ABSTRACT
Introduction: Most areas under spring sugar beet cultivation face severe water restrictions and increasing the area under cultivation of this crop in most of these areas is contrary to the principle of conservation of water and soil resources. The use of new areas for winter sugar beet cultivation should be the area under cultivation of this crop in hot and dry areas. Therefore, winter sowing (pending) of sugar beet with emphasis on the limitations of the country's water resources has been proposed as a solution. Materials and Methods: In this study, the quantitative and qualitative yield of 16 sugar beet genotypes in winter planting were studied as a randomized complete block design with four replications in the Torbat-e-Jam region in the two cropping years (2020-2021 and 2021-2022). The studied genotypes included F-20739, F-20837, F-21083, SBSI-5, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, FDIR 19 B 4028, F-20591, SBSI-6, SBSI-16, SBSI-7 and SBSI-17 are the breeding populations obtained from the gene bank of the Sugar Beet Seed Breeding Research Institute. In this research, traits such as root yield, sugar content, sugar yield, white sugar yield, Na, K, N, alkalinity, molasses sugar, white sugar content, and extraction coefficient of sugar were measured. Data were analyzed using SAS 9.1 software. The analysis of variance on test data and comparison to the middle of the Duncan test was performed at the 5% level. Factor analysis was calculated to identify the main factors using MINITAB software. Cluster analysis of the studied genotypes was obtained after standardizing the data by the Ward method and using Euclidean distance criterion with the help of SPSS software. Results and Discussion: The results of the combined analysis of variance showed that there was a significant difference between different genotypes of sugar beet at the level of 1% probability for all studied traits except for nitrogen content. The mean comparison showed that the SBSI-15 genotype had the highest root yield (60.66 ton.ha). It should be noted that this genotype in terms of yield index traits did not show significantly different from genotypes F-20739, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, and FDIR 19 B 4028. Also, the F-20739 genotype had the highest amounts of sugar content (19.5%), white sugar content (16.3%) and extraction coefficient of sugar (83.2%) and the lowest amount of potassium (4.24 meq .100 g-1 of root weight) and Molasses sugar (2.7%). In addition, the highest sugar yield (10.69 t/ha) and white sugar yield (8.68 t/ha) were in FDIR 19 B 3021 genotype. Investigating the correlation of traits showed the highest positive and significant correlation was between sugar yield and white sugar yield (0.99**) and the highest negative and significant correlation was between extraction coefficient of sugar and molasses sugar (-0.95**). Principal factor analysis based on the mean of the traits identified three factors that accounted for a total of 91% of the variability between the data. SBSI-15, SVZA 2019-JD0398, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, and FDIR 19 B 4028 genotypes are distinguished different from other genotypes and they were as superior genotypes in terms of yield index traits. The dendrogram generated from the cluster analysis for white sugar yield classified genotypes into three main groups.
ABSTRACT
Artificial intelligence (AI) development and its application in human life are continuing at an astounding rate. Among the variety of examples of AI being used for a variety of tasks, its contribution to epidemic control has recently captured a great deal of interest at the time of the recent Covid-19 pandemic, a crisis that occurred due to the Coronavirus spread. As the entire world has been concerning over urgent efforts addressing the damaging effects since the outbreak, Artificial Intelligence emerged as a great possible solution. This study is aimed at examining how artificial intelligence gets us ready to combat and control COVID-19 and other future pandemics, as this is unlikely to be the last of the epidemics. Moreover, several key technological solutions are outlined that could help combat future pandemics and make us prepared. As a result, technology development can be promoted to overcome any possible unexpected subsequent crisis. © 2021 IEEE.
ABSTRACT
During the COVID-19 pandemic, patients with better general conditions are sent to their own homes for self-quarantine due to a lack of resources in the health system, especially the lack of beds and human resources. Improving patient care may force households to inevitably use home care services, which can be examined from the health equity perspective. In the first step, home care services should be expanded by medical universities in all regions of the country, including less developed areas. In the second step, the financial protection of the recipients of these services should be provided through interventions, such as health insurance coverage. In addition, after the COVID- 19 pandemic (post-corona period), it is necessary to organize home care services as soon as possible due to the population aging trend. Finally, despite the problems caused by the COVID-19 pandemic in the country, it is better to use the challenges, actions, and lessons learned from this crisis to complete the infrastructure of the health system in various ways.
ABSTRACT
The purpose of this preliminary investigation is to find the effect of the COVID-19 pandemic on water quality parameters in rivers, especially in the Great Lakes Basins. Several rivers and coastal areas in the Great Lakes region are highly polluted due to industrial and agricultural activities. The lockdown has caused industrial activities to shut down, people to work from home, and less waste to be introduced into natural bodies of water. Several studies show that air quality has improved during the lockdown in a variety of places, especially in big cities, but there are fewer studies on water quality parameters. Recent studies, using satellite images, show there are improvements in the water quality of lakes and bays due to less traffic and industrial activities. In this study, with the collaboration of two high schoolers, we want to find rivers with dissolved oxygen data, in the Great Lakes region, and compare the period of lockdown with the same period of time in 2019. The outcome of this study will provide a better understanding of the role of human activities on water quality in natural systems and can be used for public education and awareness of environmental protection. © ASCE.