Lima, Eliana
(2020)
A data driven approach to the evaluation of ewe, lamb, flock and farmer factors that influence productivity of UK sheep farms.
PhD thesis, University of Nottingham.
Abstract
In light of current concerns about the environmental and economic sustainability of livestock production, a clear understanding of the best husbandry strategies and drivers of animal productivity is paramount. In the United Kingdom (UK) alone there are 17 million breeding sheep, representing an important share of the total ruminant population; however, there is no baseline information on the most common sheep husbandry practices or which factors make an enterprise most productive. In this context, this thesis aimed at expanding the current knowledge on the most common management strategies implemented by UK sheep farmers, and at comparing the productivity levels across farms, to gain an understanding of the factors and practices related to enterprise production. Since the growth of lambs greatly influences the productivity of a flock, a further objective was to explore in detail the role of disease on lamb growth. Furthermore, because flock recording practices were hypothesised to have a positive influence on productivity, an additional aim of this work was to explore the factors behind adoption of technology on sheep farms for recording of animal information.
This thesis is structured into seven Chapters. Chapter 1 provides background information on the whole project and defines the objectives of the research. Chapter 2 provides a detailed review of the statistical and modelling methods used, as well as the types of data available. Chapters 3 to 6 present the main results of this research, which are summarised below and Chapter 7 comprises a discussion of the wider relevance of the results.
Chapter 3 presents the results corresponding to the first objective of this thesis, which was to evaluate husbandry with an influence on productivity at flock level, with a special emphasis on disease control practices. A questionnaire focusing on farm characteristics, general husbandry and flock health management was carried out in 648 farms located in the UK over summer 2016. Abattoir sales data (lamb sales over 12 months) was compared with the number of breeding ewes on farm to estimate flock productivity (number of lambs sold for meat per 100 ewes per farm per year). The results of a multivariable linear regression model, conducted on 615 farms with complete data, indicated that farms vaccinating ewes against abortion and clostridial agents and administering a group 4 or 5 anthelmintic to ewes (as recommended by the Sustainable Control of Parasites in Sheep Initiative) during quarantining, had a greater flock productivity than farms not implementing these. Flocks with maternal breed types had higher productivity indices (number of lambs sold for meat per 100 ewes per farm per year) compared with flocks with either pure hill or terminal breeds, and farms weighing lambs during lactation had greater productivity than those not weighing. Importantly, these actions were associated with other disease control practices, for example, treating individual lame ewes with an antibiotic injection, and carrying out faecal egg counts as well as weaning lambs between 13 and 15 weeks of age suggesting that an increase in productivity may be associated with the combined effect of these factors. This study provided new evidence on the positive relationship between sheep flock performance and disease control measures and demonstrated that lamb sales data can be used as a baseline source of information on flock performance and for farm benchmarking.
The first objective of this thesis was further addressed with a complementary study to investigate additional factors (related to flock nutrition, grassland management and animal selection) with a relationship to flock productivity, defined in this case as financial lamb-derived revenue. The results of this study are presented in Chapter 4. From a population of 830 sheep farms, 408 farmers completed a detailed online questionnaire comprising over 300 variables. Total lamb-derived revenue was calculated for each farm which included the use of detailed abattoir information on carcass weight and conformation. The median flock size was 560 ewes and median land size 265 acres. The median revenue per acre from lambs sold during the study period (2017) was £197 (IQR=120-296) and median revenue per ewe £95 (IQR=72-123). A robust analytic approach using regularised (elastic net) regression with bootstrapping was implemented to account for multicollinearity in the data and to reduce the likelihood of model over-fitting. To provide model inference and allow ranking of variables in terms of relevance for follow up intervention studies, both covariate stability and coefficient distributions were evaluated. Factors with high stability and a relatively large positive association with revenue per acre were; increased stocking rate, fertilizer being used on most of the grazing land, the use of rotational grazing, decreased proportion of ewes with prolapses, separation of lame sheep from the rest of the flock, selecting ewes for culling based on prolapses and infertility, conducting body condition scoring of at least the majority of ewes in the flock at lambing, early lactation or weaning, increased farmer education and farmers with a positive business attitude. Additional factors with a high stability and relatively large associations with increased revenue per ewe were; never trimming diseased feet of lame ewes and keeping good farm records. This appears to be the first study in animal health epidemiology to use bootstrapped regularised regression to evaluate a wide dataset to provide a ranking of the importance of explanatory covariates. From a wide dataset, this enabled identification of a relatively small set of variables with a potentially large influence on lamb-derived revenue which can be considered prime candidates for future intervention studies.
The second objective of this project was to gain a better understanding of the role of lamb and ewe factors on lamb growth, with a special emphasis on the impact of disease cases. The corresponding results are presented in Chapter 5. The primary aim of this study was to use longitudinal data to quantify the simultaneous effects of multiple ewe and lamb factors on lamb growth rate; a secondary aim was to evaluate model structures that specifically account for lamb grouping effects during the growth period and compare these to classical hierarchical growth rate models. A total of 4172 weight recordings from 805 lambs and data on disease events were collected over a 6-month period from a commercial pedigree sheep flock. Three mixed model structures were compared, hierarchical, cross classified and multiple membership, and final estimates determined within a Bayesian framework. The multiple membership structure provided the best model fit and was used for final inference; taking account of the effect of lamb grouping over time provided the best estimates of lamb growth rate. Ewe lameness and mastitis cases had a deleterious impact on lamb growth. Lambs from ewes identified with mastitis during lactation were on average 3.0 kg lighter during the four month growth period than lambs from unaffected ewes. Lambs from ewes that were not lame during pregnancy were 3.0 kg heavier at eight weeks of age than lambs from ewes with a least one lameness case during the same period. Lambs from ewes lame either during the first 4 weeks or between 4-8 weeks of a lamb’s life (but not lame during pregnancy) were also significantly heavier at 56 days of age, than lambs reared by ewes that were lame during pregnancy (2.8 and 3.3 kg respectively). Cases of pneumonia and bacterial arthritis in lambs had a significant negative impact on lamb growth with affected lambs being on average 5.5 kg and 2.2 kg less than non-affected lambs respectively after the disease event. Prior to a case of lameness or pneumonia, lambs were significantly heavier than unaffected lambs suggesting a possible trade-off between growth and immune function. Overall, the study provided evidence that a combination of ewe and lamb characteristics and disease events play an important role in determining lamb growth rate and that heavier lambs may be more susceptible to disease.
The last objective of this thesis was to enhance the understanding of factors that influence the use of tools for recording of animal information on sheep farms, and to evaluate the impact of both farmer characteristics and attitudes towards flock recording technology. The results of the first chapters of this thesis indicated that farmers with greater levels of flock productivity were carrying out more recording practices. The fact that individual electronic identification is mandatory in all adult sheep presents a great opportunity for more frequent and accurate recording on farms. The use of technologies such as Electronic Identification (EID) aid recording of individual animal specific information, but anecdotal evidence suggests they are not widely used. The aim of this study was to assess uptake of EID technology, and explore drivers and barriers of adoption of related tools among English and Welsh farmers, including the influence of farmer attitudes and demographic factors on the uptake decision. In this context, farm beliefs and management practices associated with adoption of this technology were investigated via a questionnaire. A total of 2000 questionnaires were sent, with a response rate of 22%. Among the respondents, 87 had adopted EID tools for recording flock information, 97 intended to adopt it in the future, and 222 had neither adopted it, nor intended adopting it. Exploratory factor analysis (EFA) and multivariable logistic regression modelling were used to identify farmer beliefs and management practices significantly associated with the adoption of EID technology. Exploratory factor analysis identified three factors expressing farmer’s beliefs – usefulness and practicality, and external pressure and negative feelings. These results suggest that farmer beliefs play a significant role in technology uptake. Interestingly, non-adopters of technology were more likely than adopters to believe that ‘government pressurise farmers to adopt technology’. In contrast, adopters were significantly more likely than non-adopters to see EID as practical and useful. Farmers with higher information technology literacy and intending to intensify production in the future were significantly more likely to adopt EID technology. Importantly, flocks managed with EID tools had significantly lower farmer- reported flock lameness levels. These findings bring insights on the dynamics of adoption of EID tools and suggest that communicating evidence of the positive effects EID tools on flock performance and strengthening farmer’s capability in use of technology are likely to enhance the uptake of this technology in sheep farms.
The application of a wide range of modelling methods, such as traditional linear regression, logistic regression, multilevel (mixed effect) modelling and regularised regression combined with rich cross-sectional and longitudinal datasets, have allowed the identification of a range of factors associated with productivity on UK sheep farms. From the factors identified, those with the greatest effects on productivity at individual and flock levels provide a basis for where future research may be appropriate to ensure the effects are causal. The issue of causality is discussed in Chapter 7 and possible causal pathways hypothesised; next research steps could include conducting randomised controlled trials to evaluate more clearly the impact of specific factors identified in this research on sheep farm productivity.
| Item Type: |
Thesis (University of Nottingham only)
(PhD)
|
| Supervisors: |
Kaler, Jasmeet
Lovatt, Fiona
Davies, Peers
Green, Martin |
| Keywords: |
Sheep husbandry; Lamb growth; Flock recording practices; Disease control; Use of technology |
| Subjects: |
S Agriculture > SF Animal culture |
| Faculties/Schools: |
UK Campuses > Faculty of Medicine and Health Sciences > School of Veterinary Medicine and Science |
| Item ID: |
59596 |
| Depositing User: |
Lima, Eliana
|
| Date Deposited: |
20 Oct 2023 08:15 |
| Last Modified: |
20 Oct 2023 08:15 |
| URI: |
https://eprints.nottingham.ac.uk/id/eprint/59596 |
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