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[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)

# ascotraceR: A weather driven model to simulate the spread of Ascochyta blight in chickpea over a growing season

The goal of of _ascotraceR_ is to develop a weather driven model to simulate the spread of Ascochyta blight disease in a chickpea field over a growing season.

This model is adapted from a model developed by [(Diggle _et al._ 2002)](https://doi.org/10.1094/PHYTO.2002.92.10.1110) for simulating the spread of anthracnose in a lupin field.
The model is run using local weather data, and simulates both host and pathogen related activities.
The growth of chickpea is described in terms of development of growing points, and disease progress is measured by quantifying the loss of healthy growing points.
As the model runs, it keeps a continuous track of non-infected, latent, infected and sporulating growing points (lesions).
The ascotraceR's minimum input requirements are location specific weather data and a list of input variables.
[![tic](https://github.com/IhsanKhaliq/ascotraceR/actions/workflows/tic.yml/badge.svg)](https://github.com/IhsanKhaliq/ascotraceR/actions/workflows/tic.yml)

# ascotraceR: A An R package resource to simulate the spatiotemporal spread of Ascochyta blight in a chickpea field over a growing season

The goal of of *ascotraceR* is to develop a weather driven model to simulate the spread of Ascochyta blight disease in a chickpea field over a growing season.

This model is adapted from a model developed by [(Diggle *et al.* 2002)](https://doi.org/10.1094/PHYTO.2002.92.10.1110) for simulating the spread of anthracnose in a lupin field. The model is run using local weather data. The ascotraceR model simulates the pathogen related processes of conidial production, dispersal, successful deposition and infection on chickpea plants. Host related processes of growth are simulated in terms of development of growing points. The model divides the paddock into 1 square metre cells
(observation quadrats/units) and simulates chickpea growth and _A. rabiei_
activities in each cell. Initially, there is one growing point per sown seed
when seed are sown. Chickpea growth is then described in terms of increase in
the number of growing points. Conidia are dispersed from infested stubble by
rain splash or wind driven rain when rainfall threshold is reached. Rainfall
threshold refers to the minimum amount of rainfall required to disperse conidia
from pycnidia and to provide sufficient duration of moisture for conidia to
germinate and penetrate into the host tissues. After penetrating host tissues,
conidia produce infected growing points. Infected growing points become
sporulating lesions after completion of a latent period. The length of the
latent period is a function of temperature, and the number of conidia produced
per sporulating growing point depends on the level of resistance of the chickpea
cultivar.
As the model runs, it keeps a continuous track of non-infected, latent, infected
and sporulating growing points (lesions). The ascotraceR’s minimum input
requirements are location specific weather data and a list of input variables.

## Quick start

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81 changes: 42 additions & 39 deletions README.md
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# ascotraceR: A An R package resource to simulate the spatiotemporal spread of Ascochyta blight in a chickpea field over a growing season

The goal of of *ascotraceR* is to develop a weather driven model to simulate the
spread of Ascochyta blight disease in a chickpea field over a growing season.
The goal of of *ascotraceR* is to develop a weather driven model to
simulate the spread of Ascochyta blight disease in a chickpea field over
a growing season.

This model is adapted from a model developed by [(Diggle *et al.*
2002)](https://doi.org/10.1094/PHYTO.2002.92.10.1110) for simulating the spread
of anthracnose in a lupin field. The model is run using local weather data. The
ascotraceR model simulates the pathogen related processes of conidial
production, dispersal, successful deposition and infection on chickpea plants.
Host related processes of growth are simulated in terms of development of
growing points. The model divides the paddock into 1 square metre cells
(observation quadrats/units) and simulates chickpea growth and _A. rabiei_
activities in each cell. Initially, there is one growing point per sown seed
when seed are sown. Chickpea growth is then described in terms of increase in
the number of growing points. Conidia are dispersed from infested stubble by
rain splash or wind driven rain when rainfall threshold is reached. Rainfall
threshold refers to the minimum amount of rainfall required to disperse conidia
from pycnidia and to provide sufficient duration of moisture for conidia to
germinate and penetrate into the host tissues. After penetrating host tissues,
conidia produce infected growing points. Infected growing points become
sporulating lesions after completion of a latent period. The length of the
latent period is a function of temperature, and the number of conidia produced
per sporulating growing point depends on the level of resistance of the chickpea
cultivar.
As the model runs, it keeps a continuous track of non-infected, latent, infected
and sporulating growing points (lesions). The ascotraceR’s minimum input
requirements are location specific weather data and a list of input variables.
2002)](https://doi.org/10.1094/PHYTO.2002.92.10.1110) for simulating the
spread of anthracnose in a lupin field. The model is run using local
weather data. The ascotraceR model simulates the pathogen related
processes of conidial production, dispersal, successful deposition and
infection on chickpea plants. Host related processes of growth are
simulated in terms of development of growing points. The model divides
the paddock into 1 square metre cells (observation quadrats/units) and
simulates chickpea growth and *A. rabiei* activities in each cell.
Initially, there is one growing point per sown seed when seed are sown.
Chickpea growth is then described in terms of increase in the number of
growing points. Conidia are dispersed from infested stubble by rain
splash or wind driven rain when rainfall threshold is reached. Rainfall
threshold refers to the minimum amount of rainfall required to disperse
conidia from pycnidia and to provide sufficient duration of moisture for
conidia to germinate and penetrate into the host tissues. After
penetrating host tissues, conidia produce infected growing points.
Infected growing points become sporulating lesions after completion of a
latent period. The length of the latent period is a function of
temperature, and the number of conidia produced per sporulating growing
point depends on the level of resistance of the chickpea cultivar. As
the model runs, it keeps a continuous track of non-infected, latent,
infected and sporulating growing points (lesions). The ascotraceR’s
minimum input requirements are location specific weather data and a list
of input variables.

## Quick start

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## 4: 4 1492.26177 19934.89 0 0 2020-06-07 159
## 5: 5 1793.24969 21728.14 0 0 2020-06-08 160
## ---
## 143: 143 31.00028 1992022.25 8 719 2020-10-24 298
## 144: 144 22.35445 1992044.61 9 719 2020-10-25 299
## 145: 145 20.27138 1992064.88 9 719 2020-10-26 300
## 146: 146 16.22720 1992073.11 1 727 2020-10-27 301
## 147: 147 14.81122 1992087.92 1 727 2020-10-28 302
## 143: 143 31.05448 1992021.96 5 723 2020-10-24 298
## 144: 144 22.39360 1992044.36 15 723 2020-10-25 299
## 145: 145 20.30692 1992064.66 15 723 2020-10-26 300
## 146: 146 15.75760 1992076.42 11 727 2020-10-27 301
## 147: 147 14.38234 1992090.80 11 727 2020-10-28 302
## cdd cwh cr gp_standard AUDPC
## 1: 0.00000 0 0.0 40.00000 48039.5
## 2: 10.74583 0 0.0 42.77148 48039.5
## 3: 22.84583 0 0.0 46.10657 48039.5
## 4: 35.41042 0 0.0 49.83722 48039.5
## 5: 49.38958 1 0.6 54.32034 48039.5
## 1: 0.00000 0 0.0 40.00000 48821.5
## 2: 10.74583 0 0.0 42.77148 48821.5
## 3: 22.84583 0 0.0 46.10657 48821.5
## 4: 35.41042 0 0.0 49.83722 48821.5
## 5: 49.38958 1 0.6 54.32034 48821.5
## ---
## 143: 2133.81645 65 76.2 4980.06672 48039.5
## 144: 2154.64770 73 94.4 4980.12110 48039.5
## 145: 2176.49562 73 94.4 4980.17042 48039.5
## 146: 2195.63104 73 94.4 4980.20748 48039.5
## 147: 2215.57687 74 97.0 4980.24131 48039.5
## 143: 2133.81645 65 76.2 4980.06672 48821.5
## 144: 2154.64770 73 94.4 4980.12110 48821.5
## 145: 2176.49562 73 94.4 4980.17042 48821.5
## 146: 2195.63104 73 94.4 4980.20748 48821.5
## 147: 2215.57687 74 97.0 4980.24131 48821.5

## Reference

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