Determination of consumer acceptance limits to sensory defects using survival analysis

Hough, Guillermo; Garitta, Lorena; Sánchez, Ricardo

doi:10.1016/j.foodqual.2004.02.006

Cited by 50 publications

(63 citation statements)

References 8 publications

(9 reference statements)

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“…Food quality control and assurance is evidently a top subject both in industry and in public control institutions (Juran, 1974;Herschdoerfer, 1986;Stauffer, 1988). A basic requirement of any sensory quality control (QC) system is the definition of standards or tolerance limits on a sensory basis for the product (Hough, Garitta and Sánchez, 2004).…”

Section: Why Investigate Quality?mentioning

confidence: 99%

Relating physico‐chemical properties of frozen green peas (Pisum sativum L.) to sensory quality

2013

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BACKGROUND The acceptability of frozen green peas depends on their sensory quality. There is a need to relate physico‐chemical parameters to sensory quality. In this research, six brands of frozen green peas representing product sold for retail and caterer's markets were purchased and subjected to descriptive sensory evaluation and physico‐chemical analyses (including dry matter content, alcohol insoluble solids content, starch content, °Brix, residual peroxidase activity, size sorting, hardness using texture analysis and colour measurements) to assess and explain product quality. RESULTS The sensory quality of frozen green peas, particularly texture properties, were well explained using physico‐chemical methods of analysis notably alcohol insoluble solids, starch content, hardness and °Brix. Generally, retail class peas were of superior sensory quality to caterer's class peas although one caterer's brand was comparable to the retail brands. Retail class peas were sweeter, smaller, greener, more moist and more tender than the caterer's peas. Retail class peas also had higher °Brix, a*, hue and chroma values; lower starch, alcohol insoluble solids, dry matter content and hardness measured. CONCLUSIONS The sensory quality of frozen green peas can be partially predicted by measuring physico‐chemical parameters particularly °Brix and to a lesser extent hardness by texture analyser, alcohol insoluble solids, dry matter and starch content. © 2013 Society of Chemical Industry

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Section: Why Investigate Quality?mentioning

confidence: 99%

Relating physico‐chemical properties of frozen green peas (Pisum sativum L.) to sensory quality

2013

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“…To this regard, the methodology providing comprehensive information to determine shelf life using consumer data is based on survival analysis of food acceptability [17,18,25]. According to the industrial policy, the food company can choose more or less risk by selecting, as the acceptance limit, the proper percentage of consumers who reject the product.…”

Section: Identification Of the Acceptability Limitmentioning

confidence: 99%

Shelf-Life Testing of Coffee and Related Products: Uncertainties, Pitfalls, and Perspectives

2009

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The word coffee comprises a number of different products from whole-and ground-roasted coffee to a wide variety of convenience and semi-manufactured products such as instant coffee, coffee concentrates and ready-to-drink coffee beverages. Each of these products has peculiar characteristics and thus different deteriorative mechanisms determining their shelf life. For this reason, shelf-life testing should be carefully designed by taking into account the peculiarity of the product. Despite the worldwide importance of coffee products, little data are available on their shelf life and on the relevant assessment methodologies. The aim of this article is to present uncertainties and pitfalls of coffee derivatives shelf-life testing as well as to highlight novel perspectives which allow developing future approaches for their dating. In particular, after describing the main quality decay reactions in coffee derivatives, literature data on coffee shelf life will be reviewed and methodologies for shelf-life testing of coffee derivatives critically discussed.

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“…Based on an adopted rejection probability (usually 50%), the sensory shelf life of the product can thus be estimated. The methodology was then extended to estimating concentration limits of sensory defects (Hough et al 2004) and optimum concentrations of a food ingredient (Garitta et al 2006). In these studies, there was no "correct" result as consumers simply stated their acceptance or rejection for samples with different levels of the substance of interest.…”

Section: Introductionmentioning

confidence: 99%

Survival Analysis Statistics Applied to Threshold Data Obtained from the Ascending Forced‐Choice Method of Limits

Hough

Methven

Lawless

2013

Journal of Sensory Studies

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Sensory thresholds are often collected through ascending forced-choice methods. Group thresholds are important for comparing stimuli or populations; yet, the method has two problems. An individual may correctly guess the correct answer at any concentration step and might detect correctly at low concentrations but become adapted or fatigued at higher concentrations. The survival analysis method deals with both issues. Individual sequences of incorrect and correct answers are adjusted, taking into account the group performance at each concentration. The technique reduces the chance probability where there are consecutive correct answers. Adjusted sequences are submitted to survival analysis to determine group thresholds. The technique was applied to an aroma threshold and a taste threshold study. It resulted in group thresholds similar to ASTM or logarithmic regression procedures. Significant differences in taste thresholds between younger and older adults were determined. The approach provides a more robust technique over previous estimation methods. PRACTICAL APPLICATIONSDetection thresholds can indicate the level at which the average person is likely to notice a taste or smell. Therefore, they serve as an informative benchmark of when a tastant or aroma material will have an effect on consumer perception of that taste or flavor. They also serve as an indicator of the biological (sensory) potency of various taste and flavor materials. The survival analysis method outlined in this paper is recommended for the analysis of threshold data collected through the forced-choice ascending concentration series method of limits. The new method takes into consideration an individual's sequence of incorrect and correct answers and the group's overall performance for a particular concentration, adjusting the individual's answers in a uniform manner. The adjusted answers can then be submitted to survival analysis statistical estimations to obtain more accurate group thresholds.

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Determination of consumer acceptance limits to sensory defects using survival analysis

Cited by 50 publications

References 8 publications

Relating physico‐chemical properties of frozen green peas (Pisum sativum L.) to sensory quality

Relating physico‐chemical properties of frozen green peas (Pisum sativum L.) to sensory quality

Shelf-Life Testing of Coffee and Related Products: Uncertainties, Pitfalls, and Perspectives

Survival Analysis Statistics Applied to Threshold Data Obtained from the Ascending Forced‐Choice Method of Limits

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