The abstract of this article was published in the book of abstracts of the International conference held in 2013 at the University of Agronomic Sciences and Veterinary Medicine Cluj

Published online (https://sites.google.com/site/hevmetfood/mintexfood---a-novel-food-database)

on 26 march 2014

Published in the Bulletin UASVM Veterinary Medicine 71 (1) / 2014, 242-249 Print ISSN 1843-5270; Electronic ISSN 1843-5378

Update of the on-line version - June 2014

THE FIRST ROMANIAN DATABASE OF MINERAL NUTRITIONAL VALUE AND TEXTURAL PROPERTIES OF ROMANIAN FOODS OF ANIMAL ORIGIN

LilianaTUDOREANU¹⁾, Gheoghe Valentin GORAN²⁾, Victor CRIVINEANU³⁾ and Mario Darius CODREANU⁴⁾

^{1), 2), 3), 4)} Interdisciplinary Laboratory for Heavy Metals Accumulation in the Food Chain and Modeling (HEVMETFOOD), University of Agronomic Sciences and Veterinary Medicine of Bucharest, Bd Splaiul Independentei nr 105 Bucharest, Romania

¹⁾Corresponding author, e-mail: liliana_tudoreanu223@hotmail.co.uk ;

²⁾gvgoran@gmail.com; ³⁾vcrivineanu@gmail.com; ⁴⁾codveterinary@yahoo.com

Keywords: database, textural properties, minerals, foods of animal origin

Introduction: The food composition databases are offering valuable information concerning the nutritional value of food groups, the quantity of food consumed by individuals and population groups. It is also well known that food consumption depends on consumer’s preferences, habits and tradition. Consumers preferences for solid food are, for the majority of foods groups, influenced by their textural properties. For liquid food consumers are influence in their choice by food viscosity.

Food composition databases could also contain information on micronutrients as well as on textural properties for the selected food categories.

Aims: The purpose of the work was to build the first Romanian food database on mineral nutritional quality and textural properties of foods of animal origin, the MINTEXFOOD database. This database may be used to estimate the populations’ minerals intake in relation to population food preferences related to food texture.

Materials and methods: Over 200 products of animal origin were bought between the years 2008 and 2013 from the local markets and supermarkets.

Texture profile analyses was conducted for quantifying textural properties such as Hardness, Cohesiveness, Springiness, Springiness Index, Chewiness, Adhesiveness and Stiffness, as well as imitative bite tests using the Volodkevich probe and a Universal Texture Analyzer machine.

Samples total concentrations of Al, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, K, Li, Mn, Mg,Ni, Pb, Se, Sr, Zn, Tl were analyzed by ICP-MS and ICP-OES. The textural properties and total mineral concentrations were analyzed simultaneously for all samples.

Conclusion: Databases containing information on the mineral nutritional value and textural properties of foods is a valuable tool for scientist studying the link between clinical pathology, mineral nutrition and eating habits.

INTRODUCTION

Clive E. West pointed out in 1992 that: “ there was a recognition in Europe that real benefits would flow from coordinating the manner in which food composition tables were produced in the various countries of Europe. Subsequent development of computerized nutritional databases has further highlighted the potential advantages of working together. Such cooperation could lead to improved quality and compatibility of the various European nutrient databases and the values within them. This realization was one of the driving forces behind the development of the EUROFOODS initiative in the 1980s when those people in Europe interested in data on food composition began working together” (Greenfield and Southgate, 2003).

Experiments on diet-induced obesity, containing diets with different macronutrient compositions and textures (Desmarchelier, et al., 2013) may produce valuable information on the link between texture of food, eating habits and obesity. Desmarchelier, et al., (2013) experiment aim was to identify the contribution of diet macronutrient composition to obesity development and associated pathophysiological changes and to separate diet-specific effects, from obesity-mediated effects. Regardless the energy /fat content of the diets they identified that all ‘soft’ diets (close to zero chewiness and low cohesiveness, hardness and stiffness) induced obesity. However experiments such as the one developed by Desmarchelier et al.,(20013) did not take into consideration the larger variability of possible food textural properties which are available to humans and the way these properties influence the eating habits and satiety.

Rolls (2011) revised the mechanisms of obesity and mentioned food texture among the factors influencing obesity (Figure 1). He concluded that overeating and obesity are related in many cases to an increased reward value of the sensory inputs produced by foods, and their modulation by cognition and attention, which overrides existing satiety signals. He also suggested that control of all rather than one or several of these factors that influence food reward and eating might be important in the prevention and treatment of overeating and obesity

Several food composition databases are available worldwide among which are the ‘USDA Nutrient Data Laboratory’, ‘Health Canada and the Danish Food Composition Databank’ (Department of Nutrition, National Food Institute, Technical University of Denmark). ‘The Canadian Nutrient File database’ published by Health Canada is a database that reports up to 150 nutrients in over 5807 foods. This database provides entries on values for nutrients such as vitamins, minerals, protein, energy, fat etc, which are updated periodically.

These databases may be used in correlation with the ‘Dietary Reference Intakes’ developed for each country or geographical area. The Dietary Reference Intakes (DRIs) developed by American and Canadian governmental institutions represents a set of scientifically based nutrient reference values for healthy populations which describes the reference values for estimated average requirement (EAR), recommended dietary allowance (RDA), adequate intake (AI) and tolerable upper intake level (UL) for food nutrients.

The usefulness of such databases stems from several issues such as the need for considering the risks of excessive nutrient intakes and establishing upper levels of intake regarding risk of adverse health effects, when available data exist.

Usually database refers to food produced in a specific country (USA, Canada, UK, Denmark, etc). The main entries to these databases are generally grouped in proximates such as water, energy, protein, total lipid (fat) , ash, carbohydrate, sugars (total), fibber, and minerals such as Ca, Fe, Mg, P, K, Na, Zn, Cu, Mn, Se, Cr, Ni, I. Other components which are represent in the databases are vitamins, lipids and other components such as alpha and beta carotene, lycopene, Caffeine, theobromine etc.

However the databases are very different due to differences in food categories’ information and data offered by food category.

The activity for reviewing components and measuring concentrations of food components that may not meet the traditional concept of a nutrient but are of possible benefit to health is another important aspect in food mineral concentrations monitoring which has not been sufficiently taken into consideration by now.

Another important aspect which was completely disregarded in present food databases is the food textural properties data which are widely recognized to influence eating habits therefore alongside to composition data they form a strong foundations for the development of education programmes on choosing healthy diets.

The MINTEXFOOD database developed by the Interdisciplinary Laboratory for the Study of Heavy Metals Accumulation in the Food Chain and Modelling ( HEVMETFOOD), of the University of Agronomic Sciences and Veterinary Medicine of Bucharest, aims at providing information which will overcome the food composition databases’ shortcomings described previously, by including data on food mineral concentrations and on textural properties of foods, data which ca be used in the prevention and treatment of overeating and obesity.

MATERIALS AND METHODS

Over 200 products of animal origin were bought between the years 2008 and 2012 from the local markets and supermarkets.

Mineral content and textural properties of all samples were analyzed using ICP OES, ICP-MS and the TPA (texture profile analysis) method using a universal testing machine.For liquid dairy foods 1 ml of product was digested in a microwave oven as described by Qin et al., (2009).

For the solid foods 1 mg of product was digested in the microwave oven as described by Lamble and Hill (1998)

A Thermo XS series2 ICP-MS spectrometer was used for total minerals concentration analyses. The operating conditions for Thermo XS series 2 ICP-MS were: Sample uptake 40s; Washout 60s; Runs 3; Sample uptake;: 0.7 l/min; Sampling depth 15mm; Sampler 1.0mm, Ni Skimmer 0.4, Ni; Internal standard 103Rh; Neb. 1,9 bar; Spike recoveries from 80% to 110%. All operating conditions were optimized to yield the highest signal/ background ratio for 9Be, 115In, 230U, 556Fe, 209Bi, 140Ce, 156 CeO, 75As, 27Al. Prior to analysis each sample was spiked with the internal standard (Rh). The dilution factor for each sample is 10. The instrument was calibrated using commercially available aqueous ICP-MS standards. Four standards were obtained by dilution from the main standard solution. The calibration standards contain 1ppb, 10ppb, 100ppb and 1000ppb of the Al, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, K, Li, Mn, Mg,Ni, Pb, Se, Sr, Zn, Tl. The accuracy of the calibration was assessed by using reference materials such as NIST SRM 1546 and SRM1577b.

For the ICP-OES (Thermo series) analyses the operating conditions were 27.12 MHz, Rf=1.5 Kw, argon flow 14 l/min, integration time 5-3 sec, Spectral range 200-800 nm. The calibration standars were obained from a Merck standard solution of 1000mg/l containing: Al, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, K, Li, Mn, Mg,Ni, Pb, Se, Sr, Zn, Tl. The four calibration standards concentrations are: 0.1ppm 1ppm, 10ppm and 50ppm.

Textural properties were measured using the TAPlus Texture Analyser (Lloyd Instruments) universal texture analyzer machine using Nexigen and Nexigen Plus software.

The evaluation of textural properties of solid food were performed by TPA (textural profile analysis), and uniaxial double compression using a Volodkevich fixture. The TPA and the double compression tests using the Volodkevich probe mimicked the masticatory process by compressing the samples at 10mm/s and 80% deformation for cooked foods and 30% for raw produces (meat, offal). All samples for textural properties evaluation were cut to 30 mm (height) x 20mm x20mm.

RESULTS AND DISCUSSIONS

The MINTEXFOOD database developed between 2008-2012 contains the mineral concentrations and textural properties of foods including foods of animal origin. The data have been grouped by several categories and subcategories such as: (1) Egg and egg products; (2) Poultry products; (3) Pork ; (4) Beef; (5) Meat products (processed meat products); (6) Fish and fish products ; (7) Cheese; (8) Milk and yogurt. The database contains also information on food of vegetable origin which is not presented in the present paper.

The evaluation of textural properties of foods was by TPA (Texture Profile Analysis) due to its high correlation to sensory data. The TPA data from MINTEXFOOD may be correlated to the sensory evaluation of food between molars. The data from the double compression tests using a Volodkevich fixture may be correlated to the sensorial data of first and second byte between incisors teeth. The fracture properties measured by using the Vodkevich fixture are better correlated to the sensorial fracture properties of foods. Several studies (Desmarchelier et al., 2013, Rolls, 2011) revealed that the quantity of food consumed by individuals may be influenced by its textural properties, fat and salt content.

The international food composition databases do not always include the concentrations of potentially harmful elements such as Cd, Pb, Cr, Hg, however some databases (the Danish database) included the concentrations of Cr and Ni and other elements concentrations such as Pb, Cd and Al (The British diary database). The mentioned three international databases do not contain information on Sr concentrations either.

The Romanian MINTEXFOOD database (table 1) includes micro and macronutrients as well as Cd, Pb (Goran et.al, 2011) from a large variety of food groups of which several are presented in table 1. A better and complete picture on the influence of foods mineral content on human health could be drawn if the databases will contain information on nutrients as well as potential harmful metals such as Pb, Cd, Cr and Hg.

Moreover adverse food impact on human health could be driven by the overall quantity from each food groups in the daily diet due.

Overeating might also induce an adverse effect on human health not only due to its main consequence – obesity, but also due to a possible mineral imbalance. The overeating habits are driven by the textural properties of the food and other food characteristics such as fat content and salt content (Rolls, 2011).

The MINTEXFOOD database is the first database that includes textural properties of food groups and subgroups and which may be used to estimate the populations’ minerals intake in relation to population food preferences related to food texture.

Although governments have implemented the nutrition labeling of foods and there are specific requirements for producers of food products to provide their own analytical data on the composition of their products, most regulations allow the use of compositional data taken from an authoritative compilation, such as a national food composition database, as a substitute for direct analysis. Therefore data provided by the food composition databases have to be of high quality in terms of both the representativeness of the samples and the quality of the analytical data.

The MINTEXFOOD database was developed taking into account the main steps for the development of a food composition database (figure 2). This database was developed as a pilot database as part of the activity of the Interdisciplinary Laboratory for Heavy Metals

Accumulation in the Food Chain and modelling of the University of Agronomic Sciences and Veterinary Medicine of Bucharest (https://sites.google.com/site/hevmetfood/).

The food composition databases are offering valuable information on food nutritional value; however the quantity of food consumed depends on consumer’s preferences and is strongly influenced by textural properties and palatability (figure1). Consumers preferences for solid food are, for the majority of foods groups, influenced by their textural properties. For liquid food consumers are influence in their choice by food viscosity. The quantity of food consumed from each food group is influencing the total mineral intake which is playing an important role in population health status evaluation. Other factors such as costs are also influencing food consumption especially for disadvantaged population groups.

The food composition databases could be enriched with textural properties of foods in order to support initiatives such as the one of the Scottish Government (SG) and the Food Standards Agency in Scotland who in may 2013, presented a draft set of voluntary proposals to support healthier choices to representatives of the food industry. The SG will be working with industry to firm up these proposals and aim to publish final proposals in Autumn 2013. Moreover the SG also published in May 2013, the Scottish Dietary Goals, providing updated population-wide aims to influence policy and action to tackle on diet and nutrition.

The sensory properties of food such as hardness (table 2) were found to be well perceived by consumers and correlate well with the instrumental measurements made by TPA (textural profile analyses) or by SENB (single edge notch bend method) (Duizer et al., 2011).

The MINTEXFOOD database described by the present work is the firs attempt to provide a food database with information which may be correlated to consumer’s food acceptability using information on textural properties of foods.

Food textural properties data are widely recognized to influence eating habits therefore alongside to composition data, they form a strong foundation for the development of education programmes on choosing healthy diets.

From the three existing methods for the development of food composition databases: the direct method- data are obtained from analyses carried out specifically for this purpose, the indirect method - data are compiled from published literature or unpublished laboratory reports and the combination method- a combination of direct and indirect methods, the MINTEXFOOD database was developed using the direct method, in which all of the values are the results of analyses carried out specifically for this database.

The large development of food trade in Romania during the last 20 years needs to be considered when choosing a list of foods to be included in the database. At this stage the MINTEXFOOD database was compiled by using analyses of Romanian foods and by recording, when possible, the place were the food was produced. Although the meat produces are of Romanian origin, it was not possible to quantify the influence of feed on meat and meat produces.

Kenedy et al (2010) specified that for food composition databases “an essential element of food based approaches involves dietary diversification consumption of a wide variety of foods across nutritionally distinct food groups as a way to meet recommended intakes of nutrients”.

As there is no internationally standardized approach to food groupings, the MINTEXFOOD database is organized in several food groups and subgroups that help the evaluation of dietary diversity. The MINTEXFOOD database is using food subgroups such as the ones suggested in table 1 and table 2.

Mason et al., (2001) reported that micronutrient malnutrition (vitamin and mineral deficiencies), affects one third of the population worldwide. Diets based on starchy staples lack essential micronutrients and contribute to the burden of malnutrition and micronutrient deficiencies (Kennedy et al., 2010). Allen, (2008) showed that food based strategies have been recommended as the first priority to meet micronutrient needs. Mineral concentrations (Table 1) may be very different across food subgroups. Some minerals, such as Ni and Co are present in the offal subgroup however, are almost inexistent in the other subgroups. Co (cobalt) is an essential trace mineral that is a constituent of vitamin B12 and which plays a cofactor role for making the thyroxine hormone. Another mineral which is less studied as possible micronutrient is Ni which was associated lately with vitamin C. There are several opinions regarding the influence of Ni and Co over the muscular walls of the body's arteries. Some researchers consider Nickel as a trace element that ca be linked to skin allergies or dermatitis

Moreover most of plasma Ni is a constituent of the circulating nickeloplasmin and albumin, and it is also thought to be a factor in hormone, lipid and cell membrane metabolism.

Several studies showed that insulin response is increased after ingesting Ni, which may be related to its activation of enzymes associated with the breakdown or utilization of glucose. Therefore the total Ni intake from food is of great interest in studies on diabetes. The usefulness of subgroups data in evaluating the influence of dietary diversity on the minerals potential deficiency is stressed by the highly different K concentrations across food subgroups: from 4.20175 mg/kg ±1.872 mg/kg to 14861.43 mg/kg ±39.3mg/kg. (Table 1)

Information on minerals total concentrations will provide valuable data for studies on population’s heath consuming traditional foods. Therefore databases containing information on large datasets of minerals concentrations and food textural properties may be a valuable tool to scientist studying the link between clinical pathology, mineral nutrition and eating habits.

CONCLUSIONS

• • The survey conducted between 2008 - 2012 on food of animal origin from local Bucharest markets revealed that Sr, Co and Ni concentration in foods as well as Cd, Pb, concentrations should be taken into consideration for food surveys and food composition databases.

• Mineral concentrations and textural properties of raw produces (muscle and offal) may provide useful information on the health status of the farm animals too.

• For solid foods, fracture properties and textural properties such as chewiness, adhesiveness hardness and stiffness have to be considered simultaneously with their mineral content. This approach helps to quantify the total mineral intake from foods of animal origin in relation to the consumer’s preferences for a specific texture.

• Combined information on mineral concentrations and textural properties of foods can be used to estimate their contribution to the risks for obesity of certain population groups and can be used in the prevention and treatment of overeating and obesity.

• Complex database on food composition and textural properties may also contribute to a better understanding of micronutrient deficiencies for certain populations

REFERENCES

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Useful links

http://www.efsa.europa.eu/en/datexfoodcdb/datexfooddb.htm

http://www.fao.org/docrep/005/ac911e/ac911e05.htm