The　lack　of　multidimensional　knowledge　means　that　current　reasoning　methods　for　rice　fertilization　cannot　make　decisions　accurate　when　faced　with　complex　spatiotemporal　conditions　in　general.　Therefore,　we　propose　a　reasoning　method　for　rice　fertilization　strategy　based　on　spatiotemporal　knowledge　graph.　First,　we　systematically　organize　multisource　expert　knowledge　about　rice　fertilization,　and　construct　an　ontology　for　rice　fertilization　consisting　of　five　core　elements:　rice　variety,　planting　environment,　nutrition　diagnosis,　fertilization　schemes,　and　time　and　place.　Spatiotemporal　differences　in　rice　fertilization　knowledge　are　expressed　by　assessing　spatiotemporal　concepts,　relations,　and　state　instances.　Second,　we　propose　a　reasoning　method　for　rice　fertilization　strategy　based　on　the　constructed　knowledge　graph.　This　method　leverages　a　certainty　factor　model　for　nutrition　diagnosis　and　integrates　case-based　and　rule-based　reasoning　to　determine　fertilization　schemes　for　different　stages.　Finally,　taking　Pucheng　County,　China,　as　an　example,　knowledge　from　crowd-sensing　data　is　obtained　to　construct　a　knowledge　graph　using　the　proposed　method.　The　results　demonstrate　the　method　can　support　the　expression　and　complex　reasoning　of　rice　fertilization　decisions　under　different　spatiotemporal　conditions.