Assessment of table olive fermentation by functional data analysis

• Functional data analysis (FDA) was used for the first time in food fermentations.
• FDA led to the estimation of microbiological and physicochemical functional curves.
• FDA also estimated the area under such curves and their means, minima, and maxima.
• Yeast growth was not affected by treatments, according to functional ANOVA.
• Changes in pH and acidity were affected by treatments, according to functional ANOVA.

For the first time, functional data analysis (FDA) was used to assess the effects of different treatments on Protection Denomination of Origin Aloreña de Málaga table olive fermentations, focusing on the evolution of yeast population. The analysis of fermentation by a conventional approach led to scarce information. However, the transformation of microbial (and also physicochemical) data into smooth curves allowed the application of a new battery of statistical tools for the analysis of fermentations (functional pointwise estimation of the averages and standard deviations, maximum, minimum, first and second derivatives, functional regression, and functional F and t-tests). FDA showed that all the treatments assayed led to similar trends in yeast population while changes in pH and titratable acidity profiles led to several significant differences. Therefore, FDA represents a promising and valuable tool for studying table olive fermentations and for food microbiology in general.