geographical origin (9)


This review examines the potential of non-targeted metabolomic analysis to assess food authenticity. It looks at range of products, which includes wine, rice, olive oil, spices, and honey because they are regarded as the most vulnerable to fraud. The identification of biomarkers  for geographical origin is central theme of the review.

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10742783097?profile=RESIZE_400xEVOO is one of the foods lidentified as being very vulnerable to food fraud. This comprehensive review examines the  application of nuclear magnetic resonance (NMR) spectroscopy to EVOO as a reliable and rapid tool to verify different aspects of its adulteration, such as undeclared blends with cheaper oils and cultivar, and geographical origin mislabelling. NMR makes it possible to use both targeted and untargeted approaches, and to determine the olive oil metabolomic profile and the quantification of its constituents.

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Virgin coconut oil (VCO) is in high demand because of its uses in cooking, frying, as well as being used as an ingredient in food, pharmacy, and cosmetic goods. Given its high consumer demand, there is a need to establish a reliable method for the identification of its geographical origin especially if producers wish to protect regional speciality production. IAEA has collaborated with Indian researchers to develop a method based on multi-elemental analysis of VCO using ICP-MS (inductively coupled plasma mass spectrometry) to differentiate between VCO's from 5 major producing states of Southern India (Kerala, Karnataka, Andhra Pradesh, Tamil Nadu and Goa). Samples of coconuts were collected in each state and VCO prepared in the laboratory, and analysed by ICP-MS.  The concentration of 20 elements in a total of 21 samples were measured, and 17 of these elements (Na, Mg, Al, P, Ca, Cr, Mn, Fe, Ni, Cu, Zn, Se, Rb, Sr, Mo, Cs, Pb) were chosen for chemometric analysis. PCA (Principal Component Analysis), HCA (Hierachical Cluster Analysis), and LDA (Linear Discriminat Analysis) were able to differentiate and classify the VCO samples of different geographical origins.  Further, calibration models based on PCR (Principal Component Regression) and PLS-R (Partial Least Squares Regression) were developed on the calibration dataset of the elemental concentrations, and were able to distinguish between the different geographical origins. Therefore, ICP-MS combined with regression modelling can be used as an excellent tool for the identification of the geographical origin of the VCO samples of various Indian states.

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The Periodic Table of Food Initiative

9701293901?profile=RESIZE_584xFood is at the center of the world’s most urgent challenges and largest opportunities.

According to the World Health Organization, malnutrition is the leading cause of death and disease globally. In fact, there is a “triple burden” of malnutrition at all levels of the population:

  • Undernutrition: The lack of food and/or access to it. 
  • Overnutrition: The consumption of too many calories.  
  • Poor nutrition: Not the right nutritional content (vitamin and mineral deficiencies).

Given advances in the quality and cost of mass spectrometry, bioinformatics, machine learning and big data, along with the growing recognition of the important health impacts of food, the time is ripe for the PTFI.  

The PTFI will strengthen and support ongoing work by developing low–cost mass spectrometry kits, standards, methods, cloud-based analytical tools, and a public database that will include a quantitative and qualitative analysis of 1,000 foods that are representative of geographic and cultural diversity worldwide.

The PTFI will establish a Working Group, composed of experts around the globe, who will inform the selection of the first 2,000 foods based on specific criteria. The overarching goal of this selection process is to ensure inclusivity. The following dimensions we are considering arise out of provocations that help define the plenum of global food options: 

  • Biology: Where in the phylogenetic tree did the organisms that become food originate? 
  • Tissue: What part of organisms are used for food? Entire organisms or portions of plants, animals, or microbes? 
  • Geography: Where do foods originate and where do they thrive? 
  • Consumers: Who are specific foods targeted to? 
  • Processing: Broadly speaking, how are foods treated after “harvest”? 
  • Domestication: How has human intervention modified organisms from their native (wild) state? 
  • Derivation and Formulation: Is the organism (plant, animal, microbe) consumed as a food as is, or is it a derived ingredient in a formulated product or recipe? 
  • Proportional Abundance: From rice to spice – which foods are the center of a meal and the core of a cuisine, and which are tiny fractions of the diet, but can be just as frequently consumed? 
  • Affordability: Which foods are luxury and which are staples? 
  • Frequency: Which foods are consumed on a regular basis and which are associated with rare festive events, life transitions, spiritual celebrations? 
  • Complementarity: Which foods are historically consumed as ensembles? 

Once the database is in place, the scientific community and private sector can build on this public resource by adding analysis of additional foods, varieties, and cooking methods. The PTFI technical platform will enable conditions for a rapid acceleration in research and innovation in both the public and private sectors.

Visit the website for further information.

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9599079487?profile=RESIZE_400x This article in the Guardian newspaper gives some examples of where the determination of geological and ground water isotopes, and trace elements linked to the soil and geography where the food originates, is able to check claims of the origin of the food or crop. Examples are given about fraudulent claims of Egyptian cotton, New Zealand beef, and chocolate from beans sourced in Venezuela/Ivory Coast. It also describes the science behind identifying the country where "Adam" the torso of a young boy found in the water under Tower Bridge in London twenty years ago, spent his life before being taken to England. 

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Basmati rice is a high value rice because of its unique organoleptic properties, and hence is vulnerable to adulteration by non-Basmati varieties. Authentication of Basmati rice has been based on specific varietal identification using DNA markers - microsatellites or more recently KASP markers. Pakistan has designated a specific geographical region for Basmati varieties to be grown and applied to the European Commission for PGI (Protected Geographical Indication) status of its Basmati rice.This study develops a method based on elemental analysis with chemometrics to differentiate rice grown inside and outside the recognised Basmati growing region. Sixty-four rice samples were collected from the Punjab region of Pakistan, 21 from the PGI region and 43 outside this region. Elemental analysis by ICP-MS (inductively coupled plasma-mass spectrometry) of 71 elements was performed on the samples and combined with DD-SIMCA (data-driven soft independent modelling by class analogy) for the differentiation of Pakistani rice grown inside and outside the PGI Basmati growing region, The model obtained achieved a sensitivity and specificity of 100% and 98%, respectively.

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This paper gives an overview of the last 5 years literature in the application of analytical techniques such as liquid and gas chromatography, isotope ratio and elemental analysis, spectroscopic, DNA based and sensor technologies for the authentication of foods of plant origin, with a special focus on geographical origin traceability and authenticity. The review covers fruits, cereals, pulses, tea, coffee, spices, edible oil, fruit juices, and alcoholic beverages. The effectiveness of these techniques at laboratory and industrial level, and also their advantages and drawbacks are discussed.

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Honey is the third most adulterated food globally. This study by Australian researchers examined 100 honey samples from Australia (mainland and Tasmania) along with 18 other countries covering Africa, Asia, Europe, North America and Oceania. Carbon isotopic analyses of honey and protein showed that 27% of commercial honey samples tested were of questionable authenticity. The remaining 69 authentic samples were subject to trace element analysis for geographic determination, and were analysed chemometrically. The trace elements Sr, P, Mn and K were the most useful ones to differentiate honey according to its geographic origin. The findings show the common and prevalent issues of honey authenticity and the mislabelling of its geographic origin can be identified using a combination of stable carbon isotopes and trace element concentrations.

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This paper reviews the use of SIRA of biological isotopes (H, C, O, N, S) in determining geographical origin for meat, poultry and dairy products, and production origin for seafood (wild or farmed). 

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