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.

Remediation of oily wastewater from an interceptor tank using a novel photocatalytic drum reactor

A novel photocatalytic reactor has been developed to remediate oily wastewaters. In the first instance degradation rates of model organic compounds, methylene blue (MB) and 4-c hlorophenol (4-CP) were determined. The experimental set-up investigated a 1:10 w/v catalyst to organic solution volume, 30 g catalyst, 300 mls MB (10 μM) or 4-CP (100 μM). The catalyst investigated was a pellet catalyst to improve separation of the remediated volume from the catalyst following treatment. MB concentration decreased by 93% after 15 mins irradiation whilst 4-CP concentration decreased by 94% following 90 mins irradiation. Oily waste water (OWW) from an interceptor tank typically containing diesel oils was obtained from Sureclean, an environmental clean-up company. The OWW was treated using the same conditions as MB and 4-CP, the model organic compounds. Levels of total organic carbon (TOC) and total petroleum hydrocarbon (TPH) were used to monitor the efficacy of the photocatalytic reactor. TOC reduced by 45% following two 90 mins treatment cycles. TPH reduced by 45% following 90 mins irradiation and by a further 25% during a second stage of treatment. This reactor can be used as a polishing technique assembled within a wastewater treatment plant. Allowing for more than one pass through the reactor improves its efficiency. 

Phytoremediation assessment of Gomphrena globosa and Zinnia elegans grown in arsenic-contaminated hydroponic conditions as a safe and feasible alternative to be applied in arsenic-contaminated soils of the Bengal Delta

Several agricultural fields show high contents of arsenic because of irrigation with arsenic- contaminated groundwater. Vegetables accumulate arse- nic in their edible parts when grown in contaminated soils. Polluted vegetables are one of the main sources of arsenic in the food chain, especially for people living in rural arsenic endemic villages of India and Bangladesh. The aim of this study was to assess the feasibility of floriculture in the crop rotation system of arsenic en- demic areas of the Bengal Delta. The effects of different arsenic concentrations (0, 0.5, 1.0, and 2.0 mg As L−1) and types of flowering plant (Gomphrena globosa and Zinnia elegans) on plant growth and arsenic accumula- tion were studied under hydroponic conditions. Total arsenic was quantified using atomic absorption spec- trometer with hydride generation (HG-AAS). Arsenic was mainly accumulated in the roots (72 %), followed by leaves (12 %), stems (10 %), and flowers (<1 %). The flowering plants studied did not show as high phytoremediation capacities as other wild species, suchas ferns. However, they behaved as arsenic tolerant plants and grew and bloomed well, without showing any phytotoxic signs. This study proves that floriculture could be included within the crop rotation system in arsenic-contaminated agricultural soils, in order to im- prove food safety and also food security by increasing farmer’s revenue.

Liquid coordination complexes: a new class of Lewis acids as safer alternatives to BF3 in synthesis of polyalphaolefins

Liquid coordination complexes (LCCs) are a new class of liquid Lewis acids, prepared by combining an excess of a metal halide (e.g. GaCl3) with a basic donor molecule (e.g. amides, amines or phosphines). LCCs were used to catalyse oligomerisation of 1-decene to polyalphaolefins (PAOs). Molecular weight distribution and physical properties of the produced oils were compliant with those required for low viscosity synthetic (Group IV) lubricant base oils. Kinematic viscosities at 100 °C of ca. 4 or 6 cSt were obtained, along with viscosity indexes above 120 and pour points below −57 °C. In industry, to achieve similar properties, BF3 gas is used as a catalyst. LCCs are proposed as a safer and economically attractive alternative to BF3 gas for the production of polyalphaolefins.

Arsenic is not stored as arsenitephytochelatin complexes in the seaweeds Fucus spiralis and Hizikia fusiforme

Environmental context Seaweeds hyperaccumulate the toxic metalloid arsenic, but seemingly achieve detoxification by transformation to arsenosugars. The edible seaweed hijiki is a notable exception because it contains high levels of toxic arsenate and arsenite. Terrestrial plants detoxify arsenic by forming arsenitephytochelatin complexes. The hypothesis that seaweeds also synthesise phytochelatins to bind arsenite as a means of detoxification before arsenosugar synthesis is tested in this investigation. Abstract Phytochelatins (PCs), generic structure [-Glu-Cys]n-Gly, are peptides synthesised by terrestrial plants to bind toxic metal(loid)s such as cadmium and arsenic. Seaweeds are arsenic hyperaccumulators, seemingly achieving detoxification via arsenosugar biosynthesis. Whether seaweeds synthesise PCs to aid detoxification during arsenic exposure is unknown. Hizikia fusiforme (hijiki) and Fucus spiralis were used as model seaweeds: the former is known for its large inorganic arsenic concentration, whereas the latter contains mainly arsenosugars. F. spiralis was exposed to 0, 1 and 10mgL ^-1 arsenate solutions for 24h, whereas hijiki was analysed fresh. All samples contained As ^III, glutathione and reduced PC ₂, identified using HPLC-ICP-MS/ES-MS. Although hijiki contained no As ^IIIPC complexes, arsenate exposed F. spiralis generated traces of numerous arsenic compounds that might be As ^IIIGS or As ^IIIPC ₂ complexes. As ^IIIPC complexes seem not to be a principal storage form for long-term arsenic storage within seaweeds. However, 40 times higher glutathione concentrations were found in hijiki than F. spiralis, which may explain how hijiki deals with its high inorganic arsenic burden. © 2011 CSIRO.

Hardware Software Interface: a Strategy for the implementation of Urban Agriculture

This paper describes how urban agriculture differs from conventional agriculture not only in the way it engages with the technologies of growing, but also in the choice of crop and the way these are brought to market. The authors propose a new model for understanding these new relationships, which is analogous to a systems view of information technology, namely Hardware-Software- Interface.
The first component of the system is hardware. This is the technological component of the agricultural system. Technology is often thought of as equipment, but its linguistic roots are in ‘technis’ which means ‘know how’. Urban agriculture has to engage new technologies, ones that deal with the scale of operation and its context which is different than rural agriculture. Often the scale is very small, and soils are polluted. There this technology in agriculture could be technical such as aquaponic systems, or could be soil-based agriculture such as allotments, window-boxes, or permaculture. The choice of method does not necessarily determine the crop produced or its efficiency. This is linked to the biotic that is added to the hardware, which is seen as the ‘software’.
The software of the system are the ecological parts of the system. These produce the crop which may or may not be determined by the technology used. For example, a hydroponic system could produce a range of crops, or even fish or edible flowers. Software choice can be driven by ideological preferences such as permaculture, where companion planting is used to reduce disease and pests, or by economic factors such as the local market at a particular time of the year. The monetary value of the ‘software’ is determined by the market. Obviously small, locally produced crops are unlikely to compete against intensive products produced globally, however the value locally might be measured in different ways, and might be sold on a different market. This leads to the final part of the analogy - interface.
The interface is the link between the system and the consumer. In traditional agriculture, there is a tenuous link between the producer of asparagus in Peru and the consumer in Europe. In fact very little of the money spent by the consumer ever reaches the grower. Most of the money is spent on refrigeration, transport and profit for agents and supermarket chains. Local or hyper-local agriculture needs to bypass or circumvent these systems, and be connected more directly to the consumer. This is the interface. In hyper-localised systems effectiveness is often more important than efficiency, and direct links between producer and consumer create new economies.

Site Distribution at the Edge of the Palaeolithic World: A Nutritional Niche Approach

This paper presents data from the English Channel area of Britain and Northern France on the spatial distribution of Lower to early Middle Palaeolithic pre-MIS5 interglacial sites which are used to test the contention that the pattern of the richest sites is a real archaeological distribution and not of taphonomic origin. These sites show a marked concentration in the middle-lower reaches of river valleys with most being upstream of, but close to, estimated interglacial tidal limits. A plant and animal database derived from Middle-Late Pleistocene sites in the region is used to estimate the potentially edible foods and their distribution in the typically undulating landscape of the region. This is then converted into the potential availability of macronutrients (proteins, carbohydrates, fats) and selected micronutrients. The floodplain is shown to be the optimum location in the nutritional landscape (nutriscape). In addition to both absolute and seasonal macronutrient advantages the floodplains could have provided foods rich in key micronutrients, which are linked to better health, the maintenance of fertility and minimization of infant mortality. Such places may have been seen as ‘good (or healthy) places’ explaining the high number of artefacts accumulated by repeated visitation over long periods of time and possible occupation. The distribution of these sites reflects the richest aquatic and wetland successional habitats along valley floors. Such locations would have provided foods rich in a wide range of nutrients, importantly including those in short supply at these latitudes. When combined with other benefits, the high nutrient diversity made these locations the optimal niche in northwest European mixed temperate woodland environments. It is argued here that the use of these nutritionally advantageous locations as nodal or central points facilitated a healthy variant of the Palaeolithic diet which permitted habitation at the edge of these hominins’ range.

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.