Lotus　seed　is　an　important　medicine　and　edible　food,　but　to　dry　lotus　seeds　cook　requires　a　long　time,　so　lotus　seed　powder　is　more　popular　by　consumers　to　adapt　to　the　modern　fast-paced　way　of　life.　In　this　paper,　lotus　seed　powder　adulterated　with　sweet　potato　powder,　corn　flour　and　wheat　flour　were　identified　by　near　infrared　spectroscopy　(NIRs)　technique.　Support　vector　machine　(SVM),　least　squares　support　vector　machine　(LS-SVM)　and　partial　least　squares　discriminate　analysis　(PLS-DA)　were　used　to　identify　the　model　when　thecategory　was　known,　and　the　clustering　algorithm　was　usedotherwise.　In　addition,　the　moisture　content　of　lotus　seeds　powder　was　quantitatively　analyzed　by　partial　least　squares　(PLS)　regression.　The　results　showed　that　the　discrimination　accuracy　of　LS-SVM　modelis　100%,　and　the　clustering　algorithm　could　effectively　identify　the　5%　adulteration　ofsweet　potato　powder,　corn　flour　and　wheat　flour.　Moreover,　performance　of　PLS　model　to　predict　the　moisture　content　in　the　lotus　seed　powder　is　good,　and　the　accuracy　of　model　by　Normalize　was　satisfactory　with　the　coefficients　of　determination　of　calibration　(Rc2=0.973　2),　the　coefficients　of　determination　of　prediction　(Rp2=0.969　5),　root　mean　square　errors　of　calibration　(RMSEC=0.111　5),　and　good　root　mean　square　errors　of　prediction　(RMSEP=0.118　9).　The　results　showed　that　the　near　infrared　spectroscopy　is　a　fast,　accurate　and　nondestructive　analysis　method　to　rapidly　identify　the　lotus　seed　powder,　accurately　determinate　the　water　content　in　lotus　seed　powder,　and　availably　provide　a　useful　idea　for　quality　testing　of　daily　food.　©　2018,　Peking　University　Press.　All　right　reserved.