Future Farming Systems Group

Edinburgh, United Kingdom

Future Farming Systems Group

Edinburgh, United Kingdom

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Chagunda M.G.G.,Future Farming Systems Group | Gondwe S.R.,University of Malawi
Archiv fur Tierzucht | Year: 2012

Animal performance monitoring is of enormous value for management decision-making at the individual farmer level as well as for the industry and country as a whole. The aim of the study was to develop a performance monitoring tool for existing smallholder dairy production system based on lactation curves. For this purpose three equations of Wood (1967), critical exponential and double exponential were compared to evaluate their fitting and prediction ability. The full data set comprised of 11 481 daily milk records for Holstein-Friesian in various stages of lactation. Data of 84 Holstein-Friesian cows was used to develop lactation curves. Within each lactation, only milk yield from calving until 330 days post-calving were used. The three models were evaluated using three criteria which were the amount of variation accounted for by the model (coefficient of determination), b-value and distribution of residuals. © Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany. the double exponential equation was selected for developing the cow performance monitoring (CPM) curve. The CPM curve was developed based on the mean lactation curve with its confidence interval generating the upper and lower limits. The CPM curve had high prediction rates (sensitivity=93 % and specificity=93 %) hence efficient enough to guide routine management of dairy animals in smallholder farms. © Leibniz Institute for Farm Animal Biology, Dummerstorf, Germany.


Toma L.,Scotland’s Rural College | March M.,Future Farming Systems Group | Stott A.W.,Future Farming Systems Group | Roberts D.J.,Future Farming Systems Group
Journal of Dairy Science | Year: 2013

Agriculture across the globe needs to produce "more with less." Productivity should be increased in a sustainable manner so that the environment is not further degraded, management practices are both socially acceptable and economically favorable, and future generations are not disadvantaged. The objective of this paper was to compare the environmental efficiency of 2 divergent strains of Holstein-Friesian cows across 2 contrasting dairy management systems (grazing and nongrazing) over multiple years and so expose any genetic × environment (G×E) interaction. The models were an extension of the traditional efficiency analysis to account for undesirable outputs (pollutants), and estimate efficiency measures that allow for the asymmetric treatment of desirable outputs (i.e., milk production) and undesirable outputs. Two types of models were estimated, one considering production inputs (land, nitrogen fertilizers, feed, and cows) and the other not, thus allowing the assessment of the effect of inputs by comparing efficiency values and rankings between models. Each model type had 2 versions, one including 2 types of pollutants (greenhouse gas emissions, nitrogen surplus) and the other 3 (greenhouse gas emissions, nitrogen surplus, and phosphorus surplus). Significant differences were found between efficiency scores among the systems. Results indicated no G×E interaction; however, even though the select genetic merit herd consuming a diet with a higher proportion of concentrated feeds was most efficient in the majority of models, cows of the same genetic merit on higher forage diets could be just as efficient. Efficiency scores for the low forage groups were less variable from year to year, which reflected the uniformity of purchased concentrate feeds. The results also indicate that inputs play an important role in the measurement of environmental efficiency of dairy systems and that animal health variables (incidence of udder health disorders and body condition score) have a significant effect on the environmental efficiency of each dairy system. We conclude that traditional narrow measures of performance may not always distinguish dairy farming systems best fitted to future requirements. © 2013 American Dairy Science Association.


March M.D.,Future Farming Systems Group | Toma L.,Land economics and Environment Group | Stott A.W.,Future Farming Systems Group | Roberts D.J.,Future Farming Systems Group
Ecological Indicators | Year: 2016

Increased demand for protein rich nutrition and a limited land capacity combine to create a food supply issue which imposes greater dependence on phosphorus, required for yield maximization in crops for humans, and for animal feeds. To determine the technical and environmental efficiency of diverse milk production systems, this work evaluates the use of phosphorus (P), within confined, conventional grazing, and innovative dairy management regimes across two genetic merits of Holstein Friesian cows, by calculating annual farm gate P budgets and applying a series of common and novel data envelopment analysis (DEA) models. Efficiency results provide an insight into P effective dairy management systems as the DEA models consider P as an environmental pollutant as well as a non-renewable resource. We observe that dairy system efficiency differs, and can depend upon, model emphasis, whether it is the potential for losses to the environment, or the finite nature of P. DEA scores generated by pollutant focused models were wider ranging and, on average, higher for genetically improved animals within housed systems, consuming imported by-product feeds and exporting all manure. However, DEA models which considered P as a non-renewable resource presented a tighter range of efficiency scores across all management regimes and did not always favour cows of improved genetics. Divergent results arising from type of model applied generate questions concerning the importance of model emphasis and offer insight into the sustainability of P use within varied dairy systems. © 2016 Elsevier Ltd. All rights reserved.


Toma L.,Land economics and Environment Group | Stott A.W.,Future Farming Systems Group | Heffernan C.,University of Reading | Ringrose S.,Land economics and Environment Group | Gunn G.J.,Future Farming Systems Group
Preventive Veterinary Medicine | Year: 2013

The paper analyses the impact of a priori determinants of biosecurity behaviour of farmers in Great Britain. We use a dataset collected through a stratified telephone survey of 900 cattle and sheep farmers in Great Britain (400 in England and a further 250 in Wales and Scotland respectively) which took place between 25 March 2010 and 18 June 2010. The survey was stratified by farm type, farm size and region.To test the influence of a priori determinants on biosecurity behaviour we used a behavioural economics method, structural equation modelling (SEM) with observed and latent variables. SEM is a statistical technique for testing and estimating causal relationships amongst variables, some of which may be latent using a combination of statistical data and qualitative causal assumptions.Thirteen latent variables were identified and extracted, expressing the behaviour and the underlying determining factors. The variables were: experience, economic factors, organic certification of farm, membership in a cattle/sheep health scheme, perceived usefulness of biosecurity information sources, knowledge about biosecurity measures, perceived importance of specific biosecurity strategies, perceived effect (on farm business in the past five years) of welfare/health regulation, perceived effect of severe outbreaks of animal diseases, attitudes towards livestock biosecurity, attitudes towards animal welfare, influence on decision to apply biosecurity measures and biosecurity behaviour.The SEM model applied on the Great Britain sample has an adequate fit according to the measures of absolute, incremental and parsimonious fit. The results suggest that farmers' perceived importance of specific biosecurity strategies, organic certification of farm, knowledge about biosecurity measures, attitudes towards animal welfare, perceived usefulness of biosecurity information sources, perceived effect on business during the past five years of severe outbreaks of animal diseases, membership in a cattle/sheep health scheme, attitudes towards livestock biosecurity, influence on decision to apply biosecurity measures, experience and economic factors are significantly influencing behaviour (overall explaining 64% of the variance in behaviour).Three other models were run for the individual regions (England, Scotland and Wales). A smaller number of variables were included in each model to account for the smaller sample sizes. Results show lower but still high levels of variance explained for the individual models (about 40% for each country). The individual models' results are consistent with those of the total sample model. The results might suggest that ways to achieve behavioural change could include ensuring increased access of farmers to biosecurity information and advice sources. © 2012 Elsevier B.V.


Ricci P.,Future Farming Systems Group | Rooke J.A.,Future Farming Systems Group | Nevison I.,Biomathematics and Statistics Scotland | Waterhouse A.,Future Farming Systems Group
Journal of Animal Science | Year: 2013

The prediction of methane outputs from ruminant livestock data at farm, national, and global scales is a vital part of greenhouse gas calculations. The objectives of this work were to quantify the effect of physiological stage (lactating or nonlactating) on predicting methane (CH4) outputs and to illustrate the potential improvement for a beef farming system of using more specific mathematical models to predict CH4 from cattle at different physiological stages and fed different diet types. A meta-analysis was performed on 211 treatment means from 38 studies where CH4, intake, animal, and feed characteristics had been recorded. Additional information such as type of enterprise, diet type, physiological stage, CH4 measurement technique, intake restriction, and CH4 reduction treatment application from these studies were used as classificatory factors. A series of equations for different physiological stages and diet types based on DMI or GE intake explained 96% of the variation in observed CH4 outputs (P < 0.001). Resulting models were validated with an independent dataset of 172 treatment means from 20 studies. To illustrate the scale of improvement on predicted CH4 outputs from the current wholefarm prediction approach (Intergovernmental Panel on Climate Change [IPCC]), equations developed in the present study (NewEqs) were compared with the IPCC equation {CH4 (g/d) = [(GEI × Ym) × 1,000]/55.65}, in which GEI is GE intake and Ym is the CH4 emission factor, in calculating CH4 outputs from 4 diverse beef systems. Observed BW and BW change data from cows with calves at side grazing either hill or lowland grassland, cows and overwintering calves and finishing steers fed contrasting diets were used to predict energy requirements, intake, and CH4 outputs. Compared with using this IPCC equation, NewEqs predicted up to 26% lower CH4 on average from individual lactating grazing cows. At the herd level, differences between equation estimates from 10 to 17% were observed in total annual accumulated CH4 when applied to the 4 diverse beef production systems. Overall, despite the small number of animals used it was demonstrated that there is a biological impact of using more specific CH4 prediction equations. Based on this approach, farm and national carbon budgets will be more accurate, contributing to reduced uncertainty in assessing mitigation options at farm and national level. © 2013 American Society of Animal Science. All rights reserved.


Chagunda M.G.,Future Farming Systems Group
Animal : an international journal of animal bioscience | Year: 2013

The objective of this review was to examine the application and relative efficiency of the proprietary hand-held Laser Methane Detector (LMD) in livestock production, with a focus on opportunities and challenges in different production systems. The LMD is based on IR absorption spectroscopy, uses a semiconductor laser as a collimated excitation source and uses the second harmonic detection of wavelength modulation spectroscopy to establish a methane (CH4) concentration measurement. The use of the LMD for CH4 detection in dairy cows is relatively recent. Although developed for entirely different purposes, the LMD provides an opportunity for non-invasive and non-contact scan sampling of enteric CH4. With the possibility for real-time CH4 measurements, the LMD offers a molecular-sensitive technique for enteric CH4 detection in ruminants. Initial studies have demonstrated a relatively strong agreement between CH4 measurements from the LMD with those recorded in the indirect open-circuit respiration calorimetric chamber (correlation coefficient, r = 0.8, P < 0.001). The LMD has also demonstrated a strong ability to detect periods of high-enteric CH4 concentration (sensitivity = 95%) and the ability to avoid misclassifying periods of low-enteric CH4 concentration (specificity = 79%). Being portable, the LMD enables spot sampling of methane in different locations and production systems. Two challenges are discussed in the present review. First is on extracting a representation of a point measurement from breath cycle concentrations. The other is on using the LMD in grazing environment. Work so far has shown the need to integrate ambient condition statistics in the flux values. Despite the challenges that have been associated with the use of the LMD, with further validation, the technique has the potential to be utilised as an alternative method in enteric CH4 measurements in ruminants.


Chindime S.,Makerere University | Kibwika P.,Makerere University | Chagunda M.,Future Farming Systems Group
Outlook on Agriculture | Year: 2016

The preference of an innovation systems approach to development is based on its inclusiveness and the interactions of actors to co-influence each other, to learn and innovate and to bring about tangible benefits. As more actors with diverse interests engage, the innovation system becomes more complex and actors with higher influence power are likely to benefit more. Smallholder farmers in developing countries are the core actors of an agricultural innovation system, but their ability to influence other actors to maximize their benefits is questionable. This article applies a historical analysis of the progressive development and complexity of Malawi’s diary innovation system through phased emphasis on technological, organizational and institutional development to illustrate the centrality of smallholder dairy farmers in the innovation system. A social network analysis is applied to assess the influence of smallholder farmers on other actors. The existence and growth of the diary innovation system in Malawi is founded on the resilience of smallholder dairy farmers to produce milk. Whereas the smallholder farmers are the most connected in terms of interaction, they have the least influence on other actors in the innovation system. To take advantage of their central position to maximize benefits, smallholder farmers can only rely on their collective power to influence others. Organizing farmers in groups and associations is a step in the right direction but deliberate interventions by innovation brokers as intermediaries need to focus on empowering these groups. © The Author(s) 2016.


Ricci P.,Future Farming Systems Group | Ricci P.,Instituto Nacional de Tecnologia Agropecuaria | Umstatter C.,Future Farming Systems Group | Holland J.P.,Future Farming Systems Group | Waterhouse A.,Future Farming Systems Group
Journal of Animal Science | Year: 2014

A modeling study based on a dataset from a large-scale grazing study was used to identify the potential impact of grazing behavior and performance of diverse cow genotypes on predicted methane (CH4) emissions. Lactating cows grazing extensive seminatural grassland and heath vegetation were monitored with Global Positioning System collars and activity sensors. The diet selected by cows of 3 different genotypes, Aberdeen Angus cross Limousin (AxL), Charolais (CHA), and Luing (LUI), was simulated by matching their locations during active periods with hill vegetation maps. Measured performance and activity were used to predict energy requirements, DMI, and CH4 output. The cumulative effect of actual performance, diet selection, and actual physical activity on potential CH4 output and yield was estimated. Sensitivity analyses were performed for the digestibility of intake, energy cost of activity, proportion of milk consumed by calves, and reproductive efficiency. Although with a better performance (P < 0.05), LUI required less total energy than the other genotypes (P < 0.001) as the other 2 spent more energy for maintenance (P < 0.001) and activity (P < 0.001). By selecting a better quality diet (P < 0.03), estimated CH4 of CHA cow-calf pairs was lower than AxL (P = 0.001) and slightly lower than LUI (P = 0.08). Energy lost as CH4 was 0.17 and 0.58% lower for LUI than AxL and CHA (P < 0.002). This study suggests for the first time that measured activity has a major impact on estimated CH4 outputs. A 15% difference of the cow-calf pair CH4 was estimated when using different coefficients to convert actual activity into energy. Predicted CH4 was highly sensitive to small changes in diet quality, suggesting the relative importance of diet selection on heterogeneous rangelands. Extending these results to a farm systems scale, CH4 outputs were also highly sensitive to reductions in weaning rates, illustrating the impact on CH4 at the farm-system level of using poorly adapted genotypes on habitats where their performances may be compromised. This paper demonstrates that variations in grazing behavior and grazing choice have a potentially large impact on CH4emissions, illustrating the importance of including these factors in calculating realistic national and global estimates. © 2014 American Society of Animal Science. All rights reserved.


PubMed | Aberystwyth University and Future Farming Systems Group
Type: Comparative Study | Journal: Journal of applied microbiology | Year: 2016

This work aims to determine the factors which play a role in establishing the microbial population throughout the digestive tract in ruminants and is necessary to enhance our understanding of microbial establishment and activity.This study used Terminal Restriction Fragment Length Polymorphism (TRFLP) to investigate the microbial profiles of 11 regions of the digestive tract of two breeds of sheep (Beulah and Suffolk). TRFLP data revealed that the regions of the digestive tract were highly significantly different in terms of the composition of the bacterial communities within three distinct clusters of bacterial colonization (foregut, midgut and hindgut). The data also show that breed was a significant factor in the establishment of the bacterial component of the microbial community, but that no difference was detected between ciliated protozoal populations.We infer that not only are the different regions of the tract important in determining the composition of the microbial communities in the sheep, but so too is the breed of the animal.This is the first time that a difference has been detected in the digestive microbial population of two different breeds of sheep.


PubMed | Future Farming Systems Group
Type: Journal Article | Journal: Journal of animal science | Year: 2013

The prediction of methane outputs from ruminant livestock data at farm, national, and global scales is a vital part of greenhouse gas calculations. The objectives of this work were to quantify the effect of physiological stage (lactating or nonlactating) on predicting methane (CH4) outputs and to illustrate the potential improvement for a beef farming system of using more specific mathematical models to predict CH4 from cattle at different physiological stages and fed different diet types. A meta-analysis was performed on 211 treatment means from 38 studies where CH4, intake, animal, and feed characteristics had been recorded. Additional information such as type of enterprise, diet type, physiological stage, CH4 measurement technique, intake restriction, and CH4 reduction treatment application from these studies were used as classificatory factors. A series of equations for different physiological stages and diet types based on DMI or GE intake explained 96% of the variation in observed CH4 outputs (P<0.001). Resulting models were validated with an independent dataset of 172 treatment means from 20 studies. To illustrate the scale of improvement on predicted CH4 outputs from the current whole-farm prediction approach (Intergovernmental Panel on Climate Change [IPCC]), equations developed in the present study (NewEqs) were compared with the IPCC equation {CH4 (g/d)=[(GEIYm)1,000]/55.65}, in which GEI is GE intake and Ym is the CH4 emission factor, in calculating CH4 outputs from 4 diverse beef systems. Observed BW and BW change data from cows with calves at side grazing either hill or lowland grassland, cows and overwintering calves and finishing steers fed contrasting diets were used to predict energy requirements, intake, and CH4 outputs. Compared with using this IPCC equation, NewEqs predicted up to 26% lower CH4 on average from individual lactating grazing cows. At the herd level, differences between equation estimates from 10 to 17% were observed in total annual accumulated CH4 when applied to the 4 diverse beef production systems. Overall, despite the small number of animals used it was demonstrated that there is a biological impact of using more specific CH4 prediction equations. Based on this approach, farm and national carbon budgets will be more accurate, contributing to reduced uncertainty in assessing mitigation options at farm and national level.

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