Seven studies reported data for fruit or vegetable consumption and all cause mortality.
Sample list, passport data and genotyping data for fruit shape and weight (SUN, LC, OVATE, FAS, FW2.2 and FW3.2).
Later, by combining the data for fruit weight from two mapping populations 'Royal Gala' × 'Braeburn' and 'Starkrimson' × 'Granny Smith', the QTLs were detected on eight linkage groups [ 31].
Hall et al. [ 23] were the first to quantify socio-demographic prevalence data for fruit and vegetable consumption in 52 WHS countries, also noting a trend for decreased risk factor prevalence with increased household wealth status, and prevalence rates of low fruit and vegetable consumption in excess of 70%.
In this analysis, we included all transcripts containing at least one ORF associated with ribosomes (the primary ORF) and sufficiently long UTR regions as to detect ribosome profiling reads (>30 nucleotides); insufficient data for fruit fly and yeast precluded the analysis for these species.
InterORF regions showed little signal when compared to the primary ORF, both in codRNAs and lncRNAs (Wilcoxon test, p < 10−9 in human, mouse, and zebrafish, p < 0.05 in Arabidopsis, insufficient data for fruit fly and yeast precluded the analysis for these species).
Significantly higher frequencies of occurrence of pesticide residues in conventional crops were also detected when data reported for fruits, vegetables and processed crop-based foods were analysed separately (Fig. 5).
When data reported for fruits and vegetables were analysed separately, a significant difference was detected for fruits, while only a trend towards a significant difference (P= 0·06) was observed for vegetables (Fig. 4), although there was no evidence of an interaction.
Gene expression data for apple fruit development was obtained from Janssen et al. [ 29].
Sales of unprocessed foods (i.e., excluding packaged and processed products) were based on aggregating sales data for fresh eggs, fruits, meats, nuts, seafood, and vegetables.
