Incomplete block designs for the minimisation of order and carry-over effects in sensory analysis

Ball, Roderick D.

doi:10.1016/s0950-3293(96)00026-2

Cited by 31 publications

(25 citation statements)

References 20 publications

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“…These results confirm that while order and carry-over effects can be significant, if the design was constructed so that it was balanced, or nearly balanced, for order and there was a similar range in palatability of samples being tested, then statistical adjustment appeared unnecessary. This was similar to the conclusion of Ball (1997).…”

Section: Adjustment For Design and Demographic Effects On Sensory Scoressupporting

confidence: 91%

“…Previous work by Neely et al (1999) has shown between city differences in consumer overall liking scores for in-home evaluations of beef conducted in four cities in the United States. Ball (1997) discussed the difficulties in obtaining unbiased and accurate scores from sensory studies. There are constraints in the number of samples that can be tested by each panellist and the scores given by individual panellists may also be influenced by the samples that have been tasted previously (carry-over effect) and/or by the number of samples previously tasted (order of presentation effect).…”

Section: Introductionmentioning

confidence: 99%

“…There are constraints in the number of samples that can be tested by each panellist and the scores given by individual panellists may also be influenced by the samples that have been tasted previously (carry-over effect) and/or by the number of samples previously tasted (order of presentation effect). To minimise the influence of these effects, several workers (MacFie et al 1989;Schlich 1993;Ball 1997;Ferris et al 2003) have suggested the use of Latin square designs, where the samples from any treatment are allocated to different positional orders in association with different samples. The authors are not aware of studies that have examined the importance of these factors in consumer groups from diverse cultural backgrounds.…”

Section: Introductionmentioning

confidence: 99%

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Demographic and design effects on beef sensory scores given by Korean and Australian consumers

Hwang¹,

Polkinghorne²,

Lee³

et al. 2008

Aust. J. Exp. Agric.

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Abstract. Data from 648 beef samples, which had been sensory tested by 720 Korean and 540 Australian consumers were used to quantify design and demographic effects on beef sensory scores. The samples were from 36 carcasses, where sides had been either hung by the Achilles tendon or hip suspended. At boning, samples from three muscles (M. triceps brachii, M. longissimus dorsi and M. semimembranosus) were prepared and cooked by either grill (25-mm-thick steaks) or Korean barbeque (BBQ, 4-mm-thick samples) methods. A Latin square design was used to allocate samples to different presentation orders to be tasted in association with different samples. For both cooking techniques each consumer tested a starter sample followed by six experimental samples, with each sample being tasted by 10 different consumers.Design (taste panel, session, order, carry-over, sample and consumer) and demographic (age class, gender, occupation, frequency of eating meat, number of adults and children living in the house, their appreciation of meat and degree of doneness and income) effects were examined separately for tenderness, juiciness, like flavour, overall liking and a composite palatability score, within the four consumer group/cooking method subclasses. For grill samples, order of presentation was significant for most sensory variables. For BBQ samples, order of presentation failed to achieve significance for Australian consumers, but was significant (P < 0.05) for Korean consumers. Carry-over effects tended to be more important for juiciness and like flavour scores than other sensory scores. Demographic effects were generally not significant (P > 0.05) for all consumer group/cooking methods. Correlations between raw scores and those adjusted for design and demographic effects ranged from 0.93 to 0.99, indicating that if the design was balanced, or nearly balanced for design effects, then further adjustment of sensory scores was not necessary. Clipping 40% of outlying consumer scores reduced the variance of the sample mean by~30%.

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Section: Adjustment For Design and Demographic Effects On Sensory Scoressupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Demographic and design effects on beef sensory scores given by Korean and Australian consumers

Hwang¹,

Polkinghorne²,

Lee³

et al. 2008

Aust. J. Exp. Agric.

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show abstract

“…While the traditional recommendation had been to simply randomize the order in which the products are presented to the assessors, the publication of the seminal paper by MacFie, Greenhoff, Bratchell, and Vallis (1989) has started a discussion about the use of neighbour balanced designs. While MacFie et al (1989), Schlich (1993) and Wakeling and MacFie (1995) discussed construction methods for neighbour balanced designs, Ball (1997) and Périnel and Pagès (2004) deal with designs that are ''near'' such designs.…”

Section: Introductionmentioning

confidence: 99%

“…The construction methods in Ball (1997) and Périnel and Pagès (2004) try to achieve designs that are as similar as possible to such neighbour balanced Generalized Youden Designs. They do not claim to minimize some theoretical concept like bias due to carryover effects, or variance of the estimates.…”

Section: Introductionmentioning

confidence: 99%

On nearly balanced designs for sensory trials

Kunert

Sailer

2006

Food Quality and Preference

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In sensory experiments, often neighbour balanced designs are used. The idea behind these designs is to control for possible carryover effects, like, e.g. a lingering taste of the products. These designs do not allow to randomize the order of presentation of the products to the assessors. We therefore consider the randomization of assessors and product labels. For some designs, this randomization validates the use of the simple row-column model, as long as there are no carryover effects present. If there are carryover effects, the estimate of the variance becomes conservative for special neighbour balanced designs, so-called totally balanced designs.Usually, for given numbers of products, of assessors and of assessments per assessor, these special designs do not exist. Several authors [e.g. Périnel, E., & Pagès, J. (2004). Optimal nested cross-over designs in sensory analysis. Food Quality and Preference, 15, 439-446] recommend algorithms to construct designs that come near to the properties of totally balanced designs. The main purpose of the paper is to demonstrate with the help of a simulation study that these designs indeed perform similarly.It has to be pointed out, however, that these results only hold if the analysis takes period effects into account. Analysis with the simple block model can lead to grossly wrong estimation of the variance.

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