This data object was created to facilitate the access to the list of so-called 'reference points' published as part of the OpenFoodTox datasets (Carnesecchi et al. 2023). These reference points are linked to substance characterisations and the outputs of the European Food Safety Authority (EFSA) in which the data were published. Also, a table of 'reference values' is included, which is also linked to substance characterisations and EFSA outputs. Other data tables published as part of OpenFoodTox are not included in this R package.
Format
list A dm object
Source
Carnesecchi E, Mostrag A, Ciacci A, Roncaglioni A, Tarkhov A, Gibin D, Sartori L, Benfenati E, Yang C, Dorne JLCM (2023). OpenFoodTox: EFSA's chemical hazards database (Version 5). Zenodo. doi:10.5281/zenodo.8120114
Dorne JLCM, Richardson J, Livaniou A, Carnesecchi E, Ceriani L, Baldin R, Kovarich S, Pavan M, Saouter E, Biganzoli F, Pasinato L, Zare Jeddi M, Robinson TP, Kass GEN, Liem AKD, Toropov AA, Toropova AP, Yang C, Tarkhov A, Georgiadis N, Di Nicola MR, Mostrag A, Verhagen H, Roncaglioni A, Benfenati E, Bassan A. EFSA's OpenFoodTox: An open source toxicological database on chemicals in food and feed and its future developments. Environ Int. 2021 Jan;146:106293. doi:10.1016/j.envint.2020.106293
Details
See vignette("OpenFoodTox") for a description of the contents of the individual
tables.
The R code used to create this data object is installed with this package in the 'dataset_generation' directory.
Examples
library(dm, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)
# Show the relational structure of the data tables (only works in online HTML help)
dm_draw(oft, view_type = "all")
# List species used in aquatic tests
oft$reference_points |>
dplyr::filter(Study == "Ecotox (water compartment)") |>
select(Species) |>
unique() |>
arrange(Species) |>
print(n = Inf)
#> # A tibble: 70 × 1
#> Species
#> <chr>
#> 1 African clawed frog
#> 2 American flag fish
#> 3 American waterweed (Pondweed) (live plants)
#> 4 Anabaena flosaquae
#> 5 Anabaena variabilis
#> 6 Aphanizomenon flos-aquae Ralfs ex Bornet &
#> 7 Aquatic plants group
#> 8 Atlantic salmon
#> 9 Bluegill
#> 10 Brook trout
#> 11 Brown trout
#> 12 Ceriodaphnia dubia
#> 13 Ceriodaphnia sp.
#> 14 Channel catfish
#> 15 Chironomus tentans
#> 16 Chironomus yoshimatsui
#> 17 Chlorella pyrenoidosa
#> 18 Chlorella vulgaris
#> 19 Common carp
#> 20 Common duckweed
#> 21 Common hornwort (live plants)
#> 22 Ctenodrilus serratus
#> 23 Daggerblade grass Shrimp
#> 24 Daphnia magna
#> 25 Daphnia pulex
#> 26 Dungeness crab
#> 27 Eastern oyster
#> 28 Eurasian watermilfoil
#> 29 European perch
#> 30 Fathead minnow
#> 31 Floating sweet-grass
#> 32 Gammaridae
#> 33 Gammarus pseudolimnaeus
#> 34 Gammarus pulex
#> 35 Gastropoda - Gastropods
#> 36 Great pond snail
#> 37 Green alga
#> 38 Green cabomba (live plants)
#> 39 Guppy
#> 40 Harlequin fly
#> 41 Hyalella azteca
#> 42 Ide
#> 43 Inland silverside
#> 44 Louisiana crayfish
#> 45 Macrocyclops fuscus
#> 46 Marine centric diatom
#> 47 Microcystis aeruginosa
#> 48 Mosquitofish
#> 49 Mozambique tilapia
#> 50 Mysid shrimp
#> 51 Navicula pelliculosa
#> 52 Nitzschia palea
#> 53 Northern quahog
#> 54 Palaemonetes kadlakensis
#> 55 Parrot feather
#> 56 Pseudokirchneriella subcapitata
#> 57 Rainbow trout
#> 58 Red seabream
#> 59 Scenedesmus pannonicus
#> 60 Scenedesmus quadricauda
#> 61 Scenedesmus subspicatus
#> 62 Sheepshead minnow
#> 63 Spot croaker
#> 64 Swollen duckweed
#> 65 Three-spined stickleback
#> 66 Tiger worm
#> 67 Unspecified
#> 68 Wild celery (water celery) (live plants)
#> 69 Zebra fish
#> 70 not reported
# Collect endpoints on green algae
green_algae_endpoints <- oft$reference_points |>
dplyr::filter(Species %in% oft_aq_green_algae) |>
select(Substance, Species, DurationDays, Endpoint, qualifier, value, unit, Effect)
print(green_algae_endpoints)
#> # A tibble: 513 × 8
#> Substance Species DurationDays Endpoint qualifier value unit Effect
#> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr>
#> 1 (2E)-Methylcrot… Green … NA EC50 = 9.03e+2 mg/L morta…
#> 2 (3RS,4RS;3RS,4S… Scened… 3 EC50 = 2.1 e-3 mg/L bioma…
#> 3 (8,9-Z)-isomer … Pseudo… 3 EC50 > 9 e+3 µg/L bioma…
#> 4 (8,9-Z)-isomer … Pseudo… 3 EC50 > 9 e+0 mg/L bioma…
#> 5 (E,E)-8,10-Dode… Pseudo… 3 EC50 = 5.23e-1 mg/L growth
#> 6 (RS)-2,4-dinitr… Pseudo… 4 EC50 = 2.12e+0 mg/L other
#> 7 1,2,4-Triazole Pseudo… 3 EC50 = 8.2 e+0 mg/L bioma…
#> 8 1,2-Benzisothia… Scened… NA EC50 > 1 e+2 mg/L growth
#> 9 1,3-Dichloropro… Pseudo… 4 EC50 = 5.45e+0 mg/L growth
#> 10 1,4-Dimethylnap… Pseudo… 4 EC50 = 3.2 e-1 mg/L bioma…
#> # ℹ 503 more rows
# Show aquatic endpoints for spinosad
oft$reference_points |>
dplyr::filter(Study == "Ecotox (water compartment)") |>
dplyr::filter(grepl("^Spinos", Substance)) |>
arrange(Species) |>
select(Substance, Species, DurationDays, Endpoint, qualifier, value, unit, Effect)
#> # A tibble: 7 × 8
#> Substance Species DurationDays Endpoint qualifier value unit Effect
#> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr>
#> 1 Spinosad Common carp 4 LC50 = 4 mg/L morta…
#> 2 Spinosad Fathead minnow 110 NOEC = 0.217 mg/L repro…
#> 3 Spinosad Harlequin fly 2 EC50 > 32 µg/L morta…
#> 4 Spinosad Harlequin fly 25 NOEC = 0.62 µg/L not r…
#> 5 Spinosad Harlequin fly 28 NOEC = 0.0585 mg/kg not r…
#> 6 Spinosad Navicula pelli… 3 EC50 = 0.47 mg/L growth
#> 7 Spinosad Swollen duckwe… NA EC50 > 71 mg/L frond…
# Check substance characterisation of spinosad (no useful information available)
oft$substance_characterisation |>
dplyr::filter(grepl("^Spinos", Substance))
#> # A tibble: 1 × 7
#> Substance component_type Component CASNumber ECRefNo MolecularFormula smiles
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 Spinosad as such Spinosad NA NA NA NA
# List species used in terrestrial tests
oft$reference_points |>
dplyr::filter(Study == "Ecotox (soil compartment)") |>
select(Species) |>
unique() |>
arrange(Species) |>
print(n = Inf)
#> # A tibble: 51 × 1
#> Species
#> <chr>
#> 1 Aleochara bilineata
#> 2 Aphidius colemani
#> 3 Aphidius matricariae
#> 4 Aphidius rhopalosiphi
#> 5 Carrot
#> 6 Common chickweed
#> 7 Common oat
#> 8 Cucumber
#> 9 Earthworm
#> 10 Encarsia formosa
#> 11 Field bean (Fava bean)
#> 12 Folsomia candida
#> 13 Garden cress
#> 14 Garden pea
#> 15 Green lacewing
#> 16 Grey worm
#> 17 Harlequin fly
#> 18 Honey bee
#> 19 Hypoaspis aculeifer
#> 20 Lettuce
#> 21 Lob worm
#> 22 Maize
#> 23 Marmalade hoverfly
#> 24 Minute pirate bug
#> 25 Monocots
#> 26 Mung bean
#> 27 Onion
#> 28 Pardosa sp.
#> 29 Perennial ryegrass
#> 30 Poecilus cupreus
#> 31 Radish
#> 32 Rapeseed (oilseed rape)
#> 33 Red tiger worm
#> 34 Redroot amaranth
#> 35 Rye
#> 36 Seven-spot ladybird
#> 37 Sorghum
#> 38 Soybean
#> 39 Sugar beet
#> 40 Sunflower
#> 41 Swollen duckweed
#> 42 Tiger worm
#> 43 Tomato
#> 44 Trichogramma cacoeciae
#> 45 Typhlodromus pyri
#> 46 Unspecified
#> 47 Wheat
#> 48 White mustard
#> 49 Wild cabbage
#> 50 Wild oat
#> 51 not reported
# Show terrestrial endpoints for spinosad
oft$reference_points |>
dplyr::filter(Study == "Ecotox (soil compartment)") |>
dplyr::filter(grepl("^Spinos", Substance)) |>
arrange(Species) |>
select(Substance, Species, DurationDays, Endpoint, qualifier, value, unit, Effect)
#> # A tibble: 4 × 8
#> Substance Species DurationDays Endpoint qualifier value unit Effect
#> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr>
#> 1 Spinosad Aphidius rhopa… NA LR50 = 0.371 g/ha morta…
#> 2 Spinosad Honey bee NA LD50 = 0.0036 µg/p… morta…
#> 3 Spinosad Honey bee NA LD50 = 0.057 µg/p… morta…
#> 4 Spinosad Tiger worm NA NOEC = 35.2 mg/kg growth
# Show terrestrial endpoints for terbuthylazine
oft$reference_points |>
dplyr::filter(Study == "Ecotox (soil compartment)") |>
dplyr::filter(grepl("^Terbuthyl", Substance)) |>
arrange(Species) |>
select(Substance, Species, DurationDays, Endpoint, qualifier, value, unit, Effect)
#> # A tibble: 5 × 8
#> Substance Species DurationDays Endpoint qualifier value unit Effect
#> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr>
#> 1 Terbuthylazine Aphidius rh… NA LR50 > 750 g/ha morta…
#> 2 Terbuthylazine Folsomia ca… 28 NOEC = 42.2 mg/kg not r…
#> 3 Terbuthylazine Honey bee 2 LD50 > 22.6 µg/p… morta…
#> 4 Terbuthylazine Tiger worm 14 LC50 > 283. mg/kg morta…
#> 5 Terbuthylazine Typhlodromu… NA LR50 > 750 g/ha morta…
# Show terrestrial endpoints for florasulam (an example where terrestrial plant data are available)
oft$reference_points |>
dplyr::filter(Study == "Ecotox (soil compartment)") |>
dplyr::filter(grepl("^Floras", Substance)) |>
arrange(Species) |>
select(Substance, Species, DurationDays, Endpoint, qualifier, value, unit, Effect)
#> # A tibble: 8 × 8
#> Substance Species DurationDays Endpoint qualifier value unit Effect
#> <chr> <chr> <dbl> <chr> <chr> <dbl> <chr> <chr>
#> 1 Florasulam Aphidius rhop… 2 LR50 > 1.5 e+1 g/ha morta…
#> 2 Florasulam Honey bee 2 LD50 > 1 e+2 µg/p… morta…
#> 3 Florasulam Honey bee 2 LD50 > 1 e+2 µg/p… morta…
#> 4 Florasulam Rapeseed (oil… NA ER50 = 5.96e-1 g/ha seedl…
#> 5 Florasulam Sunflower NA ER50 = 2.22e-1 g/ha other
#> 6 Florasulam Tiger worm 14 LC50 > 1.32e+3 mg/kg morta…
#> 7 Florasulam Tiger worm NA NOEC = 2.03e-1 mg/kg not r…
#> 8 Florasulam Typhlodromus … 7 LR50 > 1.5 e+1 g/ha morta…