当前位置: X-MOL 学术Precision Agric. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Supporting operational site‐specific fertilization in rice cropping systems with infield smartphone measurements and Sentinel-2 observations
Precision Agriculture ( IF 6.2 ) Pub Date : 2021-02-10 , DOI: 10.1007/s11119-021-09784-0
Francesco Nutini , Roberto Confalonieri , Livia Paleari , Monica Pepe , Laura Criscuolo , Francesco Porta , Luigi Ranghetti , Lorenzo Busetto , Mirco Boschetti

Due to the low efficiency of nitrogen fertilizers in flooded rice paddies, there is a rising demand for tools able to detect crop nitrogen status in space and time to allow farmers to use the technical novelties of precision agriculture to improve fertilizer management in extensive fields. This work sets up an operational approach to increase nitrogen use efficiency of top-dressing fertilization by supporting variable rate fertilization in rice cropping systems. The procedure exploits (i) crop modelling to identify best periods for fertilization (When), (ii) Sentinel-2 imagery to draw management zones (MZ) and lead field scouting (Where), and (iii) smartphone app to measure nitrogen nutritional index (NNI) (How much). Automatically generated MZ from Sentinel-2 data were able to identify within field patches with different nutritional status and NNI data well described the crop temporal dynamic in relation to crop development and nutritional needs. The workflow was implemented to provide farmers with timely information on plant nutritional status during the 2018 growing season to define site-specific fertilization strategies implemented with variable rate technology (VRT). Tests conducted on 6 fields over 30 ha in 3 farms showed the feasibility of the proposed workflow in real farming conditions allowing a reduction of applied fertilizer up to 25% in the areas with sufficient nutritional status. Demonstration revealed that VRT based on geospatial information from integrated in-field and satellite data can provide agronomic and environmental benefits compared with standard fertilization resulting in promising outcomes both in terms of yield (increase in the range 0.2–0.5 t ha−1) and nitrogen use efficiency (increase up to 7.8%).



中文翻译:

通过现场智能手机测量和Sentinel-2观测结果支持水稻种植系统中特定地点的施肥

由于淹水稻田中氮肥的效率低下,人们越来越需要能够在空间和时间上检测农作物氮状况的工具,以使农民能够利用精准农业的技术新颖性来改善广泛领域的肥料管理。这项工作建立了一种可操作的方法,通过支持水稻种植系统中的变量施肥来提高追肥的氮肥利用率。该程序利用(i)作物建模来确定施肥的最佳时期(何时),(ii)Sentinel-2图像以绘制管理区域(MZ)和潜在田间侦察(Where),以及(iii)智能手机应用程序来测量氮素营养指数(NNI)(多少)。从Sentinel-2数据自动生成的MZ能够识别具有不同营养状况的田间斑块,而NNI数据很好地描述了与作物生长和营养需求有关的作物时间动态。该工作流的实施旨在为农民提供有关2018年生长季节植物营养状况的及时信息,以定义使用可变速率技术(VRT)实施的特定地点施肥策略。在3个农场的30公顷以上的6个田间进行的测试表明,所建议的工作流程在实际农业条件下的可行性,使得在营养状况良好的地区,施肥量最多可减少25%。-1)和氮的使用效率(提高7.8%)。

更新日期:2021-02-11
down
wechat
bug