Strawberry powdery mildew (Podosphaera aphanis) causes serious losses in UK crops, potentially reducing yields by as much as 70%. Consequently, conventional fungicide application programmes tend to recommend a prophylactic approach using insurance sprays, risking the development of fungicide insensitivity and requiring careful management relative to harvest periods to avoid residual fungicides on harvested fruit. This paper describes the development of a prediction system to guide the control of P. aphanis  by the application of fungicides only when pathogen infection and disease progression are likely. The system was developed over a 15-year period on commercial farms starting with its establishment, validation and then deployment to strawberry growers. This involved three stages: 1. Identification and validation of parameters for inclusion in the prediction system (2004-2008). 2. Development of the prediction system in compact disc format (2009-2015). 3. Development and validation of the prediction system in a web-based format and cost-benefit analysis (2016-2020). The prediction system was based on the temporal accumulation of conditions (temperature and relative humidity) conducive to the development of P. aphanis , which sporulates at 144 accumulated disease-conducive hours. Sensitivity analysis was performed to refine the prediction system parameters. Field validation of the results demonstrated that to effectively control disease, the application of fungicides was best done between 125 and 144 accumulated hours of disease-conducive conditions. A cost-benefit analysis indicated that, by comparison with the number and timing of fungicide applications in conventional insurance disease control programmes, the prediction system enabled good disease control with significantly fewer fungicide applications (between one and four sprays less) (df=7, t=7.6, p =0.001) and reduced costs (savings between £35-£493/hectare) (df=7, t=4.0, p =0.01) for the growers.

Summary Plant-parasitic nematodes (PPN) are an economically important group of crop pests and are oviparous animals; all nutrients required to develop and ensure the survival of their unhatched progeny need to be deposited within the egg, including proteins. The most abundant protein deposited is vitellin, formed of a precursor protein vitellogenin, which has roles in transporting lipids, providing amino acids and influencing post-embryonic development. The genes encoding vitellogenin have been well studied in Caenorhabditis elegans, but little is known about vitellogenin in PPN. Using the vitellogenin gene sequences from C. elegans, homologous sequences in the genomes of some economically important cyst and root-knot nematodes were identified and hypothetical vitellogenin genes were predicted. Protein domains were then determined. Sequences were aligned using MUSCLE and then used to construct phylogenetic trees using the maximum likelihood method. With the availability of genomic data and use of online local alignment tools, the vitellogenin encoding genes from C. elegans could be aligned to PPN genomes. All predicted genes contained the same protein domains as C. elegans; Vitellogenin_N, vitellogenin open beta-sheet and von Willebrand factor domain type D. The constructed phylogenetic tree clustered the species into four groups: root-knot nematodes, two cyst nematode groups and Caenorhabditis species. By determining the hypothetical vitellogenin genes in PPN and inferring their relationships, this could form a potential basis to understand further the role of vitellogenin in cyst and root-knot nematodes.

All plants grown in soil contain silicon (Si) in their tissues (e.g. leaf hairs), with concentrations that vary from 0.1% to 10% of their dry weight. Strawberry is a Si non-accumulator (<1% dry weight)