scholarly journals The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their monthly interval prediction from September 1, 2021 to December 31, 2021

2022 ◽  
Author(s):  
Avtandil G. Amiranashvili ◽  
Ketevan R. Khazaradze ◽  
Nino D. Japaridze
Keyword(s):  
Statistical Analysis ◽  
Infection Rate ◽  
Monthly Interval ◽  
Maximum Effect ◽  
Similar Data ◽  
Daily Mortality ◽  
Mean Values ◽  
Daily Data ◽  
The World ◽  
Investigation Period

The lockdown introduced in Georgia on November 28, 2020 contributed to positive trends in the spread of COVID-19 until February - the first half of March 2021. Then, in April-May 2021, the epidemiological situation worsened significantly, and from June to the end of December COVID - situation in Georgia was very difficult. In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from September 01, 2021 to December 31, 2021 are presented. It also presents the results of the analysis of monthly forecasting of the values of C, D and I. As earlier, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgia's ranking in the world for Covid-19 monthly mean values of infection and deaths cases in investigation period (per 1 million population) was determined. Among 157 countries with population ≥ 1 million inhabitants in October 2021 Georgia was in the 4 place on new infection cases, and in September - in the 1 place on death. Georgia took the best place in terms of confirmed cases of diseases (thirteenth) in December, and in mortality (fifth) - in October. A comparison between the daily mortality from Covid-19 in Georgia from September 01, 2021 to December 31, 2021with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 76.8 % (September 03, 2021), the smallest 18.7 % (November 10, 2021). As in previous work [9,10] the statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 6024 (November 3, 2021), R = 6017 (November 15, 2021), D = 86 (September 3, 2021), I = 12.04 % (November 24, 2021). Maximum mean decade values of investigation parameters are following: C = 4757 (1 Decade of November 2021), R = 4427 (3 Decade of November 2021), D = 76 (2 Decade of November 2021), I = 10.55 % (1 Decade of November 2021). It was found that as in spring and summer 2021 [9,10], from September to December 2021 the regression equations for the time variability of the daily values of C, R, D and I have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months for the indicated period of time were determined. Maximum mean decade values of investigation parameters are following: V(C) = +139 cases/day (1 Decade of October 2021), V(R) = +124 cases/day (3 Decade of October 2021), V(D) = +1.7 cases/day (3 Decade of October 2021), V(I) = + 0.20 %/ day (1 decades of October 2021). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that from September 1, 2021 to November 30, 2021 the maximum effect of recovery is observed on 12 and 14 days after infection (CR=0.77 and 0.78 respectively), and deaths - after 7, 9, 11, 13 and 14 days (0.70≤CR≤0.72); from October 1, 2021 to December 31, 2021 - the maximum effect of recovery is observed on 14 days after infection (RC=0.71), and deaths - after 9 days (CR=0.43). In Georgia from September 1, 2021 to November 30, 2021 the duration of the impact of the delta variant of the coronavirus on people (recovery, mortality) could be up to 28 and 35 days respectively; from October 1, 2021 to December 31, 2021 - up to 21 and 29 days respectively. Comparison of daily real and calculated monthly predictions data of C, D and I in Georgia are carried out. It was found that in investigation period of time daily and mean monthly real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values. Traditionally, the comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

scholarly journals The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their short-term interval prediction in spring 2021

2021 ◽  
Author(s):  
Avtandil G. Amiranashvili ◽  
Ketevan R. Khazaradze ◽  
Nino D. Japaridze
Keyword(s):  
Statistical Analysis ◽  
Infection Rate ◽  
Maximum Effect ◽  
Similar Data ◽  
Regression Equations ◽  
Daily Mortality ◽  
Short Term ◽  
Mean Values ◽  
Daily Data ◽  
The World

The lockdown introduced in Georgia on November 28, 2020 brought positive results. There are clearly positive tendencies in the spread of COVID-19 to February - first half of March 2021. However, in April-May 2021 there was a significant deterioration in the epidemiological situation. In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from March 01, 2021 to May 31, 2021 are presented. It also presents the results of the analysis of two-week forecasting of the values of C, D and I. The information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/. The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained. Georgia's ranking in the world for Covid-19 monthly mean values of infection and deaths cases in spring 2021 (per 1 million population) was determined. Among 156 countries with population ≥ 1 million inhabitants in May 2021 Georgia was in the 11 place on new infection cases and in the 14 place on Death. A comparison between the daily mortality from Covid-19 in Georgia in spring 2021 with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 25.3 % (22.05.2021), the smallest 1.42 % (15.03.2021). Data about infection rate of the population of Georgia with Covid-19 according to traffic light system shown, that Georgia in April and May 2021 was in the red zone. The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 2171 (05.05.2021), R = 2038 (17.05.2021), D = 33 (22.05.2021), I = 8.05 % (04.05.2020). Maximum mean decade values of investigation parameters are following: C = 1258 (3 Decade of April 2021), R = 1283 (2 Decade of May 2021), D = 24 (2 Decade of May 2021), I = 6.54 % (1 Decade of May 2021). It was found that as with September 2020 to February 2021 [8], in spring 2021 the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial. Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months in the spring 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +37 cases/day (1 Decade of April 2021), V(R) = +36 cases/day (3 Decade of April 2021), V(D) = +0.6 cases/day (3 Decade of April 2021), V(I) = + 0.17 %/ day (2 and 3 decades of April 2021). Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that the maximum effect of recovery is observed 9 and 13 days after infection, and deaths - after 12-17 days. Comparison of real and calculated predictions data of C, D and I in Georgia are carried out. It was found that two-week daily and mean two-week real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values for the specified time periods. The comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out. Key words: New Coronavirus COVID-19, statistical analysis, short-term prediction.

scholarly journals The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their two-week interval prediction in summer 2021

2021 ◽  
Author(s):  
Avtandil G. Amiranashvili ◽  
Ketevan R. Khazaradze ◽  
Nino D. Japaridze
Keyword(s):  
Statistical Analysis ◽  
Infection Rate ◽  
Maximum Effect ◽  
Similar Data ◽  
Regression Equations ◽  
Daily Mortality ◽  
Mean Values ◽  
Daily Data ◽  
The World ◽  
Epidemiological Situation

AbstractThe lockdown introduced in Georgia on November 28, 2020 brought positive results. There were clearly positive tendencies in the spread of COVID-19 to February - first half of March 2021. However, in April-May 2021 there was a significant deterioration in the epidemiological situation. From June to August 2021, the epidemiological situation with Covid-19 in Georgia became very difficult.In this work results of the next statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from June 01, 2021 to August 31, 2021 are presented. It also presents the results of the analysis of two-week forecasting of the values of C, D and I. As earlier, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/.The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained.Georgia’s ranking in the world for Covid-19 monthly mean values of infection and deaths cases in summer 2021 (per 1 million population) was determined. Among 159 countries with population ≥ 1 million inhabitants in August 2021 Georgia was in the 1 place on new infection cases and on Death.A comparison between the daily mortality from Covid-19 in Georgia in summer 2021 with the average daily mortality rate in 2015-2019 shows, that the largest share value of D from mean death in 2015-2019 was 66.0 % (26.08.2021 and 31.08.2021), the smallest 6.0 % (09.07.2021).The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 6208 (17.08.2021), R = 6177 (29.08.2021), D = 79 (26.08.2021 and 31.08.2021), I = 13.0 % (17.08.2021). Maximum mean decade values of investigation parameters are following: C = 5019 (2 Decade of August 2021), R = 4822 (3 Decade of August 2021), D = 69 (3 Decade of August 2021), I = 10.88 % (2 Decade of August 2021).It was found that as with September 2020 to February 2021 and in spring 2021 [7,8], from June to August 2021 the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial.Mean values of speed of change of confirmed -V(C), recovered - V(R), deaths - V(D) and infection rate V(I) coronavirus-related cases in different decades of months in the summer 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +134 cases/day (1 Decade of August 2021), V(R) = +134 cases/day (2 Decade of August 2021), V(D) = +2.4 cases/day (3 Decade of August 2021), V(I) = + 0.25 %/ day (1 decades of August 2021).Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases shows, that the maximum effect of recovery is observed 19 days after infection (RC=0.95), and deaths - after 16 and 18 days (RC=0.94). In Georgia in the summer 2021, the duration of the impact of the delta variant of the coronavirus on people (recovery, mortality) could be up to two months.Comparison of real and calculated predictions data of C, D and I in Georgia are carried out. It was found that in summer 2021 two-week daily and mean two-week real values of C, D and I practically fall into the 67% - 99.99% confidence interval of these predicted values.With September 1, 2021, it is started monthly forecasting of C, D and I values.As earlier, the comparison of data about C and D in Georgia (GEO) with similar data in Armenia (ARM), Azerbaijan (AZE), Russia (RUS), Turkey (TUR) and in the World (WRL) is also carried out.

scholarly journals The statistical analysis of daily data associated with different parameters of the New Coronavirus COVID-19 pandemic in Georgia and their short-term interval prediction from September 2020 to February 2021

2021 ◽  
Author(s):  
Avtandil G. Amiranashvili ◽  
Ketevan R. Khazaradze ◽  
Nino D. Japaridze
Keyword(s):  
Time Series ◽  
Statistical Analysis ◽  
Confidence Interval ◽  
Infection Rate ◽  
Maximum Effect ◽  
Regression Equations ◽  
Daily Mortality ◽  
Daily Data ◽  
The World ◽  
Upper Level

AbstractIn the autumn - winter period of 2020, very difficult situation arose in Georgia with the course of the pandemic of the New Coronavirus COVID-19. In particular, in November-December period of 2020, Georgia eight days was rank a first in the world in terms of COVID-19 infection rate per 1 million populations.In this work results of a statistical analysis of the daily data associated with New Coronavirus COVID-19 infection of confirmed (C), recovered (R), deaths (D) and infection rate (I) cases of the population of Georgia in the period from September 01, 2020 to February 28, 2021 (for I - from December 05, 2020 to February 28, 2021) are presented. It also presents the results of the analysis of ten-day (decade) and two-week forecasting of the values of C, D and I, the information was regularly sent to the National Center for Disease Control & Public Health of Georgia and posted on the Facebook page https://www.facebook.com/Avtandil1948/.The analysis of data is carried out with the use of the standard statistical analysis methods of random events and methods of mathematical statistics for the non-accidental time-series of observations. In particular, the following results were obtained.Georgia’s ranking in the world for Covid-19 infection and deaths from September 1, 2020 to February 28, 2021 (per 1 million population) was determined. Georgia was in the first place: Infection - November 21, 22, 27, 28 and December 04, 05, 06, 09, 2020; Death - November 22, 2020.A comparison between the daily mortality from Covid-19 in Georgia from September 1, 2020 to February 28, 2021 with the average daily mortality rate in 2015-2019 was made. The largest share value of D from mean death in 2015-2019 was 36.9% (19.12.2020), the smallest - 0.9% (21.09.2020, 24.09.2020 - 26.09.2020).The statistical analysis of the daily and decade data associated with coronavirus COVID-19 pandemic of confirmed, recovered, deaths cases and infection rate of the population of Georgia are carried out. Maximum daily values of investigation parameters are following: C = 5450 (05.12.2020), R = 4599 (21.12.2020), D = 53 (19.12.2020), I = 30.1 % (05.12.2020). Maximum mean decade values of investigation parameters are following: C = 4337 (1 Decade of December 2020), R = 3605 (3 Decade of November 2020), D = 44 (2 Decade of December 2020), I = 26.8 % (1 Decade of December 2020).It was found that the regression equations for the time variability of the daily values of C, R and D have the form of a tenth order polynomial.Mean values of speed of change of confirmed -V(C), recovered - V(R) and deaths - V(D) coronavirus-related cases in different decades of months from September 2020 to February 2021 were determined. Maximum mean decade values of investigation parameters are following: V(C) = +104 cases/day (1 Decade of November 2020), V(R) = +94 cases/day (3 Decade of October and 1 Decade of November 2020), V(D) = +0.9 cases/day (1 Decade of November 2020).Cross-correlations analysis between confirmed COVID-19 cases with recovered and deaths cases from 05.12.2020 to 28.02.2021 is carried out. So, the maximum effect of recovery is observed 13-14 days after infection, and deaths - after 13-14 and 17-18 days.The scale of comparing real data with the predicted ones and assessing the stability of the time series of observations in the forecast period in relation to the pre-predicted one was offered.Comparison of real and calculated predictions data of C (23.09.2020-28.02.2021), D (01.01.2021-28.02.2021) and I (01.02.2021-28.02.2021) in Georgia are carried out. It was found that daily, mean decade and two-week real values of C, D and I practically falls into the 67% - 99.99% confidence interval of these predicted values for the specified time periods (except the forecast of C for 13.10.2020-22.10.2020, when a nonlinear process of growth of C values was observed and its real values have exceeded 99.99% of the upper level of the confidence interval of forecast).Alarming deterioration with the spread of coronavirus parameters may arise when their daily values are higher 99.99% of upper level of the forecast confidence interval. Excellent improvement - when these daily values are below 99.99% of the lower level of the forecast confidence interval.The lockdown introduced in Georgia on November 28, 2020 brought positive results. There are clearly positive tendencies in the spread of COVID-19 to February 2021.

scholarly journals Asymmetrical heat flow distribution on the mid-oceanic ridges of the World Ocean

2019 ◽  
Vol 489 (2) ◽  
pp. 183-189
Author(s):  
M. D. Khutorskoi ◽  
E. A. Teveleva
Keyword(s):  
Statistical Analysis ◽  
Heat Flow ◽  
Northern Hemisphere ◽  
Coriolis Force ◽  
World Ocean ◽  
Flow Distribution ◽  
Mean Values ◽  
Eastern Flank ◽  
Western Flank ◽  
The World

A statistical analysis of heat flow distribution along nine geotravers crossing the mid-oceanic ridges in the Atlantic, Pacific and Indian oceans is carried out. A significant asymmetry of heat flow distribution is established-its mean values differ on opposite sides of the ridges axis. In geotraverses of the southern Earths hemisphere, their western flank has a higher heat flow mean, and in the geotraverses of the northern hemisphere there is the eastern flank. Various tectonic factors that lead to such a distribution are taken into account, but the universal cause of this regularity is suggested to be the effect of the Coriolis force, which, when the planet rotates, redistributes the magmatic material amount in the asthenospheric reservoir.

Why Democracy Protests Do Not Diffuse

2018 ◽  
Vol 63 (10) ◽  
pp. 2354-2389 ◽  
Author(s):  
Dawn Brancati ◽  
Adrián Lucardi
Keyword(s):  
Statistical Analysis ◽  
Positive Information ◽  
Demonstration Effect ◽  
Temporal Clustering ◽  
Daily Data ◽  
The World

One of the primary international factors proposed to explain the geographic and temporal clustering of democracy is the diffusion of democracy protests. Democracy protests are thought to diffuse across countries, primarily, through a demonstration effect, whereby protests in one country cause protests in another based on the positive information that they convey about the likelihood of successful protests elsewhere and, secondarily, through the actions of transnational activists. In contrast to this view, we argue that, in general, democracy protests are not likely to diffuse across countries because the motivation for and the outcome of democracy protests result from domestic processes that are unaffected or undermined by the occurrence of democracy protests in other countries. Our statistical analysis supports this argument. Using daily data on the onset of democracy protests around the world between 1989 and 2011, we find that in this period, democracy protests were not significantly more likely to occur in countries when democracy protests had occurred in neighboring countries, either in general or in ways consistent with the expectations of diffusion arguments.

PSYCHOLOGICAL FEATURES OF EDUCATION AND TOLERANCE IN STUDENTS

2018 ◽  
Vol 16 (1) ◽  
pp. 112-119
Author(s):  
VLADIMIR GLEB NAYDONOV
Keyword(s):  
Statistical Analysis ◽  
Training Program ◽  
Rich Diversity ◽  
Interethnic Differences ◽  
The World ◽  
The Rich ◽  
Correct Understanding ◽  
Psychological Features ◽  
Different Levels

The article considers the students’ tolerance as a spectrum of personal manifestations of respect, acceptance and correct understanding of the rich diversity of cultures of the world, values of others’ personality. The purpose of the study is to investgate education and the formation of tolerance among the students. We have compiled a training program to improve the level of tolerance for interethnic differences. Based on the statistical analysis of the data obtained, the most important values that are significant for different levels of tolerance were identified.

Awareness and perception of precautionary measures against Covid 19 exposure among dental practitioners- A questionnaire based study

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 550-557
Author(s):  
Harini P ◽  
Abilasha R
Keyword(s):  
Statistical Analysis ◽  
Aerosol Formation ◽  
Dental Clinic ◽  
Attitude And Practice ◽  
Dental Practitioners ◽  
Hands On ◽  
The World ◽  
Spss Software ◽  
Precautionary Measures ◽  
Knowledge And Attitude

The most unexpected pandemic global outbreak is COVID 19 which is a newly discovered viral infection which originated in Wuhan, China and it caused the outbreak of pneumonia in the rest of the world. Dental practitioners are more susceptible to COVID 19 infection as their work is related to the aerosol formation during various procedures through which the virus spreads. The aim of the study is to create awareness about precautionary measures against COVID- 19 exposure among dental practitioners in Tamilnadu. A Survey based questionnaire was formulated with questions related to the various precautionary measures to be adopted by dental practitioners which would be effective to prevent Covid-19 exposure. A questionnaire with a total of 20 questions was circulated among dental practitioners and the responses were collected by google forms SPSS software statistical analysis was done. The overall awareness of dental practitioners against Covid-19 was above average. The dental practitioners were relatively well aware of the precautions to be adopted while treating the patients, but the implementation in practice is lacking due absence of hands-on experience in using various kinds of PPE. There is a gap between knowledge and attitude and practice among the participants of this survey. It is therefore essential to plan for organising training sessions and hands-on workshops for the use of PPE and public training of the general population regarding Covid-19 to improve the knowledge among the patients visiting the dental clinic as well.

scholarly journals The Effect of Vaccination Rates on the Infection of COVID-19 under the Vaccination Rate below the Herd Immunity Threshold

2021 ◽  
Vol 18 (14) ◽  
pp. 7491
Author(s):  
Yi-Tui Chen
Keyword(s):  
Infection Rate ◽  
Herd Immunity ◽  
The United States ◽  
Vaccination Rate ◽  
Infection Rates ◽  
Vaccination Rates ◽  
The United Kingdom ◽  
The World ◽  
Almost All ◽  
The Impact

Although vaccination is carried out worldwide, the vaccination rate varies greatly. As of 24 May 2021, in some countries, the proportion of the population fully vaccinated against COVID-19 has exceeded 50%, but in many countries, this proportion is still very low, less than 1%. This article aims to explore the impact of vaccination on the spread of the COVID-19 pandemic. As the herd immunity of almost all countries in the world has not been reached, several countries were selected as sample cases by employing the following criteria: more than 60 vaccine doses per 100 people and a population of more than one million people. In the end, a total of eight countries/regions were selected, including Israel, the UAE, Chile, the United Kingdom, the United States, Hungary, and Qatar. The results find that vaccination has a major impact on reducing infection rates in all countries. However, the infection rate after vaccination showed two trends. One is an inverted U-shaped trend, and the other is an L-shaped trend. For those countries with an inverted U-shaped trend, the infection rate begins to decline when the vaccination rate reaches 1.46–50.91 doses per 100 people.

PHYSIOLOGIC HYPERBILIRUBINEMIA AND HEMOLYSIS OF ERYTHROCYTES BY HYDROGEN PEROXIDE SOLUTION IN THE NEWBORN: INVESTIGATION OF A POSSIBLE RELATIONSHIP

PEDIATRICS ◽  
1957 ◽  
Vol 20 (1) ◽  
pp. 92-97
Author(s):  
Jo-Anne E. Richards ◽  
Richard B. Goldbloom ◽  
Ronald L. Denton
Keyword(s):  
Hydrogen Peroxide ◽  
Statistical Analysis ◽  
Vitamin E ◽  
Clinical Significance ◽  
Newborn Infant ◽  
Newborn Infants ◽  
Control Group ◽  
Term Infants ◽  
Mean Values ◽  
Relative Deficiency

Forty-three full-term infants have been studied with respect to hemolysis of erythrocytes in solutions of hydrogen peroxide and concentrations of bilirubin in the serum. Mean values for concentration of bilirubin in the serum and percentage of hemolysis followed similar patterns in the first few days of life. However, statistical analysis of the data in individual cases showed no significant correlation between the degree of hemolysis in solutions of hydrogen peroxide and the concentrations of bilirubin in the serum. Administration of vitamin E prevented an increase in hemolysis of erythrocytes in solutions of hydrogen peroxide but failed to produce any significant change in concentrations of bilirubin as compared with the control group. The evidence suggests that the relative deficiency of vitamin E which exists in most newborn infants does not play a part in the causation or maintenance of physiologic hyperbilirubinemia. The clinical significance of increased hemolysis of the erythrocytes of the newborn infant in solutions of hydrogen peroxide remains a mystery. Possible approaches to the clarification of this problem are suggested.

scholarly journals Identification of Bacterial Diseases in Rice Plants Leaves by the Use of Spectroscopic Imaging

2015 ◽  
Vol 7 (6) ◽  
pp. 61 ◽  
Author(s):  
Mama Sangare ◽  
C. Tekete ◽  
O. K. Bagui ◽  
A. Ba ◽  
J. T. Zoueu
Keyword(s):  
Statistical Analysis ◽  
Bacterial Wilt ◽  
Spectral Region ◽  
Imaging Techniques ◽  
Xanthomonas Oryzae ◽  
Multivariate Statistical ◽  
Bacterial Diseases ◽  
The World ◽  
Rice Leaves ◽  
Statistical Analysis Methods

<p class="1Body">Rice is staple in the African habitats menu. Bacterial wilt (BLB) and leaf streak (BLS) are some of the phytopathological diseases which restrain rice production around the world. In this paper, multi-spectral and multi-modal imaging techniques have been developed to characterize the rice leaves with symptoms of bacterial wilt (BLB) and leaf streak (BLS), and to provide information on their effects, in order to reduce their spread. First, we recorded microscopic and spectroscopic images of the samples using multimodal and multispectral microscope, with spectral region ranging from UV to NIR, for each mode. Then, we extracted the spectral footprints of the cells constituents, in transmission, reflection and scattering from the spectral images. Applying multivariate statistical analysis methods to this optical spectra allowed us to characterize the effect of bacterial rice leaves caused by <em>Xanthomonas oryzae</em> strains. The results of the proposed technique can be useful for easy identification of this type of infection, and can serve as routine approach in biochemical and agronomic laboratories.</p>

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