An experimental study was conducted to examine the combined effects of adding a dietary protease, reducing the levels of soybean meal (SBM) and introducing corn gluten meal (CGM) in the ration of a ...group of broilers reared on a commercial Greek farm. Five hundred forty chicks were divided into three dietary treatments with six replicates of thirty birds each. The first group (Control) was fed a conventional diet based on corn and soybean meal, containing 21% w/w crude protein (CP). The second group (Soy-Prot) was supplied a corn and SBM-based diet containing a lower level of CP (20% w/w) and 200 mg of the protease RONOZYME® Proact per kg of feed. The third group (Gluten-Prot) was fed a diet without soybean-related constituents which was based on corn and CGM and with CP and protease contents identical to those of the diet of the Soy-Prot group. Body weight, feed intake, feed conversion ratio (FCR), intestinal microbiota populations and morphology, meat quality and cost were evaluated. Furthermore, a partial life cycle assessment (LCA) was performed in order to assess the potential environmental performance of the systems defined by these three dietary treatments and identify their environmental hot-spots. The growth performance of the broilers supplied the Soy-Prot diet was similar to the broilers supplied the Control diet. However, the broilers which were fed the Gluten-Prot diet at the end of the trial showed a tendency (P≤0.010) for lower weight gain and feed intake compared to those of the Control diet. When compared to the Control group, lower counts of C. perfringens (P≤0.05) were detected in the ileum and cecum parts, and lower counts of F. necrophorum (P≤0.001) were detected in the cecum part of the birds from the Gluten-Prot group. The evaluation of intestinal morphometry showed that the villus height and crypt depth values were not significantly different (P>0.05) among the experimental groups for the duodenum, jejunum and ileum parts. No significant differences (P>0.05) were observed in the quality of the breast and thigh meat and in the feed cost per kg body weight gain for the total duration of the growth period between the Control and Gluten-Prot broiler groups. The LCA suggested that the ammonia and nitrous oxide emissions due to litter handling constitute the farm level hot-spots for the Acidification and Eutrophication Potentials of the Control and Soy-Prot systems and the Global Warming Potential of the Gluten-Prot system, respectively. The Latin American soybean production and domestic corn production and lignite mining are important off-farm polluting processes for the studied life cycles. The Soy-Prot and Gluten-Prot systems both performed better than the Control system in nine of Environmental Impact Category Indicators assessed, with the respective differences being generally larger for the Gluten-Prot system. The environmental impact estimates are regarded as initial, indicative figures due to their inherent uncertainty. Overall, the results could be considered as positive indications in the effort to sustainably replace the conventional, soybean-dependent control diet in the specific broiler production system.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
European dairy production faces significant economic, environmental, and social sustainability challenges. Given the great diversity of dairy cattle production systems in Europe, region-specific ...concepts to improve environmental and socioeconomic sustainability are needed. Regionally integrated dairy cattle-crop systems emerge as a more resilient and sustainable alternative to highly specialized farming systems. Identifying different dairy cattle production typologies and their potential interactions with fodder crop production is presented as a step in transitioning to optimized agricultural systems. Currently existing typologies of integrated systems are often insufficient when characterizing structural, socioeconomic, and environmental components of farms. We fill this gap in the literature by identifying, describing, and comparing representative dairy cattle production system typologies and their interrelation with regional fodder crop production at the European regional scale. This is a necessary step to assess the scope for adapted mitigation and sustainability measures in the future. For this purpose, a multivariate statistical approach is applied. We show how different land-use practices, farm structure characteristics, socio-economic attributes, and emission intensities condition dairy production. Furthermore, the diversity of regional fodder crop production systems is demonstrated by analyzing their distribution in Europe. Together with identified typologies, varying degrees of regional specialization in milk production allow for identifying future strategies associated with the application of integrated systems in key European dairy regions. This study contributes to a better understanding of the existing milk production diversity in Europe and their relationship with regional fodder crop production. In addition, we discuss the benefits of integrated systems as a clear, viable, and resilient alternative to ongoing livestock intensification in the European context. Identifying interactions between components of integrated systems will facilitate decision-making, the design and implementation of measures to mitigate climate change, and the promotion of positive socio-economic and environmental interactions.
Growing awareness of global challenges and increasing pressures on the farming sector, including the urgent requirement to rapidly cut greenhouse gases (GHG) emissions, emphasize the need for ...sustainable production, which is particularly relevant for dairy production systems. Comparing dairy production systems across the three sustainability dimensions is a considerable challenge, notably due to the heterogeneity of production conditions in Europe. To overcome this, we developed an ex post multicriteria assessment tool that adopts a holistic approach across the three sustainability dimensions. This tool is based on the DEXi framework, which associates a hierarchical decision model with an expert perspective and follows a tree shaped structure; thus, we called it the DEXi-Dairy tool. For each dimension of sustainability, qualitative attributes were defined and organized in themes, sub-themes, and indicators. Their choice was guided by three objectives: (i) better describe main challenges faced by European dairy production systems, (ii) point out synergies and trade-offs across sustainability dimensions, and (iii) contribute to the identification of GHG mitigation strategies at the farm level. Qualitative scales for each theme, sub-theme, and indicator were defined together with weighting factors used to aggregate each level of the tree. Based on selected indicators, a list of farm data requirements was developed to populate the sustainability tree. The model was then tested on seven case study farms distributed across Europe. DEXi-Dairy presents a qualitative method that allows for the comparison of different inputs and the evaluation of the three sustainability dimensions in an integrated manner. By assessing synergies and trade-offs across sustainability dimensions, DEXi-Dairy is able to reflect the heterogeneity of dairy production systems. Results indicate that, while trade-offs occasionally exist among respective selected sub-themes, certain farming systems tend to achieve a higher sustainability score than others and hence could serve as benchmarks for further analyses.
•Decision support goals in livestock farming: animal health, GHG emissions reduction.•Overview of data-driven decision support need for Precision Livestock Farming goals.•Categorization of existing ...approaches into machine learning, modeling and simulation.
Precision Livestock Farming (PLF) is a concept that allows real-time monitoring of animals, by equipping them with sensors that surge livestock-related data to be further utilized by farmers. PLF comes with many benefits and ensures maximum use of farm resources, thus, enabling control of health status of animals, while potentially mitigating Greenhouse Gas (GHG) emissions. Due to the complexity of the decision making processes in the livestock industries, data-driven decision support systems based on not only real-time data but also expert knowledge, help farmers to take actions in support of animal health and better product yield. These decision support systems are typically based on machine learning, statistical analysis, and modeling and simulation tools. Combining expert knowledge with data obtained from sensors minimizes the risk of making poor decisions and helps to assess the impact of different strategies before applying them in reality. In this paper, we highlight the role of data-driven decision support tools in PLF, and provide an extensive overview and categorization of the different data-driven approaches with respect to the relevant livestock farming goals. We, furthermore, discuss the challenges associated with reduction of GHG emissions using PLF.
To achieve national and global air quality and climate change objectives, the agricultural sector increasingly requires dependable decision support tools for gaseous emissions at the farm level. We ...evaluated thirteen greenhouse gas (GHG)-based decision support systems (DSS), considering criteria such as not only the accessibility, user-friendliness, stakeholder involvement, sustainability methodology, and modeling aspects, but also the input parameters and outputs provided, all crucial for decision making. While most DSSs provide information for facilitating their use, only four are suitable for inexperienced users, and stakeholder participation in DSS development is infrequent. The dominant methodology for farm-level GHG estimation is IPCC 2006, with quantitative models primarily used for indicators’ assessment. Scenario and contribution analyses are the prevailing decision support approaches. Soil, crop, and fertilizer types are the most implemented non-livestock-related inputs, while climate- and feed-related costs are the least required. All DSSs assess farm-level mitigation measures, but less than half offer sustainability consultation. These tools promote environmental sustainability by evaluating mitigation strategies, disseminating farm sustainability information, and guiding sustainable farm management. Yet, challenges such as disparate estimation methods, result variations, comparison difficulties, usability concerns, steep learning curves, the lack of automation, the necessity for multiple tools, the limited integration of the results, and changing regulations hinder their wider adoption.
Livestock manure management systems can be significant sources of nitrous oxide (N2O), methane (CH4), and ammonia (NH3) emissions. Many studies have been conducted to improve our understanding of the ...emission processes and to identify influential variables in order to develop mitigation techniques adapted to each manure management step (animal housing, outdoor storage, and manure spreading to land). The international project DATAMAN (http://www.dataman.co.nz) aims to develop a global database on greenhouse gases (N2O, CH4) and NH3 emissions from the manure management chain to refine emission factors (EFs) for national greenhouse gas and NH3 inventories. This paper describes the housing and outdoor storage components of this database. Relevant information for different animal categories, manure types, livestock buildings, outdoor storage, and climatic conditions was collated from published peer reviewed research, conference papers, and existing databases published between 1995 and 2021. In the housing database, 2024 EFs were collated (63% for NH3, 19.5% for CH4, and 17.5% for N2O). The storage database contains 654 NH3 EFs from 16 countries, 243 CH4 EFs from 13 countries, and 421 N2O EFs from 17 countries. Across all gases, dairy cattle and swine production in temperate climate zones are the most represented animal and climate categories. As for the housing database, the number of EFs for the tropical climate zone is under‐represented. The DATAMAN database can be used for the refinement of national inventories and better assessment of the cost‐effectiveness of a range of mitigation strategies.
Core Ideas
Livestock manure management systems are one of the main sources of greenhouse gas and ammonia emissions worldwide.
We built a database of CH4, NH3, and N2O emissions from livestock housing and outdoor manure storage.
The housing database contains 392, 1,281, and 351 emission factors for CH4, NH3, and N2O, respectively.
The storage database contains 243, 654, and 421 emission factors for CH4, NH3, and N2O, respectively.
Due to the lack of studies, not all regions of the world are in the database.
•A modified diet based on attapulgite and benzoic acid for fatteners was tested.•The modified diet enhanced feed efficiency and growth of fatteners.•The modified diet potentially improved the ...environmental performance.•Feed intake and weight gain were decisive for the environmental performance.
Investigation of the combined addition of attapulgite clay and benzoic acid in fattening pig diets seems to be reasonable both from a pig performance and environmental point of view. In this research, an in situ experimental procedure was performed in order to investigate the effect of supplementing the conventional diet (CNVD) supplied to the fattening pigs of a commercial pig farm in Greece (based on maize, barley, wheat bran and soybean meal) with 0.4% w/w attapulgite and 0.5% w/w benzoic acid at the expense of maize (ATTBAD diet) on their feed efficiency and growth performance. The results suggested a significant increase (p ≤ 0.05) in the total weight gain and the slaughter live-weight and a significant decrease (p ≤ 0.05) in the feed intake and feed conversion ratio per fattening pig when supplied the ATTBAD. These results were further used as an input to a ‘cradle-to-farm-gate’ environmental Life Cycle Assessment. The functional unit (FU) was 1 kg of sold pig live-weight and the environmental impact categories (EICs) assessed were climate change (CC) and CC from direct land use change, acidification, eutrophication, land use, water use and fossil energy use. The indicators for all EICs were connected with lower potential estimates per FU in the ATTBAD system, suggesting an improvement of the environmental performance when the ATTBAD is supplied to the fattening pigs of the farm. The improvement of intestinal functionality and enzyme activity, an increase in digesta retention time and a drop of digesta pH in the gastrointestinal tract were indicated as possible causes for the improvement in the growth performance of the fattening pigs when supplied the ATTBAD diet, which however need to be confirmed with further research. The contribution analysis highlighted the importance of the decreased feed intake and the increased total weight gain of the fatteners on the improved environmental performance of the ATTBAD system. The reasonable differences between the indicator estimates of this study and relevant literature, the fair data quality which characterizes the compiled life cycle inventory and the results of the performed Monte Carlo simulation, are considered as a good indication of the validity of the received results and further support the argument of the ATTBAD system's improved environmental performance. Therefore, the use of the ATTBAD instead of the CNVD could potentially offer environmental benefits to the studied supply chain.
Data Driven Service Orchestration for Vehicular Networks Dalgkitsis, Anestis; Mekikis, Prodromos-Vasileios; Antonopoulos, Angelos ...
IEEE transactions on intelligent transportation systems,
2021-July, 2021-7-00, Letnik:
22, Številka:
7
Journal Article
Recenzirano
Odprti dostop
As technology progresses, cars can not only be considered as a transportation medium but also as an intelligent part of the cellular network that generates highly valuable data and offers both ...entertainment and security services to the passengers. Therefore, forthcoming 5G networks are said to enhance Ultra-Reliable Ultra-Low-Latency that will allow for a new breed of services that will disrupt the industry as we know it today. In this work, we devise a unique fusion of Deep Learning based mobility prediction and Genetic Algorithm assisted service orchestration to retain the average service latency minimal by offering personalized service migration, while tightly packing as many services as possible in the edge of the network, for maximizing resource utilization. Through an extensive simulation based on real data, we evaluate the proposed mobility orchestration combination and we find gains in low latency in all examined scenarios.
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