Panel performance: Modelling variation in sensory profiling data by multiway analysis

Sensory profiling data is essentially three-way data where samples, attributes and assessors are the three dimensions of information. It is common practice to average over the assessors and focus the analysis on the relations between samples and sensory descriptors. However, since assessor reliability can not be controlled in advance, posthoc analysis on assessors is needed to assess performance of the individual and at the panel level. For this purpose, multiway analysis is a very efficient data method as it provides information on samples, attributes and assessors, simultaneously [1]. PARAllel FACtor (PARAFAC) analysis is one of the most used multiway methods in sensory analysis [2][3]. It is based on two basic assumptions: 1) there exist latent variables behind the identified sensory descriptors describing the variation among the products; 2) assessors have different sensitivities to these common latent variables. However, assessors may perceive the factors differently, so the assumption of “common latent variables” becomes questionable. This may happen when the panel is not well trained and/or the samples present subtle differences difficult to detect. In this work a more flexible approach to the analysis of sensory data is presented. Specifically, the work proposes to use PARAFAC2 modelling [4] as it allows each assessor to have an individual idiosyncratic perceptive model. The data was obtained from a descriptive sensory analysis of organic milk samples. Results show that PARAFAC2 is very useful to highlight disagreement in the panel on specific attributes and to detect outlying assessors. In addition, by using PARAFAC2 an improvement in the description of samples is also achieved. On the other hand, PARAFAC has to be preferred to PARAFAC2 when a good panel agreement is observed, since it provides more stable solutions and no further gain in information is obtained from PARAFAC2. Finally, the work proposes an index to measure the performance of each assessor based on individual sensitivity and reproducibility

Sensory milk properties at the farm level – the terroir dimension

In recent years, the Danish milk market has shown an increase in the consumption of organic milk as well as a growing variety of milk with specific features including farm milk. The production of milk from a single farm and pasture-based (PB) feeding regimes is of special interest as it implies a “sense of place” or terroir. The PB feeding regimes vary with season and might also vary on a day-to-day basis. It is therefore important to understand the impact of the feed on the sensory properties of the milk [1]. This study aims at demonstrating how analytical sensory analysis can provide important information about the influence of breed, season and variation in farm management from PB feeding regimes on the sensory properties of organic farm milk. The study was performed in 2007 and 2008 during two seasons (spring/autumn) representing 28 milk samples from 7 organic farms with either Holstein or Jersey cows. PB feeding regimes were based on pastures with varying amounts of white clover together with perennial ryegrass and supplement feeding with silage and concentrates. Significant results were found for season and breed with a larger variation in sensory flavour properties of spring milk and milk from Holstein cows. In general, there was a tendency of the milk being characterized as having a ‘greener’ odour, ‘sweet’ and ‘maize-like’ flavour in spring and a more ‘bitter’ taste in the autumn. The results show a distinct relation between sensory milk properties and the amount of pasture in the ration and white clover in the pasture. Relations to other production conditions such as composition of the supplement feed also tended to have an impact on the sensory characteristics of the milk. It is thus concluded, that a sensory analytical tool can provide important information about the sensory properties of organic farm milk, reflecting time and place. Seasonal variations appear to be an important factor in the terroir dimension of milk and may be more actively used in relation to communication of the sensory properties to the consumer

Monitoring panel performance within and between sensory experiments by multi-way analysis

In sensory analysis a panel of trained assessors evaluates a set of samples according to specific sensory descriptors. The training improves objectivity and reliability of assessments. However, there can be individual differences between assessors left after the training that should be taken into account in the analysis. Monitoring panel performance is then crucial for optimal sensory evaluations. The quality of the results is strongly dependent on the performance of each assessor and of the panel as a whole. The present work proposes to analyze the panel performance within single sensory evaluations and between consecutive evaluations. The basic idea is to use multi-way models to handle the three-way nature of the sensory data. Specifically, a PARAFAC model is used to investigate the panel performance in the single experiment. N-PLS model is used to test the predictive ability of the panel on each experiment. A PARAFAC model is also used for monitoring panel performance over different experiments

Composition of volatile compounds in bovine milk heat treated by instant infusion pasteurisation and their correlation to sensory analysis

Volatile compounds in skim milk and nonstandardised milk subjected to instant infusion pasteurisation at 80°C, 100°C and 120°C were compared with raw milk, high temperature short time pasteurised milk and milk pasteurised at 85°C ⁄ 30 s. The composition of volatile compounds differed between infusion pasteurisation treated samples and the reference pasteurisations. The sensory properties of skim milk subjected to instant infusion pasteurisation were described by negative attributes, such as cardboard sour and plastic flavours, which are not associated normally with fresh milk. Partial least squares modelling showed good correlation between the volatile compounds and the sensory properties, indicating the predictive and possible causal importance of the volatile compounds for the sensory characteristics

Instant infusion pasteurisation of bovine milk. I. Effects on bacterial inactivation and physical-chemical properties.

Two types of milk, skim milk and non-standardized raw milk, were heat treated using direct heating by instant infusion pasteurization with treatment temperatures in the range from 72°C to 120°C and with holding times of less than 1 second. Indirect heating by HTST pasteurization (72°C for 15 seconds) was used for comparison. The inactivation of microorganisms reached at least the same level when using instant infusion pasteurization compared to HTST pasteurization. Changes in the physical-chemical properties were observed in the skim milk fractions of instant infusion pasteurized non-standardized milk, whereas for instant infusion pasteurized skim milk less influence from the treatments was observed