The food of London: a sketch of the chief varieties, sources of supply, probable quantities, modes of arrival, processes of manufacture, suspected adulteration, and machinery of distribution, of the food for a community of two millions and a half. -

Mode of access: Internet.

Purity and adulteration in native wines. Address

Mode of access: Internet.

Bilberry adulteration using the food dye amaranth

Vaccinium myrtillus or bilberry fruit is a commonly used herbal product. The usual method of determining the anthocyanin content is a single-wavelength spectrophotometric assay. Using this method, anthocyanin levels of two extracts were found to be 25% as claimed by the manufacturers. When high-performance liquid chromatography (HPLC) was used, however, one extract was found to contain 9% anthocyanins probably not derived from V. myrtillus but from an adulterant. This adulterant was subsequently identified, using HPLC, mass spectroscopy, and nuclear magnetic resonance, as amaranth, that is, 3-hydroxy-4-[(4-sulfo-1-naphthalenyl)azo]-2,7-naphthalenedisulfonic acid trisodium saltsa synthetic dark red sulfonic acid based naphthylazo dye. As described in this study, if deliberate adulteration occurs in an extract, a single-wavelength spectrophotometric assay is inadequate to accurately determine the levels of compounds such as anthocyanins. Detection of deliberate adulteration in commercial samples thus requires the use of alternative, more sophisticated, methods of analysis such as HPLC with photodiode array detection as a minimum.

Continuous statistical modelling for rapid detection of adulteration of extra virgin olive oil using mid infrared and Raman spectroscopic data

The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

The determination of essential oils in Sandalwood via NIR Spectroscopy

Sandalwood oil is widely used in the medicinal, cosmetic and aromatherapy industries. The oil is distilled from the heartwood of the sandalwood tree Santalum - a genus of hemi-parasitic tree species occurring throughout South and Southeast Asia, Australia and the Pacific. With international concern on the sustainability Sandalwood oil (Fox, 2000), the quality of oil entering the market is being compromised either through extraction from underdeveloped heartwoods or through adulteration with lower grade Sandalwood oils or synthetic substitutes (Howes et al. 2004). Although no standard method exists to assess the quality of Sandalwood oil, the International Organisation for Standardisation recommends GCMS analysis of santalol oil content. NIR spectroscopy has had a demonstrated success for other essential oils (Schulz et al. 2004, Steur et al. 2001). In addition, NIR spectroscopy has also been applied as both a qualitative and quantitative analytical tool in the forestry industry (Steur et al. 2001). This project aimed to assess the ability of NIR spectroscopy as a non-invasive, rapid and cheap analytical alternative to GCMS for Santalol determination.

Phytomedicinal importance of Saraca asoca (Ashoka): an exciting past, an emerging present and a promising future

Since the dawn of civilization, natural resources have remained the mainstay of various remedial approaches of humans vis-a-vis a large number of illnesses. Saraca asoca (Roxb.) de Wilde (Saraca indica L.) belonging to the family Caesalpiniaceae has been regarded as a universal panacea in old Indian Ayurvedic texts and has especially been used to manage gynaecological complications and infections besides treating haemmorhagic dysentery, uterine pain, bacterial infections, skin problems, tumours, worm infestations, cardiac and circulatory problems. Almost all parts of the plant are considered pharmacologically valuable. Extensive folkloric practices and ethnobotanical applications of this plant have even lead to the availability of several commercial S. asoca formulations recommended for different indications though adulteration of these remains a pressing concern. Though a wealth of knowledge on this plant is available in both the classical and modern literature, extensive research on its phytomedicinal worth using state-of-the-art tools and methodologies is lacking. Recent reports on bioprospecting of S. asoca endophytic fungi for industrial bioproducts and useful pharmacologically relevant metabolites provide a silver lining to uncover single molecular bio-effectors from its endophytes. Here, we describe socio-ethnobotanical usage, present the current pharmacological status and discuss potential bottlenecks in harnessing the proclaimed phytomedicinal worth of this prescribed Ayurvedic medicinal plant. Finally, we also look into the possible future of the drug discovery and pharmaceutical R&D efforts directed at exploring its pharma legacy.

Direito Penal Econômico e o Compliance como forma de prevenção da adulteração de combustível

Esse trabalho apresenta como tema o Direito Penal Econômico e a importância do compliance como critério de prevenção no crime de adulteração de combustível, que encontra previsão na Lei 8.176, de 08 de fevereiro de 1991. Os objetivos centrais do estudo, portanto, orientam-se no sentido de demonstrar a importância do cumprimento de efetivas normas de conduta no âmbito empresarial, de forma a se desenvolver uma postura ética suficiente a evitar a prática de condutas delituosas, sobretudo aquelas relacionadas à adulteração de combustível. Trata-se de refletir acerca de critérios preventivos, de forma a se evitar a futura incidência do Direito Penal e por consequência, da aplicação da pena. Busca-se apresentar o campo de incidência do Direito Penal Econômico, dentro do qual se situa o tratamento da conduta delitiva de adulteração de combustível. Aborda-se o conceito e normas de fiscalização ligadas ao crime de adulteração de combustível, para em seguida demonstrar o desenvolvimento e incidência de compliance como critério de prevenção criminal.

Differentiation of the rainbow trout (Oncorhynchus mykiss) from Atlantic salmon (Salmon salar) by the AFLP-derived SCAR

A species-specific SCAR marker for rainbow trout, which was used to detect adulteration and fraudulent labeling in Atlantic salmon products, has been developed based on the AFLP analysis and evaluated in this study. The SCAR marker could be amplified and visualized in 1% agarose gel in all tested rainbow trout samples and absent in all salmon samples. Using DNA admixtures, the detection of 1% (0.5 ng), 10% (5 ng) rainbow trout DNA in Atlantic salmon DNA for fresh and processed samples, respectively was readily achieved. The molecular approach was sensitive and demonstrated to be a rapid and reliable method for identifying frauds in salmon products and could be extended for applications of species identification in food industry.

Botany origin and protein content of homemade honeys from Galicia hives (NW Spain)

The botanic origin and the protein content of 15 honeys from small bee farms exploitations of Galicia, for family consume, were studied; the aim is to check if the protein wealth and the pollen wealth are dependent parameters. Seven honeys resulted to be Rhamnus frangula unifloral (pollen patterns with low diversity), two Castanea sativa Miller unifloral, other one heather unifloral, and five was multifloral honeys of various pollen patterns (four Castanea predominant and one Rhamnus frangula predominant). Their pollen wealth was low; eight honeys classified in the Maurizio Class I, 3 in Class II, 2 in Class III, and one in Maurizio Class IV. There has been a wide variability in its protein content (0.09- 4.83 mg prot./g honey). The relative amount of pollen from different taxa has a direct or inverse proportionality to wealth protein.

Use of a novel micro-fluidic device to create arrays for multiplex analysis of large and small molecular weight compounds by surface plasmon resonance

There is an increasing demand to develop biosensor monitoring devices capable of biomarker profiling for predicting animal adulteration and detecting multiple chemical contaminants or toxins in food produce. Surface plasmon resonance (SPR) biosensors are label free detection systems that monitor the binding of specific biomolecular recognition elements with binding partners. Essential to this technology are the production of biochips where a selected binding partner, antibody, biomarker protein or low molecular weight contaminant, is immobilised. A micro-fluidic immobilisation device allowing the covalent attachment of up to 16 binding partners in a linear array on a single surface has been developed for compatibility with a prototype multiplex SPR analyser.

The immobilisation unit and multiplex SPR analyser were respectively evaluated in their ability to be fit-for-purpose for binding partner attachment and detection of high and low molecular weight molecules. The multiplexing capability of the dual technology was assessed using phycotoxin concentration analysis as a model system. The parent compounds of four toxin groups were immobilised within a single chip format and calibration curves were achieved. The chip design and SPR technology allowed the compartmentalisation of the binding interactions for each toxin group offering the added benefit of being able to distinguish between toxin families and perform concentration analysis. This model is particularly contemporary with the current drive to replace biological methods for phycotoxin screening.

Identification of oil mixtures in extracted and refined vegetable oils

Identification of adulteration in mechanically extracted oils or the botanical origin of refined vegetable oil blends can be effectively achieved through the combination of spectroscopic methods and chemometric techniques. Chromatographic methods remain highly relevant but suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques have demonstrated that it is possible to identify patterns and effectively classify unknown samples in both cases. Development of robust analytical methodologies requires however vigorous validation. Spectroscopic methods combined with chemometric techniques lack established validation protocols and this might hinder their use by law enforcement authorities. 

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.

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.

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.