In-Season Estimation of Rice Nitrogen Status With an Active Crop Canopy Sensor

被引:38
|
作者
Yao, Yinkun [1 ]
Miao, Yuxin [1 ]
Cao, Qiang [1 ]
Wang, Hongye [1 ]
Gnyp, Martin L. [2 ]
Bareth, Georg [2 ]
Khosla, Rajiv [3 ]
Yang, Wen [4 ]
Liu, Fengyan [4 ]
Liu, Cheng [5 ]
机构
[1] China Agr Univ, Coll Resources & Environm Sci, ICASD, Beijing 100193, Peoples R China
[2] Univ Cologne, Inst Geog, ICASD, D-50923 Cologne, Germany
[3] Colorado State Univ, Dept Soil & Crop Sci, Ft Collins, CO 80523 USA
[4] Jiansanjiang Inst Agr Sci, Fujin 156300, Heilongjiang, Peoples R China
[5] Qixing Modern Agr Dev Ctr, Fujin 156300, Heilongjiang, Peoples R China
关键词
Active crop sensor; biomass; nitrogen nutrition index (NNI); plant nitrogen concentration; plant nitrogen uptake; precision nitrogen management; NUTRITION INDEX; PADDY RICE; CHLOROPHYLL CONTENT; VEGETATION INDEXES; DILUTION CURVE; MANAGEMENT; BIOMASS; PLANT; GROWTH; CORN;
D O I
10.1109/JSTARS.2014.2322659
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Timely nondestructive estimation of crop nitrogen (N) status is crucial for in-season site-specific N management.,Active crop canopy sensors are the promising tools to obtain the needed information without being affected by environmental light conditions. The objective of this study was to evaluate the potential for the GreenSeeker active crop canopy sensor to estimate rice (Oryzu sativa L.) N status. Nine N rate experiments were conducted from 2008 to 2012 in Jiansanjiang, Ileilongjiang Province in Northeast China. The results indicated that across site-years and growth stages, normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) obtained with the GreenSeeker sensor could explain 73%-76"/o and 70%-73% of rice aboveground biomass and plant N uptake variability in this study, respectively. The NDVI index became saturated when biomass reached about 4 t ha(-1) or when plant N uptake reached about 100 kg ha(-1), whereas RVI did not show obvious saturation effect. The validation results, however, indicated that both indices performed similarly, and their relative errors (RE) were still large (> 40%).,Although the two indices only explained less than 40% of plant N concentration or N nutrition index (NNE) variability-, the RE values were acceptable (< 26%). The results indicated some potentials of using the GreenSeeker sensor to estimate rice N status nondestructively, but more studies are needed to further evaluate and improve its performance for practical applications.
引用
收藏
页码:4403 / 4413
页数:11
相关论文
共 50 条
  • [41] In-season dynamic diagnosis of maize nitrogen status across the growing season by integrating proximal sensing and crop growth modeling
    Dong, Lingwei
    Miao, Yuxin
    Wang, Xinbing
    Kusnierek, Krzysztof
    Zha, Hainie
    Pan, Min
    Batchelor, William D.
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 224
  • [42] Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China
    Huang, Shanyu
    Miao, Yuxin
    Zhao, Guangming
    Yuan, Fei
    Ma, Xiaobo
    Tan, Chuanxiang
    Yu, Weifeng
    Gnyp, Martin L.
    Lenz-Wiedemann, Victoria I. S.
    Rascher, Uwe
    Bareth, Georg
    [J]. REMOTE SENSING, 2015, 7 (08) : 10646 - 10667
  • [43] In-season calibration of the CERES-Rice model using proximal active canopy sensing data for yield prediction
    Zha, H.
    Lu, J.
    Li, Y.
    Miao, Y.
    Kusnierek, K.
    Batchelor, W. D.
    [J]. PRECISION AGRICULTURE'21, 2021, : 927 - 932
  • [44] Evaluating a Crop Circle Active Canopy Sensor-based Precision Nitrogen Management Strategy for Rice in Northeast China
    Shi, Wei
    Lu, Junjun
    Miao, Yuxin
    Cao, Qiang
    Shen, Jianning
    Wang, Hongye
    Hu, Xiaoyi
    Hu, Shanshan
    Yang, Wen
    Li, Honglin
    [J]. 2015 FOURTH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS, 2015,
  • [45] Theoretical basis for sensor-based in-season nitrogen management
    Adamchuk, V. I.
    [J]. PRECISION AGRICULTURE '13, 2013, : 403 - 410
  • [46] Impact of residual soil nitrate on in-season nitrogen applications to irrigated corn based on remotely sensed assessments of crop nitrogen status
    Bausch W.C.
    Delgado J.A.
    [J]. Precision Agriculture, 2005, 6 (6) : 509 - 519
  • [47] In-Season Potato Crop Nitrogen Status Assessment from Satellite and Meteorological Data (vol 65, 729, 2022)
    Goffart, D.
    Abdallah, F. Ben
    Curnel, Y.
    Planchon, V.
    Defourny, P.
    Goffart, J. -p.
    [J]. POTATO RESEARCH, 2023, 66 (04) : 1215 - 1223
  • [48] In-Season Canopy Reflectance Can Aid Fungicide and Late-Season Nitrogen Decisions on Winter Wheat
    Cruppe, Giovana
    Edwards, Jeffrey T.
    Lollato, Romulo P.
    [J]. AGRONOMY JOURNAL, 2017, 109 (05) : 2072 - 2086
  • [49] Development of a model using the nitrogen nutrition index to estimate in-season rice nitrogen requirement
    Wang, Yuan
    Shi, Peihua
    Ji, Rongting
    Min, Ju
    Shi, Weiming
    Wang, Dejian
    [J]. FIELD CROPS RESEARCH, 2020, 245
  • [50] Evaluating different approaches to non-destructive nitrogen status diagnosis of rice using portable RapidSCAN active canopy sensor
    Junjun Lu
    Yuxin Miao
    Wei Shi
    Jingxin Li
    Fei Yuan
    [J]. Scientific Reports, 7