Sorting for Defects and Visual Quality Attributes

Bollen, A. F.; Prussia, Stanley E.

doi:10.1016/b978-0-12-374112-7.00014-7

Cited by 3 publications

(5 citation statements)

References 26 publications

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“…There are alternative framings of the classification problem, such as that described by signal detection theory (SDT; Bollen and Prussia, 2009). SDT theory uses similar concepts to the classification statistics described above but then narrowly frames the problem as the detection of one distinct 'signal' population within another, for instance, of two distinctly different normally distributed populations of differing means and standard deviations.…”

Section: Figurementioning

confidence: 99%

Sampling and statistics in assessment of fresh produce

Walsh¹,

McGlone²,

Wohlers³

2021

Burleigh Dodds Series in Agricultural Science

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New measurement technologies are facilitating new approaches to the improvement of safety and quality in agri-food supply chains. However, measurement uncertainty and choice of sampling strategy can influence the outcomes of assessment programmes. This chapter provides a sampler of calculations of population statistics, required sample sizes and approaches to developing and implementing a sampling strategy. While examples from the fresh produce sector are given, the sampler is of relevance to both the student and the practitioner operating in agri-supply chains more generally.

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Section: Figurementioning

confidence: 99%

Sampling and statistics in assessment of fresh produce

Walsh¹,

McGlone²,

Wohlers³

2021

Burleigh Dodds Series in Agricultural Science

View full text Add to dashboard Cite

show abstract

“…supply chain coordination) (Ahumada & Villalobos, 2009;Rong et al, 2009;East, 2011) or from a quality control perspective (e.g. temperature control) (Bollen & Prussia, 2009;Kader, 2010). The interventions seldom consider concurrently improving quality control and logistics control along the supply chain.…”

Section: Problem Statementmentioning

confidence: 99%

“…During quality control, the decision on sampling design, which includes sampling location and number of samples, is important in relation to the PHL. A sample that does not represent the quality of the whole batch can result in acceptance of a poor quality products that will be rejcted by the customers (Bollen & Prussia, 2009). Furthermore, inadequacies in technological expertise and operators'…”

Section: Tactical Decisionsmentioning

confidence: 99%

“…Daily decisions on corrective action to take on non-conforming products and out-of-specification process conditions can influence PHL. Inadequate product control during grading can result in spoiled products being mixed with good quality products, increasing chances for the products to be rejected by customers (Bollen & Prussia, 2009). Furthermore, inadequate monitoring and control of temperature during storage can affect quality deterioration leading to spoiled products (Shewfelt & Prussia, 2009).…”

Section: Operational Decisionsmentioning

confidence: 99%

“…These investments could further mitigate vulnerability to PHL inherent to the farmers' context and are long-term investments. Examples of such interventions in quality control are automated grading and packing systems (Bollen & Prussia, 2009), use of intelligent packaging material (Jedermann et al, 2014). Using of refrigerated trucks to transport the produce (Yahia, 2010) and having all logistics activities determined based on real-time product quality information (van der Vorst et al, 2011) are examples of interventions in logistics control.…”

Section: Proposed Interventions For Postharvest Loss Reduction In Thementioning

confidence: 99%

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Understanding the influence of context characteristics, logistics control and quality control on postharvest losses : a case of Zimbabwean tomato supply chains

Macheka

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1.1 Background Approximately 1.3 billion tonnes of fresh food crops produced in the world for human consumption, amounting to roughly US$ 680 billion in developed countries and US$ 310 billion in developing countries, is lost after harvest every year (Gustavsson et al., 2011). Agriculture, especially the production of fruit and vegetables, is the mainstay of the economy for most Sub-Saharan African countries. Production of fruit and vegetables in Sub-Saharan Africa as of 2014, is approximated at 34.22 and 31.95 million tonnes, respectively (FAOSTAT, 2016). However, fresh produce chains are characterised by high postharvest losses (PHL), which can occur at all stages and processes between harvesting and consumption (James & Zikankuba, 2017). PHL in fresh produce chains in Sub-Saharan Africa ranges from 30 to 50% (Kitinoja et al., 2011; Affognon et al., 2015). The high PHL are a major obstacle in achieving sustainable fresh produce chains (Hodges et al., 2010). Sustainable food supply chains consider the environmental, social, and economic aspects of supply chain operations (Soysal et al., 2012; Mota et al., 2015; Zhu et al., 2018). The UK Sustainable Development Commission (DEFRA, 2002) described sustainable food supply chains as those that: (i) produce safe, healthy products in response to market demands, (ii) enable viable livelihoods to be made from sustainable land management, (iii) respect and operate within the biological limits of natural resources, (iv) achieve consistently high standards of environmental performance, (v) ensure a safe and hygienic working environment and high social welfare, and (vi) sustain the resource available for growing food. Considering this description of sustainable food chains, PHL have repercussions on sustainability of fresh produce chains as they translate to loss of production resources, such as water and crop land used for production, and loss in income for the various actors in the supply chain (Prusky, 2011). With the world population expected to balloon to nine billion by 2050, food insecurity is likely to worsen if measures are not put in place to minimise loss of the available food (Parfitt et al., 2010). PHL reduction can contribute to increasing food availability, eliminating hunger and improving farmers' livelihoods (Kasso & Bekele, 2016; Kumar & Kalita, 2017). However, the complexity of PHL requires to get insight into the multiple factors causing PHL. Despite many intervention strategies having been proposed in literature, PHL still remain a persistent problem, presenting an enormous threat to food security (Affognon et al., Chapter 1 2015). Hence, there is an urgent need for understanding the multiple causes of PHL to develop strategies for reduction. 1.1.1 Multiple causes of postharvest losses in fresh produce chains Fruit and vegetables are highly perishable in nature and are characterised by high moisture content, active metabolism, and are highly prone to mechanical damage, leading to pathological decay. These characteristics set high requirements to achieve ...

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