Vulnerability of global food production to extreme climatic events

Yeni, Filiz; Alpas, Hami

doi:10.1016/j.foodres.2017.03.020

Cited by 19 publications

(10 citation statements)

References 62 publications

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“…Flooding of terrains where leafy green vegetables are grown can lead to an increase in the presence of pathogenic microorganisms in irrigation water and/or in the plants, weeks after rainfall (Castro‐Ibáñez, Gil, Tudela, & Allende, ). In fact, extreme rain and/or flooding events can lead to contamination of produce by means of direct contact of contaminated water with the plants, wash‐off, or splashing of pathogenic microorganisms from contaminated soil or manure, or indirectly via contamination of the water sources used for irrigation and production of plants (Cann, Thomas, Salmon, Wyn‐Jones, & Kay, ; Yeni & Alpas, ). The preparation of packaged salads is of concern, as contamination can occur during preparation and packaging (infected handlers; Julien‐Javaux et al., ), as well as during washing (contaminated water or cross contamination among plants; Gombas et al., ).…”

Section: Resultsmentioning

confidence: 99%

“…contaminated water with the plants, wash-off, or splashing of pathogenic microorganisms from contaminated soil or manure, or indirectly via contamination of the water sources used for irrigation and production of plants (Cann, Thomas, Salmon, Wyn-Jones, & Kay, 2013; Yeni & Alpas, 2017). The preparation of packaged salads is of concern, as contamination can occur during preparation and packaging (infected handlers; Julien-Javaux et al, 2019), as well as during washing (contaminated water or cross contamination among plants; Gombas et al, 2017).…”

Section: Resultsmentioning

confidence: 99%

“…Extreme rain can lead to flooding of terrains or run off events that can result in contamination of crops. On the other hand, extreme drought conditions can lead to the utilization of water of lower microbiological quality, due to the lack of potable water, increasing the chances of contamination (Yeni & Alpas, ). Microbial contamination of produce has also been shown to be dependent on growth season (Marine et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Microbial Contamination of Fresh Produce: What, Where, and How?

Machado-Moreira

Richards

Brennan

et al. 2019

Comp Rev Food Sci Food Safe

185

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Promotion of healthier lifestyles has led to an increase in consumption of fresh produce. Such foodstuffs may expose consumers to increased risk of foodborne disease, as often they are not subjected to processing steps to ensure effective removal or inactivation of pathogenic microorganisms before consumption. Consequently, reports of ready‐to‐eat fruit and vegetable related disease outbreak occurrences have increased substantially in recent years, and information regarding these events is often not readily available. Identifying the nature and source of microbial contamination of these foodstuffs is critical for developing appropriate mitigation measures to be implemented by food producers. This review aimed to identify the foodstuffs most susceptible to microbial contamination and the microorganisms responsible for disease outbreaks from information available in peer‐reviewed scientific publications. A total of 571 outbreaks were identified from 1980 to 2016, accounting for 72,855 infections and 173 deaths. Contaminated leafy green vegetables were responsible for 51.7% of reported outbreaks. Contaminated soft fruits caused 27.8% of infections. Pathogenic strains of Escherichia coli and Salmonella, norovirus, and hepatitis A accounted for the majority of cases. Large outbreaks resulted in particular biases such as the observation that contaminated sprouted plants caused 31.8% of deaths. Where known, contamination mainly occurred via contaminated seeds, water, and contaminated food handlers. There is a critical need for standardized datasets regarding all aspects of disease outbreaks, including how foodstuffs are contaminated with pathogenic microorganisms. Providing food business operators with this knowledge will allow them to implement better strategies to improve safety and quality of fresh produce.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Microbial Contamination of Fresh Produce: What, Where, and How?

Machado-Moreira

Richards

Brennan

et al. 2019

Comp Rev Food Sci Food Safe

185

View full text Add to dashboard Cite

show abstract

“…Several studies have attempted to incorporate adaptive capacity in the vulnerability assessment using approaches such as aggregated quantitative indicators [8][9][10] or semi-structured interviews [11][12][13]. Indicators of adaptive capacity were also grounded in sustainable livelihood theory as a set of different forms of assets to which people have access, such as financial, human, resource, or physical assets [14].…”

Section: Introductionmentioning

confidence: 99%

“…Despite the extensive research, improvement is required to identify and choose driving forces and indicators that more accurately determine the relationship between socio-economic factors and vulnerability [17]. Detailed studies along these lines have been recently conducted at the European [7,11,18], Australian [13,16,19], and in few cases at global scales [8,20], but the issue has not been thoroughly addressed in SSA countries. Naumann et al [21] calculated composite indicators that reflect different aspects of vulnerability and adaptive capacity at the Pan-African level.…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Analysis of Socio-Economic Determinants Influencing Crop Drought Vulnerability in Sub-Saharan Africa

et al. 2019

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Drought events have significant impacts on agricultural production in Sub-Saharan Africa (SSA), as agricultural production in most of the countries relies on precipitation. Socio-economic factors have a tremendous influence on whether a farmer or a nation can adapt to these climate stressors. This study aims to examine the extent to which these factors affect maize vulnerability to drought in SSA. To differentiate sensitive regions from resilient ones, we defined a crop drought vulnerability index (CDVI) calculated by comparing recorded yield with expected yield simulated by the Environmental Policy Integrated Climate (EPIC) model during 1990–2012. We then assessed the relationship between CDVI and potential socio-economic variables using regression techniques and identified the influencing variables. The results show that the level of fertilizer use is a highly influential factor on vulnerability. Additionally, countries with higher food production index and better infrastructure are more resilient to drought. The role of the government effectiveness variable was less apparent across the SSA countries due to being generally stationary. Improving adaptations to drought through investing in infrastructure, improving fertilizer distribution, and fostering economic development would contribute to drought resilience.

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