Impacts of Milk Fraud on Food Safety and Nutrition with Special Emphasis on Developing Countries

Milk in its natural form has a high food value, since it is comprised of a wide variety of nutrients which are essential for proper growth and maintenance of the human body. In recent decades, there has been an upsurge in milk consumption worldwide, especially in developing countries, and it is now forming a significant part of the diet for a high proportion of the global population. As a result of the increased demand, in addition to the growth in competition in the dairy market and the increasing complexity of the supply chain, some unscrupulous producers are indulging in milk fraud. This malpractice has become a common problem in the developing countries, which lack strict vigilance by food safety authorities. Milk is often subjected to fraud (by means of adulteration) for financial gain, but it can also be adulterated due to ill-informed attempts to improve hygiene conditions. Water is the most common adulterant used, which decreases the nutritional value of milk. If the water is contaminated, for example, with chemicals or pathogens, this poses a serious health risk for consumers. To the diluted milk, inferior cheaper materials may be added such as reconstituted milk powder, urea, and cane sugar, even more hazardous chemicals including melamine, formalin, caustic soda, and detergents. These additions have the potential to cause serious health-related problems. This review aims to investigate the impacts of milk fraud on nutrition and food safety, and it points out the potential adverse human health effects associated with the consumption of adulterated milk.

Food fraud and consumers' choices in the wake of the horsemeat scandal

Purpose – In 2012, the European food industry was hit by a food fraud: horsemeat was found in
pre-prepared foods, without any declaration on the package. This is commonly referred to as the
“horsemeat scandal”. The purpose of this paper is to investigate consumers’ preferences across
Europe for a selected ready meal, ready to heat (RTH) fresh lasagne, to consider whether the effects of
potential food frauds on consumers’ choices can be mitigated by introducing enhanced standards of
RTH products.
Design/methodology/approach – An online survey was administered to 4,598 consumers of RTH
lasagne in six European countries (Republic of Ireland, France, Italy, Spain, Germany and Norway),
applying discrete choice experiments to estimate consumers’ willingness to pay for enhanced food
safety standards and highlight differences between countries.
Findings – Many similarities across countries emerged, as well as some differences. Consumers in
Europe are highly concerned with the authenticity of the meat in ready meals and strongly prefer to
know that ingredients are nationally sourced. Strong regional differences in price premiums exist for
enhanced food safety standards.
Originality/value – This research adds relevant insights in the analysis of consumers’ reaction to
food fraud, providing practical guidelines on the most appropriate practices that producers should
adopt and on the information to reduce food risk perception among consumers. This would prove
beneficial for the food processing industry and the European Union. The survey is based on a
representative sample of European consumers making this the largest cross-country study of this kind.

Copyright, Licences, and Statutory Fraud

In this article we explore the interplay between the law of copyright, contract, and statutory fraud within the digital environment, and in particular with respect to the business of commercial image licensing within the UK.

Point-and-shoot: rapid quantitative detection methods for on-site food fraud analysis – moving out of the laboratory and into the food supply chain

Major food adulteration and contamination events occur with alarming regularity and are known to be episodic, with the question being not if but when another large-scale food safety/integrity incident will occur. Indeed, the challenges of maintaining food security are now internationally recognised. The ever increasing scale and complexity of food supply networks can lead to them becoming significantly more vulnerable to fraud and contamination, and potentially dysfunctional. This can make the task of deciding which analytical methods are more suitable to collect and analyse (bio)chemical data within complex food supply chains, at targeted points of vulnerability, that much more challenging. It is evident that those working within and associated with the food industry are seeking rapid, user-friendly methods to detect food fraud and contamination, and rapid/high-throughput screening methods for the analysis of food in general. In addition to being robust and reproducible, these methods should be portable and ideally handheld and/or remote sensor devices, that can be taken to or be positioned on/at-line at points of vulnerability along complex food supply networks and require a minimum amount of background training to acquire information rich data rapidly (ergo point-and-shoot). Here we briefly discuss a range of spectrometry and spectroscopy based approaches, many of which are commercially available, as well as other methods currently under development. We discuss a future perspective of how this range of detection methods in the growing sensor portfolio, along with developments in computational and information sciences such as predictive computing and the Internet of Things, will together form systems- and technology-based approaches that significantly reduce the areas of vulnerability to food crime within food supply chains. As food fraud is a problem of systems and therefore requires systems level solutions and thinking.

The current and potential applications of Ambient Mass Spectrometry in detecting food fraud

The adulteration of food has received substantial amounts of media attention in the last few years, with events such as the European horsemeat scandal in 2013 sending shockwaves through society. Almost all cases are motivated by the pursuit of profits and are often aided by long and complex supply chains. In the past few years, the rapid growth of ambient mass spectrometry (AMS) has been remarkable, with over thirty different ambient ionisation techniques available. Due to the increasing concerns of the food industry and regulators worldwide, AMS is now being utilised to investigate whether or not it can generate results which are faster yet comparable to those of conventional techniques. This article reviews some aspects of the adulteration of food and its impact on the economy and the public's health, the background to ambient mass spectrometry and the studies that have been undertaken to detect food adulteration using this technology.

Geological fakes and frauds

Some geological fakes and frauds are carried out solely for financial gain (mining fraud), whereas others maybe have increasing aesthetic appeal (faked fossils) or academic advancement (fabricated data) as their motive. All types of geological fake or fraud can be ingenious and sophisticated, as demonstrated in this article. Fake gems, faked fossils and mining fraud are common examples where monetary profit is to blame: nonetheless these may impact both scientific theory and the reputation of geologists and Earth scientists. The substitution or fabrication of both physical and intellectual data also occurs for no direct financial gain, such as career advancement or establishment of belief (e.g. evolution vs. creationism). Knowledge of such fakes and frauds may assist in spotting undetected geological crimes: application of geoforensic techniques helps the scientific community to detect such activity, which ultimately undermines scientific integrity.

Identifying oil species in oil mixtures

Detection of adulteration of non-processed vegetable oil with lesser value seed oils (classic example is hazelnut in virgin olive oil) has been in the centre of scientific attention for many years and several chemical methods were proposed. The recent EC Regulation 1169/2011, however, introduces necessity for different analytical method in a more complicated matrix. From the end of 2014, food businesses required to declare the composition of the refined oil mixture in the food product label. This creates a gap since there is no analytical method currently available to perform such analysis. In the first phase the work focused on 100% oil blends of various oil species of palm oil (and derivatives), sunflower and rapeseed oil before expanding to foodstuffs. Chromatographic methods remain highly relevant although suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques based on machine learning algorithms, however, when applied in FTIR, Raman spectroscopic data have a strong potential in tackling the problem.

Mining Money: the generative capacities of scientific and legal knowledge practices in the making of resource economies

In 1997 a scandal associated with Bre-X, a junior mining firm, and its prospecting activities in Indonesia, exposed to public scrutiny the ways in which mineral exploration firms acquire, assess and report on scientific claims about the natural environment. At stake here was not just how investors understood the provisional nature of scientific knowledge, but also evidence of fraud. Contemporaneous mining scandals not only included the salting of cores, but also unreliable proprietary sample preparation and assay methods, mis-representations of visual field estimates as drilling results and ‘overly optimistic’ geological reports. This paper reports on initiatives taken in the wake of these scandals and prompted by the Mining Standards Task Force (TSE/OSC 1999). For regulators, mandated to increase investor confidence in Canada’s leading role within the global mining industry, efforts focused first and foremost upon identifying and removing sources of error and wilfulness within the production and circulation of scientific knowledge claims. A common goal cross-cutting these initiatives was ‘a faithful representation of nature’ (Daston and Galison 2010), however, as the paper argues, this was manifest in an assemblage of practices governed by distinct and rival regulative visions of science and the making of markets in claims about ‘nature’. These ‘practices of fidelity’, it is argued, can be consequential in shaping the spatial and temporal dynamics of the marketization of nature.

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

Fraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.