Frøydis Bjerke

Vitamin C, total phenolics and antioxidative activity in tip-cut green beans (Phaseolus vulgaris) and swede rods (Brassica napus var. napobrassica) processed by methods used in catering

BACKGROUND Retention of nutrients in vegetables during blanching/freezing, cooking and warm-holding is crucial in the preparation of both standard and therapeutic diets. In the present study, conventional cooking in water, and cooking by pouch technology (boil-in-bag, sous vide) were compared in their ability to retain vitamin C, total phenolics and antioxidative activity (DPPH and FRAP) in industrially blanched/frozen tip-cut green beans and swede rods. RESULTS After conventional cooking, 50.4% total ascorbic acid, 76.7% total phenolics, 55.7% DPPH and 59.0% FRAP were recovered in the drained beans. After boil-in-bag cooking, significantly (P < 0.05) higher recoveries were obtained, i.e. 80.5% total ascorbic acid, 89.2% total phenolics, 94.8% DPPH and 92.9% FRAP. Recoveries after sous vide cooking were comparable to those of boil-in-bag cooking. By conventional cooking, 13.5-42.8% of the nutrients leaked into the cooking water; by sous vide about 10% leaked to the exuded liquid, while no leakage occurred by boil-in-bag cooking. Warm-holding beans after cooking reduced recoveries in all components. Recoveries in swede rods were comparable but overall slightly lower. CONCLUSION Industrially blanched/frozen vegetables should preferably be cooked by pouch technology, rather than conventional cooking in water. Including cooking water or exuded liquid into the final dish will increase the level of nutrients in a meal. Warm-holding of vegetables after cooking should be avoided.

A comparison of design and analysis techniques for mixtures

Abstract This paper compares design and analysis techniques for mixtures. The main focus is on comparing a statistical treatment taking the mixture aspect fully into account and another where only a subset of the mixture variables is considered both in the design phase and during analysis. Mixture techniques are of special importance for product development and optimization of food products and processes. The methods are tested on data from a baking experiment where three flours were mixed in different proportions and the different flours were baked in three different process conditions. The example is of importance for understanding the relationship between flour quality, baking process and bread quality. The main conclusion is that treating the design as a true mixture design and analyzing the data in terms of all variables involved is advantageous compared to a treatment where only a subset of the mixture variables is considered. ©

An application of projection design in product development

Abstract The area of mixture design and analysis is of vital importance in food science and industry, since all foods are mixtures of a number of different ingredients. Mixture methods respect constraints among the ingredients in both the set-up of the design and the analysis of the results. This methodology is, therefore, more complex than, e.g., factorial and fractional factorial designs. Projection design methodology as proposed by Hau and Box [I.Hau, G. Box, Constrained experimental designs: Part I. Construction of projection designs, I, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI, USA, 1990; I. Hau, G. Box, Constrained experimental designs: Part II. Analysis of projection designs, II, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI, USA, 1990; I. Hau, G. Box, Constrained experimental designs: Part III. Properties of projection designs, III, Center for Quality and Productivity Improvement, University of Wisconsin, Madison, WI, USA, 1990] is developed to keep some of the simplicity of the factorial approach while working with the more complex area of mixture designs and constrained situations in general. The method is based on setting up a fractional factorial design and then projecting this onto a space determined by the set of constraints. In some cases, the analysis can also be done by “factorial-like” techniques. In the present paper, the projection design method is investigated and compared with the more conventional mixture model method [J.A. Cornell, Experiments with Mixtures. Designs, Models and the Analysis of Mixture Data, 2nd edn., 1990, Wiley-Interscience]. The discussion is based on a case study where process and mixture variables are combined. Both design and modelling aspects are discussed. The overall conclusion is that both approaches are useful. However, the mixture model approach seems somewhat more flexible with respect to design region and also somewhat easier to analyse and interpret. The projection design approach seems to be a useful and simple way of providing fractional versions of combined designs. This may be difficult by using other techniques.

Restricted randomization and multiple responses in industrial experiments

Two issues regarding designed experiments are discussed; restrictions on randomization and multiple responses. The former is typically related to hard-to-vary factors and factors appearing in separate stages of a process experiment. Randomization restrictions should be taken into account in the construction of the design as well as in the statistical modelling. In the paper, a case study of sausage production is discussed, having a split-plot model with correlated multiple responses. Multiple responses are handled in two ways, by principal component analysis (PCA) followed by ANOVA of the principal components, and by a newly developed alternative, the ‘50–50 MANOVA’. Multiple tests of correlated response variables are also described. Practical aspects of the planning, performing, response measurements, and statistical analysis are emphasized throughout. Hence, the paper aims to extend the utility of statistical methods in industry by linking design of experiments to multivariate analysis of the responses. Copyright

Design and Analysis of Storing Experiments: A Case Study

Abstract In order to achieve robust and stable food products of desired quality and characteristics, all stages of the food production process, including storage conditions, should be considered during product development projects. This article describes a multistage production development project on low-fat mayonnaise, where experimental design was used to set up a pilot plant study involving ingredient factors, processing factors, and storage factors and their effect on mayonnaise viscosity. The article discusses three alternative empirical modeling approaches to analyze the data—namely, a simple graphics approach, a robustness approach, and a mixed models approach—considering their multistratum (split-plot) structure and repeated measurements of each subsample. In the case study, all information relevant for business decisions was obtained through the combination of graphical analysis and the robustness approach. This information could also be extracted by a practitioner, while the mixed model analysis clearly requires a graduate statistician. In order to obtain valid and useful information for the practitioner in an efficient way, the authors believe that, usually, the first two approaches would be sufficient. The more complex mixed model strategy might be advisable if a deeper understanding is required or desired.

Analysing multivariate data from designed experiments: a case study of photo‐oxidation in sour cream

Exposure to light induces photo-oxidation in dairy products, causing undesired off-taste/rancidity. In this case study we present the results of a designed experiment in four factors: illumination source, type of packaging, distance to illumination source and exposure time, in order to observe the resulting oxidation of low-fat sour cream, measured by fluorescence spectroscopy. Such spectroscopic data yield highly correlated response variables. A novel multivariate method, 50–50 MANOVA, is applied for the statistical analysis. The main objective is to present and interpret complex and comprehensive data results to researchers and practitioners in an informative way. The experimentation revealed that several factors and interactions must be taken into consideration when designing optimal environment for sour cream storage. Copyright