Health Care and Expectations for Beef Cattle
Introduction
Beef cattle (including buffaloes) are the 3rd most numerous farmed animals worldwide (afterwards poultry and pigs), with 71.61 meg tonnes produced globally in 2018. In the aforementioned twelvemonth, the European union produced 10.64 million tonnes of beef meat (ane). Globally, cattle meat production has more than than doubled since 1961, increasing from 28 million tonnes per year to 68 million tonnes in 2014 (i). In numerical terms, between 2000 and 2050 the global cattle population might grow from 1.five billion in 2000 to two.six billion (2). Beef cattle farming practices differ essentially across the earth, ranging from all-encompassing to intensive and using dissimilar breeds (3). Each rearing system presents specific challenges for creature welfare (iv–6) and, while guidance on best practice is available for some of the identified problems, knowledge gaps persist, for instance in the areas of affliction prevention and monitoring, optimisation of live send, employ of ecology features, and enrichments (iv). Specific issues are associated to the management, transport and rearing of male calves coming from the dairy industry, which are of limited commercial value (vii).
The science of creature welfare has considerably evolved from the 1990s to the present day, and with information technology the recognition that animals are sentient beings, deserving of "a good life," which includes opportunities to experience positive affective states (8). It is therefore of involvement to investigate if and nether what respects the sustained global increase in cattle product has propelled an interest in researching beefiness cattle welfare. This paper uses text mining (TM) and topic analysis (TA) to analyse the scientific literature on beef cattle welfare published in English language from 1990 until 2019 to ameliorate understand the most of import topics discussed in academic publications and their evolution over time. TM is defined equally "The knowledge discovery process which looks for identifying and analysing useful information on data which is interesting to users from large amounts of textual data" and as such it is unique in its ability to analyse concept relationships "in order to find new structures, patterns or associations" and to "discover new facts and trends about the world itself" (9). More in item, TM can exist used to summarise or cluster information into charts or maps; identify hidden structures (and associations) between concepts or groups or concepts; extract hidden associations between textual elements; provide an overview of the contents of a big collection of documents; categorise texts past discovering relevant groupings (ix). In other words, TM and TA represent tools that can produce a preliminary thematic screening of large numbers of documents to reveal a structured "map" of textual noesis (10, 11) by uncovering recurrent topics and latent themes when the prepare of documents to analyse is large. For these reasons, TM is increasingly being used in the scientific literature every bit a tool to identify themes and future research avenues beyond a broad range of topics, including animal welfare studies (12, 13).
Materials and Methods
Data Gear up
A literature search protocol was set upward to identify peer-reviewed papers with at least an English abstract that covered the topic of beef cattle welfare using Scopus®, the abstracts and citation database of Elsevier©. The keywords used were "bovine meat welfare," "meat cattle welfare," "veal welfare," "beefiness welfare," "beef cattle welfare," and "heifer welfare." The search was performed in January 2020. The initial timespan considered was between 1960 and 2019. Every bit less than one relevant paper per year was published in the menstruation 1960–1989, only papers published from 1990 onwards were retained for the full statistical analysis. An electronic Excel workbook was used to collect the data extracted from the identified papers. The spreadsheet was built in a 2-way table format considering every newspaper (record) as a row and its descriptive information in columns. A listing of the descriptors used and additional information on data format are provided as Supplementary Materials. All datasets were merged and overlapping records were erased. Reasons for automated exclusion were: no author bachelor, no source available, document type erratum, no document blazon bachelor. Additionally, two reviewers (EN and BC) independently screened the titles and abstracts for relevance to the research topic (i.e., papers dealing with i or more aspects of beef cattle welfare). The criteria for manual exclusion of the papers were (i) wrong topic or focus (for instance, social and economic welfare) or (two) incorrect species or sector (eastward.g., welfare of dairy cattle). Citations were excluded from the database if one or both criteria for exclusion were chosen by both reviewers for the same paper. Disagreements were resolved by consensus with the mediation of FG. The geographical localisation of each record was derived based on the affiliation of the respective author/showtime author. Some descriptive statistics of the selected records were prepared to profile the scientific corpus based on information recorded from the Scopus database. A regression analysis of the number of published papers on years was performed to summate the trend past year of the scientific involvement for this topic.
Text Mining
A TM analysis was performed on the abstracts of the selected papers to find important patterns in text information as described by Wang et al. (ten) and Contiero et al. (12). This technique converts text into numeric information and highlights the word frequency distributions. The text pre-processing consisted in three steps: tokenisation, filtering and stemming (14). Tokenisation is the process of finding words, separating them and reducing them to lowercase. Filtering is likewise called stop-discussion removal (exclusion of characters such every bit punctuation and blanks, exclusion of stop words such every bit manufactures, prepositions, and conjunctions, etc.). Stemming reduces word variants to their root form and we used Porter stemming algorithm to perform this characteristic (fifteen). In addition, keywords used in the bibliographic search were removed to avoid poor discriminative information due to their presence in almost all abstracts retrieved (10). The words were organised into a matrix that contains the documents along the rows and the terms along the columns (so-called certificate-term matrix). A term frequency-changed document frequency technique (TFIDF) was used to attribute a relative weight to words (16). This represents the frequency of a term adjusted for how widely it is used, thus reflecting how of import a word is in the whole collection of documents. The words with the greatest relevance (TFIDF ≥ eight) were represented as histogram. A cloud of the nigh relevant words (TFIDF≥5) was also created (https://www.wordclouds.com/) in which a bigger character size indicates a higher TF-IDF value. The statistical analysis was conducted with R package (2017) using the libraries tm, stringr, and SnowballC.
Topic Modelling
Topic modelling is a tool to uncover the structure of meaningful themes among collections of documents too as to notice hidden textual patterns [something similar to a principal component assay of a given dataset of words; (17)]. Latent Dirichlet allocation (LDA), one of the most pop approaches to perform topic modelling analysis, was practical for the text mining of our abstract corpus (10). A unmarried topic tin can be described as a multinomial distribution of words, and a single document can be described as a multinomial distribution of latent topics. This model provides both a topic representation of all the documents and the give-and-take distributions of all the topics, in an iterative process implemented using a Gibbs sampling. At the end of the iterative procedure, a posterior distribution was calculated to judge the topic mixture of each document (by counting the proportion of words assigned to each topic inside that document) and the words associated to each topic (by counting the proportion of words assigned to each topic overall). We used LDA function with Gibbs sampling option of the topicmodels package in R (xviii). The individual topics were presented every bit an unstructured set of words using the bar histogram representation, where every bar relative to every give-and-take is proportional to the probability of the word within a topic (beta value). The cumulative probability of the 10 about probable words for dissimilar numbers of topics was calculated.
The number of topics needs to be stock-still a-priori. As the "ideal" number is in general non known, several models with unlike number of topics were fitted and measures of evaluation were calculated. In a outset approach, the perplexity of holdout and training datasets was calculated. Perplexity measures how well a probability model predicts a sample. A lower perplexity score indicates better generalization performance (19). The document-term matrix was split in two parts: the kickoff one, which included 80% of the documents, was used as grooming dataset and the last i as test dataset (hold-out set). For dissimilar numbers of topics (from 2 to xx) LDA models were fitted on the grooming dataset. Using the results obtained in the training dataset, the perplexity index was calculated both for the preparation and the holdout datasets. This machine learning approach permits to test the adequacy of a model developed in a training dataset measuring its performance on an hold-out dataset. A second arroyo to set the number of topics is based on the harmonic mean of the likelihood of a ready of samples generated by the Gibbs sampler (twenty). In this case a college value of the harmonic mean is better. A hierarchical cluster analysis approach was adopted for the topics analyses with dissimilar number of topics. The topic-word matrix (showtime 100 about probable words) was transformed to binary data with a one/0 to point presence of a word in a given topic. Finally, a tendency assay of the proportion of each topic by year was performed to test the dynamics of all topics over fourth dimension.
To explore the relationship betwixt topics, we performed hierarchical clustering analysis. The results are presented as Supplementary Materials.
Results
Descriptive Statistics
The distribution of the results of the initial bibliographic search past string on titles, abstracts, and keywords is shown in Tabular array i. The nearly numerous articles concerned the cord "beefiness welfare" (81%), followed by "beefiness cattle welfare" (60%), "meat cattle welfare" (41%), "heifer welfare" (30%), "bovine meat welfare" (15%) and, lastly, "veal welfare" (xi%). Subsequently removal of overlapping records and transmission removal of irrelevant ones, 983 records were retained for further analysis.
Table 1. Bibliographic search strings for the text mining assay on the welfare of beef cattle carried out on titles, abstracts and keywords of peer-reviewed literature in English published between 1990 and 2019.
Looking at the trend for the number of papers per publication year, from 1990 to 1996 fewer than x papers on beef cattle welfare were published annually, whereas from 1996 to 2019 there was a significant increase of 3 papers per year (interpolation of information using a regression assay from 1990 to 2019: y = 3.28x-6529 R 2=0.85; Figure 1).
Effigy one. Peer-reviewed articles on the welfare of beef cattle published within the period 1990–2019. From 1996 onwards at that place was a significant increase in the number of papers published annually (past interpolation: 3/yr).
Nearly half of the identified papers had first or respective authors based in Europe (members of the European Economic Area and Switzerland; 46%). The second about important surface area of provenance of authors was North America (25%), followed past Due south America (eleven%), Oceania (9%), Asia (6%) and, lastly, Africa (3%).
A breakdown of articles per land of the European block is shown in Figure 2.
Figure two. Distribution by European country of peer-reviewed papers on the welfare of beef cattle based on the nationality of the first/corresponding authors and published between 1990 and 2019.
The distribution of published papers by periodical championship (with at to the lowest degree 10 papers published on the topic in the period considered) is shown in Figure iii. The most frequent publishing sources of the retained papers were scientific journals dealing with animal (production) science, brute welfare and behaviour, and meat quality, whereas the journals focused on veterinary science were a less important publishing channel (fifteen%).
Figure 3. Distribution of published papers by journal title (with at least x papers published on the topic in the period considered). The most frequent publishing sources of the retained papers were scientific journals dealing with animal (production) scientific discipline, creature welfare and behaviour, and meat quality, whereas the journals focused on veterinary science were a less important publishing aqueduct (15%).
Research articles represented the well-nigh common type of retained newspaper (76%) followed by reviews (13%), briefing papers (6%), and others (5%). The papers were published in 310 scientific journals. Every bit a whole, the 983 articles had nerveless—as of January 2020—a full of 15,208 citations. The about cited commodity was published in 2004, collecting 392 citations, followed by an commodity published in 2010 that collected 235 citations.
Text Mining Results
Text mining analysis was performed to identify the most important words of the information corpus. The pre-processing of the data produced 106,108 words and afterward reduction of sparseness (exclusion of the "rare words") 1,490 terms were retained from the selected 983 documents. The most relevant words co-ordinate to the TFIDF ponderation system (TFIDF≥5) are represented in Figure 4 as a deject in which the size of the font is proportional to the TFIDF of every word. Looking at the first x word stems, the most of import was calv- (TFIDF=eighteen.4), followed by transport (TFIDF=13.eight), product (TFIDF=12.3), slaughter (TFIDF=11.vi), system and farm (TFIDF=ten.7), consum- (TFIDF=ten.5), stun- (TFIDF=ten.ane), castrat- (9.ix), and behaviour (9.six).
Figure four. Deject representation of the most relevant words (stems) in the database (TFIDF≥5). The relative importance of the terms is reflected by their size.
Topic Visualisation
We created a visualisation (histograms) of the ten near probable words of the topics in LDA taking into account 5, ten, xv and twenty topics, respectively. The cumulative probability of the ten about frequent words for LDA with five topics was smaller than that for LDA with 10, 15 and xx topics. The boilerplate cumulative probability of the x most frequent words was 0.xix, 0.26, 0.31, and 0.35 for 5, 10, 15, and 20 topics, respectively. This is considering if a small number of topics is assumed, a few words may not convey a topic meaning sufficiently and different issues will exist lumped together (10). By expanding the number of topics assumed information technology is possible to find boosted themes. We tried several approaches to select an optimal number of topics. The get-go was based on the calculation of the perplexity alphabetize for a grooming and a test dataset, respectively (19). A 2nd approach was based on the harmonic means of the likelihood of different models obtained with different number of topics (20). The results of these 2 approaches are shown in Figure five.
Figure 5. (A) Perplexity index of preparation (green) and exam (cerise) datasets for different number of topics. (B) Harmonic mean of the likelihood of a gear up of samples generated by the Gibbs sampler.
Every bit expected (Figure 5A), the perplexity of the training dataset was lower than the one calculated for the examination fix. Both curves decreased as the number of topics increased. In Figure 5B the harmonic means was instead increasing. No local minimum or maximum were found for perplexity or harmonic means. The two functions were monotonically decreasing or increasing, respectively, according to the increasing number of topics. Therefore, no clear suggestion on the ideal number of topics could be derived from these analyses.
Lastly, we considered the hierarchical clustering of the topics obtained with 5, ten, fifteen and 20 topics. The within-form variance component deemed for 89, 96, 96, and 97% of variance, respectively. The maximum increment was accomplished between five and ten topics; a plateau was reached with higher values. This means, in do, that beyond ten topics there was no improvement in the adequacy of the model.
Taking into account the outcomes of these three analyses, nosotros selected the LDA with 15 topics. The ten well-nigh probable words in the xv topics are reported in Figure half-dozen.
Figure six. Histograms representing the well-nigh relevant words per topic in the LDA with fifteen topics (beta=probability that a word belongs to a given topic).
Based on the most relevant words and the papers belonging to each topic, we tentatively attributed a theme to each topic (Table 2). The first three topics per number of papers published under each topic were topic 12 (effects of transport and slaughter on carcass quality), topic 2 (stakeholders' perceptions), and topic 8 (efficiency and environmental sustainability). Topic 4 (food condom and public wellness) closely followed topic viii. The cumulative probabilities (cp) calculated for the ten virtually relevant words in the topics showed that topics 5 (dogie behaviour and management), 8 (efficiency and environmental sustainability) and 12 (effects of transport and slaughter on carcass quality) were the near important statistically (cp = 0.fifty, 0.41 and 0.38, respectively).
Table 2. Topics that emerge from the LDA analysis.
Table three shows the results of the trend analysis for the menstruation 1990 to 2019. For each topic, the percentage of papers published in the considered fourth dimension interval was analysed equally a function of the twelvemonth. The estimated regression coefficient represents the variation (increment/decrease depending on the sign of the coefficient) in the percentage of published papers for each incremental unit of the time. There was a significant increase in the number of papers dealing with topics two (stakeholders' perceptions), seven (gamble factors for health and mortality), 9 (health and welfare of heifers) and 14 (prevention and treatment of common bovine diseases), whereas the numbers of papers published on topic 15 (new economical models) decreased in the considered time frame. Topic 12 (effects of transport and slaughter on carcass quality), although the commencement for number of papers published over time, had a stable trend, whereas topic 2 (stakeholders' perceptions) was the ane showing the most pronounced trend toward increase.
Table 3. Trend analysis of the 15 LDA topics by year (1990–2019).
Discussion
LDA applied to academic papers on beef cattle welfare captured several fields of investigation that are of known relevance, for instance pain relief during invasive procedures, the effects of transport and slaughter, the management of heifers and calves, and the treatment and prevention of illness. This characteristic—beingness able to identify known facts—has been proposed as evidence of the trustworthiness of the text mining algorithms (10). Additionally, the terms "heifer" and "dogie" were included in the search keywords, and the topic analysis recaptured them, which is an indicator of the soundness of the methodology used. LDA modelling also revealed other topics that are of increasing societal involvement, such every bit the link between animal welfare, sustainability and wider market issues, and the attitudes and perceptions of stakeholders such every bit consumers and farmers.
The geographical distribution of the first authors shows that half of the papers had first authors in Europe, followed by the United States. Likewise having a strong focus on scholarly publishing in English, these two geographical areas accept similar beef production data [10.64 million tonnes for the European union vs. 12.22 meg tonnes for the U.s.; (ii)]. Inside the European union, the UK had the highest proportion of first authors, which does not surprise, as the Great britain is the cradle of the farmed animal welfare move in Europe (21, 22) as well every bit being an of import beef producing country. The first x countries with high proportions of first authors are also amidst the main beef producing countries in Europe, with the exception of Switzerland, which even so, just like the United kingdom of great britain and northern ireland, has a long-standing tradition of protecting animal welfare [since 1992, Switzerland has recognised in its constitution the concept of animal dignity as well as animate being well-being; (23)]. Compared to other fields of research, in which Asia (China in detail), Due south America and Oceania are very well-represented in terms of scientific publications, beef cattle welfare literature in English language was less popular.
From 1960 to 1989, our search criteria identified on average less than one relevant paper per twelvemonth published in English on beef cattle welfare. This is non surprising if nosotros consider the history of animal welfare science. As highlighted by Broom (24), in the 1970s and early 1980s the term animal welfare was used but yet non defined, and many considered information technology to be unscientific. Only in the early 1990s did scientists agree that animal welfare is measurable, and hence that information technology is a scientific concept (24). Our results show a steady increase in the number of papers on beef cattle welfare published yearly in English starting from 1996. Considering that cattle numbers worldwide increased in a gradual and consistent way from the 1960s onwards (one), the number of published research papers on beef cattle welfare appears to have been markedly influenced by the evolution of animal welfare science.
The main word stems that emerged from the TDIF analysis were, in descending lodge of importance, "calv-," "transport-," "production-," "slaughter," "system-," "subcontract-," "consum-," "stun-," "castrat-," and "behaviour." Almost of these terms are also included in the get-go three topics identified after LDA analysis, and therefore they volition exist discussed below.
The identified topics are comprehensive equally, besides animate being welfare, they include fauna health and behaviour, meat quality, sustainability, and the social dimension. The assay of cumulative probability identified the three about important topics statistically. The near meaning was "calf behaviour and management" (topic v). The tokenised words belonging to this topic were "calv-, group-, behaviour-, observ-, differ-, calf-, wean-, indic-, studi-, frequenc-." The articles retained in the database reveal a scientific focus on aspects of animal welfare at calving and the optimisation of calf welfare (based on behavioural and physiological indicators) to reduce stress and better growth. Some aspects were common to the literature on beef and dairy cattle, whereas others were specific to each sector. A common attribute is the correct management of difficult calving (dystocia) from the perspective of the health and welfare of both the cow and calf (25, 26). Several studies also assessed weaning stress. The weaning procedure includes handling, a more or less sharp cow-calf separation and, sometimes simultaneously, transportation, sudden changes in the diet, and social reorganisation due to regrouping. All of the events taking place around this stage are sources of stress and potential wellness problems for both beef and dairy calves (27, 28). Cows also experience stress due to separation from their calves at weaning (28–30). Studies assessing methods to reduce stress around weaning typically rely on a mixture of behavioural and physiological indicators to compare the relative benefits of unlike separation strategies (e.g., two-step weaning; (27, 31, 32). Handling and transport also have an effect on stress indicators and growth in beef calves (33). The veal sector presents specific challenges: male dairy calves are typically separated from the cows immediately or 24–48 h after nascence. They are ordinarily housed individually for the offset weeks of life and weaning—the gradual change in nutrition from milk or milk replacers to solid feed—can occur as early as 6 weeks of age. This is in itself a very stressful consequence with potentially long-lasting consequences (34). Enquiry has shown that male dairy calves are given less care and attending than heifer calves due to their lower commercial value (7). Ane determination is that farmers need better data on colostrum feeding government and pain management for these animals. Studies in the database also dealt with the direction of calves kept in grouping housing to better animal welfare and maximise growth (35–37).
The second most important topic identified past the statistical analysis was "efficiency and environmental sustainability" (topic 8). The word stems making up this theme are "product-, organisation-, increase-, organ-, surround-, improv-, effici-, chang-, sustain-, nutrit-." The recurring theme in this group of papers is a recognition that the beefiness industry is nether public scrutiny for several respects (e.thousand., nutrient safety, environmental footprint, animate being welfare) and that several adaptations volition be necessary to address all of these concerns (38, 39). According to the selected literature, such adaptations tin can be maybe achieved past improving production efficiency and meat quality, addressing animal welfare issues, and diversifying rearing systems wherever possible, for example past adopting organic or agro-ecological farming techniques (xl, 41). Achieving and expanding the profitability of "alternative" beef rearing systems depends on a complex coaction of factors. These include market readiness and resource availability (42, 43), applied technical cognition (41, 44), land suitability and availability (45), and whether it is possible to guarantee fauna health and welfare under a range of climatic and geographical conditions (46–48). Remote sensor technology can help in monitoring animal welfare in grazing systems (49, 50).
The third most important topic dealt with "transport, slaughter and carcass quality" (topic 12). The word stems included in this topic are "slaughter, transport, carcass-, stun-, qualiti-, bruis-, load-, handl-, time, loss-." The identified literature reflects a tension between the economically driven pressure to increase slaughter speed on the one hand, and the need to minimise financial losses due to bruising, guarantee meat quality, and protect animal welfare and public health on the other (51). Minimising stress and suffering during the pre-slaughter and slaughter phases is an important component of overall cattle welfare, in part also due to societal expectations almost how food animals should exist killed (52, 53). From an economic perspective, stress and rough treatment during transport, lairage and slaughter can compromise carcass quality (54–56) with consequences that tin even affect the global market price of beef originating from a specific country (57). One of the near studied aspects in this group of papers concerned the effects of send on cattle welfare and meat quality, likewise as potential strategies to mitigate the associated risks (58–60). In effect, the fiscal losses due to rough handling during the pre-slaughter phase tin be significant (61). In the slaughter phase, stun quality is important to ensure that animals do not regain consciousness until death (62); to reduce health and safe risks for slaughter-house operators (63); to preserve meat quality, as incorrect stunning causes a surge in blood cortisol and the secretion of heat shock proteins (64). Non-stun slaughter presents specific challenges for animal welfare, such as fourth dimension to loss of consciousness later on the neck cut (65). Some papers investigated ante- and post-mortem animal-based indicators to assess and improve animal welfare on subcontract and during transport (66, 67).
Although not included in the first three about statistically relevant topics, "castrat-" was among the first ten most important word stems co-ordinate to the TFIDF analysis and is included in Topic iii ("hurting management"). The castration of male person calves or mature bulls is a mutual practice in many parts of the world and is carried out to facilitate management and preclude unwanted breeding (68). Castration tin exist carried out upon arrival at the feedlot (69), in some cases together with other painful procedures [eastward.m., dehorning, branding (seventy)]. Physiological and behavioural indicators of inflammation and hurting tin can last for days or weeks depending on the method and historic period of the beast at the time of castration (71, 72). The legal requirements on the provision of hurting relief during castration and other painful procedures differ by geographical region and even by country. However, there is increasing awareness on this topic and veterinary codes of practice equally well as some manufacture guidelines increasingly recommend the use of amazement and/or analgesia, especially when castrating older animals [see (73–75) for some examples]. Research papers on castration included in Topic 3 focused on the availability and potential effectiveness of methods to reduce or eliminate the acute and chronic pain associated with this procedure (69, 76–78). A painless alternative such as immunisation confronting GnRF (gonadotropin-releasing factor) could be a viable pick according to some studies (79, 80). With a view to acknowledging scientific evidence on the astute and chronic pain acquired by routine invasive husbandry practices, and to encounter societal expectations on the upstanding handling of farmed animals, some authors have proposed a "3S" approach ("suppress, substitute, soothe"), which is the equivalent of the "3R" ("reduce, supersede, refine") principle for animals used in inquiry (81).
Another interesting attribute that emerged from this written report is the development of different topics over time. Topic n. 2 ("stakeholders' perceptions") showed the most pronounced upward tendency throughout the years. This topic deals with the attitudes, behavior, expectations and preferences of unlike stakeholders (citizens/consumers, veterinarians, farmers, etc.) toward animal welfare and other attributes of beef meat. Such aspects have important implications for the treatment of animals on the ane hand, and for the market on the other, since they influence purchase decisions. Consumers' perceptions of the beef cattle industry—and the livestock industry at large—are constantly changing and can influence willingness to pay for meat produced and marketed in certain ways (82–84). At the same time, farmers' perceptions and beliefs can accept a profound affect on their behaviour, and thus also on animal welfare (85, 86). The same applies to cattle veterinarians (87, 88) and hauliers (89).
The 2d topic showing the most significant upward trend in terms of papers published was n. 7 ("risk factors for morbidity and bloodshed"). Papers in this thematic grouping deal with risk factors for wellness and mortality in all categories of beef cattle. They are all quite recent, dating from 2002 onwards. The topics that feature virtually prominently in this thematic group are (a) antimicrobial use and resistance and (b) calf health, with particular reference to factors affecting morbidity and early on mortality. The ii topics are interdependent: veal calves are typically transported to specialised fattening facilities when nevertheless unweaned, sometimes passing via auction markets, and often with insufficient passive immunity (90). Transport over long distances, lairage and handling at auctions, and mixing upon arrival at the fattening facility are all health and welfare challenges (90, 91). Every bit a result, morbidity, mortality and antimicrobial use are yet high in the veal sector, and solutions are needed to ameliorate the wellness and welfare of veal calves, likewise in light of the global fight against antimicrobial resistance (92–94). Other papers deal with mortality rates in cow-calf and beef fattening operations (95–97). The trend for an increase in the number of publications on these topics is very pronounced, showing a growing interest in improving animal health and welfare also as a ways to protect public wellness.
Text mining with LDA is a methodology that enables researchers to have a proficient overview of the current state of a given domain or topic and provide indications for farther research if relevant, especially when the number of documents to consider is large (10). Even so, two important limitations of our report are that the document option was restricted to peer-reviewed inquiry (Scopus) and to articles written in English or having at least an abstract in English. The selection of Scopus was based on the fact that it is a citational bibliometric database comprising a greater number of scientific journals compared to other databases. However, one limitation of Scopus is that it does non include grayness literature, which could have been an interesting source of additional information. Concerning the literature in English, by including in our search criteria all relevant papers with at to the lowest degree an abstract in English, nosotros managed to cover a broad geographical range for our research. However, as already mentioned in the results, geographical areas that normally have a skilful scientific output in English for other disciplines were less represented in our database. For instance, papers with a offset author located in South America, where beef production is economically and numerically important, represent 11% of our database. Still, due to the specific challenges associated to the rearing, handling, transport, and slaughter of beef cattle in that geographical surface area, it is plausible that text mining on papers written in Spanish and Portuguese, besides equally in other languages (due east.g., German, Chinese, etc.), volition reveal different trends and topics. For this reason, an analysis of non-English literature on beef cattle welfare certainly merits to exist carried out.
Based on the analysis of the top ten word stems, the virtually of import topics statistically, and the emerging trends, 2 considerations can exist made. The first i is that beast welfare is now perceived every bit an of import component of beef cattle management, and one that can have a positive affect on animal and human health. This is perfectly in line with the OneHealth framework, especially concerning the global fight against antimicrobial resistance (98). The second consideration is that, based on our TM analysis of the literature in English, it would announced that research on beefiness cattle welfare is increasingly addressing wider societal concerns that, admitting to a variable extent, are office of contemporary global policy discussions on livestock farming. Such concerns include nearly notably ecology sustainability, but as well production efficiency, painful husbandry procedures, as well as the attitudes of diverse stakeholders toward beef cattle farming.
Conclusions
Our LDA topic analysis of scholarly articles on beef cattle welfare published in English between 1990 and 2019 shows an increasing scrutiny into the wellness and welfare of calves, including behavioural aspects. There is likewise a growing interest in sustainability issues and organic farming practices. Brute welfare during pre-slaughter and stunning, especially during transport, has an affect on meat quality and is therefore also an of import research topic. In this specific case, in that location is a articulate convergence of interest betwixt fiscal gains and improved cattle welfare in the pre-slaughter and slaughter phases. The results indicate a item focus on the welfare of calves, particularly in the veal industry. Research is besides increasingly assessing aspects of beefiness cattle welfare that are interlinked to meat quality, the social and environmental sustainability of the sector in relation to market opportunities, and public health. The upshot of pain relief during castration featured prominently and is probable to become increasingly important as societal scrutiny into the upstanding treatment of farmed animals converges with the scientific show on the acute and chronic painfulness of routine husbandry practices. The topic showing the virtually meaning increase in popularity in the scientific literature on beef cattle welfare had to practise with attitudes of consumers, farmers, and other stakeholders in the beef supply chain and their role in driving college welfare practices and market opportunities. Another cluster of topics that has shown a marked increment in the literature since 2002 has to do with run a risk factors for morbidity and mortality, in detail in relation to the high use of antimicrobials in veal calf fattening facilities, which should be reduced by amend addressing certain calf health and welfare issues. Although in some cases the focus is all the same on creature wellness and production parameters such as meat quality, our analysis shows that research on beef cattle welfare is increasingly incorporating and analysing environmental and societal topics that are relevant for the evolution of future local and global policies on livestock productions. The identified topics represent a bones source of information that tin can exist used for further and more detailed analyses (e.thousand., systematic reviews) focussed on specific enquiry themes or geographical areas.
Information Availability Statement
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the respective author/southward.
Author Contributions
EN, FG, and GC contributed to the conceptualisation and methodology of the original draft. BC performed the formal assay. EN, BC, FG, and GC contributed to writing, reviewing, and editing the manuscript.
Conflict of Involvement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of involvement.
Acknowledgments
The authors wish to thank Reineke Hameleers for her insightful comments and suggestions on the commencement typhoon of the article.
Supplementary Material
The Supplementary Material for this commodity can be plant online at: https://www.frontiersin.org/articles/10.3389/fvets.2020.588749/total#supplementary-material
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