Nitrogen determination on tomato (Lycopersicon esculentum Mill.) seedlings by color image analysis (RGB)

In order to investigate the effectiveness of a new method based on color image analysis and the Minolta SPAD-502 chlorophyll meter for the diagnosis of nitrogen deficiencies of tomato seedlings, a field experiment was conducted. In this study, five levels of nitrogen fertilization were established so as to induce nitrogen deficiencies in tomato seedlings. Thirty-five days after sowing, total nitrogen was evaluated by laboratory analysis. The chlorophyll index was determined using a SPAD-502 chlorophyll meter. Also, color images were taken with a digital camera; the color images were processed in MATLAB in order to determine the averages of the red color, green color and the blue color. The relationships between variables were analyzed by linear regressions and a one way analysis of variance (p < 0.01). Results showed that color image analysis correlated better with the status of plant nitrogen than the SPAD. From the color image analysis, the red and blue colors were more accurate predictors of nitrogen status on plants with R2 above 0.89. Color image analysis provides an accurate and quick way for nitrogen estimation and can contribute for early detection of nitrogen deficiency in tomato seedlings. The SPAD method is not a reliable way to estimate the nitrogen status on tomato seedlings. Keywords: Color image analysis (RGB), chlorophyll meter, nitrogen deficiency African Journal of Biotechnology Vol. 9(33), pp. 5326-5332, 16 August, 2010

[1]  P. Sexton,et al.  COMPARISON OF SPAD CHLOROPHYLL METER READINGS vs. PETIOLE NITRATE CONCENTRATION IN SUGARBEET , 2002 .

[2]  Makoto Nakatani,et al.  An Algorithm for Estimating Chlorophyll Content in Leaves Using a Video Camera , 1998 .

[3]  L. Bacci,et al.  Two methods for the analysis of colorimetric components applied to plant stress monitoring , 1998 .

[4]  Scott X. Chang,et al.  Nondestructive and rapid estimation of hardwood foliar nitrogen status using the SPAD-502 chlorophyll meter , 2003 .

[5]  Jianjun Chen,et al.  Nondestructive and Rapid Estimation of Leaf Chlorophyll and Nitrogen Status of Peace Lily Using a Chlorophyll Meter , 2004 .

[6]  Andrew D. Richardson,et al.  An evaluation of noninvasive methods to estimate foliar chlorophyll content , 2002 .

[7]  O. Fernando,et al.  Evolución de un índice de verdor en hoja para evaluar el status nitrogenado en trigo , 2004 .

[8]  F. Blanco. Métodos apropiados de análisis estadístico subsiguientes al análisis de varianza (ANDEVA) , 2001 .

[9]  Amanullah,et al.  Timing and rate of nitrogen application influence grain quality and yield in maize planted at high and low densities. , 2010, Journal of the science of food and agriculture.

[10]  Caroline Mohammed,et al.  Chlorophyll and nitrogen determination for plantation-grown Eucalyptus nitens and E. globulus using a non-destructive meter , 2006 .

[11]  Z. Cerovic,et al.  Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.) , 2005 .

[12]  Andreas Buerkert,et al.  Use of Digital Camera to Assess Nitrogen Status of Winter Wheat in the Northern China Plain , 2004 .

[13]  MICHAEL B. Jones,et al.  A note on a non-destructive method of chlorophyll determination in wheat (Triticum aestivum L.) , 1997 .

[14]  Annie Lou Ware,et al.  On correlation theory , 1941 .

[15]  A. A. Steiner The universal nutrient solution , 1984 .

[16]  Mohammad Kafi,et al.  Evaluation of chlorophyll meter for prediction of nitrogen status of corn (Zea mays) , 2008 .

[17]  M. A. Badr,et al.  Effect of Fertigation Frequency from Subsurface Drip Irrigation on Tomato Yield Grown on Sandy Soil , 2007 .

[18]  George W. Snedecor,et al.  Statistical methods applied to experiments in agriculture and biology. , 1946 .