Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

Biosensors for the analysis of microbiological and chemical contaminants in food

Increases in food production and the ever-present threat of food contamination from microbiological and chemical sources have led the food industry and regulators to pursue rapid, inexpensive methods of analysis to safeguard the health and safety of the consumer. Although sophisticated techniques such as chromatography and spectrometry provide more accurate and conclusive results, screening tests allow a much higher throughput of samples at a lower cost and with less operator training, so larger numbers of samples can be analysed. Biosensors combine a biological recognition element (enzyme, antibody, receptor) with a transducer to produce a measurable signal proportional to the extent of interaction between the recognition element and the analyte. The different uses of the biosensing instrumentation available today are extremely varied, with food analysis as an emerging and growing application. The advantages offered by biosensors over other screening methods such as radioimmunoassay, enzyme-linked immunosorbent assay, fluorescence immunoassay and luminescence immunoassay, with respect to food analysis, include automation, improved reproducibility, speed of analysis and real-time analysis. This article will provide a brief footing in history before reviewing the latest developments in biosensor applications for analysis of food contaminants (January 2007 to December 2010), focusing on the detection of pathogens, toxins, pesticides and veterinary drug residues by biosensors, with emphasis on articles showing data in food matrices. The main areas of development common to these groups of contaminants include multiplexing, the ability to simultaneously analyse a sample for more than one contaminant and portability. Biosensors currently have an important role in food safety; further advances in the technology, reagents and sample handling will surely reinforce this position.

Dietary switching of collembola in grassland soil food webs

Soil food webs are characterised by complex direct and indirect effects among the organisms. Consumption of microorganisms by soil animals is considered as an important factor that contributes to the stability of communities, though cascading effects within the food web can be difficult to detect. In a greenhouse experiment, an addition of a high number the fungal feeding collembola Folsomia quadrioculata was applied to grassland soil food webs in monocultures of three plant species: Plantago lanceolato (forb), Lotus corniculatus (legume) and Holcus lanatus (grass). The abundance of microorganisms, determined as the abundances of phospholipid fatty acids (PLFAs) and the abundances of resident invertebrates, nematodes and collembolans, did not change due to the addition of E quadrioculata. Trophic positions of collembolans were determined by analyses of natural abundances of N-15 stable isotopes. The use of food resources by microorganisms and collembolans was determined by C-13 analysis of microbial PLFAs and solid samples of collembolans. delta C-13 values of the resident collembola Folsomia fimetaria were lower in the presence of E quadrioculata than in the control food webs indicating a use of more depleted C-13 food resources by E fimetaria. The delta N-15 values of E fimetaria did not change at the addition of E quadrioculata thus no change of trophic levels was detected. The switch of E fimetaria to a different food resource could be due to indirect interactions in the food web as the two collembolan species were positioned on different trophic positions, according to different delta N-15 values. (c) 2008 Elsevier Ltd. All rights reserved.

Inorganic arsenic in Chinese food and its cancer risk

Even moderate arsenic exposure may lead to health problems, and thus quantifying inorganic arsenic (iAs) exposure from food for different population groups in China is essential. By analyzing the data from the China National Nutrition and Health Survey (CNNHS) and collecting reported values of iAs in major food groups, we developed a framework of calculating average iAs daily intake for different regions of China. Based on this framework, cancer risks from As in food was deterministically and probabilistically quantified. The article presents estimates for health risk due to the ingestion of food products contaminated with arsenic. Both per individual and for total population estimates were obtained. For the total population, daily iAs intake is around 42 mu g day(-1), and rice is the largest contributor of total iAs intake accounting for about 60%. Incremental lifetime cancer risk from food iAs intake is 106 per 100,000 for adult individuals and the median population cancer risk is 177 per 100,000 varying between regions. Population in the Southern region has a higher cancer risk than that in the Northern region and the total population. Sensitive analysis indicated that cancer slope factor, ingestion rates of rice, aquatic products and iAs concentration in rice were the most relevant variables in the model, as indicated by their higher contribution to variance of the incremental lifetime cancer risk. We conclude that rice may be the largest contributor of iAs through food route for the Chinese people. The population from the South has greater cancer risk than that from the North and the whole population. (C) 2011 Elsevier Ltd. All rights reserved.

Efficacy of Biocides Used in the Modern Food Industry To Control Salmonella enterica, and Links between Biocide Tolerance and Resistance to Clinically Relevant Antimicrobial Compounds

Biocides play an essential role in limiting the spread of infectious disease. The food industry is dependent on these agents, and their increasing use is a matter for concern. Specifically, the emergence of bacteria demonstrating increased tolerance to biocides, coupled with the potential for the development of a phenotype of cross-resistance to clinically important antimicrobial compounds, needs to be assessed. In this study, we investigated the tolerance of a collection of susceptible and multidrug-resistant (MDR) Salmonella enterica strains to a panel of seven commercially available food-grade biocide formulations. We explored their abilities to adapt to these formulations and their active biocidal agents, i.e., triclosan, chlorhexidine, hydrogen peroxide, and benzalkonium chloride, after sequential rounds of in vitro selection. Finally, cross-tolerance of different categories of biocidal formulations, their active agents, and the potential for coselection of resistance to clinically important antibiotics were investigated. Six of seven food-grade biocide formulations were bactericidal at their recommended working concentrations. All showed a reduced activity against both surface-dried and biofilm cultures. A stable phenotype of tolerance to biocide formulations could not be selected. Upon exposure of Salmonella strains to an active biocidal compound, a high-level of tolerance was selected for a number of Salmonella serotypes. No cross-tolerance to the different biocidal agents or food-grade biocide formulations was observed. Most tolerant isolates displayed changes in their patterns of susceptibility to antimicrobial compounds. Food industry biocides are effective against planktonic Salmonella. When exposed to sublethal concentrations of individual active biocidal agents, tolerant isolates may emerge. This emergence was associated with changes in antimicrobial susceptibilities.

Food of the Blue

An episode of BBC Radio 4's detective series 'Baldi'. Paolo Baldi finds himself in a world of superstar academics, but why are their bloodless corpses littering the college? And what is that thing they drink to rejuvenate the venerable institution?

A qualitative study of psychological, social and behavioral barriers to appropriate food portion size control

Background: Given the worldwide prevalence of overweight and obesity, there is a clear need for meaningful practical healthy eating advice - not only in relation to food choice, but also on appropriate food portion sizes. As the majority of portion size research to date has been overwhelmingly quantitative in design, there is a clear need to qualitatively explore consumers’ views in order to fully understand how food portion size decisions are made. Using qualitative methodology this present study aimed to explore consumers’ views about factors influencing their portion size selection and consumption and to identify barriers to appropriate portion size control.

Methods: Ten focus groups with four to nine participants in each were formed with a total of 66 persons (aged 19–64 years) living on the island of Ireland. The semi-structured discussions elicited participants’ perceptions of suggested serving size guidance and explored the influence of personal, social and environmental factors on their food portion size consumption. Audiotapes of the discussions were professionally transcribed verbatim, loaded into NVivo 9, and analysed using an inductive thematic analysis procedure.
Results: The rich descriptive data derived from participants highlight that unhealthy portion size behaviors emanate from various psychological, social and behavioral factors. These bypass reflective and deliberative control, and converge to constitute significant barriers to healthy portion size control. Seven significant barriers to healthy portion size control were apparent: (1) lack of clarity and irrelevance of suggested serving size guidance; (2) guiltless eating; (3) lack of self-control over food cues; (4) distracted eating; (5) social pressures; (6) emotional eating rewards;
and (7) quantification habits ingrained from childhood.

Conclusions: Portion size control strategies should empower consumers to overcome these effects so that the consumption of appropriate food portion sizes becomes automatic and habitual.
Keywords: Food portion size, Barriers, Obesity, Consumers, Qualitative study. © 2013 Spence et al.; licensee BioMed Central Ltd

Food miles or carbon emissions? Exploring labeling preference for food transport footprint with a stated choice study

The ecological footprint of food transport can be communicated using carbon dioxide emissions (CO2 label) or by providing information about both the length of time and the mileage travelled (food miles label). We use stated choice data to estimate conventional unobserved taste heterogeneity models and extend them to a specification that also addresses attribute nonattendance. The implied posterior distributions of the marginal willingness to pay values are compared graphically and are used in validation regressions. We find strong bimodality of taste distribution as the emerging feature, with different groups of subjects having low and high valuations for these labels. The best fitting model shows that CO2 and food miles valuations are much correlated. CO2 valuations can be high even for those respondents expressing low valuations for food miles. However, the reverse is not true. Taken together, the results suggest that consumers tend to value the CO2 label at least as much and sometimes more than the food miles label.