采用倒置“W”取样法对唐山、秦皇岛主要春玉米产区的田间杂草进行调查，利用茎叶处理法对烟嘧磺隆+莠去津药剂组合进行最佳配比筛选。结果表明，冀东地区发生优势度较大的杂草有马唐、稗草、鸭跖草、虎尾草、藜、反枝苋、马齿苋、苘麻、苣荬菜、铁苋菜、小马泡、豚草、葎草、狗尾草共14种。秦皇岛地区以藜、反枝苋、马齿苋、马唐、稗、苘麻、鸭跖草、苣荬菜和虎尾草为主，Shannon's指数H'为0.63，Shannon's均匀度指数E为0.09，Margalef物种丰富度指数D_MG为0.98；唐山地区以藜、马唐、鸭跖草、反枝苋、铁苋菜、苘麻、小马泡、豚草、葎草为主，Shannon's指数H'为0.51，Shannon's均匀度指数E为0.11，Margalef物种丰富度指数D_MG为1.56。药剂筛选结果显示，与其他处理相比，烟嘧磺隆+莠去津(30 g/hm²+285 g/hm²)组合对玉米田主要杂草的防效最高，药后14 d的株防效为93.55%，药后28 d的株防效和鲜重防效分别为95.32%和93.24%。

Weeds in the main spring corn production areas of Tangshan and Qinhuangdao were investigated by using the inverted "W"sampling method, and the optimal combination of nicosulfuron and atrazine was screened for control effect by by using the stem and leaf treatment method. There were 14 dominant weeds in eastern Hebei province, such as Digitaria sanguinalis, Echinochloa crusgalli, Commelina communis, Chloris virgata, Chenopodium album, Amaranthus retroflexus, Portulaca oleracea, Abutilon theophrasti, Sonchus arvensis, Acalypha australis, Cucumis bisexualis, Ambrosia artemisiifolia, Humulus scandens and Setaria viridis. The region of Qinhuangdao was dominated by C. album, A. retroflexus, P. oleracea, D. sanguinalis, E. crusgalli, A. theophrasti, C. communis, S. arvensis and C. virgata, Shannon's index H' was 0.63, Shannon's evenness index E was 0.09, and Margalef species richness index D_MG was 0.98, respectively. Furthermore, the region of Tangshan was dominated by C. album, D. sanguinalis, C. communis, A. retroflexus, A. australis, A. theophrasti, C. bisexualis, A. artemisiifolia and H. scandens, Shannon's index H' was 0.51, Shannon's evenness index E was 0.11, and Margalef species richness index D_MG was 1.56, respectively. Drag screening results showed that compared with other treatments, the combination of nicosulfuron and atrazine(30 g/ha+285 g/ha) had the highest control effect on main weeds in corn field, with the plant control effect of 93.55% at 14 days, the plant control effect and fresh weight control effect of 95.32% and 93.24% at 28 days, respectively.

S435.131

国家重点研发计划(2018YFD0200607)、河北省重点研发项目(19226504D)、河北省自然科学基金(C2020204036)