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Edinburgh, United Kingdom

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.

Chagunda M.G.G.,Future Farming Systems Group | Mwangwela A.,University of Malawi | Mumba C.,University of Zambia | Dos Anjos F.,Eduardo Mondlane University | And 3 more authors.
Regional Environmental Change | Year: 2015

Smallholder farmers play an important part in the dairy value chain in Sub-Saharan Africa. Three technological approaches have been used to improve productivity. These are through, applying agricultural ecological processes (ecological intensification), utilising modern livestock breeding (genetic intensification), and socio-economic intensification. Ecological intensification includes continuous housing of cows applying a cut-and-carry feeding system, introduction of purpose-bred forages and pastures, and the introduction of agro-forestry within the dairy systems. Genetic intensification strategies include: importation of dairy breeds such as Holstein–Friesian (HF) and cross-breeding of the indigenous breeds with HF. Training and capacity-building activities to create sustainable livelihoods have been initiated for farming and technological practices of animal husbandry, but also to enhance appropriate leadership and corporative-building skills that would create and support an enabling environment for sustainability. These improvements and initiatives in the service delivery have been championed by national governments, development partner institutions, or non-governmental organisations through different programmes. Challenges of intensification include matching management to genetic potential of imported and cross-bred improved dairy breeds, ensuring low post-harvest losses, proper utilisation, and reducing environmental impact. Using examples from Kenya, Malawi, Mozambique, Tanzania, and Zambia, this paper reviews the management and assessment approaches used in fostering smallholder dairy development strategies and dairy’s contribution to sustainable livelihoods in the face of intensification. © 2015 Springer-Verlag Berlin Heidelberg

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.

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.

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.

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