A non‐destructive and real‐time method of monitoring leaf nitrogen status in wheat

2007 ◽  
Vol 50 (5) ◽  
pp. 935-942 ◽  
Author(s):  
X. Yao ◽  
W. Feng ◽  
Y. Zhu ◽  
Y. C. Tian ◽  
W. X. Cao
2011 ◽  
Vol 37 (6) ◽  
pp. 1039-1048 ◽  
Author(s):  
Fang-Yong WANG ◽  
Ke-Ru WANG ◽  
Shao-Kun LI ◽  
Shi-Ju GAO ◽  
Chun-Hua XIAO ◽  
...  

2006 ◽  
Vol 86 (4) ◽  
pp. 1037-1046 ◽  
Author(s):  
Yan Zhu ◽  
Yingxue Li ◽  
Wei Feng ◽  
Yongchao Tian ◽  
Xia Yao ◽  
...  

Non-destructive monitoring of leaf nitrogen (N) status can assist in growth diagnosis, N management and productivity forecast in field crops. The objectives of this study were to determine the relationships of leaf nitrogen concentration on a leaf dry weight basis (LNC) and leaf nitrogen accumulation per unit soil area (LNA) to ground-based canopy reflectance spectra, and to derive regression equations for monitoring N nutrition status in wheat (Triticum aestivum L.). Four field experiments were conducted with different N application rates and wheat cultivars across four growing seasons, and time-course measurements were taken on canopy spectral reflectance, LNC and leaf dry weights under the various treatments. In these studies, LNC and LNA in wheat increased with increasing N fertilization rates. The canopy reflectance differed significantly under varied N rates, and the pattern of response was consistent across the different cultivars and years. Overall, an integrated regression equation of LNC to normalized difference index (NDI) of 1220 and 710 nm of canopy reflectance spectra described the dynamic pattern of change in LNC in wheat. The ratios of several near infrared (NIR) bands to visible light were linearly related to LNA, with the ratio index (RI) of the average reflectance over 760, 810, 870, 950 and 1100 nm to 660 nm having the best index for quantitative estimation of LNA in wheat. When independent data were fit to the derived equations, the average root mean square error (RMSE) values for the predicted LNC and LNA relative to the observed values were no more than 15.1 and 15.2%, respectively, indicating a good fit. Our relationships of leaf N status to spectral indices of canopy reflectance can be potentially used for non-destructive and real-time monitoring of leaf N status in wheat. Key words: Wheat, leaf nitrogen concentration, leaf nitrogen accumulation, canopy reflectance, spectral index, nitrogen monitoring


2018 ◽  
Vol 9 ◽  
Author(s):  
Songyang Li ◽  
Xingzhong Ding ◽  
Qianliang Kuang ◽  
Syed Tahir Ata-UI-Karim ◽  
Tao Cheng ◽  
...  

2011 ◽  
Vol 103 (2) ◽  
pp. 441-448 ◽  
Author(s):  
Jian Jin ◽  
Xiaobing Liu ◽  
Guanghua Wang ◽  
Judong Liu ◽  
Liang Mi ◽  
...  

2020 ◽  
Vol 87 (6) ◽  
pp. 404-413
Author(s):  
Fabian Zechel ◽  
Rouwen Kunze ◽  
Niels König ◽  
Robert Heinrich Schmitt

AbstractIn this review paper, conventional non-destructive testing (NDT) methods are briefly introduced and compared with selected examples for applications of optical coherence tomography (OCT) for NDT. The contactless, non-destructive and purely optical method enables multi-dimensional imaging for tomographic real-time evaluation in various fields of application. Depending on the material, penetration depths of several millimeters can be achieved, thus providing an attractive solution that can be used both as a stand-alone and as a process-integrated solution.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arka Ghosh ◽  
David John Edwards ◽  
M. Reza Hosseini ◽  
Riyadh Al-Ameri ◽  
Jemal Abawajy ◽  
...  

PurposeThis research paper adopts the fundamental tenets of advanced technologies in industry 4.0 to monitor the structural health of concrete beam members using cost-effective non-destructive technologies. In so doing, the work illustrates how a coalescence of low-cost digital technologies can seamlessly integrate to solve practical construction problems.Design/methodology/approachA mixed philosophies epistemological design is adopted to implement the empirical quantitative analysis of “real-time” data collected via sensor-based technologies streamed through a Raspberry Pi and uploaded onto a cloud-based system. Data was analysed using a hybrid approach that combined both vibration-characteristic-based method and linear variable differential transducers (LVDT).FindingsThe research utilises a novel digital research approach for accurately detecting and recording the localisation of structural cracks in concrete beams. This non-destructive low-cost approach was shown to perform with a high degree of accuracy and precision, as verified by the LVDT measurements. This research is testament to the fact that as technological advancements progress at an exponential rate, the cost of implementation continues to reduce to produce higher-accuracy “mass-market” solutions for industry practitioners.Originality/valueAccurate structural health monitoring of concrete structures necessitates expensive equipment, complex signal processing and skilled operator. The concrete industry is in dire need of a simple but reliable technique that can reduce the testing time, cost and complexity of maintenance of structures. This was the first experiment of its kind that seeks to develop an unconventional approach to solve the maintenance problem associated with concrete structures. This study merges industry 4.0 digital technologies with a novel low-cost and automated hybrid analysis for real-time structural health monitoring of concrete beams by fusing several multidisciplinary approaches into one integral technological configuration.


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