PROBIT ANALYSIS for calculating LC 50 VALUES

Probit analysis

1. UNIVERSITY OF AGRICULTURAL SCIENCES, BANGLORE COLLEGE OF SERICULTURE ,CHINTAMANI SUB:TOXICOLOGY OF INSECTICIDES ENT 506 (2+1) PRESENTED TO, Dr. Narasareddy , G. Asst. Professor Dept. of Entomology College of Sericulture Chintamani PRESENTED BY, Punith kumar S.R PAMC3008 Jr.MSc (Agri.)Entomology College of Agriculture Chintamani

2. PROBIT ANALYSIS UNDERSTANDING AND APPLYING THE TECHNIQUE

3. Background The idea of probit analysis was originally published in Science by Chester Ittner Bliss in 1934. He was primarily concerned with finding an effective pesticide to control insects that fed on grape leaves (Greenberg 1980). Each pesticide affected the insects at different concentrations. By plotting the response of the insects to various concentration of pesticides The most logical approach would be to fit a regression of the response versus the concentration, or dose and compare between the different pesticides. Yet, the relationship of response to dose was sigmoid in nature and at the time regression was only used on linear data. Therefore, Bliss developed the idea of transforming the sigmoid dose-response curve to a straight line.

4. 1952 – David Finney – book – Probit Analysis

5. PROBIT ANALYSIS Probit analysis is a type of regression used to analyze binomial response variables. Remember that regression is a method of fitting a line to your data to compare the relationship of the response variable or dependent variable (Y) to the independent variable (X). Y = a + b X + e Where • a = y-intercept • b = the slope of the line • e = error term

6. Applications To analyze many kinds of dose-response or binomial response experiments in a variety of fields. Toxicology - determine the relative toxicity of chemicals to living organisms. Transformation from sigmoid to linear and then runs a regression on the relationship.

7. Once a regression is run, the researcher can use the output of the probit analysis To compare the amount of chemical required to create the same response in each of the various chemicals LC 50 (liquids) or LD 50 (solids) are the most widely used outcomes of the modern dose-response experiments

8. How does probit analysis work? How to get from dose-response curve to an LC50? The easiest by far is to use a statistical package such as SPSS, SAS, R, or S, but it is good to see the history of the methodology to get a thorough understanding of the material.

9. LD50 Lethal dose of the chemical per unit weight which will kill 50 per cent population of test animals or organisms Represented as-milligrams per kilogram of body weight 1927 : J.W. Trevan ; to estimate the relative poisoning potency of drugs- developed the LD50 test

10. Importance of LD50: Depending on how the chemical will be used, many kinds of toxicity tests may be required  Different chemicals cause different toxic effects, comparing the toxicity of one with another is hard To compare the toxic potency or intensity of different chemicals, researchers must measure the same effect One way is to carry out lethality testing -"quantal" test It measures an effect that "occurs" or "does not occur".

11. Applications Aid in developing emergency procedures To help develope guidelines for the use of appropriate safety clothing and equipment. For the development of transportation regulations Aid in establishing occupational exposure limits Safety Data Sheets

12. Determination of LD50: Dragstedet-Behren’s method Spearman- karber method Probit analysis approach

13. While number of methods are available for probit analysis- Dragstedt-Behren’s method graphical method rapid approximate method by Huson Finney’s Method of probit analysis The method of Finney is the most accepted one, as it estimates critical doses or susceptibility with sufficient accuracy from a probit –log concentration graph.

14. Probit Analysis probability + unit Conducted by three techniques: Using tables to estimate the probits and fitting the relationship Use of regression Use of statistical package such as SPSS

15. METHOD 1: Step 1: Convert % mortality to probits (short for probability unit) Method A; Determine probits by looking up those corresponding to the % responded in Finney’s table (Finney 1952): Method B : Hand calculations (Finney and Stevens 1948): Method C : Computer software such as SPSS, SAS, R, or S convert the percent responded to probits automatically.

16. Step 2; Take the log of the concentrations: Done by hand calculations, calculator or computer program of choice.

17. Step 3: Graph the Probits Vs the Log Concentration: Hand fit the line by eye that minimizes the space between the line and the data. Step 4: Find the LD50: Find the probit of 5 in the y-axis, then move down to the x-axis and find the log of the concentration associated with it. Then take the inverse of the log. That value is LD50 value.

18. Log concentration Vs Probit m = 0.678 LD50 = log 10 of 0.678 = 4.86

19. Method 2: Use of statistical package such as SPSS: Step 1: Simply input a minimum of three columns into the Data Editor Number of individuals per container that responded Total of individuals per container Concentrations

20. Step 2:

21. Step 3:

22. Step 4:

23. Merits Accuracy: Probit analysis provides accurate estimates of lethal doses (LD50, LD90, etc.), which are crucial for risk assessment and pest management. Efficiency: It allows for the efficient analysis of dose-response data, reducing the need for extensive experimentation. Sensitivity: Probit analysis is sensitive to changes in response rates, making it suitable for detecting subtle differences between treatments or populations. Flexibility: It can be applied to a wide range of entomological studies, including toxicity testing, pest control, and biological assays. Statistical rigor: Probit analysis is based on sound statistical principles, providing reliable results and inferences.

24. Demerits Assumptions: Probit analysis relies on certain assumptions, such as normality of the probit scores and homogeneity of variances. Violations of these assumptions can affect the accuracy of the results. Data requirements: It requires a sufficient number of data points and a wide range of doses to obtain reliable estimates. Complexity: The statistical calculations involved in probit analysis can be complex, requiring specialized software or knowledge. Limited applicability: Probit analysis is primarily suitable for binary response variables (e.g., dead/alive, present/absent). It may not be appropriate for continuous response variables. Sensitivity to outliers: Outliers in the data can have a significant impact on the probit analysis results, potentially leading to biased estimates.

25. LC50 assessment of cypermethrin in Heteropneustes fossilis : Probit analysis Akanksha Singh and Dr Kannez Zahra (2017) The present study was performed to investigate the toxicity of cypermethrin (25% EC) on fresh water fishes Heteropneustes fossilis . In acute toxicity bioassay LC 50 values after 24, 48, 72 and 96 h were determined by direct interpolation method. LC 50 values obtained by plotting a graph between % mortality and concentrations of toxicant were0.00064 ml/l, 0. 00050 ml/l, 0.00036 ml/l and 0.00025 ml/l after 24, 48, 72 and 96 h of cypermethrin intoxication. Data obtained from acute toxicity test were evaluated using the probit analysis statistical method. The LC 50 values for different exposure periods were 0.00066, 0.00044, 0.00033, and 0.00022. The results revealed that a lower concentration of cypermethrin is found to be highly toxic to fishes.

26. Conc. Of toxicant (ml/l) No. of fishes 24hrs 48hrs 72hrs 96hrs M % M M % M M % M M % M 0.00010 10 2 20 0.00025 10 2 20 3 50 0.00040 10 1 10 2 30 3 60 1 70 0.00055 10 2 20 4 60 2 80 1 90 0.00070 10 7 70 1 80 1 90 1 100 0.00085 10 8 80 1 90 1 100     0.001 10 8 80 2 100        

27. Sl. No. Conc. 24h Log Conc. No. of Fishes   24h     48h   % dead Correct % Probit % dead Correct % Probit 1 0.00010 -4 10 2.5 3.04 2.5 3.04 2 0.00025 -3.60206 10 2.5 3.04 2.5 3.04 3 0.00040 -3.39794 10 10 10 3.72 30 30 4.48 4 0.00055 -3.25964 10 20 20 4.16 60 60 5.25 5 0.00070 -3.1549 10 70 70 5.52 80 80 5.84 6 0.00085 -3.07058 10 80 80 5.84 90 90 6.28 7 0.001 -3 10 80 80 5.84 100 97.5 6.96

28. S. No. Conc. 24h Log Conc. No. of Fishes   72h     96h   % dead Correct % Probit % dead Correct % Probit 1 0.0001 -4 10 2.5 3.04 20 20 4.16 2 0.00025 -3.60206 10 20 20 4.16 50 50 5 3 0.0004 -3.39794 10 60 60 5.25 70 70 5.52 4 0.00055 -3.25964 10 80 80 5.84 90 90 6.28 5 0.0007 -3.1549 10 90 90 6.28 100 97.5 6.96 6 0.00085 -3.07058 10 100 97.5 6.96 100 97.5 6.96 7 0.001 -3 10 100 97.5 6.96 100 97.5 6.96

29. After plotting a graph between the log conc and probit, the values at 5 probit following different exposure were -3.18, -3. 35, -3.48, -3.65. By taking antilog of these values the actual LC50 were 0.00066, 0.00044, 0.00033, and 0.00022 after 24, 48, 72 and 96 h respectively.

30. Development of a web-based tool for probit analysis to compute LC 50 /LD 50 /GR 50 for its use in toxicology studies Kumar V. et al . (2020) Dose(ml.) Total No Dead 2.6 50 6 3.8 48 16 5.1 46 24 7.7 49 42 10.2 50 44 0 50 0

31. Summary • Probit Analysis is a type of regression used with binomial response variables. It is very similar to logit, but is preferred when data are normally distributed. • Most common outcome of a dose-response experiment in which probit analysis is used is the LC50/LD50. Probit analysis can be done by eye, through hand calculations, or by using a statistical program.