CHEMICAL PREDICTORS OF SWEETNESS AND SOURNESS IN BANANA
Assessing sensory properties is time consuming because it is labor intensive and requires a lot of logistics. To be able to take sweetness and sourness into account earlier in the assessment of a new banana hybrid in a selection scheme, we looked for chemical indicators. Ten trained panellists evaluated the two taste attributes on a 0-9 scale in 17 dessert banana cultivars. Dry matter (DM), total soluble solids (TSS), pH, and titratable acidity (TA) were concomitantly measured in the fruits. Linear regressions were established between sensory properties and chemical parameters with a set of 46 data. Sweetness was best predicted as a function of pH and TSS (Y = 2.85×pH + 0.25×TSS - 13.6; R2= 0.79). Sourness was best predicted as a function of TA (Y= 0.56×TA - 0.46; R2= 0.75). Our data suggest that these chemical parameters, which are easy to measure, can thus be used to predict taste in new hybrid bananas without undertaking sensory analysis.
Bugaud, C., Daribo, M.O., Deverge, E., Fils-Lycaon, B. and Mbéguié-A-Mbéguié, D. (2012). CHEMICAL PREDICTORS OF SWEETNESS AND SOURNESS IN BANANA. Acta Hortic. 928, 211-215
Musa, fruit, sensory profile analysis, acidity, cultivar, linear regression