Sinesio F.(1), Paoletti F.(1), D’Egidio M.G.(2), Moneta E.(1), Nardo N.(1), Peparaio M.(1), Comendador F.J.(1)
(1) Istituto Nazionale di Ricerca per gli Alimenti e la Nutrizione (INRAN),
via Ardeatina 546 - 00178 Roma, Italy
(2) C.R.A. - Istituto Sperimentale per la Cerealicoltura
via Cassia, 176 - 00191 Roma, Italy
The quality of alimentary pasta is traditionally expressed by peculiar indices such as weight increase at optimal cooking time, stickiness or state of surface degradation, liveliness or degree of adhesion of pasta strands and firmness (effect to crush the pasta pieces). The last three indices are expressed as quality scores by a jury of experts (ISO/DIS 7304-2). Pasta quality is also expressed by mechanical properties defined as firmness, elasticity and adhesiveness, instrumentally measured. All these methods are quick and give accurate results, but objective methods without any correlation to sensory judgements make no sense.
Therefore, this study was aimed at exploring if such methods provide consistent correlation with a quantitative sensory evaluation of texture attributes.
Samples of spaghetti at the optimal cooking time were submitted to a descriptive trained panel. The sensory parameters of texture were hardness, or resistance to the compression between teeth, stickiness, defined as degree of adhesion of the pasta pieces during mastication, adhesiveness to teeth/palate after mastication due to the formation of a surface coating of amylase and springiness, or degree of length extension before breaking. Instrumental texture parameters were firmness (share work), adhesiveness and elasticity, determined as elastic modulus from the initial slop of the stress-strain curve, force at the strand rupture (tensile strength) and elongation at the strand rupture.
A PLS calibration/prediction model was built to identify the most relevant quality cooking indices and instrumental parameters to predict sensory attributes of texture. Elongation was a very good predictor of springiness; the quality index of firmness and the share work were the best predictors of hardness. The quality index of stickiness was an important descriptor of stickiness perceived in the mouth, whereas liveliness and adhesiveness (instrumental measure) were less predictive.
The validity of the model was tested for predictive ability and the predictive values were compared to the actual measured values. For most samples and attributes the predictive values were within 5% off of the real values.
