Integrated multi-omic analysis of fruit maturity identifies biomarkers with drastic abundance shifts spanning the harvest period in ‘Royal Gala’ apple

Accurate assessment of apple fruit maturity at harvest is required since fruit harvested too early or too late are susceptible to physiological disorders or excessive softening during subsequent storage. Biological markers of early fruit maturity allow forecasting of optimal harvest time, contributing significant industry value through more accurate management of harvest logistics. This study investigated the changes in cortex of apple ( Malus x domestica ‘Royal Gala’) fruit at four harvests: very early (H1), early (H2), commercial (H3) and late (H4), using a combination of transcriptomics, metabolomics, hormone abundances and enzyme activity profiles. Harvest times were discriminated based on several sets of variates, showing that metabolism was very active within this short time period. Good discrimination between H1 and H2 and between H2 and H3 was observed in the declining abundance of a range of photosystem transcripts and the increasing abundance of early ripening markers. Degradation of the photosynthetic apparatus was correlated with ethylene production. Multi-omics analysis using mixOmics identified groups of variates whose abundance declined or increased during the harvest period, and strong correlations between components of different pathways were evident. We identify a suite of biomarkers, including Chl a/b binding protein of LHCII , Xyloglucan glycosyltransferase 5 , PG1 , ACO1 , internal ethylene concentration and starch pattern index, for orchardists to accurately predict harvest time several weeks in advance, thus providing time to mobilise the necessary logistical resources. • Apple fruit maturity around the harvest period was assessed using multi-omics. • MixOmics and DIABLO was used to identify biomarkers of apple fruit maturity. • CAB of LHCII , XyGT5 , PG1 , ACO1 , IEC and SPI were identified as best biomarkers. • These biomarkers can be deployed to predict harvest time several weeks in advance. • Advance notice of optimal harvest provides time to mobilise logistical resources.