The Nitrogen Quantitative Model Based on Hyperspectral Image of Tomato Leaf

Abstract:

Based on hyperspectral image which integrates spectrum and image information, the tomato leaf nitrogen model is built. Tomato samples were soillessly cultured with different nitrogen content. The hyperspectral images of tomato leaves are gathered at different stages of tomato. Kjeldahl method determines nitrogen content of the corresponding tomato leaves. According to the hyperspectral information of leaf, the characteristic wave bands of tomato nitrogen are obtained in the method of stepwise regression. The images in the characteristic bands are processed and analyzed, and image features which have high correlation with nitrogen contents of tomato leaves are picked up. The PLS algorithm is used in three growth periods to build tomato nitrogen prediction model, The result of the predicted test shows that the forecast average relative error of PLS model may achieve 10%, and can satisfy the forecast request.

• Periodical: Advanced Materials Research (Volumes 466-467)
• Pages: 191-195
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.466-467.191
• Online since: February 2012
• Authors: Jun Sun, Yan Wang, Xiao Hong Wu, Xiao Dong Zhang
• Keywords: High Spectral Image, Nitrogen, PLS, Tomato Leaf Blade

References

[1] H. Y. Ji, P. X. Wang, Winter whewt living specimen leaf blade chlorophyll and moisture content and reflection spectrum model building,. Spectroscopy and spectral analysis, Mar 2007, pp.514-516.

[2] H. P. Mao, X. D. Zhang, X. Li, et al. Based on spectral reflection characteristics of grape leaf moisture content model of, Journal of jiangsu university (natural science edition), May 2008, pp.369-1737.

[3] M. Pagola, R. Ortiz, et al. New to assess barley of nitrogen nutrition they based on comparison,. Add color order SPAD – 502 and electronics in agriculture, Mar 2009, pp.213-218.

[4] A. A. Gowen, C. P. O'Donnell, P. J. Cullen, G. Downey, and J. M. Frias. Hyperspectral imaging - an emerging process analytical tool for food quality and safety control,. Trends in Food Science & Technology. 2007, vol. 18, pp.590-598.

DOI: 10.1016/j.tifs.2007.06.001

[5] O. N. Johnson, S. Mark, K. Peter, et a1. Hyperspectral imaging: An emerging technology as a potential novel adjunct in assessing peripheral perfusion deficits and success of lower extremity revascularizations,. Journal of the American College of Surgeons (S1072-7515), Mar 2008, Sl14.

DOI: 10.1016/j.jamcollsurg.2008.06.295

[6] J. Sun, J. F. Wu, Soilless cultivation of rice and the measurement of leaf water and nitrogen content,. Journal of Anhui Agricultural sciences, 2009, vol. 12, pp.17414-17415, 17418.

[7] X. C. Zhu, L. Q. Wang, Research on PLS modeling for detecting oil acid value by near infrared spectrum,. Information Technology, Dec 2009, pp.33-35.