Parameter required to add the number of infected quadrats at the date of initial infection

[IhsanKhaliq]

As described in Art's paper, "For a comparison with the experimental results, the model was initialized with the same start and end dates (20 May and 10 November), field size (45 × 8 m), and plant density (40 plants per m2) as the experiment. The model was run with the recorded weather data. On the date of initial infection in the experiment, one infective growing point was added to each of the two subunits corresponding to the points of initial infection in the field. The model was run four times, with no wrapping option, for each cultivar so that the mean of the model runs would be comparable in both magnitude and variability with the experimental data"

A paramter is required to add the number of infected quadrats to the model at the date of initial infection.

primary_infection_intensity = 3 for Tosari primary_infection_intensity = 1 for Billa Billa

[IhsanKhaliq]

It will be important to keep infection and inoculum separate to avoid further confusions. Inoculum is the source of infection (infested stubble placed at the centre of the plot to initiate infection). Infection is the disease initiated by stubble. primary_inoculum_intensity = number of lesions on infested stubble primary_infection_intensity = number of infected quadrats at the date of infection Before closing this issue

• [ ] Model output needs to be exported and checked i) that disease has actually started at the date of initial_infection, in the model and ii) the specified number of quadrats have been infected (1 for Billa Billa & 3 for Tosari) at the date of initial_infection in the model

[IhsanKhaliq]

primary_infection_intensity parameter has totaly disappeared from ascotraceR.

[PaulMelloy]

You have cited two different "issues" here.

First I will address this point.

As described in Art's paper, "For a comparison with the experimental results, the model was initialized with the same start and end dates (20 May and 10 November), field size (45 × 8 m), and plant density (40 plants per m2) as the experiment. The model was run with the recorded weather data. On the date of initial infection in the experiment, one infective growing point was added to each of the two subunits corresponding to the points of initial infection in the field. The model was run four times, with no wrapping option, for each cultivar so that the mean of the model runs would be comparable in both magnitude and variability with the experimental data"

A paramter is required to add the number of infected quadrats to the model at the date of initial infection.

primary_infection_intensity = 3 for Tosari primary_infection_intensity = 1 for Billa Billa

You need to describe the location of the infection coordinates (or quadrats) in x and y coordinates. Currently, the xlsx file only describes a plot number and distance from the centre? The model works in two dimensions width of the paddock(x) and length of the paddock (y).

When you have the xy coordinates of the infection locations at tosari, for example lets say they are as follows

x	y
3	5
5	5
8	5

make a data.frame to describe these three locations of the primary_infection and the intensity of the infection

PI <- data.frame(x = c(3,5,8),
                 y = c(5,5,5),
                 load = c(1,1,1))

This will give you a data.frame that will look something like this	x	y	load
3	5	1
5	5	1
8	5	1

Input this data.frame (PI) into the the primary_infection_foci argument eg

traced <- trace_asco(
  weather = weather_dat,
  paddock_length = 100,
  paddock_width = 100,
  initial_infection = "1998-06-10",
  sowing_date = "1998-06-09",
  harvest_date = "1998-06-30",
  time_zone = "Australia/Perth",
  gp_rr = 0.0065,
  primary_infection_foci= PI,              #    <----------  SEE HERE
  spores_per_gp_per_wet_hour = 0.22,
  primary_infection_foci = "centre")

[IhsanKhaliq]

I have all the information in the excel sheet. The quadrat column gives you directions too. We currently have infections in central quadrats F only at the time of initial infection, which is the central quadrat/centre of the plot x = 10, y =10 You have two primary_infection_foci in the same function call. I have no issues however it can be incorporated, but we need to take account this last issue to submit the ms.

[IhsanKhaliq]

The quadrat column gives you everything (the numbers refer to distance e.g., NE3 means NE qudarat located 3 m away from the central inoculated quadrat). S9 means quadrat in the south direction which is 9 m away from the inoculated central quadrats and so on....

[PaulMelloy]

The excel spreadsheet still does not have x and y columns, which is needed for the model to interpret the spatial locations. It is a matter of human-readable vs computer-readable.

If the two or three infections are in the same 1 x1 m cell. Then the initial_inoculum_intensity = 2 (or 3) for the centre foci or that coordinate

[IhsanKhaliq]

Yes, same infections. I agree but we have should do our job.

So we just need? initial_inoculum_intensity = 3 (Tosari) initial_inoculum_intensity = 1 (Billa Billa)

[adamhsparks]

I don't think it's necessary here, but I have converted distance (m) and cardinal direction (degrees) to x and y values for another project that I'm working on.

So just for future reference for both of you, here's how you can get x, y from coordinates like Ihsan has for the quadrats that were inspected.

library(geometry)
xy <- data.frame(pol2cart(theta = dat$degrees, r = dat$distance))

[PaulMelloy]

Yes, same infections. I agree but we have should do our job.

So we just need? initial_inoculum_intensity = 3 (Tosari) initial_inoculum_intensity = 1 (Billa Billa)

Yes

[IhsanKhaliq]

Okay then. I'm going to run the valascotraceR code to get those updated stats values. If everything worked, we can submit ms too. Did we flag Phytopathology for submission?

[PaulMelloy]

I digress from the issue topic, Degrees in radians

I don't think it's necessary here, but I have converted distance (m) and cardinal direction (degrees) to x and y values for another project that I'm working on.

So just for future reference for both of you, here's how you can get x, y from coordinates like Ihsan has for the quadrats that were inspected.

So if your dat$degrees were in degrees

library(geometry)
xy <- data.frame(pol2cart(theta = dat$degrees * (180/pi), r = dat$distance))

I wonder if this would be faster than our current implemetation

[adamhsparks]

You're thinking in ascotraceR? Open an issue there and let's discuss. 😊

But yes, dat$degrees is as the name suggests, degrees on a compass