An appraisal of carbon footprint of milk from commercial grass-based dairy farms in Ireland according to a certified life cycle assessment methodology

Purpose

Life cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass-based farms are usually limited to small numbers of farms (<30) and rarely certified to international standards, e.g. British Standards Institute publicly available specification 2050 (PAS 2050). The goals of this study were to quantify CF of milk from a large sample of grass-based farms using an accredited PAS 2050 method and to assess the relationships between farm characteristics and CF of milk.

Materials and methods

Data was collected annually using on-farm surveys, milk processor records and national livestock databases for 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fed into a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model in CO₂ equivalents (CO₂-eq) and allocated economically between dairy farm products, except exported crops. Carbon footprint of milk was estimated by expressing GHG emissions attributed to milk per kilogram of fat and protein-corrected milk (FPCM). The Carbon Trust tested the LCA model for non-conformities with PAS 2050. PAS 2050 certification was achieved when non-conformities were fixed or where the effect of all unresolved non-conformities on CF of milk was?<?±5 %.

Results and discussion

The combined effect of LCA model non-conformities with PAS 2050 on CF of milk was <1 %. Consequently, PAS 2050 accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO₂-eq/kg of FPCM, but varied from 0.87 to 1.72 kg of CO₂-eq/kg of FPCM. Although some farm attributes had stronger relationships with CF of milk than the others, no attribute accounted for the majority of variation between farms. However, CF of milk could be reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacement rate (R ²?=?0.75). Management changes can be applied simultaneously to improve each of these traits. Thus, grass-based farmers can potentially significantly reduce CF of milk.

Conclusions

The certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approach to quantify CF of milk at a farm or national level. The application of the certified model highlighted a wide range between the CF of milk of commercial farms. However, differences between farms’ CF of milk were explained by variation in various aspects of farm performance. This implies that improving farm efficiency can mitigate CF of milk.     

Tularemia in Alaska, 1938 - 2010

Background

A major challenge in sheep farming during the grazing season along the coast of south-western Norway is tick-borne fever (TBF) caused by the bacteria Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus.

Methods

A study was carried out in 2007 and 2008 to examine the prevalence of A. phagocytophilum infection and effect on weaning weight in lambs. The study included 1208 lambs from farms in Sunndal Ram Circle in Møre and Romsdal County in Mid-Norway, where ticks are frequently observed. All lambs were blood sampled and serum was analyzed by an indirect fluorescent antibody assay (IFA) to determine an antibody status (positive or negative) to A. phagocytophilum infection. Weight and weight gain and possible effect of infection were analyzed using ANOVA and the MIXED procedure in SAS.

Results

The overall prevalence of infection with A. phagocytophilum was 55%. A lower weaning weight of 3% (1.34 kg, p < 0.01) was estimated in lambs seropositive to an A. phagocytophilum infection compared to seronegative lambs at an average age of 137 days.

Conclusions

The results show that A. phagocytophilum infection has an effect on lamb weight gain. The study also support previous findings that A. phagocytophilum infection is widespread in areas where ticks are prevalent, even in flocks treated prophylactic with acaricides.     

Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

Purpose

Various approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.

Methods

We applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.

Results and discussion

The typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.

Conclusions

This approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

     

Reducing methane on-farm by feeding diets high in fat may not always reduce life cycle greenhouse gas emissions

Purpose

To consider whether feed supplements that reduce methane emissions from dairy cows result in a net reduction in greenhouse gas (GHG) intensity when productivity changes and emissions associated with extra manufacturing and management are included.

Methods

A life cycle assessment was undertaken using a model farm based on dairy farms in Victoria, Australia. The system boundary included the creation of farm inputs and on-farm activities up to the farm gate where the functional unit was 1 L of fat and protein corrected milk (FPCM). Electricity and diesel (scaled per cow), and fertiliser inputs (scaled on farm size) to the model farm were based on average data from a survey of farms. Fertiliser applied to crops was calculated per area of crop. Animal characteristics were based on available data from farms and literature. Three methane-reducing diets (containing brewers grain, hominy or whole cotton seed) and a control diet (cereal grain) were modelled as being fed during summer, with the control diet being fed for the remainder of the year in all cases.

Results and discussion

Greenhouse gas intensity (kg CO₂-eq/L FPCM) was lower than the control diet when the hominy (97 % compared with control) and brewers grain (98 %) diets were used but increased when the whole cottonseed diet was used (104 %). On-farm GHG emissions (kg CO₂-eq) were lower than the control diet when any of the methane-reducing diets were used (98 to 99.5 % of emissions when control diet fed). Diesel use in production and transport of feed supplements accounted for a large portion (63 to 93 %) of their GHG intensity (kg CO₂-eq/t dry matter). Adjusting fertiliser application, changing transport method, changing transport fuel, and using nitrification inhibitors all had little effect on GHG emissions or GHG intensity.

Conclusions

Although feeding strategies that reduce methane emissions from dairy cows can lower the GHG emissions up to the farm gate, they may not result in lower GHG intensities (g CO₂-eq/L FPCM) when pre-farm emissions are included. Both transport distance and the effect of the feed on milk production have important impacts on the outcomes.     

Rearing performances and environmental assessment of sea cage farming in Tunisia using life cycle assessment (LCA) combined with PCA and HCPC

Purpose

The present study aims to understand the influence of rearing practices and the contributions of production phases of fish farming to their environmental impacts and determine which practices and technical characteristics can best improve the farms’ environmental performance. Another objective is to identify the influence of variability in farming practices on the environmental performances of sea cage aquaculture farms of sea bass and sea bream in Tunisia by using principal component analysis (PCA) and hierarchical clustering on principal components (HCPC) methods and then combining the classification with life cycle assessment (LCA).

Methods

The approach consisted of three major steps: (i) of the 24 aquaculture farms in Tunisia, 18 were selected which follow intensive rearing practices in sea cages of European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) and then a typology was developed to classify the studied farms into rearing practice groups using HCPC; (ii) LCA was performed on each aquaculture farm and (iii) mean impacts and contributions of production phases were calculated for each group of farms. Impact categories included acidification, eutrophication, global warming, land occupation, total cumulative energy demand and net primary production use.

Results and discussion

Results revealed high correlation between rearing practices and impacts. The feed-conversion ratio (FCR), water column depth under the cages and cage size had the greatest influence on impact intensity. Rearing practices and fish feed were the greatest contributors to the impacts studied due to the production of fish meal and oil and the low efficiency of feed use, which generated large amounts of nitrogen and phosphorus emissions. It is necessary to optimise the diet formulation and to follow better feeding strategies to lower the FCR and improve farm performance. Water column depth greatly influenced the farms’ environmental performance due to the increase in waste dispersion at deeper depths, while shallow depths resulted in accumulation of organic matter and degradation of water quality. Cage size influences environmental performances of aquaculture farms. Thus, from an environmental viewpoint, decision makers should grant licences for farms in deeper water with larger cages and encourage them to improve their FCRs.

Conclusions

This study is the first attempt to combine the HCPC method and the LCA framework to study the environmental performance of aquacultural activity. The typology developed captures the variability among farms because it considers several farm characteristics in the classification. The LCA demonstrated that technical parameters in need of improvement are related to the technical expertise of farm managers and workers and to the location of the farm.

     

Enhancement of the thermal and alkaline pH stability of <Emphasis Type="Italic">Escherichia coli</Emphasis> lysine decarboxylase for efficient cadaverine production

Objective

To enhance the thermal and alkaline pH stability of the lysine decarboxylase from Escherichia coli (CadA) by engineering the decameric interface and explore its potential for industrial applications.

Results

The mutant T88S was designed for improved structural stability by computational analysis. The optimal pH and temperature of T88S were 7.0 and 55 °C (5.5 and 50 °C for wild-type). T88S showed higher thermostability with a 2.9-fold increase in the half-life at 70 °C (from 11 to 32 min) and increased melting temperature (from 76 to 78 °C). Additionally, the specific activity and pH stability (residual activity after 10 h incubation) of T88S at pH 8.0 were increased to 164 U/mg and 78% (58 U/mg and 57% for wild-type). The productivity of cadaverine with T88S (284 g l-lysine L^?1 and 5 g DCW L^?1) was 40 g L^?1 h^?1, in contrast to 28 g L^?1 h^?1 with wild-type.

Conclusion

The mutant T88S showed high thermostability, pH stability, and activity at alkaline pH, indicating that this mutant is a promising biocatalyst for industrial production of cadaverine.

     

Appraisal of environmental profiles of pasture-based milk production: a case study of dairy farms in the Waikato region,New Zealand

Purpose

Dairying is a relatively intensive livestock production system and contributes to a range of environmental impacts. In the southern hemisphere, dairy farming systems are based mainly on outdoor grazing of permanent pastures. The objectives of this study were to (i) assess environmental profiles and (ii) to identify environmental hotspots in a pasture-based dairy farming system.

Methods

A cradle-to-farm gate life cycle assessment of 53 dairy farms in the Waikato region, New Zealand, was carried out, using 1 kg of fat- and protein-corrected milk as the functional unit. Twelve environmental impact categories were assessed: climate change (CC), ozone depletion potential (ODP), cancer effects (Cancer), non-cancer effects (non-cancer), particulate matter (PM), ionizing radiation (IR), photochemical ozone formation potential (POFP), acidification potential (AP), terrestrial eutrophication potential (TEP), freshwater eutrophication potential (FEP), marine eutrophication potential (MEP) and ecotoxicity for aquatic freshwater (Ecotox). Contribution and sensitivity analyses were performed to determine key hotspots and investigate potential changes in results due to methodological choices.

Results and discussion

The on-farm stage contributed >50 % of the total result for 7 out of 12 indicators (CC, Non-cancer, PM, POFP, AP, TEP, MEP). The off-farm rearing of replacement animals contributed 11–20 % to the total result for all indicators. The production of brought-in (from off-farm) feeds for use on the dairy farms contributed >10 % to the indicator results for Non-cancer (25 %), FEP (15 %), MEP (12 %) and Ecotox (19 %). The manufacturing of agrichemicals for use on the dairy farms contributed >10 % to the indicator results for ODP (26 %), Cancer (26 %), PM (19 %), IR (46 %), FEP (25 %) and Ecotox (42 %). The transportation of off-farm inputs for use on the dairy farms contributed >10 % to the impacts on ODP (15 %), IR (21 %) and POFP (11 %). Sensitivity analysis demonstrated the influence of choices associated with data sources, inventories and impact assessment models on the results.

Conclusions

The off-farm activities together contributed >50 % to 5 out of 12 impact indicator results, >45 % to a further two impact indicator results and 32 % of the CC result. Therefore, environmental improvement options should focus on both on-farm and off-farm activities. A focus on just one impact category (such as CC) risks ignoring the environmental hotspots that are revealed in a more comprehensive environmental assessment.

     

Organic versus conventional citrus. Impact assessment and variability analysis in the Comunitat Valenciana (Spain)

Purpose

Taking into account the large area of citrus in Spain and the impacts generated by agriculture, reducing the environmental impact of this crop represents an important goal. This study attempts to compare the environmental impact of two citrus cropping systems, organic and conventional, in the region of Valencia (Spain), and to assess the variability within both farming systems in order to highlight the influence of management practices on the environmental performance.

Methods

A survey was carried out on citrus farmers, 145 corresponding to organic production and 122 to conventional. Life cycle assessment (LCA) was used to estimate the environmental impacts of farms and the contribution of each production stage to impacts. Two functional units (FUs), mass- and area-based, were chosen. The variability and confidence intervals of the average impact results were assessed by means of a bootstrap technique. Finally, a k-means cluster analysis was performed to identify groups of farms with comparable impact levels.

Results and discussion

The mean impact values of the conventional farm sample were higher than those of the organic farms, when using 1 ha year^?1 as FU, whereas for the FU of 1 kg no differences were found for some impact categories. Most of the impact results were also observed to be highly variable. The distribution of the mean after the bootstrap confirmed both the variability of the impacts and the differences between the farming systems. The cluster analysis determined two groups via their impact categories. Cluster-1, which showed higher impacts, was made up of part of the conventional farms while cluster-2 included the remaining conventional farms and all the organic ones. No difference in yield was found between the conventional farms of both clusters.

Conclusions

Bootstrapped LCA offers the ability to assess the variability of the impacts, regardless of the sample size and the non-normal impact distributions. The cluster analysis shows that conventional farms can attain similar impacts than the organic ones, while maintaining the yield. FU selection is crucial, since a mass-based FU reduces the difference in the environmental performance between conventional and organic farms. To attain a more sustainable citrus farming, a careful selection of the management practices is needed.

     

Consequential LCA of switching from maize silage-based to grass-based dairy systems

Purpose

This study aimed to investigate the environmental consequences (on climate change and land use) of an increase in preference for grass-based milk in France using a consequential life cycle assessment (CLCA) approach. This increase in preference was assumed to be satisfied domestically, by converting maize silage-based dairy farms (MS farm) to grass-based dairy farms (G farm) while keeping on-farm usable agricultural area and total milk production of farm constant.

Methods

The possible consequences of an increase in preference for grass-based milk were identified based on cause and effect relationships. The conversion from MS to G farm reduced the use of soybean meal, changed the on-farm cropping pattern and produced more animals but less wheat and no rapeseed. Effects on on-farm soil C were predicted with the RothC model and on global land use change (LUC) with models of global agricultural markets (Global Trade Analysis Project (GTAP) and Landbouw Economisch Instituut Trade Analysis Project (LEITAP)). System expansion using animals from a suckler beef production system was applied to estimate the impacts of milk and animal co-products from the dairy system. Land occupation and climate change impacts were estimated. The consequences of farm conversion were attributed only to the milk, as preference for grass-based milk drove the conversion process.

Results and discussion

The conversion from the MS to G farm increases land occupation and climate change impacts for the G farm, respectively, by 9 and 7 % according to GTAP and 14 and 51 % according to LEITAP. Land occupation and climate change impacts of milk produced by the G farm after conversion increased, respectively, by 82 and 13 % with GTAP and 123 and 97 % with LEITAP relative to those for the MS farm (before conversion). The production of additional wheat and rapeseed outside the G farm increased impacts of the G farm (by 29–69 % depending on impacts and model used). Results indicate that the farm conversion would probably have consequences on global LUC and that it is important to account for this in a LCA approach.

Conclusions

Land use and land use change (LULUC) contributed to the impacts of grass-based milk, and results were highly sensitive to the LULUC model used. The many possible chain-of-event pathways that follow a change in preference for a given product yield high uncertainty in CLCA results. This study only assessed one possible way to meet the increase in preference for grass-based milk; it is necessary to perform a sensitivity analysis to investigate other possible scenarios resulting from this increase in preference.     

Outpatient treatment with the wearable cardioverter defibrillator: clinical experience in two Dutch centres

Introduction

The latest European Society of Cardiology Guidelines recommend consideration of a wearable cardioverter-defibrillator (WCD) for patients with a poor left ventricular ejection fraction (LVEF) who are at risk of sudden arrhythmic death but are not eligible for an implantable defibrillator. For these patients a WCD can be an alternative to long-term hospitalisation.

Purpose

To evaluate the use of WCD therapy in these patient groups in two Dutch centres.

Methods

All consecutive patients treated with the WCD between 2009 and 2016 were included from two centres in the Netherlands. Data on events and compliance were collected retrospectively through home monitoring systems and adjudicated by the investigators.

Results

A total of 79 patients were treated with a WCD. Common indications were newly diagnosed cardiomyopathy without optimal medical treatment in 46 patients (58.2%) and bridge to implantable cardioverter-defibrillator (ICD) implant in 33 patients (41.8%). Bridge to implant indications consisted of contraindications for immediate implantation such as infections (e.?g. previous device-related infections) and radiotherapy. Compliance was over 97% per day (median 23.3?h, 22.6–23.7), during a median of 79 days (50.0–109.8.0). Two patients (2.6%) received an appropriate shock (annual rate 13.6%), there was 1 (1.3%) inappropriate shock (annual rate 6.7%). In 24 patients (52.2%) without optimal medical treatment, the LVEF was sufficiently improved and ICD implant was avoided. Eight (10.1%) patients did not receive an ICD. In 45 patients an ICD was implanted (57.0%).

Conclusion

WCD therapy provides a safe and effective treatment in outpatient setting for patients at high risk for sudden cardiac death and reduces the number of ICDs implanted.

     

A prospective observational cohort study in primary care practices to identify factors associated with treatment failure in <Emphasis Type="Italic">Staphylococcus aureus</Emphasis> skin and soft tissue infections

Background

The incidence of outpatient visits for skin and soft tissue infections (SSTIs) has substantially increased over the last decade. The emergence of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) has made the management of S. aureus SSTIs complex and challenging. The objective of this study was to identify risk factors contributing to treatment failures associated with community-associated S. aureus skin and soft tissue infections SSTIs.

Methods

This was a prospective, observational study among 14 primary care clinics within the South Texas Ambulatory Research Network. The primary outcome was treatment failure within 90 days of the initial visit. Univariate associations between the explanatory variables and treatment failure were examined. A generalized linear mixed-effect model was developed to identify independent risk factors associated with treatment failure.

Results

Overall, 21% (22/106) patients with S. aureus SSTIs experienced treatment failure. The occurrence of treatment failure was similar among patients with methicillin-resistant S. aureus and those with methicillin-susceptible S. aureus SSTIs (19 vs. 24%; p = 0.70). Independent predictors of treatment failure among cases with S. aureus SSTIs was a duration of infection of ≥7 days prior to initial visit [aOR, 6.02 (95% CI 1.74–19.61)] and a lesion diameter size ≥5 cm [5.25 (1.58–17.20)].

Conclusions

Predictors for treatment failure included a duration of infection for ≥7 days prior to the initial visit and a wound diameter of ≥5 cm. A heightened awareness of these risk factors could help direct targeted interventions in high-risk populations.

     

Accounting for inter-annual <Emphasis Type="Italic">variability</Emphasis> of farm activity data for calculation of greenhouse gas emissions in dairy farming

Purpose

This study examines the inter-annual variability of production data in an organic dairy farm and its effect on the estimation of product-related greenhouse gas emissions (GHG) using a detailed material flow model. It is believed that the examination of only one production year may not adequately reflect temporal representativeness and may therefore lead to unreliable results. The current study also provides a method to deal with variability when temporal representativeness cannot be ensured.

Methods

All material flows related to milk production from six consecutive milk years in an organic dairy farm in northern Germany were analysed. The milk yield of the 75 to 91 cows varied between 5418 and 7102 kg energy corrected milk (ECM) per cow and year. GHG emissions were estimated using calculation guidelines from the International Dairy Federation (IDF) and the Intergovernmental Panel on Climate Change (IPCC). Emissions were calculated in the Flow Analysis and Resource Management (FARM) model ensuring mass balances for nitrogen and phosphorous in every subsection of the model. Based on the variability of crop yields, the number of years for representative average data was calculated as well as an uncertainty when only a limited number of years was available.

Results and discussion

Estimated GHG emissions varied between 0.88 and 1.09 kg CO₂-eq kg^?1 ECM^?1 (mean, standard deviation of the mean = 0.97 and 0.07 kg CO₂-eq kg^?1 ECM^?1). Emissions from ruminant digestion had the highest contribution (50.9 ± 2.3) percent in relation to overall product-related GHG emissions. Direct emissions from soil showed the highest coefficient of variation (36%) due to simultaneous changes in fertilization amount, crop yield and milk yield which showed no significant direct relationship. The number of years needed to be assessed for representative average yields was between 27 and 215 years for clover grass and maize silage, respectively. When performing a sensitivity analysis based on the variability of crop yields, the assessed farm showed reliable results with average data of at least 4 years.

Conclusions

Temporal representativeness should be dealt with explicitly in GHG assessments for dairy farming. If the representativeness of crop yields cannot be ensured, an uncertainty bandwidth of the results based on variability of yields can provide a basis for comparing different farms or farming systems. This approach could also be extended to other variabilities in dairy farming for more reliability of results.

     

Geographic and temporal genetic structure in <Emphasis Type="Italic">Lepeophtheirus salmonis</Emphasis> from four salmon farms along the northwest and west coasts of Ireland: results from a microsatellite analysis

The marine ectoparasitic copepod of salmonids, Lepeophtheirus salmonis (Krøyer), is a major pest of farmed Atlantic salmon (Salmo salar L.) causing great economic impact. The spatial scales over which L. salmonis populations in different salmon farms are typically connected, and the temporal scales over which L. salmonis from the same farm typically undergo genetic change are largely unknown. These questions were posed in a small-scale geographic study of population structure in L. salmonis from four salmon farms, along the northwest and west coasts of Ireland, using two outgroups from Norway and Canada. The temporal stability of genetic composition was also studied in samples collected quarterly during one year from one salmon farm in Ireland. Genetic composition in L. salmonis was characterised using four nuclear microsatellites. Significant but low genetic differentiation was observed between all sites (F _ST = 0.08), with no evidence that differentiation was correlated with geographic distance. Temporal genetic differentiation was also evident (F _ST = 0.07). An analysis of all L. salmonis samples except the ones from Norway detected two separate clusters. Each cluster contained both geographical and temporal samples. These results are consistent with a population model in which L. salmonis in salmon farms along the northwest and west coasts of Ireland are not isolated, but are potentially subject to (i) localised ecological factors at the particular farm sites or (ii) selection post-settlement or a combination thereof.     

Purification of chicken carbonic anhydrase isozyme-III (CA-III) and its measurement in White Leghorn chickens

Background

The present study hypothesized that GH-AluI and IGF-I-SnabI polymorphisms do change the metabolic/endocrine profiles in Holstein cows during the transition period, which in turn are associated with productive and reproductive parameters.

Methods

Holstein cows (Farm 1, primiparous cows, n = 110, and Farm 2, multiparous cows, n = 76) under grazing conditions were selected and GH and IGF-I genotypes were determined. Blood samples for metabolic/endocrine determinations were taken during the transition period and early lactation in both farms. Data was analyzed by farm using a repeated measures analyses including GH and IGF-I genotypes, days and interactions as fixed effects, sire and cow as random effects and calving date as covariate.

Results and Discussion

Frequencies of GH and IGF-I alleles were L:0.84, V:0.16 and A:0.60, B:0.40, respectively. The GH genotype was not associated with productive or reproductive variables, but interaction with days affected FCM yield in multiparous (farm 2) cows (LL yielded more than LV cows) in early lactation. The GH genotype affected NEFA and IGF-I concentrations in farm 1 (LV had higher NEFA and lower IGF-I than LL cows) suggesting a better energy status of LL cows. There was no effect of IGF-I genotype on productive variables, but a trend was found for FCM in farm 2 (AB cows yielded more than AA cows). IGF-I genotype affected calving first service interval in farm 1, and the interaction with days tended to affect FCM yield (AB cows had a shorter interval and yielded more FCM than BB cows). IGF-I genotype affected BHB, NEFA, and insulin concentrations in farm 1: primiparous BB cows had lower NEFA and BHB and higher insulin concentrations. In farm 2, there was no effect of IGF-I genotype, but there was an interaction with days on IGF-I concentration, suggesting a greater uncoupling somatropic axis in AB and BB than AA cows, being in accordance with greater FCM yield in AB cows.

Conclusion

The GH and IGF-I genotypes had no substantial effect on productive parameters, although IGF-I genotype affected calving-first service interval in primiparous cows. Besides, these genotypes may modify the endocrine/metabolic profiles of the transition dairy cow under grazing conditions.     

Environmental Impact assessment of a semi-intensive beef cattle production in Brazil’s Northeast

Purpose

The aim of this study is to identify and evaluate the main environmental impacts related to semi-intensive beef cattle production system in the State of Bahia, in Brazil’s Northeast.

Methods

A cradle to gate study was undertaken in a beef cattle production system comprising two stages: calves production in one farm (farm 1) and cattle production in another farm (farm 2), both located in the central-southern meso-region of Bahia. The functional unit was 1?kg live weight. Impact assessment was performed using five impact categories from the ReCiPe method.

Results and discussion

When compared to calves, the cattle production had the greatest contributions in all of the five studied impact categories. The process pasture cultivation had expressive environmental impacts in all categories, with 70.05 % for climate change (CC), 82.01 % for terrestrial acidification (TA), 76.53 % for fossil depletion (FD), 86.14 % for freshwater eutrophication (FE) and 100 % for agricultural land occupation (ALO). In CC and TA, the principal elementary flow was the direct emissions due to the use of mineral fertilizers. In FE and FD, the dominant flow was related to the use of phosphate fertilizer. In ALO, the process pasture cultivation was predominant due to the physical area of the farms, which is a characteristic of pasture-based production systems. The processes breeding-rearing and fattening were second in the contribution analysis, with 29.95 % and 17.99 %, respectively, for CC and TA, due to the enteric methane (CH₄) and the direct emissions of nitrous oxide (N₂O) volatilization from the animal excreta.

Conclusions

The cattle production is responsible for the greater part of impacts, compared to the calves production. The direct emissions from fertilizers used in the pastures, from enteric emissions and from animal wastes in the breeding-rearing and fattening processes were identified as the critical points of the analysed cattle production system. Measures aiming at the improvement of the feed conversion of the animals and at the substitution of synthetic nitrogen fertilizers by natural nitrogen fixation can considerably contribute to the reduction of environmental impacts of these production systems. Accordingly, the respective modifications should be considered in future studies on the potential of these measures to enhance the environmental performance of semi-intensive beef cattle production. These results will complement other similar studies conducted in other regions of the country, following the tendency of growing usage of the life cycle assessment methodology in Brazilian agricultural and livestock systems.

     

Including GHG emissions from mangrove forests LULUC in LCA: a case study on shrimp farming in the Mekong Delta,Vietnam

Purpose

Mangrove forests have been recognized as important regulators of greenhouse gases (GHGs), yet the resulting land use and land-use change (LULUC) emissions have rarely been accounted for in life cycle assessment (LCA) studies. The present study therefore presents up-to-date estimates for GHG emissions from mangrove LULUC and applies them to a case study of shrimp farming in Vietnam.

Methods

To estimate the global warming impacts of mangrove LULUC, a combination of the International Panel for Climate Change (IPCC) guidelines, the Net Committed Emissions, and the Missed Potential Carbon Sink method were used. A literature review was then conducted to characterize the most critical parameters for calculating carbon losses, missed sequestration, methane fluxes, and dinitrogen monoxide emissions.

Results and discussion

Our estimated LUC emissions from mangrove deforestation resulted in 124 t CO₂ ha^?1 year^?1, assuming IPCC’s recommendations of 1 m of soil loss, and 96% carbon oxidation. In addition to this, 1.25 t of carbon would no longer be sequestered annually. Discounted over 20 years, this resulted in total LULUC emissions of 129 t CO₂ ha^?1 year^?1 (CV = 0.441, lognormal distribution (ln)). Shrimp farms in the Mekong Delta, however, can today operate for 50 years or more, but are 1.5 m deep (50% oxidation). In addition to this, Asian tiger shrimp farming in mixed mangrove concurrent farms (the only type of shrimp farm that resulted in mangrove deforestation since 2000 in our case study) resulted in 533 kg methane and 1.67 kg dinitrogen monoxide per hectare annually. Consequently, the LULUC GHG emissions resulted in 184 and 282 t CO₂-eq t^?1 live shrimp at farm gate, using mass and economic allocation, respectively. These GHG emissions are about an order of magnitude higher than from semi-intensive or intensive shrimp farming systems. Limitations in data quality and quantity also led us to quantify the uncertainties around our emission estimates, resulting in a CV of between 0.4 and 0.5.

Conclusions

Our results reinforce the urgency of conserving mangrove forests and the need to quantify uncertainties around LULUC emissions. It also questions mixed mangrove concurrent shrimp farming, where partial removal of mangrove forests is endorsed based upon the benefits of partial mangrove conservation and maintenance of certain ecosystem services. While we recognize that these activities limit the chances of complete removal, our estimates show that large GHG emissions from mangrove LULUC question the sustainability of this type of shrimp farming, especially since mixed mangrove farming only provide 5% of all farmed shrimp produced in Vietnam.

     

A perspective for reducing environmental impacts of mussel culture in Algeria

Purpose

In Algeria, the Ministry of Fisheries and Halieutic Resources has designed a strategic plan for the development of marine aquaculture for the years 2015–2025, which aims at expanding the annual production of Mediterranean mussel from less than 150 metric tonnes year^?1 in 2013 to 7600 metric tonnes year^?1 in 2025. We used Life Cycle Assessment (LCA) for evaluating the environmental impact of suspended mussel culture in Algeria and suggest management practices which could reduce it.

Methods

In order to estimate the current and perspective impact of this industry, we (1) applied LCA to one of the few farms currently operating in Algeria and (2) investigated two management scenarios for the farms to be established in the future in the same coastal area. The first scenario (Comp_S) represents the continuity with the current situation, in which each farm is competing with the other ones and is therefore managing the production cycle independently. In the second scenario (Coop_S), mussel farms are grouped in an aquaculture management area and shared the same facilities for post-processing harvested mussels before sending them to the market. The midpoint-based CML-IA method baseline 2000 V 3.01 was employed using SimaPro software. Furthermore, we carried out a Monte Carlo simulation, in order to assess the uncertainty in the results.

Results and discussion

The analysis focused on impact categories related to acidification and global warming potential. We took into account the energy consumptions (electricity and vessel fuel), the rearing infrastructure, including longlines, and a building for stabling, grading, and packing the mussel. Electricity contributes with 38.1 and 31.8 % respectively to global warming potential (GWP) and acidification, while fuel consumption contributes with 19.5 % to GWP and 31.8 % to acidification. Results of this work are compared with other LCA studies recently carried out in France (Aubin and Fontaine 2014) and in Spain (Iribarren et al. 2010c).

Conclusions

The LCA results show that important reductions in environmental impacts could be attained if the mussel farming activity would be operated according to the cooperative scenario here proposed. In this case, the environmental benefits will be a reduction of 3150 MJ and 156 kg CO₂ eq per metric tonne of mussel produced, compared with the alternative scenario. The results of this study suggest that LCA should be applied to the seafood production sector in Algeria, in order to identify best management practices.

     

Complement C4 induces regulatory T cells differentiation through dendritic cell in systemic lupus erythematosus

Background

Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disease. Complement component 4 (C4) has be proved to play a role in pathogenesis of SLE. In the present study, we investigated the effect of C4 on T cells differentiation.

Methods

Thirty SLE patients were included in this study. CD4+ T cells were isolated from healthy subjects, and dendritic cells (DCs) were isolated from healthy subjects or SLE patients. C4 was supplemented to co-incubate with T cells and DCs.

Results

Serum C4 concentration was positively correlated with regulatory T cell (Treg) percentage (R² = 0.5907, p < 0.001) and TGFβ concentration (R² = 0.5641, p < 0.001) in SLE patients. Different concentrations of C4 had no effect on T cells differentiation. Co-incubated T cells with DCs and C4 for 7 days, the Treg percentage and TGF-β concentration were significantly elevated. In addition, pre-treated DCs (from healthy subjects or SLE patients) with C4 and then co-incubated with T cells, the increases of Treg percentage and TGF-β concentration were also observed.

Conclusion

C4 takes part in T cells differentiation to Treg cells via DCs.

     

A parametric whole life cost model for offshore wind farms

Purpose

Life cycle cost (LCC) considerations are of increasing importance to offshore wind farm operators and their insurers to undertake long-term profitable investments and to make electricity generation more price-competitive. This paper presents a cost breakdown structure (CBS) and develops a whole life cost (WLC) analysis framework for offshore wind farms throughout their life span (～25 years).

Methods

A combined multivariate regression/neural network approach is developed to identify key cost drivers and evaluate all the costs associated with five phases of offshore wind projects, namely pre-development and consenting (P&C), production and acquisition (P&A), installation and commissioning (I&C), operation and maintenance (O&M) and decommissioning and disposal (D&D). Several critical factors such as geographical location and meteorological conditions, rated power and capacity factor of wind turbines, reliability of sub-systems and availability and accessibility of transportation means are taken into account in cost calculations. The O&M costs (including the cost of renewal and replacement, cost of lost production, cost of skilled maintenance labour and logistics cost) are assessed using the data available in failure databases (e.g. fault logs and O&M reports) and the data supplied by inspection agencies. A net present value (NPV) approach is used to quantify the current value of future cash flows, and then, a bottom-up estimate of the overall cost is obtained.

Results and discussion

The proposed model is tested on an offshore 500-MW baseline wind farm project, and the results are compared to experimental ones reported in the literature. Our results indicate that the capital cost of wind turbines and their installation costs account for the largest proportion of WLC, followed by the O&M costs. A sensitivity analysis is also conducted to identify those factors having the greatest impact on levelized cost of energy (LCOE).

Conclusions

The installed capacity of a wind farm, distance from shore and fault detection capability of the condition monitoring system are identified as parameters with significant influence on LCOE. Since the service lifetime of a wind farm is relatively long, a small change in interest rate leads to a large variation in the project’s total cost. The presented models not only assist stakeholders in evaluating the performance of ongoing projects but also help the wind farm developers reduce their costs in the medium–long term.

     

Spondylodiskitis and endocarditis due to <Emphasis Type="Italic">Streptococcus gordonii</Emphasis>

Background

Streptococcus gordonii is an infrequent cause of infective endocarditis (IE); associated spondylodiskitis has not yet been described in the literature.

Purpose

We describe 2 patients who presented with new-onset, severe back pain; blood cultures revealed S. gordonii bacteremia, which led to the diagnosis of spondylodiskitis and IE. We review our 2-decade experience with S. gordonii bacteremia to describe the clinical and epidemiological characteristics of these patients.

Results

In our hospital over the last 20 years (1998–2017), a total of 15 patients with S. gordonii bacteremia were diagnosed, including 11 men and 4 women, and the mean age was 65 ± 22 (range 23–95). The most common diagnosis was IE (9 patients), spondylodiskitis (the presented 2 patients, who in addition were diagnosed with endocarditis), necrotizing fasciitis (1), sternitis (1), septic arthritis (1) and pneumonia (1). The 11 patients with IE were treated with penicillin ± gentamicin, or ceftriaxone for 6 weeks, 5 required valve surgery and 10/11 (91%) attained complete cure. The 2 patients with diskitis required 2–3 months of intravenous antibiotics to achieve complete cure.

Conclusion

Spondylodiskitis was the presenting symptom of 2/11 (18%) patients with S. gordonii endocarditis. Spondylodiskitis should probably be looked for in patients diagnosed with S. gordonii endocarditis and back pain as duration of antibiotic treatment to achieve complete cure may be considerably longer.