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Hubert Fonteijn; Jim Groot; Xuezhen Guo; Wass. Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain. Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain 2021, 1 .
AMA StyleHubert Fonteijn, Jim Groot, Xuezhen Guo, Wass. Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain. Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain. 2021; ():1.
Chicago/Turabian StyleHubert Fonteijn; Jim Groot; Xuezhen Guo; Wass. 2021. "Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain." Analysing the resilience of food systems with scenario analyses and reverse stress tests : Concepts and an application on the Ethiopian sesame seed value chain , no. : 1.
X. Guo; FBR Supply Chain & Information Management; J.C.M.A. Snels; S. Tromp; Wass. Quality-controlled logistics with internet of things: a conceptual framework. Quality-controlled logistics with internet of things: a conceptual framework 2021, 1 .
AMA StyleX. Guo, FBR Supply Chain & Information Management, J.C.M.A. Snels, S. Tromp, Wass. Quality-controlled logistics with internet of things: a conceptual framework. Quality-controlled logistics with internet of things: a conceptual framework. 2021; ():1.
Chicago/Turabian StyleX. Guo; FBR Supply Chain & Information Management; J.C.M.A. Snels; S. Tromp; Wass. 2021. "Quality-controlled logistics with internet of things: a conceptual framework." Quality-controlled logistics with internet of things: a conceptual framework , no. : 1.
Bio-based supply chains are by nature complex to optimize. The new logistic concept of integrated biomass logistical center (IBLC) provides us the opportunity to make full use of the idle capacity for a food/feed plant to produce biobased products so that the entire chain efficiency can be improved. Although research has been conducted to analyze the IBLC concept, is yet to be an optimization model that can optimally arrange the activities in the supply chain where an IBLC stands in the middle. To fill the knowledge gap in the literature, this paper makes the first step to develop a MILP model that enables biobased supply chain optimization with the IBLC concept, which supports logistic and processing decisions in the chain. The model is applied in a case study for a feed and fodder plant in Spain where managerial insights have been derived for transferring the plant to a profitable IBLC.
Xuezhen Guo; Juliën Voogt; Bert Annevelink; Joost Snels; Argyris Kanellopoulos. Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers. Energies 2020, 13, 6153 .
AMA StyleXuezhen Guo, Juliën Voogt, Bert Annevelink, Joost Snels, Argyris Kanellopoulos. Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers. Energies. 2020; 13 (22):6153.
Chicago/Turabian StyleXuezhen Guo; Juliën Voogt; Bert Annevelink; Joost Snels; Argyris Kanellopoulos. 2020. "Optimizing Resource Utilization in Biomass Supply Chains by Creating Integrated Biomass Logistics Centers." Energies 13, no. 22: 6153.
Reducing food loss and waste (FLW) is prioritized in UN sustainable development goals (SDG) target 12.3 to contribute to “ensure sustainable consumption and production patterns”. It is expected to significantly improve global food security and mitigate greenhouse gas (GHG) emissions. Identifying “hotspots” from different perspectives of sustainability helps to prioritize the food items for which interventions can lead to the largest reduction of FLW-related impacts. Existing studies in this field have limitations, such as having incomplete geographical and food commodity coverage, using outdated data, and focusing on the mass of FLW instead of its nutrient values. To provide renewed and more informative insights, we conducted a global hotspot analysis concerning FLW with its associated GHG emissions and protein losses using the most recent data (the new FAO Food Balance Sheets updated in 2020). The findings of this research are that there were 1.9 Gt of FLW, 2.5 Gt of associated GHG emissions, and 0.1 Gt of associated protein losses globally in 2017. The results of the FLW amounts, GHG emissions, and protein losses per chain link are given on the scale of the entire world and continental regions. Next to this, food items with relatively high FLW, GHG emissions, and protein losses are highlighted to provide the implications to policymakers for better decision making. For example, fruits and vegetables contribute the most to global FLW volumes, but the product with the highest FLW-associated GHG emissions is bovine meat. For bovine meat, FLW-associated GHG emissions are highest at the consumer stage of North America and Oceania. Oil crops are the major source of protein losses in the global food chain. Another important finding with policy implications is that priorities for FLW reduction vary, dependent on prioritized sustainability criteria (e.g., GHG emissions versus protein losses).
Xuezhen Guo; Jan Broeze; Jim Groot; Heike Axmann; Martijntje Vollebregt. A Worldwide Hotspot Analysis on Food Loss and Waste, Associated Greenhouse Gas Emissions, and Protein Losses. Sustainability 2020, 12, 7488 .
AMA StyleXuezhen Guo, Jan Broeze, Jim Groot, Heike Axmann, Martijntje Vollebregt. A Worldwide Hotspot Analysis on Food Loss and Waste, Associated Greenhouse Gas Emissions, and Protein Losses. Sustainability. 2020; 12 (18):7488.
Chicago/Turabian StyleXuezhen Guo; Jan Broeze; Jim Groot; Heike Axmann; Martijntje Vollebregt. 2020. "A Worldwide Hotspot Analysis on Food Loss and Waste, Associated Greenhouse Gas Emissions, and Protein Losses." Sustainability 12, no. 18: 7488.
SUMMARYDecision making on hazard surveillance in livestock product chains is a multi-hazard, multi-stakeholder, and multi-criteria process that includes a variety of decision alternatives. The multi-hazard aspect means that the allocation of the scarce resource for surveillance should be optimized from the point of view of a surveillance portfolio (SP) rather than a single hazard. In this paper, we present a novel conceptual approach for economic optimization of a SP to address the resource allocation problem for a surveillance organization from a theoretical perspective. This approach uses multi-criteria techniques to evaluate the performances of different settings of a SP, taking cost-benefit aspects of surveillance and stakeholders’ preferences into account. The credibility of the approach has also been checked for conceptual validity, data needs and operational validity; the application potentials of the approach are also discussed.
X. Guo; G. D. H. Claassen; A. G. J. M. Oude Lansink; H. W. Saatkamp. A conceptual framework for economic optimization of an animal health surveillance portfolio. Epidemiology and Infection 2015, 144, 1084 -1095.
AMA StyleX. Guo, G. D. H. Claassen, A. G. J. M. Oude Lansink, H. W. Saatkamp. A conceptual framework for economic optimization of an animal health surveillance portfolio. Epidemiology and Infection. 2015; 144 (5):1084-1095.
Chicago/Turabian StyleX. Guo; G. D. H. Claassen; A. G. J. M. Oude Lansink; H. W. Saatkamp. 2015. "A conceptual framework for economic optimization of an animal health surveillance portfolio." Epidemiology and Infection 144, no. 5: 1084-1095.
Economic analysis of hazard surveillance in livestock production chains is essential for surveillance organizations (such as food safety authorities) when making scientifically based decisions on optimization of resource allocation. To enable this, quantitative decision support tools are required at two levels of analysis: (1) single-hazard surveillance system and (2) surveillance portfolio. This paper addresses the first level by presenting a conceptual approach for the economic analysis of single-hazard surveillance systems. The concept includes objective and subjective aspects of single-hazard surveillance system analysis: (1) a simulation part to derive an efficient set of surveillance setups based on the technical surveillance performance parameters (TSPPs) and the corresponding surveillance costs, i.e., objective analysis, and (2) a multi-criteria decision making model to evaluate the impacts of the hazard surveillance, i.e., subjective analysis. The conceptual approach was checked for (1) conceptual validity and (2) data validity. Issues regarding the practical use of the approach, particularly the data requirement, were discussed. We concluded that the conceptual approach is scientifically credible for economic analysis of single-hazard surveillance systems and that the practicability of the approach depends on data availability.
Xuezhen Guo; G.D.H. Claassen; Alfons Oude Lansink; H.W. Saatkamp. A conceptual framework for economic optimization of single hazard surveillance in livestock production chains. Preventive Veterinary Medicine 2014, 114, 188 -200.
AMA StyleXuezhen Guo, G.D.H. Claassen, Alfons Oude Lansink, H.W. Saatkamp. A conceptual framework for economic optimization of single hazard surveillance in livestock production chains. Preventive Veterinary Medicine. 2014; 114 (3-4):188-200.
Chicago/Turabian StyleXuezhen Guo; G.D.H. Claassen; Alfons Oude Lansink; H.W. Saatkamp. 2014. "A conceptual framework for economic optimization of single hazard surveillance in livestock production chains." Preventive Veterinary Medicine 114, no. 3-4: 188-200.