Detection of Soil Total Nitrogen, Phosphorus and Potassium Content Based on the Spectral Information of Citrus Canopy
- 1 South China Agricultural University, China
Abstract
The content of total nitrogen, phosphorus and potassium in the soil is an important basis for calculating the best fertilization amount and realizing the reasonable fertilization of the orange planting soil in time and accurately. In this research, hyper-spectral technology is applied to detect the three soil nutrient elements in the cultivated soil of citrus trees. Four spectral bands with central wavelengths of 660, 780, 870 and 970 nm and width of 20 nm are selected to measure the spectral reflectance of the potted kumquats canopy by hand-held spectrometer. At the same time, the content of total nitrogen, phosphorus and potassium in the cultivated soil of kumquat is determined using traditional methods. The correlation between the spectral information of kumquat canopy and the content of soil nutrient elements is analyzed by correlation coefficient method. The prediction model of soil nutrient element content based on the spectral information is established by multiple linear regression method. The results showed that the total potassium content of soil is significantly correlated with the spectral reflectance at 660 nm wave band and significantly correlated with the spectral indexes of R660/R780, R660/R870 and R660/R970. R2 of the prediction model of total potassium content established on the basis of spectral reflectance and ratio spectral index of the selected band is 0.756 and 0.857 respectively, which shows good prediction effect of the model. There is no significant correlation between the spectral reflectance and ratio spectral index of the selected band towards the total soil nitrogen and phosphorus content and it cannot be used for the rapid measurement of total nitrogen and phosphorus content. Further study is needed to select suitable spectral band and spectral index.
DOI: https://doi.org/10.3844/ajbbsp.2020.177.183
Copyright: © 2020 Lin Yunshuo, Li Zhen, Lv Shilei, Huang Heqing and Hu Jiapei. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- 4,016 Views
- 2,640 Downloads
- 10 Citations
Download
Keywords
- Citrus
- Spectrometer
- Nutrient Elements
- Spectral Analysis
- Fine Agriculture