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Open AccessArticle

Monitoring Wheat Growth Using a Portable Three-Band Instrument for Crop Growth Monitoring and Diagnosis

by Huaimin Li 1,2,3,4, Weipan Lin 1,2,3,4, Fangrong Pang 1,2,3,4, Xiaoping Jiang 1,2,3,4, Weixing Cao 1,2,3,4, Yan Zhu 1,2,3,4 and Jun Ni 1,2,3,4,*
1
College of Agriculture, Nanjing Agricultural University, Nanjing 210095, China
2
National Information Agricultural Engineering Technology Center, Nanjing 210095, China
3
Engineering Research Center of Smart Agriculture, Ministry of Education, Nanjing 210095, China
4
Jiangsu Collaborative Innovation Center for the Technology and Application of Internet of Things, Nanjing 210095, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(10), 2894; https://doi.org/10.3390/s20102894
Received: 27 March 2020 / Revised: 13 May 2020 / Accepted: 18 May 2020 / Published: 20 May 2020
(This article belongs to the Special Issue Sensors in Agriculture 2020)
An instrument developed to monitor and diagnose crop growth can quickly and non-destructively obtain crop growth information, which is helpful for crop field production and management. Focusing on the problems with existing two-band instruments used for crop growth monitoring and diagnosis, such as insufficient information available on crop growth and low accuracy of some growth indices retrieval, our research team developed a portable three-band instrument for crop-growth monitoring and diagnosis (CGMD) that obtains a larger amount of information. Based on CGMD, this paper carried out studies on monitoring wheat growth indices. According to the acquired three-band reflectance spectra, the combined indices were constructed by combining different bands, two-band vegetation indices (NDVI, RVI, and DVI), and three-band vegetation indices (TVI-1 and TVI-2). The fitting results of the vegetation indices obtained by CGMD and the commercial instrument FieldSpec HandHeld2 was high and the new instrument could be used for monitoring the canopy vegetation indices. By fitting each vegetation index to the growth index, the results showed that the optimal vegetation indices corresponding to leaf area index (LAI), leaf dry weight (LDW), leaf nitrogen content (LNC), and leaf nitrogen accumulation (LNA) were TVI-2, TVI-1, NDVI (R730, R815), and NDVI (R730, R815), respectively. R2 values corresponding to LAI, LDW, LNC and LNA were 0.64, 0.84, 0.60, and 0.82, respectively, and their relative root mean square error (RRMSE) values were 0.29, 0.26, 0.17, and 0.30, respectively. The addition of the red spectral band to CGMD effectively improved the monitoring results of wheat LAI and LDW. Focusing the problem of vegetation index saturation, this paper proposed a method to construct the wheat-growth-index spectral monitoring models that were defined according to the growth periods. It improved the prediction accuracy of LAI, LDW, and LNA, with R2 values of 0.79, 0.85, and 0.85, respectively, and the RRMSE values of these growth indices were 0.22, 0.23, and 0.28, respectively. The method proposed here could be used for the guidance of wheat field cultivation. View Full-Text
Keywords: multispectral sensor; crop growth status; vegetation index; growth period; spectral monitoring model; precision agriculture; agricultural remote sensing multispectral sensor; crop growth status; vegetation index; growth period; spectral monitoring model; precision agriculture; agricultural remote sensing
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Li, H.; Lin, W.; Pang, F.; Jiang, X.; Cao, W.; Zhu, Y.; Ni, J. Monitoring Wheat Growth Using a Portable Three-Band Instrument for Crop Growth Monitoring and Diagnosis. Sensors 2020, 20, 2894.

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