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An experiment was conducted to determine the effects of prebiotic on growth performance and coccidiosis prevention in challenged broilers with Eimeria. A total of 420 1-d-old male Ross 308 chicks were used in a completely randomized design with 7 treatments and 5 replicates with 12 birds in each replication. Dietary treatments were: 1) negative control (without prebiotic and without challenge), 2) positive control (challenged with sporulated oocysts of Eimeria (SOE) without prebiotic), 3) 0.2 % prebiotic in starter, 0.1 % in grower and 0.05 % in finisher challenged with SOE, 4) 0.2 % prebiotic in starter,0.1 % in grower and 0.05 % in finisher without challenge, 5) 0.2 % prebiotic in the whole rearing period challenged with SOE, 6) 0.2 % prebiotic in the whole rearing period without challenge and 7) and Salinomycin (0.05 % of diet). At 7 d of age, treatments were challenged with 20-fold dose of the EIMERIAVAX 4 m as a trivalent live attenuated coccidiosis vaccine. On d 28, intestinal coccidiosis lesions and dropping were scored in the scale of 0-3 and 0-4, respectively, and oocysts per gram feces (OPG) were measured. Prebiotic at either supplementation rate increased body weight gain and improved feed conversion ratio compared with PC group. Challenged broilers fed fixed level of prebiotic displayed lower OPG, dropping scores and coccidiosis lesions scores in upper and middle regions of intestine than PC group, with the effect being similar to unchallenged birds., Competing Interests: Declaration of competing interest The authors report no declarations of interest., (Copyright © 2024. Published by Elsevier Ltd.)

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.

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

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.

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.