• ISSN 1008-505X
  • CN 11-3996/S
付江鹏, 贾彪, 魏雪, 兰宇. 基于冠层覆盖度的玉米植株临界氮浓度模型构建与产量预测[J]. 植物营养与肥料学报, 2021, 27(10): 1703-1713. DOI: 10.11674/zwyf.20621
引用本文: 付江鹏, 贾彪, 魏雪, 兰宇. 基于冠层覆盖度的玉米植株临界氮浓度模型构建与产量预测[J]. 植物营养与肥料学报, 2021, 27(10): 1703-1713. DOI: 10.11674/zwyf.20621
FU Jiang-peng, JIA Biao, WEI Xue, LAN Yu. Construction of critical nitrogen concentration model based on canopy coverage and the accuracy in yield prediction of maize[J]. Journal of Plant Nutrition and Fertilizers, 2021, 27(10): 1703-1713. DOI: 10.11674/zwyf.20621
Citation: FU Jiang-peng, JIA Biao, WEI Xue, LAN Yu. Construction of critical nitrogen concentration model based on canopy coverage and the accuracy in yield prediction of maize[J]. Journal of Plant Nutrition and Fertilizers, 2021, 27(10): 1703-1713. DOI: 10.11674/zwyf.20621

基于冠层覆盖度的玉米植株临界氮浓度模型构建与产量预测

Construction of critical nitrogen concentration model based on canopy coverage and the accuracy in yield prediction of maize

  • 摘要:
    目的 依据临界氮浓度稀释原理,构建基于冠层覆盖度的覆膜滴灌玉米植株临界氮浓度稀释曲线,并通过氮营养指数和氮累积亏缺量模型对玉米氮营养状况进行诊断和评价,以期达到基于该模型的玉米产量预测。
    方法 于2019—2020年,在宁夏引黄灌区开展了4个氮肥用量(0、120、240、360 kg/hm2)田间试验,采用滴灌水肥一体化技术,氮肥按照苗期10%、拔节—大喇叭口期45%、抽雄—吐丝期20%和灌浆期25%的比例分8次随水追肥。在玉米关键生育时期测定农学参数和图像参数,分别测定了地上部生物量、植株氮浓度和产量,建立和验证基于冠层覆盖度的玉米植株临界氮浓度经验模型。
    结果 基于冠层覆盖度的玉米植株临界氮浓度、最大氮浓度和最小氮浓度模型R2分别为0.917、0.843、0.873。临界氮浓度模型检验参数RMSEn-RMES分别为 0.242和 11.753%。以冠层覆盖度为基础的氮营养指数和氮累积亏缺量推算出玉米最佳施氮处理为240 kg/hm2。不同生育时期氮营养指数、氮累积亏缺量与相对产量的关系极显著,R2均不小于0.922,且大喇叭口期和抽雄期R2值最高。采用独立试验验证表明,在大喇叭口期和抽雄期表现出稳定的模型性能,R2值≥0.944,n-RMSE均≤9.089%。在大喇叭口期和抽雄期,氮营养指数、氮累积亏缺量与相对产量呈极显著相关,能准确地解释受氮素限制和不受氮素限制生长条件下相对产量的变化。
    结论 基于冠层覆盖度构建的植株临界氮浓度稀释曲线可准确判断和评价玉米拔节期至吐丝期的氮素营养状况,依据氮营养指数、氮累积亏缺量与相对产量所构建的关系模型可对玉米产量进行准确估计,其为玉米生长过程中氮肥的精确管理和产量预测提供了一种简便的新方法。

     

    Abstract:
    Objectives The critical nitrogen concentration dilution curve of irrigated maize based on canopy coverage was constructed. Then, the nitrogen in maize was assessed by nitrogen nutrient index and nitrogen accumulation deficit model for predicting maize yield.
    Methods Field trials with four nitrogen fertilizer rates (0, 120, 240 and 360 kg/hm2) were conducted in Ningxia Yellow River Irrigation Area of China from 2019 to 2020. Water and fertilizer integration technology of drip irrigation was adopted. Nitrogen top-dressing was divided into eight times with irrigation according to the proportion of 10% at seedling stage, 45% at jointing to flare opening stage, 20% at tasseling to silking stage, and 25% at grain-filling stage. Aboveground biomass, plant nitrogen concentration and yield were measured during the critical growth stages of maize, and the empirical model of maize critical nitrogen concentration based on canopy coverage was established and verified.
    Results The R2 values of maize critical N concentration, maximum N concentration and minimum N concentration based on canopy coverage were 0.917, 0.843 and 0.873, respectively. RMSE and n-RMSE of critical nitrogen concentration model were 0.242 and 11.753%, respectively. Based on N nutrient index and N accumulation deficit, the optimal N application treatment for maize was 240 kg/hm2. The relationships between N nutrient index, N accumulation deficit and relative yield were strongly significant at different growth stages, with R2 not less than 0.922, and the R2 values were the highest at trumpet and tasseling stages. The independent test results showed that the model performance was stable at the flaring stage and tasseling stage, with R2 value greater than 0.944 and n-RMSE less than 9.089%. At the trumpet stage and tasseling stage, the N nutrient index and N accumulation deficit were significantly correlated with the relative yield, which could accurately explain the change of relative yield under the growth conditions of nitrogen restriction and no nitrogen restriction.
    Conclusions The critical nitrogen concentration dilution curve constructed based on the canopy coverage can accurately judge and evaluate the N nutrition status from the jointing stage to the silking stage of maize. The relationship model constructed based on the N nutrition index, N accumulation deficit and relative yield can more accurately predict the yield at the large bell-opening and tasseling stages. This study provides a simple and new method for precise management of nitrogen fertilizer and yield prediction during crop growth.

     

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