Flood　has　an　important　effect　on　plant　growth　by　affecting　their　physiologic　and　biochemical　properties.　Soybean　is　one　of　the　main　cultivated　crops　in　the　world　and　the　United　States　is　one　of　the　largest　soybean　producers.　However,　soybean　plant　is　sensitive　to　flood　stress　that　may　cause　slow　growth,　low　yield,　small　crop　production　and　result　in　significant　economic　loss.　Therefore,　it　is　critical　to　develop　soybean　cultivars　that　are　tolerant　to　flood.　One　of　the　current　bottlenecks　in　developing　new　crop　cultivars　is　slow　and　inaccurate　plant　phenotyping　that　limits　the　genetic　gain.　This　study　aimed　to　develop　a　low-cost　3D　imaging　system　to　quantify　the　variation　in　the　growth　and　biomass　of　soybean　due　to　flood　at　its　early　growth　stages.　Two　cultivars　of　soybeans,　i.e.　flood　tolerant　and　flood　sensitive,　were　planted　in　plant　pots　in　a　controlled　greenhouse.　A　low-cost　3D　imaging　system　was　developed　to　take　measurements　of　plant　architecture　including　plant　height,　plant　canopy　width,　petiole　length,　and　petiole　angle.　It　was　found　that　the　measurement　error　of　the　3D　imaging　system　was　5.8%　in　length　and　5.0%　in　angle,　which　was　sufficiently　accurate　and　useful　in　plant　phenotyping.　Collected　data　were　used　to　monitor　the　development　of　soybean　after　flood　treatment.　Dry　biomass　of　soybean　plant　was　measured　at　the　end　of　the　vegetative　stage　(two　months　after　emergence).　Results　show　that　four　groups　had　a　significant　difference　in　plant　height,　plant　canopy　width,　petiole　length,　and　petiole　angle.　Flood　stress　at　early　stages　of　soybean　accelerated　the　growth　of　the　flood-resistant　plants　in　height　and　the　petiole　angle,　however,　restrained　the　development　in　plant　canopy　width　and　the　petiole　length　of　flood-sensitive　plants.　The　dry　biomass　of　flood-sensitive　plants　was　near　two　to　three　times　lower　than　that　of　resistant　plants　at　the　end　of　the　vegetative　stage.　The　results　indicate　that　the　developed　low-cost　3D　imaging　system　has　the　potential　for　accurate　measurements　in　plant　architecture　and　dry　biomass　that　may　be　used　to　improve　the　accuracy　of　plant　phenotyping.