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The aim of this study was to examine the suitability of different growth functions (linear, sinusoidal, Gompertz, Schumacher and Richards) to fit cumulative milk production data from buffalo cows. Cumulative milk production at each day in milk was calculated from two published datasets reporting (i) fortnightly test-day milk yield records of the first lactation of Murrah buffalo that had calved during 1977-2012 and (ii) the first lactation records of Jaffarabadi buffalo collected from history-cum-pedigree registers for each quinquennium between 1991 and 2010. Each function was fitted to the lactation curves using nonlinear regression procedures. The Richards and sinusoidal equations provided the smallest root mean square error values, Akaike's and Bayesian information criteria and, therefore, the best fit for the cumulative lactation curves for milk yield. The Richards equation appeared to provide the most accurate estimate of the cumulative milk production at peak milk yield. Sinusoidal and flexible classical growth functions are appropriate to describe cumulative milk production curves and estimate lactation traits in buffalo.
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Búfalos , Lactação , Leite , Animais , Búfalos/fisiologia , Lactação/fisiologia , Feminino , Leite/química , Dinâmica não Linear , Teorema de BayesRESUMO
Twenty-two Assaf male lambs (29.2 ± 0.9 kg live weight and 89 ± 0.2 days of age), distributed in two experimental groups, were used to evaluate the use of either feed-grade conventional urea (Control diet; n = 11) or slow-release urea (SRU diet; n = 11) as sources of dietary nitrogen on animal performance, ruminal fermentation, blood acid-base status, plasmatic metabolic profile, and carcass and meat quality. Animals were housed individually and fed ad libitum. At the end of the fattening period (day 70), the animals were slaughtered to compare the fermentation patterns in ruminal digesta and to evaluate the carcass and meat characteristics. No statistically significant differences (p > 0.05) were observed between treatments in the dry matter intake, final live weight, average daily gain, and feed conversion rate. Regarding the ruminal fermentation parameters, the molar proportion of propionic acid was higher (p < 0.05) and that of butyric acid was lower (p < 0.05) with the SRU than with the Control diet. There were no significant differences (p > 0.05) between experimental treatments in the blood acid-base status and biochemical profile, except for the concentration of urea in plasma, which was significantly (p < 0. 05) greater in SRU than in Control lambs. No statistically significant differences were observed between treatments (p > 0.05) in the carcass and meat characteristics. In conclusion, the use of slow-release urea as a replacement for feed-grade conventional urea in the diet of Assaf fattening lambs, under the experimental conditions of this study, did not improve animal performance and increased the feeding costs.
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An in vitro trial was carried out to investigate the effects of natural Thymbra capitata essential oil (NEO) and its main compounds [including carvacrol, p-cymene, γ-terpinene given alone or in a synthetic combination (SEO)] on ruminal fermentation and the bacterial community using batch cultures inoculated with ruminal digesta and incubating two different basal diets [high-forage (F) and high-concentrate (C) diet]. After 24 h of incubation, primary fermentation end-products [gas, methane, volatile fatty acids (VFAs) and ammonia] and rumen microbial diversity were determined. NEO reduced the total VFA concentration (P < 0.05) only in the C diet. In contrast, SEO and carvacrol decreased the total VFA concentration (P < 0.05) only in the F diet. Methane production was not affected (P > 0.05) by any of the experimental treatments or diets evaluated. Microbial diversity analysis showed only a moderate effect of carvacrol and SEO on 13 genera, including, mainly, Atopobium and Blautia (involved in subacute ruminal acidosis) or Candidatus Saccharimonas (related to laminitis). In conclusion, T. capitata EO has a limited potential to attain nutritional or environmental benefits, but further research should be carried out to clarify its effects on animal health and microbial food safety.
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Óleos Voláteis , Animais , Fermentação , Óleos Voláteis/farmacologia , Óleos Voláteis/metabolismo , Rúmen/microbiologia , Ácidos Graxos Voláteis/metabolismo , Bactérias , Dieta , Metano/metabolismo , Ração Animal/análise , DigestãoRESUMO
The aim of this study was to investigate the in vivo transfer of aflatoxin B1 (AFB1) to Assaf ewes' milk (aflatoxin M1, AFM1) and its effect on animal performance and health. Thirty Assaf ewes were allocated to three groups (C, L, H), and received a different individual daily dose of AFB1 (0, 40 and 80 µg) for 13 days. Milk (days 1, 2, 3, 4, 7, 14, 16 and 18) and blood (days 1, 7, 14 and 18) samples were collected. Milk yield, composition (except protein) and somatic cell counts (SCC) were not affected by AFB1 intake (p > 0.05). Haemoglobin concentration increased (p < 0.05) and haematocrit and alanine aminotransferase levels tended to increase (p < 0.10) in group H on day 14. AFM1 excretion was highly variable and detected in L and H animals from days 1 to 16 (3 days increase, 10 days steady-state, 3 days clearance). Carry-over rate (0.23%) was significantly higher in L (0.22-0.34%) than in H (0.16-0.19%) animals (p < 0.05). AFB1 daily doses of 40 to 80 µg do not impair milk yield; however, it may start affecting animals' health. Milk AFM1 depends mainly on the AFB1 intake whereas carryover rate is positively influenced by the level of milk production.
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Simulation models represent a low-cost approach to evaluating agricultural systems. In the current study, the precision and accuracy of the RUMINANT model to predict dry matter intake (DMI) and methane emissions from beef cattle fed tropical diets (characteristic of Colombia) was assessed. Feed intake (DMI) and methane emissions were measured in Brahman steers housed in polytunnels and fed six forage diets. In addition, DMI and methane emissions were predicted by the RUMINANT model. The model's predictive capability was measured on the basis of precision: coefficients of variation (CV%) and determination (R2, percentage of variance accounted for by the model), and model efficiency (ME) and accuracy: the simulated/observed ratio (S/O ratio) and slope and mean bias (MB%). In addition, combined measurements of accuracy and precision were carried out by means of mean square prediction error (MSPE) and correlation correspondence coefficient (CCC) and their components. The predictive capability of the RUMINANT model to simulate DMI resulted as valuable for mean S/O ratio (1.07), MB% (2.23%), CV% (17%), R2 (0.886), ME (0.809), CCC (0.869). However, for methane emission simulations, the model substantially underestimated methane emissions (mean S/O ratio = 0.697, MB% = -30.5%), and ME and CCC were -0.431 and 0.485, respectively. In addition, a subset of data corresponding to diets with Leucaena was not observed to have a linear relationship between the observed and simulated values. It is suggested that this may be related to anti-methanogenic factors characteristic of Leucaena, which were not accounted for by the model. This study contributes to improving national inventories of greenhouse gases from the livestock of tropical countries.
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The ability of four non-linear mixed models and one linear mixed model to describe phosphorus (P) retention as a function of dietary P intake, expressed on an available P (avP) basis, was assessed in growing and finishing pigs. Of the four non-linear models, the monomolecular and Michaelis-Menten describe diminishing returns behaviour, while the Richards and Morgan describe sigmoidal behaviour with the ability to also describe diminishing returns. Using a meta-analysis approach, models were fitted to avP intake vs. P retention data from P balance studies. Pig bodyweights (BW) ranged from 43.5 to 133 kg, P intake ranged from 0.055 to 0.468 g kg-1 BW0.75 d-1 for avP, and 0.151 to 0.806 g kg-1 BW0.75 d-1 for total P, with P retention ranging from 0.026 to 0.329 g kg-1 BW0.75 d-1. Models were evaluated using statistical measures of goodness-of-fit and inspection of residuals. The monomolecular and Michaelis-Menten best described the relationship between P retention and P intake. Endogenous P losses and P requirement for maintenance were found to be higher in finishing pigs compared to growing pigs as BW increased.
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This research communication reports a study to model the growth curves for withers height (WH) and body weight (BW) to withers height ratio (BW:WH) using monthly records (from 1 to 24 months of age) for three breeds of dairy heifer (Holstein, Jersey and Brown Swiss). The data sets used were those reported by the Dairy Heifer Evaluation Project of Penn State Extension (USA) between 1991 and 1992. Four growth functions (monomolecular and Michaelis-Menten, both with diminishing returns behaviour, and Schumacher and López, both with asymptotic sigmoidal behaviour) were fitted using the non-linear regression procedure of the SigmaPlot software and the parameters estimated. The models were judged for goodness of fit using adjusted coefficient of determination ($R_{{\rm adj}}^2 $), root mean square error (RMSE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC). Assessing the goodness of fit by $R_{{\rm adj}}^2 $ (>0.99 in all cases) reveals the generally appropriate fit of the models to the data. The non-sigmoidal functions (i.e. Michaelis-Menten and monomolecular) provided the best fits giving the lowest values of RMSE, AIC and BIC. Based on the chosen statistical criteria, the Schumacher and López equations provided acceptable fits to the WH and BW:WH growth curves, but showed points of inflexion at times before birth, indicating that these growth curves are not sigmoidal. In conclusion, evaluation of the different non-linear growth functions used in this study indicated their potential for modelling growth patterns in dairy heifers.
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A better knowledge of the growth of horses can facilitate sounder intervention in their health control, nutrition and management. This study compared five growth functions with either diminishing returns (monomolecular and Michaelis-Menten) or asymptotic sigmoidal (Gompertz, Richards and Lopez) behavior for describing the growth curves of horses, based on the relationship between a given somatic growth trait (body weight, withers height, or body weight to withers height ratio) and age. Data used in this study were those available in the literature for quarter horse males and thoroughbred foals and fillies from birth to maturity. Estimates of the model parameters were obtained using nonlinear regression procedures and the Marquardt-Levenberg algorithm. Functions were compared using goodness-of-fit statistics such as adjusted coefficient of determination and root mean square error. The results obtained with the Richards, Lopez and Gompertz equations suggest that curves are not sigmoidal, and that the diminishing returns models are adequate for describing the growth curves in horses.
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Diploide , Modelos Biológicos , Animais , Peso Corporal , Feminino , Cavalos , MasculinoRESUMO
Gas production profiles typically show a monotonically increasing monophasic pattern. However, atypical gas production profiles exist whereby at least two consecutive phases of gas production or additional extraneous features that distort the typical profile are present. Such profiles are more likely to occur with the use of a fecal inoculum and are much less well described. The presence of multiple phases or non-descript extraneous features makes it difficult to apply directly recommended modeling approaches such as standard response functions or classical growth functions. To overcome such difficulties, extensions of the Mitscherlich equation and a numerical modeling option also based on the Mitscherlich are explored. The numerical modeling option uses an estimate of relative rate obtained from the smoothed data profile and an estimate of maximum gas produced together with any lag time information drawn from the raw data to construct a simple Mitscherlich equation. In summary, this article illustrates the analysis of atypical gas production profiles obtained using a fecal inoculum and explores the methodology of numerical modeling to reconstruct equivalent typical growth-like trends.
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Using plant essential oils (EOs) contributes to the growing number of natural plants' applications in livestock. Scientific data supporting the efficacy of EOs as anti-inflammatory, antibacterial and antioxidant molecules accumulates over time; however, the cumulative evidence is not always sufficient. EOs antioxidant properties have been investigated mainly from human perspectives. Still, so far, our review is the first to combine the beneficial supporting properties of EOs in a One Health approach and as an animal product quality enhancer, opening new possibilities for their utilization in the livestock and nutrition sectors. We aim to compile the currently available data on the main anti-inflammatory effects of EOs, whether encapsulated or not, with a focus on mammary gland inflammation. We will also review the EOs' antioxidant activities when given in the diet or as a food preservative to counteract oxidative stress. We emphasize EOs' in vitro and in vivo ruminal microbiota and mechanisms of action to promote animal health and performance. Given the concept of DOHaD (Developmental Origin of Health and Diseases), supplementing animals with EOs in early life opens new perspectives in the nutrition sector. However, effective evaluation of the significant safety components is required before extending their use to livestock and veterinary medicine.
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The aim of the work reported here was to investigate the appropriateness of a sinusoidal function by applying it to model the cumulative lactation curves for milk yield and composition in primiparous Holstein cows, and to compare it with three conventional growth models (linear, Richards and Morgan). Data used in this study were 911 144 test-day records for milk, fat and protein yields, which were recorded on 834 dairy herds from 2000 to 2011 by the Animal Breeding Centre and Promotion of Animal Products of Iran. Each function was fitted to the test-day production records using appropriate procedures in SAS (PROC REG for the linear model and PROC NLIN for the Richards, Morgan and sinusoidal equations) and the parameters were estimated. The models were tested for goodness of fit using adjusted coefficient of determination $\lpar {R_{{\rm adj}}^2 } \rpar $, root mean square error (RMSE), Akaike's information criterion (AIC) and the Bayesian information criterion (BIC). $R_{{\rm adj}}^2 $ values were generally high (>0.999), implying suitable fits to the data, and showed little differences among the models for cumulative yields. The sinusoidal equation provided the lowest values of RMSE, AIC and BIC, and therefore the best fit to the lactation curve for cumulative milk, fat and protein yields. The linear model gave the poorest fit to the cumulative lactation curve for all production traits. The current results show that classical growth functions can be fitted accurately to cumulative lactation curves for production traits, but the new sinusoidal equation introduced herein, by providing best goodness of fit, can be considered a useful alternative to conventional models in dairy research.
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Bovinos/fisiologia , Lactação/fisiologia , Leite/química , Leite/fisiologia , Modelos Teóricos , Animais , Feminino , Irã (Geográfico) , Modelos Lineares , Lipídeos/análise , Proteínas do Leite/análise , Modelos Estatísticos , ParidadeRESUMO
In vitro gas production systems are utilized to screen feed ingredients for inclusion in ruminant diets. However, not all in vitro systems are set up to measure methane (CH4) production, nor do all publications report in vitro CH4. Therefore, the objective of this study was to develop models to predict in vitro CH4 production from total gas and volatile fatty acid (VFA) production data and to identify the major drivers of CH4 production in these systems. Meta-analysis and machine learning (ML) methodologies were applied to a database of 354 data points from 11 studies to predict CH4 production from total gas production, apparent DM digestibility (DMD), final pH, feed type (forage or concentrate), and acetate, propionate, butyrate and valerate production. Model evaluation was performed on an internal dataset of 107 data points. Meta-analysis results indicate that equations containing DMD, total VFA production, propionate, feed type and valerate resulted in best predictability of CH4 on the internal evaluation dataset. The ML models far exceeded the predictability achieved using meta-analysis, but further evaluation on an external database would be required to assess generalization ability on unrelated data. Between the ML methodologies assessed, artificial neural networks and support vector regression resulted in very similar predictability, but differed in fitting, as assessed by behaviour analysis. The models developed can be utilized to estimate CH4 emissions in vitro.
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Two new models, based upon the principles promulgated by Baranyi and co-workers are presented and resulting growth functions evaluated based upon their ability to mimic bacterial growth of the fish pathogen Flavobacterium psychrophilum. These growth functions make use of a dampening function to suppress potential growth, represented by a logistic, and are derived from rate:state differential equations. Dampening effects are represented by a rectangular hyperbola or a simple exponential, incorporated into a logistic differential equation and solved analytically resulting in two newly derived growth equations, viz. logistic × hyperbola (log × hyp) and logistic × exponential (log × exp). These characteristics result in flexible and robust growth functions that can be expressed as equations with biologically meaningful parameters. The newly derived functions (log × hyp and log × exp), along with the Baranyi (BAR), simple logistic (LOG) and its modified form (MLOG) were evaluated based upon examination of residuals and measures of goodness-of-fit and cross-validation. Using these criteria, log × hyp, log × exp and BAR performed better than, or at least equally well as, LOG and MLOG. In contrast with log × exp and BAR, log × hyp can be easily manipulated mathematically allowing for simple algebraic expressions for time and microbial biomass at inflexion point, in addition to maximum and scaled maximum growth rates.
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Two models are proposed to describe atypical biphasic gas production profiles obtained from in vitro digestibility studies. The models are extensions of the standard Mitscherlich equation, comprising either two Mitscherlich terms or one Mitscherlich and one linear term. Two models that describe typical monophasic gas production curves, the standard Mitscherlich and the France model [a generalised Mitscherlich (root-t) equation], were assessed for comparison. Models were fitted to 25 gas production profiles resulting from incubating feedstuffs with faecal inocula from equines. Seventeen profiles displayed atypical biphasic patterns while the other eight displayed typical monophasic patterns. Models were evaluated using statistical measures of goodness-of-fit and by analysis of residuals. Good agreement was found between observed atypical profiles values and fitted values obtained with the two biphasic models, and both can revert to a simple Mitscherlich allowing them to describe typical monophasic profiles. The models contain kinetic fermentation parameters that can be used in conjunction with substrate degradability information and digesta passage rate to calculate extent of substrate degradation in the rumen or hindgut. Thus, models link the in vitro gas production technique to nutrient supply in the animal by providing information relating to digestion and nutritive value of feedstuffs.
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Ruminants contribute to the emissions of greenhouse gases, in particular methane, due to the microbial anaerobic fermentation of feed in the rumen. The rumen simulation technique was used to investigate the effects of the addition of different supplemental plant oils to a high concentrate diet on ruminal fermentation and microbial community composition. The control (CTR) diet was a high-concentrate total mixed ration with no supplemental oil. The other experimental diets were supplemented with olive (OLV), sunflower (SFL) or linseed (LNS) oils at 6%. Rumen digesta was used to inoculate the fermenters, and four fermentation units were used per treatment. Fermentation end-products, extent of feed degradation and composition of the microbial community (qPCR) in digesta were determined. Compared with the CTR diet, the addition of plant oils had no significant (P > 0.05) effect on ruminal pH, substrate degradation, total volatile fatty acids or microbial protein synthesis. Gas production from the fermentation of starch or cellulose were decreased by oil supplementation. Methane production was reduced by 21-28% (P < 0.001), propionate production was increased (P < 0.01), and butyrate and ammonia outputs and the acetate to propionate ratio were decreased (P < 0.001) with oil-supplemented diets. Addition of 6% OLV and LNS reduced (P < 0.05) copy numbers of total bacteria relative to the control. In conclusion, the supplementation of ruminant diets with plant oils, in particular from sunflower or linseed, causes some favorable effects on the fermentation processes. The addition of vegetable oils to ruminant mixed rations will reduce methane production increasing the formation of propionic acid without affecting the digestion of feed in the rumen. Adding vegetable fats to ruminant diets seems to be a suitable approach to decrease methane emissions, a relevant cleaner effect that may contribute to alleviate the environmental impact of ruminant production.
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Anaerobiose/efeitos dos fármacos , Fermentação/efeitos dos fármacos , Metano/metabolismo , Microbiota/efeitos dos fármacos , Óleos de Plantas/metabolismo , Rúmen/efeitos dos fármacos , Amônia/metabolismo , Animais , Dieta/métodos , Fibras na Dieta/metabolismo , Suplementos Nutricionais , Digestão/efeitos dos fármacos , Ácidos Graxos Voláteis/metabolismo , Propionatos/metabolismo , Rúmen/metabolismo , Rúmen/microbiologia , Ovinos/metabolismoRESUMO
Lipid supplementation of ruminant diets may trigger changes in the ruminal microbiota and in anaerobic digestion. Changes in the bacterial community composition and in the fatty acid hydrogenation caused by the addition of different supplemental plant oils to a high concentrate diet were investigated in vitro using RUSITEC (rumen simulation technique) fermenters. The control (CTR) diet was a high-concentrate total mixed ration for dairy sheep, with no supplementary oil. The other experimental diets were supplemented with olive (OLV), sunflower (SFL) or linseed (LNS) oils at 6% (dry matter basis). Four RUSITEC fermenters were used for each experimental diet, all inoculated with rumen digesta of sheep. Extent of dry matter and fat degradation, composition of the bacterial community and long-chain fatty acids in digesta were determined. The addition of plant oils increased (P < 0.001) apparent degradation of fat in the fermenters, whereas fermentation kinetics (gas production and average fermentation rate) were lower (P < 0.05) with the LNS than with the CTR diet. Hydrogenation of C18 unsaturated fatty acids (P < 0.05), in particular that of oleic acid (P < 0.001), and stearic acid proportion (P < 0.001) were reduced, and oleic acid proportion was increased (P < 0.001) with all oil supplements. Addition of OLV decreased linoleic and LNS increased α-linolenic (P < 0.001), whereas conjugated linoleic was increased with SFL oil (P = 0.025) and vaccenic increased with both SFL and LNS oils (P = 0.008). Addition of 6% OLV and LNS reduced (P < 0.05) microbial community diversity and quantity of total bacteria relative to the control. Some specific microbial groups were affected (P < 0.001) by oil addition, with less relative abundance of Clostridiales and Actinobacteria and increased Bacteroidales, Aeromonadales and Lactobacillales species. In conclusion, the supplementation of high-concentrate ruminant diets with plant oils, in particular from sunflower or linseed, causes shifts in the rumen microbiota and fatty acid hydrogenation in the rumen increasing the formation of vaccenic and conjugated linoleic acids.
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Suplementos Nutricionais , Ácidos Graxos/metabolismo , Fermentação , Microbiota , Óleos de Plantas , Rúmen/microbiologia , Ração Animal/análise , Animais , Técnicas Bacteriológicas , Metagenômica/métodosRESUMO
Thirty-six Assaf male lambs (29.4 ± 3.10 kg body weight (BW)) were used to study the feasibility of including urea (at 0, 0.6 or 0.95% of dry matter for Control, Urea1, and Urea2 diets, respectively) in substitution of soybean meal in fattening diets. Animals were individually penned and feed intake was recorded daily. Blood samples were taken at days 35 and 63 of the experimental period to determine the acid-base status and the biochemical profile. At the end of the experiment (nine weeks), lambs were slaughtered, ruminal contents were collected and carcass and meat quality were evaluated. There were not differences (p > 0.05) among treatments in dry matter intake, animal performance, ruminal fermentation pattern, and carcass and meat parameters. Serum albumin concentration was higher and concentration of HCO3 and total CO2 in blood were lower in Urea2 compared to Urea1 and Control lambs. These results, together with the tendency to lower (p = 0.065) blood pH in this group might suggest a moderate metabolic acidosis. Partial replacement of soybean meal with urea did not impair growth rate in heavy fattening Assaf lambs (from 29 to 50 kg body weight), reduced feeding costs and had no adverse effects on feed efficiency, rumen fermentation and carcass and meat quality.
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The nutritive value of 26 agro-industrial by-products was assessed from their chemical composition, in vitro digestibility and rumen fermentation kinetics. By-products from sugar beet, grape, olive tree, almond, broccoli, lettuce, asparagus, green bean, artichoke, peas, broad beans, tomato, pepper, apple pomace and citrus were evaluated. Chemical composition, in vitro digestibility and fermentation kinetics varied largely across the by-products. Data were subjected to multivariate and principal component analyses (PCA). According to a multivariate cluster analysis chart, samples formed four distinctive groups (A-D). Less degradable by-products were olive tree leaves, pepper skins and grape seeds (group A); whereas the more degradable ones were sugar beet, orange, lemon and clementine pulps (group D). In the PCA plot, component 1 segregated samples of groups A and B from those of groups C and D. Considering the large variability among by-products, most of them can be regarded as potential ingredients in ruminant rations. Depending on the characteristic nutritive value of each by-product, these feedstuffs can provide alternative sources of energy (e.g., citrus pulps), protein (e.g., asparagus rinds), soluble fibre (e.g., sugar beet pulp) or less digestible roughage (e.g., grape seeds or pepper skin).
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The objective of the present study is to examine the effect of yeast (Saccharomyces cerevisiae) on reduction of methane (CH4) production in dairy and beef cattle using meta-analytic methods. After compilation of relevant scientific publications available from the literature between 1990 and 2016, and applying exclusion and inclusion criteria, meta-analyses of data from dairy and beef cattle were applied for the pooled dataset or for each animal category (dairy or beef). The results of meta-analysis of all three datasets (all cattle, dairy cattle, or beef cattle) suggested that effect size of yeast either on daily CH4 production or on CH4 production per dry matter intake (CH4/DMI) was not significant. The results of Q test and I2 statistic suggest that there is no heterogeneity between different studies on CH4 production and CH4/DMI. The results of meta-analysis suggest that use of yeast (Saccharomyces cerevisiae) as feed additive does not offer significant results in terms of reduction of CH4 production in dairy and beef cattle. Further research on the effects of different doses of yeast, use of yeast products, different strains, and experimental designs is warranted to elucidate the effects of yeasts on methane production in the rumen.
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Ração Animal/microbiologia , Metano/biossíntese , Rúmen/metabolismo , Saccharomyces cerevisiae , Animais , Bovinos , Indústria de Laticínios , Feminino , Probióticos/farmacologia , Carne VermelhaRESUMO
Two models were derived to describe fish growth while accounting for the effects of fluctuating water temperatures. The models were initially expressed in a rate:state form and subsequently integrated resulting in two analytical solutions, representing two distinct types of growth: exponential (Model 1) and asymptotic (Model 2). Both models share the assumptions that growth machinery works at a rate which varies with water temperature and that growth is irreversible. In addition, in Model 1 it is assumed that quantity of growth machinery is proportional to live body weight and substrate is non-limiting over the period of growth; whereas Model 2 is based on the assumption that quantity of growth machinery is proportional to available substrate. Effects of seasonal variations in water temperature on fish growth are represented in both models by a sinusoidal function. The potential of these models was investigated through their ability to describe growth in eight datasets encompassing three species: European bullhead (Cottus gobio), brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss). Models were evaluated using statistical measures of goodness-of-fit and through the analysis of residuals. Of the eight datasets, six displayed asymptotic growth while the other two exhibited exponential growth. Both models yield suitable simple growth functions with acceptable goodness-of-fit to fish growth curves under fluctuating water temperatures. However, Model 1, representing exponential growth, shows limited ability to predict fish size (length) when growth curves follow a clear asymptotic trend. This study enforces the idea that a given model is not always superior to another and that data structure and underlying model assumptions must be considered in model selection.