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Effects of drip irrigation nitrogen coupling on dry matter accumulation and yield of Summer Maize in arid areas of China
Field Crops Research  (IF5.224),  Pub Date : 2021-10-16, DOI: 10.1016/j.fcr.2021.108321
Liang Ma, Xu Zhang, Qingyuan Lei, Feng Liu

To explore the effects of irrigation and nitrogen on dry matter accumulation (DMA) and yield of summer maize in arid regions, field experiments were conducted in experimental plot in 2017 and 2018. There were three drip irrigation quotas (3000 m3/hm2, 3750 m3/hm2, and 4500 m3/hm2) and four nitrogen levels (no nitrogen applied, 168 kg/hm2, 306.5 kg/hm2, and 444.5 kg/hm2) set in the experiment. The Richards model was used to fit the relationship of DMA and irrigation quantity or nitrogen level, and then the dynamics of DMA of maize were investigated. Furthermore, the effects of irrigation and nitrogen on maize grain yield were analyzed. Results showed that the maximum and average DMA rates in maize plants increased as irrigation quota increased from 3000 to 3750 m3/hm2 and as the applied nitrogen increased from 0 to 306.5 kg/hm2. Maize plants under the condition of irrigation 3750 m3/hm2 together with nitrogen 306.5 kg/hm2 showed the maximum dry matter growth rate (GRmax), the maximum average dry matter growth rate (GRavg), the maximum duration of dry matter fast growth period, and the maximum DMA and grain yield. The maximum grain yield was up to 1.340 × 104 kg/hm2 and 1.291 × 104 kg/hm2 in 2017 and 2018, respectively. However, when the irrigation quota was increased to 4500 m3/hm2 and the nitrogen application rate was up to 444.5 kg/ hm2, GRmax, GRavg, and yield of maize were all decreased with the increase of irrigation quantity, this law is reproducible between years. So the management practice of irrigation 3750 m3/hm2 along with nitrogen 306.5 kg/hm2 is optimal for maize production in the experimental region. Furthermore, a stepwise regression model was established to predict grain yield (Y1) on the basis of the characteristic parameters of the Richards model, and the regression model was: Y1 = 0.499YGRmax+0.074GRavg-6.399x2+2.25, R2 = 0.803. The contribution rate of each characteristic parameter to yield prediction model from high to low was: YGRmax>GRavg>x2. GRavg was extremely positive correlated with the final DMA and yield of maize, the study would provide technical basis for the efficient utilization of water and nitrogen in arid regions.