Production of high-quality tree fruit requires management of tree health and vigor during orchard establishment, especially with regard to soil-borne pathogens. Available strategies for the mitigation of soil-borne diseases include chemical fumigants, Brassicaceous seed meal (SM) soil treatments, and the use of disease-tolerant rootstock genotypes. It has been documented that superior disease suppression can be achieved using specific combinations of rootstock genotype and soil treatment that, in part, alter the soil microbiome. However, regardless of soil treatment strategy or rootstock genetics, sublethal levels of phytotoxic compounds are known to have negative effects on the reproductive output of plants. Yet the effects of SM amendments and the resultant restructuring of the soil microbiome on fruit quality are not well studied. Thus, our objective was to explore the effects of pathogen suppression strategies on at-harvest and postharvest fruit quality of ‘Gala’ apples (Malus domestica) by observing effects of both rootstock genetics [‘Malling 26’ (‘M.26’) vs. ‘Geneva 41’ (‘G.41’)] and soil treatment strategy (fumigation vs. SM). We observed that rootstock genotype generally appeared to have a stronger effect than soil treatment strategy on at-harvest fruit quality and postharvest outcomes. Further, although we did observe some fruit quality differences in each year of the study, there was no discernible pattern from year to year. We therefore conclude that, in our study, soil treatment does not have a consistent, significant influence on ‘Gala’ apple fruit quality, and importantly, efficacious ARD control using SM is without an apparent downside regarding fruit quality.
Complex changes in gene expression occur during postharvest storage of apple (Malus ×domestica) and often precede or accompany changes in ripening and disorder development. Targeted gene expression analysis fundamentally relies on previous knowledge of the targeted gene. Minimally, a substantial fragment of the gene sequence must be known with high accuracy so that primers and probes, which bind to their targets in a complimentary fashion, are highly specific. Here, we describe a workflow that leverages publicly available transcriptome data to discover apple cultivar–specific gene sequences to guide primer design for quantitative real-time polymerase chain reaction (qPCR). We find that problematic polymorphisms occur frequently in ‘Granny Smith’ and ‘Honeycrisp’ apple when candidate primer binding sites were selected using the ‘Golden Delicious’ genome. We attempted to validate qPCR-based gene expression measurements with RNA sequencing (RNA-Seq) analysis of the same RNA samples. However, we found that agreement between the two technologies was highly variable and positively correlated with the similarity between cultivar-specific genes and RNA-Seq reference genes. Thus, we offer insight that 1) improves the accuracy and efficiency of qPCR primer design in cultivars that lack sufficient sequence resources and 2) better guides the essential step of validation of RNA-Seq data with a subset of genes of interest examined via qPCR.