Food traceability: New trends and recent advances. A review

Accepted Manuscript Food Traceability: New Trends and Recent Advances. A Review R. Badia-Melis, P. Mishra, L. Ruiz-García PII:

S0956-7135(15)00269-8

DOI:

10.1016/j.foodcont.2015.05.005

Reference:

JFCO 4439

To appear in:

Food Control

Received Date: 12 February 2015 Revised Date:

27 April 2015

Accepted Date: 5 May 2015

Please cite this article as: Badia-Melis R., Mishra P. & Ruiz-García L., Food Traceability: New Trends and Recent Advances. A Review, Food Control (2015), doi: 10.1016/j.foodcont.2015.05.005. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Food Traceability: New Trends and Recent Advances.

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A Review

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Authors: Badia-Melis, R1; Mishra, P2; Ruiz-García, L.1

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de Madrid, Spain

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Universidad Politécnica de Madrid, CEI-Campus Moncloa. ETSI Agrónomos, Edificio

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Motores, Avda. Complutense s/n, 28040 Madrid, Spain

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Corresponding author. E-mail: [email protected]

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Current traceability systems are characterized by the inability to link food chains

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records, inaccuracy and errors in records and delays in obtaining essential data, which

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are fundamental in case of food outbreak disease; these systems should address the

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recall and withdraw of non-consumable products. The present paper provides a review

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of the various latest technological advancements such as innovative implementations of

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RFID that can make to increase the sales of wheat flour, or allowing the consumer to

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know the full record of the IV range products through the smartphone; knowing the

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food authenticity with an isotope analysis or by analysing the DNA sequences. There

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are also presented some conceptual advancements in the field of food traceability such

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as the development of a common framework towards unifying the present technical

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regulations, the interconnectivity between agents, environment loggers and products, all

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of them in the form of Internet of things system as well as the development of

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intelligent traceability, where it is possible to retrieve the temperature of a product or its

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remaining shelf-life.

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These new techniques and concepts provide new opportunities for enhancing the

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efficiency and compatibility of the present traceability systems.

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Keywords: Food traceability, food control, traceability systems, Internet of Things

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Departamento de Ingeniería Agroforestal. ETSI Agrónomos. Universidad Politécnica

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Laboratorio de Propiedades Físicas y Tecnologías Avanzadas en Agroalimentación,

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Abstract

1.

Introduction

ACCEPTED MANUSCRIPT After a detailed investigation of the true definition of traceability Olsen & Borit (2013),

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came with a compendium of all the definitions saying that traceability is “The ability to

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access any or all information relating to that which is under consideration, throughout

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its entire life cycle, by means of recorded identifications”.

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Food traceability pretends to be of high potential for consumer’s protection by targeting

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precisely the recall, eliminate the non-consumable food products and promoting the

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investigation of the causes of food safety issues; all of that by being an integral part of

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food safety, food quality, food defence and intrinsic requirement of the food supply-

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chain. The worldwide acceptance of the food traceability such as Patagonia traces in

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Argentina (Welt, 2012), merging of GS1 Australia with Efficient Consumer Response

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Australasia (ECRA), supported by the Australian Food and Grocery Council (AFGC)

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and other key government agencies and department to establish a portal for all products

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recall and withdraw (Australia GS1, 2010), National Agriculture and Food Traceability

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System (NAFTS, 2013) in Canada, the embracement of “Internet of Things” and

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establishment of a future cloud computing centre in Shanghai’s Jinshan district to

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ensure food traceability in China (Anon et al., 2011), regulation no. 178/2002 and EU

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Rapid Alert System for Food and Feed (RASFF) in European Union, use of tracking

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and tracing software Grapenet for export of table grapes from India to EU (Buiji et al.,

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2012), introduction of full beef traceability system in Korea (ICT in 2011), the US

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Bioterrorism Act (2001, H.R. 3448) and the Food Modernization and Safety Act

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(FMSA, 2011. H.R. 2751) in USA, further strengthen the faith of global community in

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Food Traceability. Therefore since traceability is a well-known concern for the majority

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of the food industry, a study like the presented here aims to bring some perspective

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about the new trends and recent advances, presenting the newer technological and

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conceptual techniques and showing their novelty.

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Pizzuti, et al. (2014) write about the inability to link food chains records that

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characterizes the current traceability systems, also describes the inaccuracy and errors in

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records and delays in obtaining essential data. The access to this information is key in

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case of a food outbreak disease and it’s necessary for the job of food safety agents.

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Also traceability has driven many issues related to Food crisis management, traceability

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of bulk products, Quality and identity-preservation concerns and Fraud prevention and

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anti-counterfeiting concerns in the past years (Dabbene et al., 2014). USDA Economic

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ACCEPTED MANUSCRIPT Research Service states that besides ensuring a safe food supply, use of traceability

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system results in lower cost distribution systems, reduced recall expenses, and expanded

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sales of products with attributes that are difficult to discern (Golan et al., 2004). Even

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many food producers have good electronic traceability system internally, but exchange

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of information between the links in the supply chain is very time consuming or difficult

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due to the diversity and proprietary nature of the respective internal systems (Storøy et

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al., 2013) hence, they do not realize the true value of using an electronic traceability

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system as the cost of installing technology and operating the system exceeds the

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benefits.

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So there is a need of a change, where all the agents in the supply chain stand to gain,

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there are new trends in the Food Traceability sector focused on improving the processes

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such as Food Track and Trace Ontology (FTTO) and Critical Tracking Point (CTE)

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combined within the TraceFood Framework, can provide new advances for improving

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the efficiency and compatibility of the present traceability system. On one hand the

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Critical Tracking Event provides fast and effective food traceability system (McEntire

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et al., 2010) with security in terms of data ownership, data access and proprietary

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information protection, and Food Track and Trace Ontology provides integration among

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heterogeneous databases enabling inter-operability among different systems (Pizzuti et

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al., 2014), which is not a common fact in Food Traceability, in the other hand

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TraceFood Framework provide principles and guidelines for implementing traceability

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in food value chains. The growing diffusion of new technologies coupled together with

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the availability of new computational and simulation models seems to be significantly

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improving the present value of Food Traceability and would solve the problems of no

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communication between agents and provide a solid and homogeneous line to work,

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instead having a whole variety of rules completely heterogeneous.

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Tracking and tracing can only be effective; if it is implemented as a sector

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encompassing systems approach (Fritz & Schiefer, 2009). In order to do an efficient

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product monitoring, the industries have always required an easily applicable and low

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cost traceability technique, the most recent advances can offer efficiency with the latest

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technologies such as chemometrics modelling, isotope analysis or DNA barcoding

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despite of not being the cheapest techniques. And in the other hand wireless monitoring

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devices are still being improved and implemented in many innovative research studies

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(Zou Z. et al., 2014; Lin Qi et al., 2014; Badia-Melis et al., 2014; Badia-Melis et al.,

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2013; Badia-Melis et al., 2015), with the purpose of bringing an affordable and easy

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way of traceability

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Supply chain visibility is being pushed to a new stage by government regulations and

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consumer requirements; it means that food traceability is becoming a reality, reality that

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will go from “farm to fork” (Min Aung & Seok Chang, 2014). 2. Technological Advancements

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In the recent years as the world has become more global, food traceability has gained

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importance, traditional methods are not enough for certain products and the necessity

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for obtaining food records has increased, the recent advances in terms of technology are

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summarized in the Table 1.

2.1. RFID, still a promising tool for traceability control

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The current advancements in RFID technology and the incorporation of integral parts

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such as data logger capabilities and integrated sensors, has provided a new dimension to

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the application of RFID technology in the food traceability systems, as it is gathered in

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the article of Ruiz-Garcia and Lunadei (2011), the applications of RFID to the food

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traceability are many and varied. During the last decade RFID has emerged as a lead

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actor in the development of traceability systems in the food supply chain and their

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implementations are increasing at a fast rate (Costa et al., 2013). With the

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implementation of RFID technology, food traceability systems can become more

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reliable and efficient since RFID enables a higher reading rate than traditional barcodes

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(Hong et al., 2011). With identification of the products without any physical contact, the

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RFID technology provides effective information sharing with efficient customization

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and handling (Zhang & Li, 2012). Kelepouris (2007) proposed an infrastructure using

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RFID, where it was compared with the traditional lot numbering and internal

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information systems, it has the advantages of automatic identification, uniform EPC for

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all partners, small investment in equipment and easily drawn information.

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Agro-food logistics and supply chain management processes for food traceability using

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RFID are discussed since some years ago by several authors, i.e. Jones et al. (2004),

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Angeles et al. (2005), Twist et al. (2005), Attaran et al. (2007), Ngai et al. (2007),

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Sugahara et al. (2009). Also quality oriented tracking and tracing systems FEFO

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implementing Radio Frequency Identification tags, is a topic argued in the literature

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ACCEPTED MANUSCRIPT (Koutsoumanis et al., 2005; Emond & Nicometo, 2006; Scheer et al., 2006). Amador &

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Emond (2010) developed a system of RFID temperature tracking for combat feeding

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logistics. The capability of hosting sensors of the tags allows the called ‘‘cold

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traceability’’, concept that has been introduced to trace groups of temperature- sensitive

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products are transported in different atmosphere requirements (Ruiz-Garcia et al., 2010)

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A Wheat Flour Milling Traceability System was developed by Qian et al. (2012)

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(WFMTS), incorporating 2D barcode and RFID technology, to validate the system in

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wheat flour mill in China. Labels with a QR Code were used to identify small wheat

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flour packages, and RFID tags were used to identify wheat flour bins and record

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logistics information automatically. They obtained that the total cost of the system

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increased by 17.2% however, with the new system the sales income increased by 32.5%

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and proved the high potential of good application of WFMTS in medium and large

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wheat mill enterprises.

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Feng et al. (2013) developed and evaluated a cattle/beef traceability system, which

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integrated RFID technology with PDA and barcode printer. They obtained real-time and

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accurate data acquisition and transmission, and the high efficiency of information

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tracking and tracing across the cattle/beef supply chain.

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Barge et al. (2014) automatically recorded cheese wheels movements during the

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production, handling in the maturing room and warehouse, delivery, packing and selling

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phases in a dairy factory with the help different techniques by fixing RFID tags to the

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cheese. They considered factors such as tag type and shape, required power, antennas

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polarization and orientation, fixing method and ripening duration to verify their effect

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on reading performance and system reliability.

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Catarinucci, et al. (2011) used a combination between WSN and RFID, in order to

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enhance the traceability of the white wine from vineyard to consumer glass. WSN is a

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wireless technology like RFID also tried in many other authors to improve the

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traceability in food quality (Qi et al., 2014) and aquaculture (Qiet al., 2011).

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An IoT platform with a two-layer network architecture is the innovative way for

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implementing RFID for traceability in what is called "intelligent food logistics" (which

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is discussed further in this article), it consist on an asymmetric tag-reader link (RFID

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ACCEPTED MANUSCRIPT layer) and an ad-hoc link between readers (WSN layer), which are further connected to

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the Internet via cellular or Wi-Fi (Zou et al., 2014).

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RFID barriers

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Some of the Ultra High Frequency tags (bands 860 MHz Europe 915 MHz USA)

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potentially useful and currently used for cold chain monitoring and traceability control

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present the disadvantages of more interferences than other frequencies. These different

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bands are only available in USA and Europe. Japan and China do not allow these

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transmissions (Ruiz-Garcia & Lunadei, 2011).

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The main barriers for implementing the RFID system in cattle/beef traceability system

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are the inapplicable method of inputting information, the inefficient sequence of data

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input and communication mechanism associated with RFID reader, and the high

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implementation cost (Feng et al., 2013).With many advantages of RFID technology it is

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still not a preferable choice of most of the companies as it leads additional cost to the

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company. However, the balance between the benefit and safety requirement of the

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company is the major driving force for the adoption of technologies like RFID (Zhang

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& Li, 2012).

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NFC or Near Field Communication is actually an extension or a subcategory of RFID.

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NFC technology enables simple and safe two-way interactions between electronic

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devices; it complements many popular wireless technologies at consumer level (in the

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existing standards for contactless card technologies ISO/IEC 14443 A&B and JIS-X

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6319-4). NFC enables devices to share information in less than 4 cm (NFC Forum,

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2014). It operates at 13.56 MHz and currently supports data rates of 106, 212, 424 or

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848 Kbit/s (Mainetti et al., 2013a). These tags are made very small so that they can fit

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inside products for various reasons such as security, anti-theft and individual

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identification. NFC is the newer version of RFID that is typically for use in a very short

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distance for making payments (Mainetti, et al., 2012) and information retrieval. Like

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RFID, the main advantage of NFC technology above barcode and QR codes is that it

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does not require a laser beam to have a solid path so that it can travel between two

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devices.

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ACCEPTED MANUSCRIPT Recently, Mainetti et al. (2013b) describe the potentialities from the combination of

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RFID and NFC; it allows the end consumer to know the complete history of the

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purchased product. They implemented the usage of NFC in a IV range products supply

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chain. NFC is proved to work together with a mobile app to allow the linking of plants

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and traceability information (Mainetti et al., 2013a).

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Yu-Yi Chen et al. (2014) propose a scenario in the near future, where the consumer can

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use the smart phone to read passive information and essential parameters, and finally

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safely purchase the food.

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MIT chemists have developed a NFC tag based in chemiresistors that is able to detect

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certain gases. They disrupted the electronic circuit by making a hole in it, and after

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reconnect the circuit with a linker made of carbon nanotubes. When the targeted gas is

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present the conductivity of the nanotubes change and they are able to read the tag with a

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smartphone and detect the presence of the gas (Trafton MIT, 2014).

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2.3 New advances in unique identification and quality of livestock

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In order to reduce the food waste and improve the resources efficiency of food

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production, Mack et al. (2014) developed a quality tracing model for vacuum-packed

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lamb that is applicable in different meat supply chains. It is a system able to register the

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most relevant sensory parameters, then processing the data with Arrhenius model, a

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linear primary model and finishing with a decision support tool, in combination with the

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temperature monitoring equipment for the improvement of quality and storage

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management within the meat logistics network.

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Shanahan et al. (2009) proposed a system of traceability that can be used to identify all

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aspects of beef traceability from farm to slaughter, as they point, an integrated

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traceability system involving all of the stakeholders along the supply chain, can serve to

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increase consumer confidence in beef products by making traceability data accessible to

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the consumer. In their publication they propose the usage of RFID, biometrics and

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identifiers for verification of cattle identity. The final idea is to convert the animal ID

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data to the EPC, in order to facilitate the use of EPC global Network for the exchange of

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traceability data. Also Mc Carthy et al. (2011) wrote about the traditional ear tag in

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calves and its challenges above all the human interaction and the consequent error

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possibility and manipulation, that is why they included in their paper the concept farm-

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ACCEPTED MANUSCRIPT to-fork traceability with the use of GS1-128 barcode. Since the animal is slaughtered

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and divided in quarters a barcode is printed and attached to each quarter with

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information such as carcass number, ear tag number, origin, factory of slaughter and

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some other relevant points, then as the meat is being processed to smaller parts the

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information of the process is recorded, including even the time under cold storage.

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There are certain problems according to Mc Carthy et al. (2011) like the limited data in

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the barcode and the weak integrity of the label in harsh environments. Due to these

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limitations they presented an alternative using RFID tags.

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Mc Inerney et al. (2010) performed a preliminary in vivo study on application of e-

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tracking in poultry using different inks printed 10 x 10 DataMatrix barcodes onto the

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beaks of broiler chickens in a live commercial setting but the results demonstrated very

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poor percentage of readability. However they project future work possibilities, like

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using different kinds of inks, such as delayed effect ink, apply pre- or post-printing

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treatments to the beak or laser printing. These alternative are worthy of investigation in

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the future because the development of an individual identification system for the poultry

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chain would greatly enhance the security of the chain.

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2.4 Traceability for food products and processed food using isotope

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analysis and DNA barcoding

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The term stable isotope is preferably used when speaking of nuclides of a specific

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elements, it usually refers to isotopes of the same element. The relative abundance of

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such stable isotopes can be measured experimentally (isotope analysis), yielding an

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isotope ratio that can be used as a research tool. Stable isotope ratio analysis combined

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with other chemical methods like isotope ratio mass spectroscopy (IRMS), inductively

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coupled plasma mass (ICP-MS), chromatography, near infrared spectroscopy provides a

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promising approach for agro-product authenticity and traceability (Zhao et al., 2014).

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Stable isotope analysis has emerged as a powerful tool for tracing the geographical

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origin of the agro food products. Varying degrees of success has been obtained in

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identifying and differentiating the different agro food products such as meat, milk,

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cereal crops, wine and oil. Horacek & Min (2010) examined for carbon, nitrogen and

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hydrogen isotopes ratio in the defatted dry mass of beef samples from Korea, USA,

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Mexico, Australia and New Zealand and obtained a clear trend of carbon isotope for

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each group of sample and identifying their origin. Perini et al. (2009) with the help of

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ACCEPTED MANUSCRIPT multi-element stable isotope classified the lambs from seven Italian regions according to

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their feeding and obtained a high classification of 97.7 %. Molkentin & Giesemann

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(2007) with the analysis of carbon isotope differentiated the conventional and organic

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milk successfully. Suzuki et al. (2008) clearly differentiated the rice samples from

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different areas of Australia, Japan and USA based on elemental and isotopic

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composition. Dutra et al. (2011) differentiated wines from three different wine making

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regions in south Brazil with the isotopic ratios of oxygen of wine water and carbon of

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ethanol. Camin et al. (2010) classified 95 % of the olive oil samples from 8 European

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sites according to their production areas based on H, C and O stable isotope ratios and

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14 other elements.

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The validation of food authenticity relies mostly on the analysis of proteins and/or DNA

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sequences. Protein-based methods include immunological assays, electrophoretical and

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chromatographic techniques such as HPLC and TLC (Galimberti et al., 2013).

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DNA barcoding has been proven to be particularly effective in the traceability of

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seafood (Becker et al., 2011), this can be considered a reliable method for traceability of

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mammalian meat (Cai et al., 2011) or raw milk (Arcuri et al., 2013), as well as tracing

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system for edible plants (De Mattia et al., 2011). Other uses are encountered also for

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processed food, fruit residues (e.g. banana) in juices, purees, chocolates, cookies, etc.

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(Sakai et al., 2010).

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2.5 Chemometrics and NIRS for food traceability

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Chemometrics is the mathematical and statistical modeling applied to analytical data

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acquired in wide ranges of platforms in order to obtain relevant chemical information.

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The benefits of chemometric models over normal statistical models are that they are

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easy to maintain with good updatability, simple, robust for defective data and also can

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be easily converted into a set of specifications which can help in developing decision

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rules on the authenticity of the origin of food, which is an important consideration for

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traceability studies (Vandeginste, 2013). Synergistic use of instrumental analytical

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techniques and chemometrics modeling represents a promising way for the development

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of authenticity and traceability models, as traceability of food is an essential element in

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ensuring safety and high quality of food (Bertacchini et al., 2013).

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ACCEPTED MANUSCRIPT Cozzolino (2014) performed a review regarding the use of near infrared (NIR)

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spectroscopy and mid infrared (MIR) spectroscopy combined with multivariate data

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analysis such as such as principal component analysis (PCA), partial least squares

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discriminant analysis (PLS-DA), linear discriminant analysis (LDA) to aid on the

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authentication and traceability of cereals. He stated and concluded that the development

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of new spectroscopy technologies such as hyper spectral imaging, micro spectroscopy

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combine with new algorithms will enhance the use of spectroscopy as one of the most

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useful tools for traceability and authentication of cereals.

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Bevilacqua et al. (2012) used mid- and near-infrared spectroscopic techniques and

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chemometric methods for the traceability of extra virgin olive oil samples. Their results

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concluded that infrared spectroscopy with chemometrics being a fast, relatively cheap

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and non-invasive/non-destructive analysis is a powerful tool for the traceability of olive

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oil.

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Versari et al. (2014) reviewed typification and authentication of wine and found that

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analytical chemistry tools, used in combination with chemometric analyses are well

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successful on the discrimination and classification of wines. Thus improved

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classification power can be helpful in traceability of wine.

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Consonni & Cagliani (2010) successfully used Near Magnetic Resonance (NMR) with

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chemometrics to access geographical origin and quality of traditional food products.

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Ren et al. (2013) used Near-infrared spectroscopy (NIRS) combined with chemometrics

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as a rapid analysis method to assess quality and to differentiate geographical origins of

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black tea. Their study demonstrated that determine regarding the main chemical

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compositions and geographical origins of black tea can be made successfully and

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rapidly with NIR spectroscopy.

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It has been proven that near-infrared spectroscopy (NIRS) combined with chemometric

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methods are able to predict the geographic origin of wheat grain. 76% of the wheat

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grain samples were classified correctly and in the case of the flour between 90% to 96%

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(Gonzalez-Martin et al., 2014).

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3. Conceptual advancements 3.1. The concept of Critical Tracking Events and Key Data Elements

ACCEPTED MANUSCRIPT The Critical Tracking Event (CTE) concept is flexible, scalable, adaptive, efficient and

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interconnected and that is the reason why it can simplify the food logistics supply chain

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by identifying the smallest and the most useful units in the supply chain (Welt et al.,

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2012). CTE provides traceability by combining latest tools and technologies for

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targeting the main sources of actual interest of the investigation to provide an easily

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understandable, fast and accurate recall. CTE changes its approach from being specific

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to food products for collecting data than to more focus on the events that manipulate the

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products in the supply chain. The events are viewed and corresponding data related to

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specific locations, dates and times are stored for future recall (Miller et al., 2014).

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Miller et al. (2014), provided the classification of CTEs by dividing the supply chain

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into four main categories i.e. Terminal CTEs, Aggregation/Disaggregation CTEs,

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Transfer CTEs and Commingling CTEs. Terminal CTEs are the events existing at the

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terminals

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Aggregation/Disaggregation CTEs are events followed by terminal CTEs such as

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packaging. Transfer CTEs are associated with any movement of the products in the

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supply chain for example shipping, receiving, and loading on truck. Commingling CTEs

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are the events which arise when a new product is formed by using different products

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from different sources.

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CTEs have certain advantages over the other concepts of food traceability. In CTEs,

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while maintaining ownership and control of the CTE data, operators are free to choose

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the methods and technologies according to their requirements and availability. Also, an

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immediate universal participation is not a requirement of the CTEs to benefit from it

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(Welt et al., 2012). An example of CTEs is use of shopper-cased data and the event data

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together. This data can be queried by investigators by consciously designed Critical

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Tracking Events at critical points in the supply chain to better facilitate product tracing.

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3.2. Food Track and Trace Ontology (FTTO) model

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Ontology is an explicit formal specification of terms in the domain and relations among

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them (Kim et al. 1995), supports the management of a unique body of knowledge

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through the integration of different concepts and terms coming from heterogeneous

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sources of information and users involved in the supply chain (Pizzuti et al., 2014).

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Many authors have focussed their work on the definition of ontologies but remained

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specified on a specific product or on a particular class of products, such as fruits and

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(Easwaran & Thottupuram, 2011), wine (Graça et al., 2005; Noy & McGuinness, 2001),

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pizza (Drummond et al., 2007). However, their work can be reused and correctly

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implemented for the definition of the Global Food Track and Trace Ontology (FTTO)

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for traceability purpose (Pizzuti et al., 2014).

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The FTTO ontology consists of the following main classes: •

manipulation.

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Food Product: This class include ingredients such as salt, spices, sugar, oil and vinegar and food products in the form of raw material or manipulated products.

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Agent: An agent is an entity or actor involved in the process of food

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Service Product: These are the product used during the manipulation of raw material (or unprocessed food) or during the transformation phase, such as

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phytosanitary products, colouring, and flavouring and food additives. It includes

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also material for packaging and container of products.

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Process: Business processes and agro-food processes are included in this class.

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3.3.The TraceFood Framework

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Several different definitions and principles of traceability are currently being applied,

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which make the concept of traceability confusing. There is no common theoretical

363

framework with respect to implementation of food traceability (Karlsen et al. 2013).

364

However, there is a joint collaboration of many EU-funded projects TraceFood

365

Framework, dealing with traceability of food products. The TraceFood Framework has

366

been designed to provide an international, non-proprietary standard for electronic

367

exchange of data related to Food Traceability. With recommendations for “Good

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Traceability Practice”, common principles for unique identification of food items, a

369

common generic standard for electronic exchange of traceability information

370

(TraceCore XML) and sector-specific ontologies it describes how a message can be

371

constructed, sent and received and also how the data elements in the messages should be

372

identified, measured and interpreted (Storøy et al., 2013).

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The framework consists of the following components (TraceFood Wiki, 2009).

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Documentation of transformations of products

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Generic language for electronic exchange of information

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Sector-specific language

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Generic guidelines for implementation of traceability

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Sector-specific guidelines

Both FTTO like the Trace Food Framework are focused on the information

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management but each in a different way, as it is showed in Table 2.

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3.4. Internet of Things

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The Internet of Things (IoT) is a network that combines everyday objects with the

385

ability to identify and interact with each other to reach cooperation goals (Giusto et al.

386

2010). Its purpose is that all the items can be perceived and controlled remotely, and

387

combined with the internet to form a more wisdom production and living systems. IoT

388

describes a world where humans are surrounded by machines that communicate with

389

each other and can allow people to interact with the digital world. The concept of IoT

390

break the traditional ideas and start a new technology field, it will bring a new

391

revolution of world information industry after the computer, internet and mobile

392

communication network.

393

Internet of things is an infrastructure to facilitate the information exchange of products

394

(Atzori et al. 2010 and Leonardo et al. 2011). The system itself is composed of three

395

dimensions which contain information items, independent networks and intelligent

396

applications. Information items are those that can identify and perceive their own

397

message; independent networks have the capabilities of self-configuration, self-healing,

398

self-optimizing, self-protection; intelligent applications mean the application with the

399

capabilities of intelligent control and processing.

400

RFID can enhance the efficiency of Food chain by storing the meaningful information

401

such as producing area, the planting methods, the producing process and other special

402

information that consumer will consider about them when they purchase products

403

(Zhang & Li, 2012). The conceptual sensor data integration has been exploited the

404

classification approach by using the EPC in RFID (Theodorou et al. 2007). Dimitris

405

(2011) introduced the “intelligent products”, which are meant to be used in the IoT.

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Atzori et al. (2010) describe in their article how EPC is a mean to support the spread

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use of RFID in world-wide modern trading networks, and to create the industry-driven

408

global standards for the EPCglobal Network™. These standards are mainly designed to

409

improve object visibility (i.e. the traceability of an object and the awareness of its status,

410

current location, etc.).

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3.5. Intelligent traceability inside intelligent food logistics

412

After an extensive review of many studies, Bosona & Gebresenbet (2013) concluded

414

that food traceability should be considered as an important and integral part of logistics

415

management, so the information is stored on the go and it can be retrieved at any

416

moment.

417

The term intelligent food logistics is becoming and important topic about food chain,

418

meantime, as described by Jederman et al. (2014a), intelligent food logistics are called

419

to reduce the perishable waste along the food supply chain by means of reduction of the

420

deviation from the optimal cold chain, to do that it is necessary to quantify these

421

deviations, making shelf life variation know and remote monitoring.

422

In the other hand, traceability as is described in the introduction of this document, is an

423

integral part of food safety, food quality and food defence which make it part of the

424

food supply-chain, pretends to be of high potential for the protection of consumers.

425

Both intelligent logistics like traceability are happening during the supply chain.

426

As Scheen (2006) described in his article, the data obtained in the traditional tracking

427

and tracing (T&T) systems are usually used only to recall management, nonetheless the

428

proposed quality oriented tracking and tracing system (QTT) uses the information

429

retrieved with what we could call intelligent logistic tools, such as wireless sensors

430

(temperature and humidity for instance).

431

The QTT concept represents a perfect alliance between logistics and traceability,

432

improving the supply chain. Jedermann et al. (2014b) published how the integration of

433

QTT and FEFO (first expire first out) using shelf life models, can enhance the demand

434

and supply chain. Jack et al. (2007) also emphasizes in the implementation of quality

435

controlled logistics in the food supply chain networks, if the product quality can be

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predicted in advance it can lead to a better goods flow and better chain design.

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ACCEPTED MANUSCRIPT Ruiz Garcia et al. (2010) proposed a web-based system for data processing, storage and

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transfer. It integrates all information along the food and feed chain, oriented for the

439

needs of the consumer.

440

Fuzzy Cognitive Maps (FCM)

441

This system can also help improving intelligent traceability. First introduced by Kosko

442

(1986). A FCM consists of nodes and weighted arcs. Nodes represent concepts or states.

443

A FCM is composed of concept node of a problem, signed directed arrows, and

444

causality value among the other nodes. Glykas (2010) gathers some of the most

445

important applications of FCM in the food supply chain.

446

Thakur et al. (2011) present that state and transitions (nodes and arcs) can be used for

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modelling food traceability information.

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3.6. Traceability normative and legal advances worldwide As it is gathered in the European Commission Health and Consumers. (2010, p. 15,

451

Article 3 Point 15) tracing and tracking became mandatory by legislation in 2005 by EU

452

as “the ability to trace and follow a food, feed, food-producing animal or substance

453

through all stages of production and distribution”.

454

The requirements gathered in this regulation are low and restrict themselves to a

455

documentation of supplier and customer relationships, failing to require the monitoring

456

of batches inside enterprises or any further specifics on a system’s quality as, e.g. speed

457

of analysis etc. (Regattieri et al. 2007).

458

In September 2011, the U.S. Food and Drug Administration (FDA) asked the Institute

459

of Food Technologists (IFT) to execute product tracing pilot projects (Bhatt et al.,

460

2013c) and to address how to meet the growing requirement for agriculture and food

461

traceability (Bhatt et al., 2013a).

462

Although any forthcoming actions from the US FDA are unknown, industry fully

463

expects that improvements in product tracing will be necessary. While the ability to

464

rapidly link products across the supply chain serves as an ideal goal, there are still

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466

(Newsome et al., 2013).

467

IFT's Traceability Improvement Initiative aims to advance work in the area of food

468

product tracing through several means, pilots or implementation studies in seafood,

469

dairy, and other industries (Bhatt et al., 2013b).

470

The objectives of the pilot projects were 1) to identify and gather information on

471

methods to improve product tracing of foods in the supply chain and 2) to explore and

472

evaluate methods to rapidly and effectively identify the recipient of food to prevent or

473

mitigate a foodborne illness outbreak and to address credible threats of serious adverse

474

health consequences or death to humans or animals (Bhatt et al., 2013c).

475

IFT found inconsistencies in terminology, numbering systems, formatting while the

476

participants appeared to have the tools and processes required for the tracking process.

477

IFT developed some recommendations to allow rapid effective investigations during

478

foodborne illness outbreaks which lead to enhance protection of public health (Bhatt et

479

al., 2013c).

480

Better information management can provide a return of investment if the data is well

481

managed. Standards in data and interoperability of technology were approached by the

482

report of Bhatt et al. (2013b). The first approach “one up/one down" by requiring

483

electronic records has the benefits low cost of implementation, resulting in a higher

484

probability of adoption. The major disadvantage to this process is the longer response

485

time required during a trace (back or forward).

486

The second approach is similar to a "pedigree", historical information about the food. A

487

major advantage of this approach is the quickest response time during a trace. Some of

488

the disadvantage is a big volume of data.

489

The third approach requires individual nodes to maintain electronic records for its own

490

data and make them available for querying during a traceback for outbreak

491

investigation. The major advantage of this approach is the protection of confidential

492

information and quick access during a trace. However, the primary disadvantage of this

493

approach is the need for greater computational power.

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ACCEPTED MANUSCRIPT Bhatt & Zhang (2013) conducted a study analysing product tracing information to

495

identify the contaminated ingredient and likely source, as well as distribution of the

496

product. It also determined if these systems can work together to better secure the food

497

supply (their interoperability). IFT provided supply-chain data for one complex product

498

to 9 products tracing technology providers, and then compared and contrasted their

499

effectiveness at analysing product tracing information to identify the contaminated

500

ingredient and likely source. Only 6 were able to provide the data required and only 4 of

501

them were able to provide the evidence of the contamination. Nonetheless they also

502

demonstrated this interoperability capability mandatory by the U.S. FDA.

503

As these systems get deployed by clients in the food industry, interoperability will no

504

longer be an afterthought but will be built into their traceability systems (Bhatt & Zhang

505

2013)

506 507 508

4. Conclusions

509

certain increment in efficiency and effectiveness. Nowadays it is possible to achieve

510

essential information by using RFID during the food supply chain and NFC when the

511

product arrives to the end consumer, this wireless monitoring devices have been

512

improved for the past few years, they offer control in situ or in the moment while the

513

goods are on the go; nonetheless none are capable to fulfil all the requirements of the

514

nowadays heterogeneous food supply chains. The very new advancements (DNA

515

barcoding, chemometrics…) can cover some of the gaps, like the disease spreading or

516

historical control, but these technologies are in testing phases or require a big

517

deployment of resources not affordable for all the agents of the food chain, therefore it

518

is assumed that they will not become an alternative in the short term.

519

New trends are about how to aboard the traceability, this means a whole new point of

520

view of traceability, focusing in the parts implicated in the food supply chain such as

521

agents involved, processes, elements added to the food and the product itself which was

522

the only objet of study before these new trends. In the same line, the CTE are focusing

523

in the events that manipulate the products in the supply chain. Also the way of acquiring

524

the data and transmitting it is becoming more standardized, thank to concepts like the

525

Trace Food Framework.

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The most recent advances in food traceability in terms of technology are able to provide

ACCEPTED MANUSCRIPT Food traceability is having new uses since these new traceability concepts are pointing

527

to register not only the origin of the products but new parameters integrated in the

528

intelligent logistics, so it is possible to know the quality of the product and therefore

529

enhance the chain design and the goods flow. The connection between identifiers or,

530

environment/event loggers, allows a dynamic traceability of quality, and finally it is

531

possible to achieve a homogeneous traceability system.

532

In the future it would be expected the possibility of having the traceability information

533

absolutely centralized across the supply chain, being able to access at any moment in

534

order to act in case it would be necessary. This possibility seems to be still a bit far in

535

time, since it is showed in this article that the research performed by the FDA in US

536

proved that the continuous traceability during the supply chain is very difficult to

537

achieve.

538

Another great challenge is to engage the technology and the conceptual advancements

539

together, future research can be directed on implementing these two topics, for the

540

moment intelligent food logistics is advancing in that direction.

541

Acknowledgements

542

To the research project “A Traceability and Early warning system for supply chain of

543

Agricultural Product: complementarities between EU and China (TEAP)”, with the

544

reference: PIRSES-GA-2013-612659. This is a Marie Curie International Research

545

Staff Exchange Scheme (IRSES) action funded by the European Commission, in the

546

Seventh Framework Program.

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ACCEPTED MANUSCRIPT Concept

Author

Higher reading rate than traditional barcodes.

Hong et al. (2011)

RFID proved better than lot numbering.

Kelepouris (2007)

Cold traceability for combat feeding logistics.

Amador and Emond (2010)

Cold traceability for temperature sensitive products.

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Wheat Flour Milling Traceability System. RFID

RI PT

Technology

Qian et al. (2012)

Integration of RFID and Barcode printer for cattle/beef

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Cheese wheels tracking.

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supply chain.

M AN U

Enhance the traceability of the white wine.

Zou et al. (2014)

End consumer knows the history of the product.

Mainetti et al. (2013b)

IV gama products traceability information.

Mainetti et al. (2013a)

Safely purchase the food.

Yu-Yi Chen et al. (2014)

Gas detector in NFC tag.

Trafton MIT, (2014)

Quality tracing model for vacuum-packed lamb.

Mack et al. (2014)

and quality of

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Shanahan et al., (2009)

cattle identity.

Farm-to-fork traceability using GS1-128 barcode.

Mc Carthy et al. (2011)

DataMatrix barcodes onto the beaks of chickens.

Mc Inerney et al. (2010)

AC C

livestock

RFID, biometrics and identifiers for verification of

EP

identification

Catarinucci, et al. (2011)

Intelligent food logistics.

NFC

Unique

Barge et al. (2014)

Approach for agro-product authenticity and Zhao et al. (2014)

traceability using isotope analysis. Horacek and Min (2010);

Identification of isotopes of beef and lamb. Perini et al. (2009)

Isotope analysis Molkentin and Giesemann (2007); Suzuki et al. (2008); Classification of milk, rice, wine and olive oil. Dutra et al. (2011); Camin et al. (2010)

ACCEPTED MANUSCRIPT Cozzolino (2014); Bevilacqua Traceability of cereals, olive oil, tea and wheat grain

et al. (2012); Ren et al.

using NIR and MIR.

(2013); Gonzalez-Martin et

Chemometrics

al. (2014).

and NIRS Near Magnetic Resonance for geographical origin and

Chemometrics analysis for wine identification.

Versari et al. (2014)

DNA analysis applied for traceability of seafood, meat,

Becker et al. (2011); Cai et al.

milk, edible plants and processed food and fruit

(2011); Arcuri et al. (2013);

AC C

EP

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residues.

De Mattia et al. (2011)

SC

DNA barcoding

RI PT

Consonni and Cagliani (2010) quality of traditional food products.

ACCEPTED MANUSCRIPT

Base

FTTO

The Trace Food Framework

Unique body of knowledge

International standard

Focusing on the sources of

Focusing on electronic

information

information for data exchange

Agents involved in any process

Unique ID

Food product, raw or

Documentation of product

manipulated

transformation

Service product, which has any

Generic and specific language

intervention in the food life

for e-exchange information

Process that the food has

Generic and specific guidelines

for traceability implementation

AC C

EP

TE D

M AN U

suffered

SC

Parts

RI PT

Focus