lack of a suitable datasets. Previous studies mainly focus on posed rather than spontaneous videos, and the obtained performances were low. To address these challenges, firstly we made a hidden sadness database, which includes 13 video clips elicited from students, who were watching very sad scenes from the movie in the University environment. Secondly, a new approach for automatic hidden sadness detection algorithm is proposed. Finally, Support Vector Machine and Random Forest classifiers are applied, since it has been shown that they provide state-of-the-art accuracy for the facial expression recognition problem. Two experiments were conducted, one with all extracted features from the face, and the other with only eye region features. The best results are achieved with Random Forest algorithm using all face features, with the recognition rate of 95.72%. For further improvement of the performance, we plan to integrate the deep Convolutional Neural Network algorithm, due to its grow popularity in the visual recognition. © 2017 IEEE

Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics

The climate modelling community has trialled a large number of metrics for evaluating the temporal performance of general circulation models (GCMs), while very little attention has been given to the assessment of their spatial performance, which is equally important. This study evaluated the performance of 36 Coupled Model Intercomparison Project 5 (CMIP5) GCMs in relation to their skills in simulating mean annual, monsoon, winter, pre-monsoon, and post-monsoon precipitation and maximum and minimum temperature over Pakistan using state-of-the-art spatial metrics, SPAtial EFficiency, fractions skill score, Goodman-Kruskal's lambda, Cramer's V, Mapcurves, and Kling-Gupta efficiency, for the period 1961-2005. The multi-model ensemble (MME) precipitation and maximum and minimum temperature data were generated through the intelligent merging of simulated precipitation and maximum and minimum temperature of selected GCMs employing random forest (RF) regression and simple mean (SM) techniques. The results indicated some differences in the ranks of GCMs for different spatial metrics. The overall ranks indicated NorESM1-M, MIROC5, BCC-CSM1-1, and ACCESS1-3 as the best GCMs in simulating the spatial patterns of mean annual, monsoon, winter, pre-monsoon, and post-monsoon precipitation and maximum and minimum temperature over Pakistan. MME precipitation and maximum and minimum temperature generated based on the best-performing GCMs showed more similarities with observed precipitation and maximum and minimum temperature compared to precipitation and maximum and minimum temperature simulated by individual GCMs. The MMEs developed using RF displayed better performance than the MMEs based on SM. Multiple spatial metrics have been used for the first time for selecting GCMs based on their capability to mimic the spatial patterns of annual and seasonal precipitation and maximum and minimum temperature. The approach proposed in the present study can be extended to any number of GCMs and climate variables and applicable to any region for the suitable selection of an ensemble of GCMs to reduce uncertainties in climate projections