Establishing NDRE dynamic models of winter wheat under multi-nitrogen rates based on a field spectral sensor
文献类型: 外文期刊
第一作者: Shu, Meiyan
作者: Shu, Meiyan;Gu, Xiaohe;Zhou, Longfei;Xu, Bo;Yang, Guijun;Shu, Meiyan;Gu, Xiaohe;Zhou, Longfei;Xu, Bo;Yang, Guijun;Shu, Meiyan
作者机构:
期刊名称:APPLIED OPTICS ( 影响因子:1.98; 五年影响因子:1.943 )
ISSN: 1559-128X
年卷期: 2021 年 60 卷 4 期
页码:
收录情况: SCI
摘要: Field spectral sensors provide real-time, reliable, quantitative monitoring of crop growth. Fitting the continuous growth in the entire growing period from the measurements of limited frequency is helpful to the comparative analysis of interannual growth and fertilizer management in the field. To exploit this capacity, our work presents a model that uses the normalized difference red edge (NDRE) index derived from the field spectral sensor for real-time monitoring of the canopy growth of winter wheat in the whole growing period. We developed this model from experiments in three counties in Hebei province, China, where we obtained the near-infrared and red edge reflectance, grain yield, and canopy parameters for eight growth stages and for various nitrogen (N) rates. Given the correlation between effective accumulated temperature and crop growth, we used the growing degree-days as an adjustment parameter to develop models for dynamic monitoring of the NDRE of the winter wheat canopy during the entire growing period. The results show that high determination coefficients (R-2 = 0.89 to 0.96) are obtained From all models based on relative NDRE and effective accumulative temperature (independent of N fertilization rates). The model based on the rational function is the best of all models tested, with the accuracy for normal and high N fertilization rates being slightly greater than that for low N fertilization rates. Therefore, a relative-NDRE model with the accumulative growing degree-days since sowing could allow monitoring canopy NDRE of winter wheat at any time, which could be helpful for overcoming the shortage of incomparable growth derived from the differences of sensing date, sowing date, and fertilizer, etc. (C) 2021 Optical Society of America
分类号:
- 相关文献
作者其他论文 更多>>
-
Estimation of grain filling rate and thousand-grain weight of winter wheat ( Triticum aestivum L. ) using UAV-based multispectral images
作者:Zhang, Baoyuan;Dai, Menglei;Sun, Qian;Qu, Xuzhou;Zhang, Mingzheng;Gu, Xiaohe;Zhang, Baoyuan;Gu, Limin;Dai, Menglei;Bao, Xiaoyuan;Zhen, Wenchao;Zhen, Wenchao;Zhen, Wenchao;Zhang, Baoyuan;Liu, Xingyu;Fan, Chengzhi
关键词:Grain filling rate; Grain weight; UAV; Winter wheat; Vegetation index
-
Research on methods for estimating reference crop evapotranspiration under incomplete meteorological indicators
作者:Sun, Xuguang;Zhang, Baoyuan;Gao, Ruocheng;Gu, Limin;Zhen, Wenchao;Sun, Xuguang;Zhang, Baoyuan;Dai, Menglei;Ma, Kai;Gu, Xiaohe;Dai, Menglei;Jing, Cuijiao;Gu, Limin;Zhen, Wenchao;Gu, Shubo;Gu, Shubo;Zhen, Wenchao
关键词:reference crop evapotranspiration; Penman-Monteith; FAO-24 radiation; meteorological indicators; Bayesian estimation
-
Recognition of wheat rusts in a field environment based on improved DenseNet
作者:Chang, Shenglong;Cheng, Jinpeng;Fan, Zehua;Ma, Xinming;Li, Yong;Zhao, Chunjiang;Chang, Shenglong;Yang, Guijun;Cheng, Jinpeng;Fan, Zehua;Yang, Xiaodong;Zhao, Chunjiang
关键词:Plant disease; Wheat rust; Image processing; Deep learning; Computer vision (CV); DenseNet
-
Automatic Rice Early-Season Mapping Based on Simple Non-Iterative Clustering and Multi-Source Remote Sensing Images
作者:Wang, Gengze;Chen, Riqiang;Yang, Guijun;Feng, Haikuan;Wang, Gengze;Chen, Riqiang;Yang, Guijun;Feng, Haikuan;Meng, Di;Jin, Hailiang;Ge, Xiaosan;Wang, Laigang;Feng, Haikuan
关键词:early-season rice mapping; spectral index (SI); synthetic aperture radar (SAR); Simple Non-Iterative Clustering (SNIC); time series filtering; K-Means; Jeffries-Matusita (JM) distance
-
Unveiling Innovative Approaches to Mitigate Metals/Metalloids Toxicity for Sustainable Agriculture
作者:Charagh, Sidra;Hui, Suozhen;Wang, Jingxin;Zhou, Liang;Xu, Bo;Zhang, Yuanyuan;Sheng, Zhonghua;Tang, Shaoqing;Hu, Shikai;Hu, Peisong;Raza, Ali
关键词:
-
Improved random patches and model transfer for deriving leaf mass per area across multispecies from spectral reflectance
作者:Fei, Shuaipeng;Xiao, Shunfu;Xu, Demin;Shu, Meiyan;Feng, Puyu;Ma, Yuntao;Sun, Hong;Xiao, Yonggui
关键词:Transfer learning; Machine learning; Leaf traits; Remote sensing; Hyperspectral
-
A Two-Stage Leaf-Stem Separation Model for Maize With High Planting Density With Terrestrial, Backpack, and UAV-Based Laser Scanning
作者:Lei, Lei;Lei, Lei;Li, Zhenhong;Li, Zhenhong;Yang, Hao;Xu, Bo;Yang, Guijun;Hoey, Trevor B.;Wu, Jintao;Yang, Xiaodong;Feng, Haikuan;Yang, Guijun;Yang, Guijun
关键词:Vegetation mapping; Laser radar; Point cloud compression; Feature extraction; Agriculture; Data models; Data mining; Different cultivars; different growth stages; different planting densities; different platforms; light detection and ranging (LiDAR) data; simulated datasets; two-stage leaf-stem separation model