Grain　crops　are　easily　contaminated　by　fungi　due　to　the　existence　of　various　microorganisms　in　the　storage　process,　especially　in　humid　and　warm　storage　conditions.　Compared　with　conventional　methods,　surface-enhanced　Raman　scattering　(SERS)　has　paved　the　way　for　the　detection　of　fungi　in　grain　crops　as　it　is　a　rapid,　nondestructive,　and　sensitive　analytical　method.　In　this　work,　Aspergillus　niger,　Saccharomyces　cerevisiae,　Fusarium　moniliforme　and　Trichoderma　viride　in　grain　crops　were　detected　using　colloidal　Au　nanoparticles　and　SERS.　The　results　indicated　that　different　fungi　showed　different　Raman　phenotypes,　which　could　be　easily　characterized　by　SERS.　Combined　with　multivariate　statistical　analysis,　identification　of　a　variety　of　fungi　could　be　accomplished　rapidly　and　accurately.　This　research　can　be　applied　for　the　rapid　detection　of　fungi　in　the　food　and　biomedical　industries.