Feasibility of Little Cherry/X-Disease Detection in Prunus avium Using Field Asymmetric Ion Mobility Spectrometry.

Abstract

Little cherry disease (LCD) and X-disease have critically impacted the Pacific Northwest sweet cherry ( Prunus avium ) industry. Current detection methods rely on laborious visual scouting or molecular analyses. This study evaluates the suitability of field asymmetric ion mobility spectrometry (FAIMS) for rapid detection of LCD and X-disease infection in three sweet cherry cultivars ('Benton', 'Cristalina', and 'Tieton') at the post-harvest stage. Stem cuttings with leaves were collected from commercial orchards and greenhouse trees. FAIMS operated at 1.5 L/min and 50 kPa, was used for headspace analysis. Molecular analyses confirmed symptomatic and asymptomatic samples. FAIMS data were processed for ion current sum (I sum ), maximum ion current (I max ), and area under the curve (I AUC ). Symptomatic samples showed higher ion currents in specific FAIMS regions ( p < 0.05), with clear differences between symptomatic and asymptomatic samples across compensation voltage and dispersion field ranges. Cultivar-specific variation was also observed in the data. FAIMS spectra for LCD/X-disease symptomatic samples differed from those for asymptomatic samples in other Prunus species, such as peach and nectarines. These findings support FAIMS as a potential diagnostic tool for LCD/X disease. Further studies with controlled variables and key growth stages are recommended to realize early-stage detection.

Plant phenotyping relevance

FAIMSを用いてサクランボ樹体の感染症状を非破壊的に識別し、症候性・無症候性試料を比較評価した診断手法の検証研究であり、植物状態の取得方法が中心である。

Code and data availability

The supplied blocks describe FAIMS headspace measurements of cherry stem samples and a custom Python analysis pipeline, but contain no public dataset deposit, no author-hosted code URL, and no data availability statement. The custom Python script is mentioned only as 'custom-developed' with no availability language or,

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