I liked the publication which investigate the prediction capacity of ANN to obtain AUDPC values for tomato late blight using a lower number of evaluations to improve the process efficiency. Very informative

file:///C:/Users/Acer/Downloads/AUDPC-TomatoBlight-2016%20(3).pdf

Dear Dr. Mohammed Fayyadh, I hope thee following articles will help you much about AUDPC and please go through them. Have a wonderful study time.

This link has also an interesting issues on haw to calculate AUDPC

http://www.apsnet.org/EDCENTER/ADVANCED/TOPICS/ECOLOGYANDEPIDEMIOLOGYINR/DISEASEPROGRESS/Pages/AUDPC.aspx

Articles on how to calculate AUDPC

Thank you so much Dr.Beemnet

Dear Prof. Mohammed

AUDPC means : Area under the Disease-Progress Curve.

you can return to the following article:

The use of the area under the disease-progress curve (AUDPC) to assess quantitative disease resistance in crop cultivars. by : M. J. Jeger and S. L. H. Viljanen-Rollinson. Theoretical and Applied Genetics, January 2001, Volume 102, Issue 1, pp 32–40.

I hope it helps you.

With best greetings...

Calculation of the area under the disease-progress curve (AUDPC) as a measure of quantitative disease resistance entails repeated disease assessments. For typical sigmoid disease-progress curves, repeated assessments may be unnecessary. A mathematical procedure is derived for estimating the AUDPC from two data points. A field trial with ten cultivars with and without the gene Yr18 for resistance to stripe rust were inoculated with two pathotypes of Puccinia striiformis (from the cultivars Karamu and Oroua) and assessed for the percentage leaf area infected seven or eight times during the growing season. The AUDPCs were calculated directly from data and estimated from the described equation. Calculated values were plotted and ranked against estimated values, and excellent correspondence was obtained (Spearman’s Rank Correlation in the Karamu trial= 0.9879 and the Oroua trial=0.9515). Therefore, an estimation of the AUDPC from two data points provides an equivalent amount of information as from repeated assessments.

Also you can depend on the article below :

The use of area under the disease progress curve to assess resistance to late blight in potato germplasm. By : Kathleen G. Haynes and  Peter Weingartner. American Journal of Potato Research, March 2004, Volume 81, Issue 2, pp 137–141.

The multiple evaluation of potato cultivais and breeding selections (clones) for disease during the season can be costly and may not be necessary for accurate assessments of disease resistance or susceptiblity. For diseases whose progression can be described by sigmoid curves, an estimate of the area under the disease progress curve from two data points may provide as much information as from repeated assessments. Twentythree clones were planted in a randomized complete block design in Hastings, FL, in 1997 and evaluated for percent diseased foliage 14 times during a 31-day period after late blight was first noticed in the plots. The area under the disease progress curve (AUDPC) was calculated for all 14 assessments. The AUDPC was also calculated for nine sub-sets of the original data set. There was a high correlation between all the methods in the calculation of the AUDPC. The AUDPC calculated based on two dates (representing the beginning of the epidemic and the time until two of the clones were dead from late blight) was as informative as the AUDPC calculated on the entire data set. The AUDPC could be calculated based on any two dates from this time frame as long as one date was shortly after the epidemic started and the other date was as the epidemic was reaching its peak. Much information was lost if AUDPC was calculated based on dates involved only in the early part of the epidemic. A considerable savings in time and effort can be realized by only a few assessments.

Following

You can see too..

Area under disease progress curve and apparent infection rate of Alternaria blight disease of Indian mustard (Brassica juncea) at different plant age. By : Prabhu Dayal Meena . Archives of Phytopathology and Plant Protection, Volume 44, 2011 - Issue 7.

Plant age has a major influence on the incidence of Alternaria blight disease in Indian mustard crops. Disease progression was monitored twice a week on the two chosen Indian mustard cultivars viz., Varuna and Rohini throughout the season. Severity of blight caused by Alternaria brassicae and Alternaria brassicicola decreased with delay in sowing. Calculation for A-value (Area under disease progress curve – AUDPC) and r-value (apparent infection rate) in crops sown on different dates could identify the speed of progress in the disease on leaves and pods, as the crop does not posses resistance to the pathogen till date. Thus, the probable dates of sowing enabling slow disease progress or the weather conditions coinciding with the different crop phenological stages demarcated the advantageous dates of sowing from the disadvantageous ones. However, cultivar Varuna is more susceptible as compared to the other cultivar Rohini, as apparent infection rate both on leaves and pods was higher in former. Highest per cent disease severity (PDS) for season highly correlated with date of sowing, i.e. delayed date of sowing increased PDS.

Dear Prof.

The Area Under the Disease Progress Curve (AUDPC) is a quantitative measure of disease intensity with time. It is used in plant pathology to indicate and compare levels of resistance to diseases among varieties of plants. The trapezoid method.is the most common way to calculate AUDPC. It is performed by using a formula devised by Campbell and Madden in 1990 or by plotting a graph of percentage of infection against time and summing the trapezoids between time intervals.

How to calculate AUDPC?

Calculate AUDPC from an Equation

Add the first two infection percentages you recorded.

Divide the addition result by two to find the average or mid-value of the two readings.

Multiply the average or mid-value by the time interval, which is the number of days from the first reading to the second reading. If you took the first reading on day 20 and the second reading on day 27, for example, then the number of days, or time interval, is seven days.

Record the result in units of percentage days. The value is an area of a trapezoid.

Repeat Steps One through Four for the second and third infection readings you took. Their result will be the area of a second trapezoid. Repeat Steps One through Four until you calculated trapezoid areas for all readings.

Add all of the trapezoids to find the AUDPC. Lower AUDPCs represent slower disease progression and greater resistance to the disease. Higher AUDPCs represent faster disease progression and higher susceptibility to the disease.

Also you can find the paper titled :

The use of the area under the disease-progress curve (AUDPC)

to assess quantitative disease resistance in crop cultivars. By : M.J. Jeger · S.L.H. Viljanen-Rollinson . Theor Appl Genet (2001) 102:32–40 .

Dear Prof. Mohammed .

You must read the following abstract, it may be helpful :

Calculation of the area under the disease-pro-gress curve (AUDPC) as a measure of quantitative disease resistance entails repeated disease assessments. For typical sigmoid disease-progress curves, repeated assessments may be unnecessary. A mathematical procedure is derived for estimating the AUDPC from two data points. A field trial with ten cultivars with and without the gene Yr18 for resistance to stripe rust were inoculated with two pathotypes of Puccinia striiformis

(from the cultivars Karamu and Oroua) and assessed for the percentage

leaf area infected seven or eight times during the growing season. The AUDPCs were calculated directly from data and estimated from the described equation. Calculated values were plotted and ranked against estimated values, and excellent correspondence was obtained (Spearman’s Rank Correlation in the Karamu trial=

0.9879 and the Oroua trial=0.9515). Therefore, an estimation of the AUDPC from two data points provides an equivalent amount of formation as from repeated assissment.

Good luck..

I liked the publication which investigate the prediction capacity of ANN to obtain AUDPC values for tomato late blight using a lower number of evaluations to improve the process efficiency. Very informative

file:///C:/Users/Acer/Downloads/AUDPC-TomatoBlight-2016%20(3).pdf

Dear, Prof. Mohammed..

I hope you achieve your aim to cover the term AUDPC and support your preoject from the above informations , papers and articles that I sent .

I whish you all the best.

Thank you so much Dr Yehya

You most welcome dear Prof. Mohammed , I hope you have high usefulness.

Please accept my appreciation.

Dear Prof.

You can reed the attached paper, it my be helpful.

Also you can have a benefit from the following paper.

Also find the attached paper:

May be the attached paper is good for AUDPC..

See this too:

The attached paper also discusses the term AUDPC. Please see it.

With best regards