Evaluation of sensory parameters of grapes using near infrared spectroscopy

• Published in: Journal of food engineering Vol. 118; no. 3; pp. 333 - 339
• Main Authors: Ferrer-Gallego, Raúl, Hernández-Hierro, José Miguel, Rivas-Gonzalo, Julián C., Escribano-Bailón, M. Teresa
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2013
• Subjects: Astringency; color; Colour; decision making; grape seeds; Grapes; Hardness; harvest date; Infrared spectroscopy; least squares; Mathematical models; Near infrared spectroscopy; odors; prediction; red wines; Regression analysis; Seeds; Sensory analysis; sensory evaluation; sourness; taste; Texture; Vitaceae; Near infrared spectroscopy; Sensory analysis; Astringency; Grapes
• ISSN: 0260-8774; 1873-5770
• DOI: 10.1016/j.jfoodeng.2013.04.019

•NIRS technology has a great potential to predict sensory attributes.•It allows to evaluate taste, texture, visual and olfactory attributes from grapes.•NIRS technology seems a useful tool to determine the optimal harvest time.•4.5–8.7% of difference between sensory analysis and NIRS in seeds.•9.8–13.7% of difference between sensory analysis and NIRS in skins. Grape seed and skin sensory parameters are important characteristics in making decisions concerning the optimal harvest time and producing high-quality red wines. The potential of near infrared spectroscopy to determine several sensory parameters of seeds and skins was evaluated. Taste (sourness), texture (astringency, tannic intensity, dryness and hardness), visual (colour) and olfactory (intensity and type of aroma) attributes were considered. Calibration models were performed by modified partial least squares regression. The differences between sensory analysis and NIRS analysis in external validation were lower in the case of seeds; they were between 4.5% for hardness and 8.7% for colour. For the skins, differences in external validation were between 9.8% for tannic intensity and 13.7% for astringency. The results obtained show that NIRS technology has considerable potential for predicting the above sensory attributes.