Sensory and instrumental measurement of olive oil aroma

Sensory and instrumental measurement of olive oil aroma

Abstracts 85 Sensory-instrumentalcorrelationstrategiesto studyvarietalcharactersin raspberryflavour A. Paterson, J. R. Piggott and J. Jiang Centre fo...

126KB Sizes 4 Downloads 124 Views

Abstracts 85

Sensory-instrumentalcorrelationstrategiesto studyvarietalcharactersin raspberryflavour A. Paterson, J. R. Piggott and J. Jiang Centre forFood Quality, Food Science Group, University of Strathclyde, 131 Albion Street, Gbzsgow, UK Gl 1SD

Sensory and instrumentalmeasurementof olive oil aroma M. Bertuccioli, E. Monteleone, G. Caporale Dipartime-nto di BioIogia, University of Basilicata, Via N. Sauro, 85-85100, DISTAM,

Raspberries from varietal trials were collected from three successive crops, and quantitive descriptive analyses were performed. In general, varietal differences in volatile compounds were largely quantitive rather than qualitive. Close relationships were observed between ‘sweetness’ and sugar/acid ratio, contents. and ‘grassy’ notes and &Shexenol ‘Fruity (citric)’ character was related to dihydrodamascenone content and ‘floral’ and ‘honey’ notes to ionones. Although linalool and raspberry ketone are impact compounds for raspberry flavour, concentrations of these compounds were not important factors in varietal character. Redundancy analysis consistently explained more total variance than partial least square regression in this study.

Assessment of Braziliancoffee quality with a near-infraredspectrometer calibratedusing sensory evaluation data from an expert coffee tasterand a trainedpanel Alejandro M. Feria-Morales International

Coffee Organisation,

22 Berners Street, London,

UK WlP 400

The objective of this study was to investigate the possible development of an objective technique for the assessment of coffee quality in Brazil that would complement the present ‘tasting by an expert’ method already being correlated with the conventional profiling methodology. Approximately 500 samples of green coffee were tasted by the ‘coffee expert’ and analysed by a near-infrared spectrometer (NIR) . A selected representative number of samples of each Brazilian coffee type were assessed by conventional profiling. Principal component analysis and partial linear square regression techniques were applied. Reliable calibrations were obtained for predicting Brazilian coffee quality using the NIR directly on the samples of green coffee.

Potenza, Italy

and E. Pagliarini Via Celoria 2, 20133,

M&no,

Italy

The aroma of several samples of olive oil, varying in freshness, obtained from different olive varieties and technology systems were analysed. Seven aroma terms (cut green grassy, tomato leaf, artichoke, fresh green olive, golden apple, ripe black olive and nut/woody) were measured. Seven headspace olive oil compounds (hexanal, trans 2-hexenal, 3methyl-l-butanol, hexanol, c&%hexen1-01, trans3-hexen-l-ol and nonanal) were determined by using a purge and trap technique. A developed array of odour sensors, based on electrically conducting polymers, was utilised to produce concentration-independent patterns of responses which were used as odour descriptors. The results have shown the existence of a simple relationship between sensory and headspace volatile data (i.e. fresh green olive and cis-3hexanal) and more complicated relationship between odour pattern and the sensory and headspace data.

Sensory-instrumentalcorrelationsby combining data analysisand neural networkstechniques I. Bardot,’ L. Bochereaub N. Martinc and B. Palagos” “ENSIA 1, Avenue des Olympiades, 91305, France

Massy,

hCEA4AGRE& Part de Tourvoie, BP 121, 92185, Antony, France “TEPRAL 20, Rue Jacob, 67200 Cronenbourg, France

Strasbourg-

The paper investigates the potential of multilayer neural networks for modelling the correlations between instrumental and sensory characteristics of food products. Techniques such as principal components analysis or canonical analysis are traditionally used. Multilayer networks are artificial intelligence models well suited for dealing with non-linear prediction or classification problems. The authors suggest combining these techniques. Eighty-one beverage samples were described by their composition as well as their flavours scored