A systematic review of estimation of growth curve in goats

Tropical Animal Health and Production (2024) 56:14 https://doi.org/10.1007/s11250-023-03857-0 REVIEWS A systematic review of estimation of growth curve in goats Ledimo Faith Makgopa1 · Madumetja Cyril Mathapo1 · Thobela Louis Tyasi1 Received: 20 October 2023 / Accepted: 7 December 2023 © The Author(s) 2023 Abstract Growth is an economically important trait in animal production industry and is one of the subjects that can be justified mathematically. The literature recommends different non-linear model to estimate the growth of goats. The objective of this study was to systematically review the literature published on estimation of growth using non-linear models in goats. Databases such as Google Scholar, PubMed, ScienceDirect, and Web of Science were evaluated systematically using the combination of the following key terms: Non-linear growth curve models such as Brody, Richards, Gompertz, Von Bertalanffy, Logistic models. A total of 25 eligible articles were found published between 2008 and 2022 in Bangladesh, Brazil, China, Egypt, Germany, India, Indonesia, Iran, Pakistan, South Africa, Turkey, Tunisia, and Vietnam. The results showed that out of 25 articles, Gompertz growth curve model was the most used (n = 10), followed by Logistic (n = 8), then Brody growth curve model (n = 6). The findings further indicated that Janoscheck growth curve model was the least used model (n = 1) for estimation of growth in goats. One of the limitations is that some of the reviewed articles did not indicate the sex of the animals which make it difficult to draw the conclude for sexes. The systematic review concludes that Gompertz growth curve model is the most recommended for estimation of growth parameters of goats, followed by Logistic, and then Brody. Therefore, researchers should consider using these models when studying growth parameters of goats. Keywords Brody · Richards · Gompertz · Von Bertalanffy · Logistic models Introduction Growth is an economically important trait in animal production industry and is one of the subjects that can be justified mathematically (Waheed et al. 2011). The economic success of a small ruminant production system is influenced by the animal’s fast growth rate which dictate their meat producing potential up to marketing age (Kheirabadi and Rashidi 2019). However, growth parameters of goat are affected by several genetic and non-genetic factors at different age (Gautam et al. 2019). The growth curve parameters of goats can be predicted using non-linear models (Magotra et al. 2021). Brody, Gompertz, Von Bertalanffy, Richards, and Logistic are some of the non-linear models used to estimate biological parameters (Arré et al. 2019). Non-linear models are more preferred than linear models because the growth of an animal has a sigmoidal shape which make them suitable to describe the growth curve of goats (Rashad et al. 2022). Studies have been conducted to distinguish the growth pattern of small ruminants and models that predict weight and age data of animals (Cak et al. 2017; Waiz et al. 2019; de Sousa et al. 2021). However, to the best on our knowledge, there is no comprehensive systematic review on estimation of growth in goats using non-linear growth curve models. Therefore, this study will assist to indicate the best fit non-linear model that can be used to estimate the growth of goats. Hence, the objective of this study was to systematically review the literature published on estimation of growth in goats. The systematically reviewed outcome will provide information that will assist researchers for estimation of growth curve parameters to help goat farmers to implement goat management practices and increase their profit potential. * Thobela Louis Tyasi 1 Department of Agricultural Economics and Animal Production, University of Limpopo, Private Bag X1106, Sovenga, Limpopo 0727, South Africa 13 Vol.:(0123456789) 14 Page 2 of 8 Materials and methods Eligibility criteria Identification of Population, Exposure, and Outcomes (PEO) components of the research question were performed for this systematic review. The “goats” were defined as the population of the study, with the “non-linear growth curve models” as exposure and “recommended non-linear models for estimation of growth curve parameters of goats” as the outcomes. Prior decided to conduct the study, an initial search of the PEO elements on Google Scholar, ScienceDirect, PubMed, and Web of Science was conducted. Search strategy Two investigators (Ledimo Faith Makgopa and Thobela Louis Tyasi) performed a systematic review of articles in the databases such as Google Scholar, PubMed, ScienceDirect and Web of Science, combination of the following key terms: Brody, Richards, Gompertz, Von Bertalanffy, Logistic models. The key terms were combined in various combinations. Only English studies were considered in the study. Tropical Animal Health and Production (2024) 56:14 reached a general agreement regarding all the materials. The articles that met the criteria had: author, year of publication, and type of model. Ethical considerations Plagiarism, misconduct, informed consent, and data manipulation were considered ethical issues by all authors when performing this systematic review. Results Searched results Figure 1 represents the flowchart of the identification and selection of studies for systematic review. In the primary search, a total of 177 articles were retrieved. After excluding 7 duplicate publications, 170 articles remained. The articles were screened for title and abstract, 135 articles were removed since the articles did not have the key combinations and the abstract did not have non-linear growth curve models for growth estimation of goats. About 35 articles were selected for full-text search and eligibility verification, and a total of 25 articles were included in this systematic review. The reason for exclusion of articles is stated in Fig. 1. Inclusion criteria Characteristics of included studies Articles that were present in more than one database were removed before screening for eligibility. The inclusion criteria were articles that evaluated growth patterns of goats using growth curve models, articles that are published in English, and articles used non-linear models for growth curve analysis such as Brody, Richards, Von Bertalanffy, Gompertz and Logistic models were included. Studies that deal with the growth curve of goats, non-linear models for the growth curve of goats, and any articles that deal with the growth patterns of goats were included in the systematic review. A total of 25 articles were accessed and selected as meeting the criteria for inclusion in the review as indicated in Table 1. The results indicated that Das et al. (2016) and Paul et al. (2016) used the same number of goats (n =142) for their studies, in both studies the breed of the goats was not disclosed. The results showed that majority of the goat breed used in the 25 articles were indigeno (...truncated)