Transcriptomics, sensorial analysis and volatilome fingerprinting of fresh produce: a multi-trait approach to identify predictors of food quality

Fruit quality is determined by numerous traits including sweetness, colour, aroma, acidity and firmness. Quality has become an important characteristic for the consumer. Therefore, the fruit industry needs to ensure and optimize product quality throughout the supply chain. Volatilome fingerprinting combined with gene expression profiling can provide evidence for fruit quality differences and changes which can be related to genotype selection, geographical origins, post-harvest storage and supply chain processing (such as washing, drying, and trimming). In this context, next generation sequencing and metabolomics technologies can be very useful by allowing comprehensive, simultaneous characterization of metabolite and gene expression data from diverse genotypes of the same species as well as assessing effects of post- harvest storage conditions. Here, comprehensive two-dimensional gas chromatography (GC×GC) combined with time-of-flight mass spectrometry (TOF-MS) was used to analyse the volatilome of peach (Prunus persica (L. Batsch) fruits. An RNA-sequence transcriptomic approach was employed to identify differentially expressed genes (DEGs) amongst post-harvest treatments focusing on those associated with volatile organic compound (VOC) metabolism in order to better understand mechanisms underlying their modulation post-harvest. Peach fruits are characterized by a rapid deterioration at room temperature meaning that cold storage is widely used to delay post-harvest ripening of the fruit and extend its commercial life. It is, therefore of considerable scientific and economic interest to improve our knowledge of the mechanisms by which fruit respond to cold stress. Our study, focussed on one peach (cv Sagittaria) and one nectarine (cv Big Top) cultivar: fruits were analysed immediately after harvest and after 1, 5, 7 and 14 days of cold storage at 1°C. A total of 159 VOCs were identified for Sagittaria, while 89 VOCs were detected for Big Top. Canonical Analysis of Principal coordinates (or CAP) on VOC profiles showed a discrimination between cultivars and post-harvest storage periods. A combination of sensory evaluation and VOC profiles showed the same trend reported by CAP analysis. Furthermore, correlation between the expression profile of flavour-related genes and VOCs was shown. For example genotype specific activation of some VOC biosynthetic pathways, such as that related to sesquiterpenoid and triterpenoids biosynthesis, was observed in Sagittaria. Differences were also detected in sensory characteristics. Overall the combination of sensory evaluation, VOC profiles and gene expression could help breeders to understand which traits/aroma are more relevant to consumer perception. Furthermore, understanding of metabolic and genetic changes occurring in fruit VOC patterns post-harvest could contribute to providing a suite of simple diagnostic checks to monitor fruit quality throughout the supply chain