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Journal of Agriculture ›› 2017, Vol. 7 ›› Issue (7): 77-83.doi: 10.11923/j.issn.2095-4050.cjas16110031

Special Issue: 棉花

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Cotton Nitrogen Nutrition Diagnosis Based on Digital Image

  

  • Received:2016-11-23 Revised:2017-02-16 Accepted:2017-02-25 Online:2017-07-18 Published:2017-07-18

Abstract: To provide a scientific basis for digital image processing technique in nitrogen diagnosis of cotton, a field experiment under different fertilization treatments was carried out to explore relationship between the color parameters (G, NRI, NGI, NBI, G/R and G/B) of cotton leaves at different positions and stem sap nitrate concentration, SPAD readings and Chlorophyll content, determine the best digital parameter and regression equation. A field experiment was conducted with different nitrogen application rates from 2012-2013 at the Experimental Farm of Anhui Academy of Agricultural Sciences. Chosed xiangza8 as test cultivar. The pictures of cotton leaves were obtained with Nikon D80 digital camera at bud stage and boll forming stage, meanwhile, analyzed cotton sample of N status for determining the best color parameters and regression equations in cotton. The results showed that:(1) the correlation of stem sap nitrate content of inverse 3th leaf and NRI was best, R2=0.8754. And correlation of functional inverse 4th leaf was also good, R2=0.8013; (2)the SPAD readings and digital indicators had a good correlation of leaves at different positions except inverse 1st leaf. The best correlation was between inverse 2th leaf and NGI, the correlation coefficient was 0.9591; (3) as to the chlorophyll content, the correlation with B was the best of inverse first leaf, they had a positive curvilinear correlation, R2=0.9444. Followed by the inverse 3th leaf and 4th leaf, the correlation coefficients were 0.9294, 0.931. We should choose leaves of upper position which were inverse 1th, inverse 2th, inverse 3th and inverse 4th, and also select the color index B, NBI and NRI in cotton nitrogen nutrition diagnosis of leaves at different positions.

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