Title:	A Comprehensive R Tool for Zootechnical Metrics
Version:	1.1.1
Description:	A collection of functions to compute frequently used metrics for nutrition trials in aquaculture. Implementations include metrics to calculate growth, feed conversion, nutrient use efficiency, and feed digestibility. The package supports reproducible workflows for summarising experimental results and reduces manual calculation errors. For additional information see Machado e Silva, Karthikeyan and Tellbüscher (2025) <doi:10.13140/RG.2.2.27322.04808>.
License:	GPL (≥ 3)
VignetteBuilder:	knitr
URL:	https://github.com/TellAnAx/aquacultuR
BugReports:	https://github.com/TellAnAx/aquacultuR/issues
Encoding:	UTF-8
LazyData:	true
RoxygenNote:	7.3.3
Imports:	dplyr, magrittr
Suggests:	knitr, lubridate, tidyr, rmarkdown, testthat (≥ 3.0.0)
Config/testthat/edition:	3
Depends:	R (≥ 3.5)
NeedsCompilation:	no
Packaged:	2026-01-21 20:10:14 UTC; anil
Author:	Anıl Axel Tellbüscher [aut, cre, cph], Davide Machado e Silva [aut], Simão Correia [aut], Madhav Karthikeyan [ctb], Tomáš Pěnka [dtc]
Maintainer:	Anıl Axel Tellbüscher <atellbuscher@frov.jcu.cz>
Repository:	CRAN
Date/Publication:	2026-01-26 16:50:08 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of calling 'rhs(lhs)'.

ADC of DM

Description

Function to calculate the Apparent Digestibility Coefficient (ADC) of the dry matter fraction of a compound diet.

Usage

adc_dm(std_diet, dm_diet = 1, std_feces)

Arguments

Value

returns a single numeric value in the interval [0, 1], which is the relative ADC for the dry matter content of the diet. If the value is not within the interval, an additional warning is returned.

Author(s)

Anıl Axel Tellbüscher

References

Bureau, D. P., Harris, A. M. & Cho, C. Y. (1999): Apparent digestibility of rendered animal protein ingredients for rainbow trout (Oncorhynchus mykiss). Aquaculture, 180, p.345-358.

Examples

# use function to calculate a single ADC value

# 900 g/kg (90%) dry matter content of feed
# 10 g/kg (1%) digestibility standard in feed
# 45 g/kg (4.5%) digestibility standard in feces
adc_dm(dm_diet = 0.95, std_diet = 0.01, std_feces = 0.045)


# function can also be used within a tidyverse pipeline.
digestdm %>% 
  dplyr::group_by(diet) %>%  
  dplyr::summarise(
    `ADC DM` = adc_dm(dm = dm, 
                      std_diet = std_feed, 
                      std_feces = std_feces))

ADC of a feed ingredient (ADCingr)

Description

Function to calculate the Apparent Digestibility Coefficient of a nutrient contained in a feed ingredient of a compound diet. The calculation of the ADCingr is based on equation 4 proposed by Bureau & Hua (2006).

Usage

adc_ingr(
  adc_test,
  adc_ref,
  nut_ref,
  nut_ingr,
  dm_ref = 1,
  dm_ingr = 1,
  incl_ingr = 0.3
)

Arguments

Value

returns a single numeric value in the interval [0, 1], which is the relative ADC for the diet. If the value is not within the interval, an additional warning is returned.

Author(s)

Anıl Axel Tellbüscher

References

Bureau, D. P., & Hua, K. (2006): Letter to the Editor of Aquaculture. Aquaculture, 252, p.103–105.

Bureau, D. P., Harris, A. M., & Cho, C. Y. (1999): Apparent digestibility of rendered animal protein ingredients for rainbow trout (Oncorhynchus mykiss). Aquaculture 180, p.345-358.

Examples

# Example from Bureau et al. (1999) - Blood meal 2

# reference feed dry matter: 0.928 (92.8%)
# reference feed nutrient mass frac.: 0.45 (45%)
# reference feed apparent digestibility coef.: 0.923 (92.3%)
# test feed apparent digestibility coef.: 0.902 (90.2%)
# test ingredient dry matter: 0.895 (89.5%)
# test ingredient nutrient mass frac.: 0.846 (84.6%)

adc_ingr(adc_ref = 0.923, 
         nut_ref = 0.45, 
         dm_ref = 0.928,
         adc_test = 0.902, 
         nut_ingr = 0.846,
         dm_ingr = 0.895)

ADC of a nutrient (ADCnut)

Description

Function to calculate the Apparent Digestibility Coefficient of a nutrient in the dry matter fraction of a compound diet.

Usage

adc_nut(std_diet, std_feces, nut_diet, nut_feces)

Arguments

Value

returns a single numeric value in the interval [0, 1] which is the relative ADC for a single nutrient in the diet. If the value is not within the interval, an additional warning is returned.

Author(s)

Anıl Axel Tellbüscher

References

Bureau, D.P., & Hua, K. (2006): Letter to the Editor of Aquaculture. Aquaculture, 252, p.103–105.

Cho, C.Y., Slinger, S.J., & Bayley, H.S. (1982): Bioenergetics of salmonid fishes: energy intake, expenditure and productivity. Comp. Biochem. Physiol. 73B, p.25–41.

Examples

# 0.4 g/g (40%) CP on dry matter basis in feed
# 0.1 g/g (10%) CP on dry matter basis in feces
# 0.010 g/g (1%) digestibility standard in feed
# 0.045 g/g (4.5%) digestibility standard in feces

adc_nut(nut_diet = 0.4, nut_feces = 0.1, 
        std_diet = 0.01, std_feces = 0.045)

Absolute Growth (AG)

Description

A function that calculates the Absolute Growth (AG), also denoted as Absolute Weight Gain (AWG) based on the Initial Body weight (IBW; ibw) in gram (g) and the Final Body Weight (FBW; fbw) in gram (g).

Usage

ag(ibw, fbw)

weight_gain(ibw, fbw)

Arguments

Value

returns a numeric value that is the AG.

Author(s)

Anıl Axel Tellbüscher

References

Lugert, V., Thaller, G., Tetens, J., Schulz, C., & Krieter, J. (2016): A review on fish growth calculation: multiple functions in fish production and their specific application. Reviews in Aquaculture, 8, p.30–42.

Examples

data(weight2)
dplyr::mutate(weight2, AG = ag(ibw_g, fbw_g))

Absolute Growth Rate (AGR)

Description

A function that calculates the Absolute Growth Rate (AGR), also denoted as Weight Gain (WG) when applied to weight data.

Usage

agr(ibw, fbw, duration)

Arguments

Value

returns a numeric value which is the total body weight change over the specified period of time.

Author(s)

Anıl Axel Tellbüscher

Madhav Karthikeyan

Davide A. Machado e Silva

References

Lugert, V., Thaller, G., Tetens, J., Schulz, C., & Krieter, J. (2016): A review on fish growth calculation: multiple functions in fish production and their specific application. Reviews in Aquaculture, 8, p.30–42.

Hopkins K.D. (1992) Reporting fish growth, a review of the basics. Journal of World Aquaculture Society, 23, p.173-179

Examples

data(weight2)
dplyr::mutate(weight2, AGR = agr(ibw_g, fbw_g, duration = 84))

Fish body composition

Description

This dataset contains compositional data on the proximate composition and some key minerals in the body of Atlantic salmon (Salmo salar) at the beginning and the end of a trial. The original dataset ('BodyComposition_tank') was published by Liland et al. (2024) and is from the first out of two trials ('Trial A'). Alterations to the original data structure were done by 1) converting the double-row column names into single-row column names and 2) removing the 'sex' column.

Format

A tibble with 12 rows and 14 columns:

date

date; date of data recording.

treatment

factor; treatment identifier.

tank

factor; rearing tank identifier.

dm

numeric; dry matter content of fish tissue in g/g.

water

numeric; content of fish tissue in g/g.

ash

numeric; content of fish tissue in g/g on dry matter basis.

energy

numeric; gross energy content of fish tissue in kJ/g on dry matter basis.

fat

numeric; crude fat content of fish tissue in g/g on dry matter basis.

protein

numeric; crude protein content of fish tissue in g/g on dry matter basis.

ca

numeric; calcium content of fish tissue in mg/kg on dry matter basis.

k

numeric; potassium content of fish tissue in mg/kg on dry matter basis.

mg

numeric; magnesium content of fish tissue in mg/kg on dry matter basis.

na

numeric; sodium content of fish tissue in mg/kg on dry matter basis.

phosphorus

numeric; content of fish tissue in mg/kg on dry matter basis.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

bodycomp

Digestibility of dry matter

Description

This dataset contains example data to calculate the apparent digestibility of two diets that differ in their dry matter mass fraction and in the mass fraction of digestibility markers in the feces.

Format

A tibble with two rows and four columns:

diet

character; feed identifier.

dm

numeric; mass fraction of dry matter in the feed. Data reported as value between 0 and 1, corresponding to g/g.

std_feed

numeric; mass fraction of digestibility marker in feed. Data reported as value between 0 and 1, corresponding to g/g.

std_feces

numeric; mass fraction of digestibility marker in feces. Data reported as value between 0 and 1, corresponding to g/g.

Examples

digestdm

Digestibility of a feed ingredient

Description

This dataset contains example data for the determination of the apparent digestibility of feed ingredients by using a reference diet and replacing a part (usually 30 The dataset is based on Bureau et al. (1999) but was presented in its complete form in Bureau & Hua (2006).

Format

A tibble with one row and eight columns

diet_reference

character; reference feed identifier.

ingredient

character; feed ingredient identifier.

adc_reference

numeric; apparent digestibility coefficient of the reference feed. The data is a value between 0 and 1.

adc_test

numeric; apparent digestibility coefficient of the test feed. The data is a value between 0 and 1.

dm_reference

numeric; mass fraction of dry matter in the reference feed. Data reported as value between 0 and 1, corresponding to g/g.

dm_ingr

numeric; mass fraction of dry matter in the feed ingredient. Data reported as value between 0 and 1, corresponding to g/g.

CP_reference

numeric; mass fraction of crude protein in the pelleted reference feed reported as value between 0 and 1, corresponding to g/g.

CP_ingr

numeric; mass fraction of crude protein in the feed ingredient. Data reported as value between 0 and 1, corresponding to g/g.

References

Bureau, D. P. & Hua, K. (2006). Letter to the Editor of Aquaculture. Aquaculture, 252(2-4), 103–105. https://doi.org/10.1016/j.aquaculture.2006.01.028

Bureau, D. P., Harris, A. M. & Cho, C. Y. (1999). Apparent digestibility of rendered animal protein ingredients for rainbow trout (Oncorhynchus mykiss). Aquaculture, 180, 345–358. https://doi.org/10.1016/S0044-8486(99)00210-0

Examples

digestingr

Digestibility of feed nutrients

Description

This dataset contains example data for the calculation of apparent digestibility coefficients for the digestibility of nitrogen in the dry matter fraction of an aquaculture feed.

Format

A tibble with two rows and six columns:

diet

character; feed identifier.

dm

numeric; mass fraction of dry matter in the feed. Data reported as value between 0 and 1, corresponding to g/g.

N_feed

numeric; mass fraction of nitrogen in feed. Data reported as value between 0 and 1, corresponding to g/g.

std_feed

numeric; mass fraction of digestibility marker in feed. Data reported as value between 0 and 1, corresponding to g/g.

N_feces

numeric; mass fraction of nitrogen in feces in g/kg.

std_feces

numeric; mass fraction of digestibility marker in feces. Data reported as value between 0 and 1, corresponding to g/g.

Examples

digestnut

Feed conversion efficiency (FCE)

Description

A function that calculates the feed conversion efficiency (FCE), which is the inverse of the feed conversion ratio (FCR). As FCR, this metric measures how effectively cultivated species convert feed into weight. However, contrarily to FCR, the higher the FCE the more efficient the feed conversion is.

Usage

fce(ibw, fbw, feed, dm = 1)

Arguments

Value

a numeric value that is the feed conversion efficiency (FCE)

Author(s)

Anıl Axel Tellbüscher

Davide A. Machado e Silva

Madhav Karthikeyan

Examples

# Feed intake = 1500 g
# Feed dry matter = 0.96 g/g (= 96%)
# Initial bodyweight = 100 g
# Final bodyweight = 1000 g

fce(100, 1000, 1500, 0.96)

Feed Conversion Ratio (FCR)

Description

A function that calculates the Feed Conversion Ratio (FCR) based on the Initial Body weight (IBW; ibw) in gram (g), the Final Body Weight (FBW; fbw) in gram (g), the Feed fed (Ff; ff) in gram and the dry matter (DM; dm) content of the feed in percent.

Usage

fcr(ibw, fbw, feed, dm = 1)

Arguments

Details

The Feed Conversion Ratio (FCR) describes the amount of feed on dry matter (DM) basis that is required to gain 1 kg of body weight on wet weight basis. Depending on whether the Feed fed refers to the total amount of feed administered or the total amount corrected for non-eaten feed, the result resembles the economic FCR (eFCR) or the biological FCR (bFCR), respectively (Glencross et al., 2024).

Value

returns a numeric value that is the FCR.

Author(s)

Anıl Axel Tellbüscher

References

Lugert, V., Thaller, G., Tetens, J., Schulz, C., & Krieter, J. (2016): A review on fish growth calculation: multiple functions in fish production and their specific application. Reviews in Aquaculture, 8, p.30–42.

Glencross, B., Bachis, E., Robb, D., & Newton, R. (2024): The evolution of sustainability metrics for the marine ingredient sector: Moving towards holistic assessments of aquaculture feed. Reviews in Fisheries Science & Aquaculture, 32(4), p.545-561.

Examples

# Feed intake = 1500 g
# Feed dry matter = 0.96 g/g (= 96%)
# Initial bodyweight = 100 g
# Final bodyweight = 1000 g

fcr(100, 1000, 1500, 0.96)

Daily feed intake

Description

This dataset contains daily feed intake data from a feeding trial with Atlantic salmon (Salmo salar). The original dataset ("FeedIntake") was published by Liland et al. (2024) and is from the first out of two trials ("Trial A"). Alterations to the original data structure were done by 1) converting the double-row column names into single-row column names, 2) shortening the column names, and 3) converting the table into long format by moving the tank IDs into a separate column. NA values have been replaced by the recalculated feed intakes for the respective day.

Format

A tibble with 270 rows and 4 columns:

date

date; date of data recording.

tank

factor; rearing tank identifier.

daily_feed_intake

numeric; daily feed intake in gram per fish.

cumulative_feed_intake

numeric; cumulatic feed intake in gram per fish.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

feed_intake

Feed composition

Description

This dataset contains compositional data of Skretting Protec, a commercial fish feed. The data comprises the proximate composition, phosphorus, and some essential amino acids.

Format

A tibble with one row and 25 columns:

diet

character; feed name.

dry_matter

numeric; content of feed in g/g.

crude_protein

numeric; content of feed in g/g as fed.

crude_lipids

numeric; content of feed in g/g as fed.

ash

numeric; content of feed in g/g as fed.

gross_energy

numeric; content of feed in MJ per kg as fed.

phosphorus

numeric; content of feed in g/g as fed.

arginine

numeric; content of feed in g/g as fed.

histidine

numeric; content of feed in g/g as fed.

isoleucine

numeric; content of feed in g/g as fed.

leucine

numeric; content of feed in g/g as fed.

lysine

numeric; content of feed in g/g as fed.

threonine

numeric; content of feed in g/g as fed.

tryptophan

numeric; content of feed in g/g as fed.

valine

numeric; content of feed in g/g as fed.

methionine

numeric; content of feed in g/g as fed.

cysteine

numeric; content of feed in g/g as fed.

phenylalanine

numeric; content of feed in g/g as fed.

tyrosine

numeric; content of feed in g/g as fed.

aspartic_acid

numeric; content of feed in g/g as fed.

glutamic_acid

numeric; content of feed in g/g as fed.

alanine

numeric; content of feed in g/g as fed.

glycine

numeric; content of feed in g/g as fed.

proline

numeric; content of feed in g/g as fed.

serine

numeric; content of feed in g/g as fed.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

feedcomp

Daily count of live and dead fish

Description

This dataset contains the daily count of dead and alive fish during a 29-day feeding trial with Atlantic salmon (Salmo salar). The original dataset ('NumberOfFish') was published by Liland et al. (2024) and is from the first out of two trials ('Trial A'). Alterations to the original data structure were done by 1) converting the double-row column names into single-row column names, 2) shortening the column names, and 3) converting the table into long format by moving the tank IDs into a separate column.

Format

A tibble with 270 rows and 4 columns:

date

date; date of data recording.

tank

factor; rearing tank identifier.

total_number

numeric; count of fish stocked at the beginning of the experiment.

dead

numeric; count of dead fish on each recorded day of the experiment.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

fishcount

Geometric Mean Bodyweight (GMBW)

Description

A function that calculates the geometric mean of the initial and final bodyweight.

Usage

gbw(ibw, fbw)

Arguments

Details

While the arithmetic mean assumes a linear relationship between the averaged numbers, the geometric mean accounts for the non-linear and potentially variable nature of animal growth.

Value

numeric value that is the geometric mean bodyweight.

Author(s)

Anıl Axel Tellbüscher

Examples

data(weight2)
dplyr::mutate(weight2, GMBW = gbw(ibw_g, fbw_g))

Metabolic bodyweight (MBW)

Description

The metabolic bodyweight is the rate of energy expenditure in dependence of the bodyweight of an organism. The metabolism of larger animals is generally slower per Kg when comparing with smaller animals. An exponent between 0-1 takes that relationship into account in a fairly simple equation.

Usage

mbw(ibw, fbw, mb_exp = 0.8)

Arguments

Details

The default exponent is suited to fish only. It was set to 0.8 based on Lupatsch et al. (2003) and should be adjusted to other scenarios.

Value

returns a numeric value that is the metabolic bodyweight.

Author(s)

Anıl Axel Tellbüscher

Davide A. Machado e Silva

Madhav Karthikeyan

References

Lupatsch, I. et al. (2003): Comparison of energy and protein efficiency among three fish species gilthead sea bream (Sparus aurata), European sea bass (Dicentrarchus labrax) and white grouper (Epinephelus aeneus): energy expenditure for protein and lipid deposition. Aquaculture 225, p.175-189.

Examples

data(weight2)
dplyr::mutate(weight2, MBW = mbw(ibw_g, fbw_g))

Nutrient Efficiency Ratio (NER)

Description

Function to calculate the Nutrient Efficiency Ratio (NER). The NER belongs to the Nutrient Use Efficiency metrics and relates the intake of a compound with the bodyweight increase. If the feed intake (FI) is restricted and the administered diets are of comparable digestibility, then potential differences in growth could be related to differences in the sub-composition of target nutrients that are also controlled for. This would be reflected by the NER.

Usage

ner(ibw, fbw, fi, nut_f, dm = 1)

Arguments

Value

returns a single numeric value

Author(s)

Anıl Axel Tellbüscher

Examples

# Initial bodyweight = 10 g
# Final bodyweight = 100 g
# Feed intake = 240 g
# Nutrient mass fraction in feed = 0.5 g/g
ner(ibw = 10, fbw = 100, fi = 240, nut_f = 0.5)

Nutrient retention (NR)

Description

Function to calculate the Nutrient Retention (NR). The NR belongs to the Nutrient Use Efficiency metrics and is a measure for the proportion of a consumed nutrient that is retained in the tissue.

Usage

nr(ibw, fbw, ibn, fbn, fi, nut_f, dm = 1, dm_ib = 1, dm_fb = 1)

Arguments

Value

a numeric value. Multiply by 100 to convert into percentage.

Author(s)

Anıl Axel Tellbüscher

References

Willer, D.F., Newton, R., Malcorps, W. et al. Wild fish consumption can balance nutrient retention in farmed fish. Nat Food 5, 221–229 (2024). https://doi.org/10.1038/s43016-024-00932-z

Examples

# initial bodyweight = 10 g (0.01 kg)
# final bodyweight = 100 g (0.1 kg)
# initial mass fraction of N = 128 g/kg (80% CP on DM basis)
# final mass fraction of N = 132 g/kg (82.5% CP on DM basis)
# feed intake = 200 g (0.2 kg)
# N in feed = 72 g/kg (45% CP)

nr(10, 100, 0.128, 0.132, 200, 0.072) * 100

# 82.7% of the provided N has been retained


# multiple fish
nr(ibw = 10, fbw = c(93, 102, 99, 98, 101, 132),
   ibn = 0.128, fbn = 0.132,
   fi = 200, nut_f = 0.072)

Rearing data from the first polyculture experiment

Description

A dataset containing feed quantities fed per tank and the average water temperature over all tanks stocked with pikeperch oder sturgeon. The variables are as follows:

Format

A data frame containing 24 rows and four columns:

tank

character; unique identifier for each fish tank.

feed_g

numeric; total feed input in gram over the duration of the experiment.

temp_C

numeric; average water temperature in degrees Celsius.

duration

numeric; total duration of the experiment in days.

Examples

rearing

Relative Growth (RG)

Description

A function that calculates the Relative Growth (RG) based on the Initial Body weight (IBW; ibw) and the Final Body Weight (FBW; fbw) in grams (g).

Usage

rg(ibw, fbw)

Arguments

Value

returns a numeric value that is the Relative Growth. Multiply by 100 for conversion into a percentage.

Author(s)

Anıl Axel Tellbüscher

Examples

data(weight2)
dplyr::mutate(weight2, RG = rg(ibw_g, fbw_g))

Relative Growth Rate (RGR)

Description

A function that calculates the Relative Growth Rate (RGR), which is the relative weight increase per time unit.

Usage

rgr(ibw, fbw, duration, mean_fun = "init")

Arguments

Value

either a single numeric value or vector holding the calculated RGR values. Multiply by 100 for conversion into percentage.

Author(s)

Anıl Axel Tellbüscher

References

Lugert, V., Thaller, G., Tetens, J., Schulz, C., & Krieter, J. (2016): A review on fish growth calculation: multiple functions in fish production and their specific application. Reviews in Aquaculture, 8, p.30–42.

Examples

data(weight2)
dplyr::mutate(weight2, RGR = rgr(ibw_g, fbw_g, duration = 84))

Sampling data

Description

This dataset contains the fish weight, fork length, sex, liver weight, hepatosomatic index, heart weight, cardiosomatic index, gonad weight, gonadosomatic index, viscera weight, and viscerosomatic index from a feeding trial with Atlantic salmon (Salmo salar). The original dataset ('FeedIntake') was published by Liland et al. (2024) and is from the first out of two trials ('Trial A'). Alterations to the original data structure were done by 1) converting the double-row column names into single-row column names, and 2) removing the 'sex' column.

Format

A tibble with 181 rows and 14 columns:

date

date; date of data recording.

tank

factor; rearing tank identifier.

replicate

factor; replicate identifier.

sample_type

factor; type of sample.

fish_weight

numeric; weight of fish in gram.

fork_length

numeric; length of fish from the tip of the snout to the end of the middle caudal fin rays in centimeter.

liver_weight

numeric; weight of the liver in gram.

hsi

numeric; hepatosomatic index in percent.

heart_weight

numeric; weight of the heart in gram.

csi

numeric; cardiosomatic index in percent.

gonad_weight

numeric; weight of the gonads in gram.

gsi

numeric; gonadosomatic index in percent.

viscera_weight

numeric; weight of the viscera in gram.

vsi

numeric; viscerosomatic index in percent.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

samplings

Specific Growth Rate (SGR)

Description

This function calculates the Specific Growth Rate (SGR) based on the Instantaneous Growth Rate (IGR). The IGR is a useful metric, although hard to interpret. The SGR, derived from IGR, can then be easily interpreted as the percentage of Body Weight gained each day. The SGR is a growth metric for aquaculture products (e.g., fish, crustaceans, bivalves, algae), describing the increase in body weight over a period of time. Body weight can be substituted by other metrics, such as length. However, body weight is the used in the vast majority of studies and alternatives are not advised for the sake of consistency.

Usage

sgr(ibw, fbw, duration, return_igr = FALSE)

Arguments

Value

Returns a numeric, which is the SGR as percentage of the body weight gain per day, or a list containing the SGR and the IGR.

Author(s)

Anıl Axel Tellbüscher

Davide A. Machado e Silva

References

Crane, D.P., Ogle, D.H. and Shoup, D.E. (2020), Use and misuse of a common growth metric: guidance for appropriately calculating and reporting specific growth rate. Rev Aquacult, 12: 1542-1547. https://doi.org/10.1111/raq.12396

Examples

dplyr::mutate(weight2, SGR = sgr(ibw_g, fbw_g, duration = 84))

Thermal Growth Coefficient (TGC)

Description

A function that calculates Thermal Growth Coefficient (TGC) based on the Initial Body weight (IBW) in grams (g), the Final Body Weight (FBW) in grams (g) and the average water temperature (Temp.) in Celsius (°C) for the duration of the trial.

The TGC is an alternative growth metric for fishes, describing the increase in bodyweight over a period of time. It is suitable for poikilothermic animals due to its standardisation for temperature. It should, however, be taken into account, that the temperature during the experiment should remain within the optimum range. It is also noteworthy that the equation is optimized for a constant temperature throughout the experiment.

Usage

tgc(ibw, fbw, duration, temp, scale_coef = 1000)

Arguments

Value

Returns a numeric value that is the TGC.

Author(s)

Anıl Axel Tellbüscher

Davide A. Machado e Silva

Madhav Karthikeyan

References

Lugert, V., Thaller, G., Tetens, J., Schulz, C., & Krieter, J. (2016): A review on fish growth calculation: multiple functions in fish production and their specific application. Reviews in Aquaculture, 8, p.30–42.

Jobling, M. (2003): The thermal growth coefficient (TGC) model of fish growth: a cautionary note. Aquaculture Research, 34, p. 581–584.

Treatments

Description

This dataset contains the rearing tank and respective treatment assigned to it. It represents the metadata from a feeding trial with Atlantic salmon (Salmo salar). The related dataset was published by Liland et al. (2024) and is from the first out of two trials ("Trial A").

Format

A tibble with nine rows and two columns:

tank

factor; rearing tank identifier.

treatment

factor; treatment identifier.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

treatments

Daily water parameters

Description

This dataset contains daily readings of water temperature, salinity, and dissolved oxygen from a feeding trial with Atlantic salmon (Salmo salar). The original dataset ("WaterParametersDaily") was published by Liland et al. (2024) and is from the first out of two trials ("Trial A"). Alterations to the original data structure were done by 1) converting the double-row column names into single-row column names, 2) shortening the column names, and 3) converting the table into long format by moving the tank IDs into a separate column.

Format

A tibble with 270 rows and 6 columns:

date

date; date of data recording.

tank

factor; rearing tank identifier.

temp

numeric; water temperature in degrees Celsius.

salinity

numeric; salinity in parts per thousand.

do_perc

numeric; dissolved oxygen in percentage saturation.

do_conc

numeric; dissolved oxygen concentration in mg/L.

References

Liland, N., Rønnestad, I., Azevedo, M., Lai, F., Oulie, F., Conceição, L., Soares, F. (2024): Dataset on the performance of Atlantic salmon (Salmo salar) reared at different dissolved oxygen levels under experimental conditions. Data in Brief 57, 110983. https://doi.org/10.1016/j.dib.2024.110983

Examples

water_params

Fish biomass and bodyweights from the first polyculture experiment

Description

A dataset containing fish weights from a polyculture experiment with pikeperch (Sander lucioperca) and Russian sturgeon.

Format

A tibble with 24 rows and eight columns:

tank

character; rearing tank identifier.

treat_id

character; treatment identifier.

count_start

numeric; fish count at the beginning of the experiment.

count_end

numeric; fish count at the end of the experiment.

biomass_kg_start

numeric; total fish biomass in kg at the beginning of the experiment.

biomass_kg_end

numeric; total fish biomass in kg at the end of the experiment.

Examples

weight

Individual fish bodyweights during a polyculture experiment

Description

A dataset holding weight data of tagged individuals of two different fish species, pikeperch (Sander lucioperca) and largemouth bass (Micropterus salmoides), at the beginning and the end of a polyculture experiment for aquaculture purposes.

Format

A tibble with 396 rows and four columns:

species

character; species identifier.

culture_sys

character; culture system identifier.

ibw_g

numeric; initial bodyweight in gram.

fbw_g

numeric; final bodyweight in gram.

References

Pěnka T., Malinovskyi O., Křišťan J., Imentai A., Policar T. (2021): Effect of density and mixed culture with pikeperch (Sander lucioperca) on effectivity of largemouth bass (Micropterus salmoides) intensive culture. Czech Journal of Animal Science, 66: 428–440.

Examples

weight2