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pest-and-disease-management

Description

The Pest and Disease Management service takes in data via datasets or live measurements and rules created
by a user, and returns when a rule was satisfied on the specified dataset.

Requirements

  • git
  • docker
  • docker-compose

Docker version used during development: 27.0.3

Installation

There are two ways to install this service, via docker or directly from source.

Deploying from source

When deploying from source, use python 3:11.
Also, you should use a venv when doing this.

A list of libraries that are required for this service is present in the "requirements.txt" file.
This service uses FastAPI as a web framework to serve APIs, alembic for database migrations sqlalchemy for database ORM mapping.

Deploying via docker

After installing docker you can run the following commands to run the application:

docker compose build
docker compose up

The application will be served on http://127.0.0.1:80 (I.E. typing localhost/docs in your browser will load the swagger documentation)

Documentation

POST 

/api/v1/data/upload/

Request body:
This API expects a dataset in the form of a .csv file.
This .csv file must contain "date" and "time" as columns, as well as at least one of the following columns:

"parcel_location", "atmospheric_temperature", "atmospheric_temperature_daily_min",
"atmospheric_temperature_daily_max", "atmospheric_temperature_daily_average", "atmospheric_relative_humidity",
"atmospheric_pressure", "precipitation", "average_wind_speed", "wind_direction", "wind_gust",
"leaf_relative_humidity", "leaf_temperature", "leaf_wetness",
"soil_temperature_10cm", "soil_temperature_20cm", "soil_temperature_30cm", "soil_temperature_40cm",
"soil_temperature_50cm", "soil_temperature_60cm", "solar_irradiance_copernicus"

The date should look like this: "2024-10-10", "2024-09-05", etc. (YYYY-mm-dd), in python: (%Y-%m-%d)
The time should look like this: "10:10:15", "01:15:59", "01:01:01", etc. (HH:MM:SS), in python: (%H:%M:%S)

An example of a dataset would look something like this:

date;time;atmospheric_temperature,wind_direction
2024-05-12;12:00:00;18;north
2024-05-12;13:00:00;19;north-east
2024-05-12;14:00:00;24;north

The order of the columns does not matter, another example of a valid dataset:

date;wind_direction;leaf_wetness;time
2022-01-01;south;0.13;01:00:00
2022-01-01;south-west;0.14;02:00:00
2022-01-01;south-west;0.13;03:00:00

The API will ignore columns that are present in the dataset but aren't part of the list above.

An example of an invalid dataset:
date;wind_direction
2022-01-01;north
2022-01-02;south

Reason: missing "time" column

Another example:
date;leaf_wetness;time;leaf_temperature;leaf_density
2021-03-03;1.25;12:00:00;11
2021-03-04;0.75;12:00:00;12
2021-03-05;0.68;12:00:00;eleven

Reasons:

  1. The leaf_wetness metric can only be expressed as a value [0, 1], the first row shows 1.25 which is outside this range.
  2. The last row has a leaf_temperature of "eleven" which will not be parsed, it should be "11".

Note:
The leaf_density column would not provide an issue when parsing, this column would just be skipped.

Response example:

{
    "msg": "Successfully uploaded file."
}

GET 

/api/v1/pest-model/

Request body:

Nothing

Response example:

{
  "pests": [
    {
      "id": "9bf91b39-04eb-4446-9139-f7181da6f31f",
      "name": "Περονόσπορος, Plasmopara viticola",
      "description": "Uncinula necator (syn. Erysiphe necator) is a fungus that causes powdery mildew of grape. It is a common pathogen of Vitis species, including the wine grape, Vitis vinifera",
      "geo_areas_of_application": "((30.123 10.32454, 40.345 40.1234563, 20.9675 40.67854, 10.23508 20.23578, 30.23465584 10.16938))"
    },
    {
      "id": "c15b5f4b-4881-4760-ab2e-3ca5090e8493",
      "name": "Botrytis cinerea",
      "description": "Botrytis cinerea (Ascomycota) infects over 200 plant species, causing grey mould, evident on the surface as grey fluffy mycelium. Worldwide, it causes annual losses of $10 billion to $100 billion.",
      "geo_areas_of_application": "POLYGON ((-60.0870329 -12.9315478, -61.5073816 -25.3204334, -62.6987366 -24.5766272, -64.1853669 -24.0497260, -67.7152546 -27.4752321, -68.4190340 -26.9510818, -67.6018452 -21.5489551, -64.3083560 -21.6772242, -63.1471630 -21.9415438, -64.1137279 -14.2398013, -60.0870329 -12.9315478))"
    }
  ]
}

This API returns a list of pest models currently in the system.

POST 

/api/v1/pest-model/

Request body:

{
  "name": "Phytophthora sojae",
  "description": "Phytophthora sojae is an oomycete pathogen of soybean, classified in the kingdom Stramenopiles. It causes 'damping off' of seedlings and root rot of older plants.",
  "geo_areas_of_application": "POLYGON ((14.2345, -2.2345))",
  "cultivations": [ "soybean", "bluebonnet", "lupinus albus" ]
}

Response example:

{
  "id": "9489c55a-847c-4cd2-8392-ddc72b549ec4",
  "name": "Phytophthora sojae",
  "description": "Phytophthora sojae is an oomycete pathogen of soybean, classified in the kingdom Stramenopiles. It causes 'damping off' of seedlings and root rot of older plants.",
  "geo_areas_of_application": "POLYGON ((14.2345, -2.2345))"
}

This API creates an empty pest model (meaning with no rules) in the system.
This pest model can then be assigned rules via the POST /rule/ API.

POST 

/api/v1/tool/calculate-risk-index/weather/{weather_dataset_id}/model/{model_ids}/verbose/

Path parameters:

  1. weather_dataset_id: the id of the weather dataset that you wish to use for this calculation (uploaded previously via the POST /api/v1/data/upload/ API)
  2. model_ids: a list of uuids (uuid-v4) that correspond to the pest_models that you wish to calculate for.

Request body:

Nothing

Response example:

{
  	"@context":
		{
			"ocsm": "https://w3id.org/ocsm/",
			"fsm": "http://www.farmtopia.com/ontology/farmtopia#",
			"foodie": "http://foodie-cloud.com/model/foodie#",
			"saref": "https://saref.etsi.org/core/"
		},
  	"@graph": [
	  	{
			"@id": "urn:openagri:pestModel:101",
			"@type": "ocsm:AIPestDetectionModel",
			"fsm:eppoCode": "UNCINE",
			"foodie:description": "Uncinula necator (syn. Erysiphe necator) is a fungus that causes powdery mildew of grape. It is a common pathogen of Vitis species, including the wine grape, Vitis vinifera",
			"ocsm:hasPredictedInfestationRisks": [
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360259a",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T01:00:00",
					"ocsm:hasRiskLevel": "Low"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360259b",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T02:00:00",
					"ocsm:hasRiskLevel": "High"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360259c",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T03:00:00",
					"ocsm:hasRiskLevel": "Medium"
				}
			],
			"ocsm:basedOnWeatherDataset": {
				"@id":"urn:openagri:weatherDataset:1234",
				"@type": "ocsm:WeatherDataset"
			}
		},
		{
			"@id": "urn:openagri:pestModel:102",
			"@type": "ocsm:AIPestDetectionModel",
			"fsm:eppoCode": "PLASVI",
			"foodie:description": "Plasmopara viticola, the causal agent of grapevine downy mildew, is a heterothallic oomycete that overwinters as oospores in leaf litter and soil.",
			"ocsm:hasPredictedInfestations": [
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250a",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T01:00:00",
					"ocsm:hasRiskLevel": "High"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250b",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T02:00:00",
					"ocsm:hasRiskLevel": "High"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250c",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T03:00:00",
					"ocsm:hasRiskLevel": "High"
				}
			],
			"ocsm:basedOnWeatherDataset": {
				"@id":"urn:openagri:weatherDataset:1234",
				"@type": "ocsm:WeatherDataset"
			}
		}
	]
}

This API returns a JSON-LD, an example of which you can view here.
The main bit of information about the risk infestation metric can be found within the "ocsm:hasPredictedInfestations" type key.
This object holds the "ocsm:hasRiskLevel" key which will have either "Low", "Medium" or "High" depending on the results of the calculations.

POST 

api/v1/tool/calculate-risk-index/weather/{weather_dataset_id}/model/{model_ids}/high/

Path parameters:

  1. weather_dataset_id: the id of the weather dataset that you wish to use for this calculation (uploaded previously via the POST /api/v1/data/upload/ API)
  2. model_ids: a list of uuids (uuid-v4) that correspond to the pest_models that you wish to calculate for.

Request body:

Nothing

Response example:

{
  	"@context":
		{
			"ocsm": "https://w3id.org/ocsm/",
			"fsm": "http://www.farmtopia.com/ontology/farmtopia#",
			"foodie": "http://foodie-cloud.com/model/foodie#",
			"saref": "https://saref.etsi.org/core/"
		},
  	"@graph": [
	  	{
			"@id": "urn:openagri:pestModel:101",
			"@type": "ocsm:AIPestDetectionModel",
			"fsm:eppoCode": "UNCINE",
			"foodie:description": "Uncinula necator (syn. Erysiphe necator) is a fungus that causes powdery mildew of grape. It is a common pathogen of Vitis species, including the wine grape, Vitis vinifera",
			"ocsm:hasPredictedInfestationRisks": [
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360259b",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T02:00:00",
					"ocsm:hasRiskLevel": "High"
				}
			],
			"ocsm:basedOnWeatherDataset": {
				"@id":"urn:openagri:weatherDataset:1234",
				"@type": "ocsm:WeatherDataset"
			}
		},
		{
			"@id": "urn:openagri:pestModel:102",
			"@type": "ocsm:AIPestDetectionModel",
			"fsm:eppoCode": "PLASVI",
			"foodie:description": "Plasmopara viticola, the causal agent of grapevine downy mildew, is a heterothallic oomycete that overwinters as oospores in leaf litter and soil.",
			"ocsm:hasPredictedInfestations": [
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250a",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T01:00:00",
					"ocsm:hasRiskLevel": "High"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250b",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T02:00:00",
					"ocsm:hasRiskLevel": "High"
				},
				{
					"@id": "urn:openagri:pestPrediction:72d9fb43-53f8-4ec8-a33c-fa931360250c",
					"@type": "fsm:PestInfestationRisk",
					"saref:hasTimestamp": "2024-08-31T03:00:00",
					"ocsm:hasRiskLevel": "High"
				}
			],
			"ocsm:basedOnWeatherDataset": {
				"@id":"urn:openagri:weatherDataset:1234",
				"@type": "ocsm:WeatherDataset"
			}
		}
	]
}

Note:
This API functions the same as the .../verbose one, while additionally filter out any risk calculations that aren't "High".

GET 

/api/v1/rule/

Request body:

Nothing

Response example:

{
  "rules": [
    {
      "id": "1",
      "name": "Plasmopara viticola",
      "description": "The causal agent of grapevine downy mildew",
      "conditions": [
        {
          "unit_id": 5,
          "operator_id": 1,
          "value": 80.0
        },
        {
          "unit_id": 1,
          "operator_id": 4,
          "value": 10.0
        },
        {
          "unit_id": 7,
          "operator_id": 5,
          "value": 10.0
        }
      ]
    },
    {
      "id": "2",
      "name": "Plasmopara viticola",
      "description": "The causal agent of grapevine downy mildew",
      "conditions": [
        {
          "unit_id": 5,
          "operator_id": 1,
          "value": 80.0
        },
        {
          "unit_id": 1,
          "operator_id": 1,
          "value": 10.0
        },
        {
          "unit_id": 1,
          "operator_id": 2,
          "value": 20.0
        },
        {
          "unit_id": 7,
          "operator_id": 5,
          "value": 10.0
        }
      ]
    }
  ]
}

This API returns a list of all rules stored in the system.
Rules make up a pest model, but they can also be added separately.

The above rules, translated into a friendlier format: \

  1. H > 80% AND T <= 10 AND P == 10 \
  2. H > 80% AND 10 < T <= 20 AND P == 10

Where:

  1. H = Humidity
  2. T = Atmospheric temperature
  3. P = Precipitation

DELETE 

/api/v1/rule/{rule_id}

Path parameters:

  1. rule_id: the id of the rule that should be deleted.

Request body:

Nothing

Response example:

{
  "message": "Successfully removed rule!"
}

This API removes a rule via its id.

POST 

/api/v1/rule/

Request body:

{
  "name": "example rule",
  "description": "my example rule",
  "probability_value": "low",
  "pest_model_id": "23cfdd48-f564-44a1-922a-e8c972fc5eac",
  "conditions": [
    {
      "unit_id": 5,
      "operator_id": 1,
      "value": 80
    },
    {
      "unit_id": 1,
      "operator_id": 1,
      "value": 10
    }
  ]
}

Response example:

{
    "id": 1,
    "name": "my_rule",
    "description": "my_description",
    "conditions": [
        {
            "unit_id": 1,
            "operator_id": 1,
            "value": 51
        },
        {
            "unit_id": 2,
            "operator_id": 2,
            "value": 12
        }
    ]
}

This API creates a single rule that is added to an existing pest model.

General guidance

in general, the way a user would attempt to use this service is the following:

  1. Upload a dataset with weather data via the POST /api/v1/data/upload/ API
  2. Create a pest model (POST /api/v1/pest-model/) with accompanying rules (POST /api/v1/rule/)
  3. Call the GET /api/v1/tool/calculate-risk-index/weather/{weather_dataset_id}/model/{model_ids}/verbose API for risk calculations

For more information about the APIs and schemas, please view the swagger documentation.

Contribution

Please contact the maintainer of this repository.

License

European Union Public License 1.2

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