作　　者： ; ; ; ; ;

机构地区： 石河子大学农学院

出　　处： 《西北农业学报》 2011年第8期89-94,共6页

摘　　要： 在滴灌条件下,研究农民习惯施氮模式、过量施氮模式、基于无机氮储量(Nmin)的氮素管理模式、基于计算机视觉的氮素营养诊断和氮素推荐施肥技术对棉花产量、氮肥利用率的影响。结果表明,基于计算机视觉的氮素营养诊断施肥技术和基于土壤Nmin的氮素管理模式比常规施肥模式分别减少了氮肥施肥量37.8%和56.3%,同时获得与常规施肥量相同的产量;与农民习惯施氮量相比,基于Nmin的氮素管理模式提高氮肥利用率27.80%,基于计算机视觉的氮素管理方法提高氮肥利用率16.96%;基于Nmin的氮素管理方法硝态氮残留为负值,基于计算机视觉的氮素管理方法比农民习惯施氮量减少了土壤硝态氮残留89.02%。基于Nmin或基于计算机视觉的氮素管理方法可明显提高氮肥施肥推荐质量,减少氮肥浪费,并减少对环境的氮排放。 This paper studied N rate,cotton yield and nitrogen use efficiency（NUE） in different N fertilization management in drip irrigation and plastic film mulch.Fertilization methods included farmer＇s conventional N fertilization practice（FP）,over N application pattern（NO）,N recommendation based on mineral nitrogen reserve of soil profiles（Nmin） and N recommendation based on computer vision（Ncv）.The results showed that compared with FP,Ncv method reduced N application by 37.8% and Nmin reduced N application by 56.3%.While cotton yield showed no significant difference among FP,Ncv and Nmin.NUE of Nmin and Ncv were significantly higher as compared to FP,increased by 27.80% and 16.96%,respectively.N soil residue in Nmin was negative,and Ncv reduced N residue in soil by 89.02%.Our results suggested that N recommendation based on Nmin or based on computer vision could significantly optimize N fertilization and reduced N environmental leakage.

关 键 词： 棉花 计算机视觉 土壤 氮素施肥管理 氮肥利用率

领　　域： [农业科学]