Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China
Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China
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DOI：
10.3390/su11030706
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发表时间：
2019-01
期刊：
影响因子：
3.9
通讯作者：
Xinbing Wang;Y. Miao;R. Dong;Zhichao Chen;Y. Guan;Xuezhi Yue;Zheng Fang;D. Mulla
中科院分区：
文献类型：
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作者：
Xinbing Wang;Y. Miao;R. Dong;Zhichao Chen;Y. Guan;Xuezhi Yue;Zheng Fang;D. Mulla
精准氮素管理是东北地区旱作玉米生产可持续发展的迫切需要。本研究旨在通过改进产量潜力预测（YP0）、基于收获产量的侧施氮响应指数（RIHarvest）和侧施氮农艺效率（AENS），建立一种基于主动冠层传感器（ACS）的雨养玉米PNM策略。在3个生长季节（2015-2017年）2种不同土壤类型上进行了6种氮肥处理和3种种植密度的田间试验。在8 ~ 9个生长期，采用手持式GreenSeeker传感器采集归一化植被指数（NDVI）和比值植被指数（RVI）。结果表明，NDVI或RVI结合相对株高（NDVI*RH或RVI*RH）与YP0的相关性（R2 = 0.44 ~ 0.78）高于单独使用NDVI或RVI （R2 = 0.26 ~ 0.68）。改进的季节性氮肥优化算法（INFOA）比平均常数AENS的氮肥优化算法（NFOA）更能预测AENS优化氮素速率。与典型的黑土和风沙土氮素管理相比，基于信息的PNM策略可使边际收益分别提高212 $ ha - 1和70 $ ha - 1，氮素盈余分别减少65%和62%，氮素利用效率（NUE）分别提高4% ~ 40%和11% ~ 65%。综上所述，基于acs的PNM策略具有显著提高东北玉米生产盈利能力和可持续性的潜力。需要更多的研究来进一步改进氮管理策略，使用更先进的传感技术并结合天气和土壤信息。
Precision nitrogen (N) management (PNM) strategies are urgently needed for the sustainability of rain-fed maize (Zea mays L.) production in Northeast China. The objective of this study was to develop an active canopy sensor (ACS)-based PNM strategy for rain-fed maize through improving in-season prediction of yield potential (YP0), response index to side-dress N based on harvested yield (RIHarvest), and side-dress N agronomic efficiency (AENS). Field experiments involving six N rate treatments and three planting densities were conducted in three growing seasons (2015–2017) in two different soil types. A hand-held GreenSeeker sensor was used at V8-9 growth stage to collect normalized difference vegetation index (NDVI) and ratio vegetation index (RVI). The results indicated that NDVI or RVI combined with relative plant height (NDVI*RH or RVI*RH) were more strongly related to YP0 (R2 = 0.44–0.78) than only using NDVI or RVI (R2 = 0.26–0.68). The improved N fertilizer optimization algorithm (INFOA) using in-season predicted AENS optimized N rates better than the N fertilizer optimization algorithm (NFOA) using average constant AENS. The INFOA-based PNM strategies could increase marginal returns by 212 $ ha−1 and 70 $ ha−1, reduce N surplus by 65% and 62%, and improve N use efficiency (NUE) by 4%–40% and 11%–65% compared with farmer’s typical N management in the black and aeolian sandy soils, respectively. It is concluded that the ACS-based PNM strategies have the potential to significantly improve profitability and sustainability of maize production in Northeast China. More studies are needed to further improve N management strategies using more advanced sensing technologies and incorporating weather and soil information.