Image-Based (RBG) Technique for Estimating Phosphorus Levels of Crops
In this glasshouse study, we developed a new imagebased
non-destructive technique for detecting leaf P status of
different crops such as cotton, tomato and lettuce. The plants were
grown on a nutrient solution containing different P concentrations,
e.g. 0%, 50% and 100% of recommended P concentration (P0 = no P,
L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P). After 7 weeks
of treatment, the plants were harvested and data on leaf P contents
were collected using the standard destructive laboratory method and
at the same time leaf images were collected by a handheld crop image
sensor. We calculated leaf area, leaf perimeter and RGB (red, green
and blue) values of these images. These data were further used in
linear discriminant analysis (LDA) to estimate leaf P contents, which
successfully classified these plants on the basis of leaf P contents.
The data indicated that P deficiency in crop plants can be predicted
using leaf image and morphological data. Our proposed nondestructive
imaging method is precise in estimating P requirements of
different crop species.
[1] J. Lloyd, J. Grace, A. C. Miranda, P. Meir, S. C. Wong, H. S. Miranda, I.
R. Wright, and J. H. C. Gash, and Jn. McIntyre “A simple calibrated
model of Amazon rainforest productivity based on leaf biochemical
properties” Plant, Cell Environ., Vol. 18, 1995, pp. 1129-1145.
[2] D. Rodríguez, W. G. Keltjens, and J. Goudriaan, “Plant leaf area
expansion and assimilate production in wheat (Triticum aestivum L.)
growing under low phosphorus conditions” Plant Soil, Vol. 200, 1998,
pp. 227-240.
[3] M. W. Shane, M. E. McCully, and H. Lambers, “Tissue and cellular
phosphorus storage during development of phosphorus toxicity in Hakea
prostrata (Proteaceae)” J. Exp. Bot., Vol. 55, 2004, pp. 1033-1044.
[4] R.. Sui, J. B. Wilkerson, W. E. Hart, L. R. Wilhelm, and D. D. Howard,
“Multi - spectral sensor for detection of nitrogen status in cotton”. App.
Eng. Agric. Vol. 21, 2005, pp. 167-172.
[5] B. Gérard, P. Hiernaux, B. Muehlig-Versen, and A. Buerkert,
“Destructive and non-destructive measurements of residual crop residue
and phosphorus effects on growth and composition of herbaceous fallow
species in the Sahel” Plant Soil, Vol. 228, 2001, pp. 265-273
[6] J. W. Radin, and M. P Eidenbock, “Hydraulic conductance as a factor
limiting leaf expansion of phosphorus-deficient cotton plants” Plant
Physiol., Vo. 75, 1984, pp. 372-377.
[7] I. Lopez‐Cantarero, F. A. Lorente, and L. Romero, “Are chlorophylls
good indicators of nitrogen and phosphorus levels?” J. Plant Nutr., Vol.
17, 1994, pp. 979-990.
[8] S. Zhang, and Y. K. Lei, “Modified locally linear discriminant
embedding for plant leaf recognition” Neurocomputing, Vol. 74, 2011,
pp. 2284-2290.
[9] D. Casanova, J. J. de Mesquita Sa Junior, and O. M. Bruno, “Plant leaf
identification using Gabor wavelets” Int. J. Imag. Sys. Technol., Vol.
19,2009, pp. 236-243.
[1] J. Lloyd, J. Grace, A. C. Miranda, P. Meir, S. C. Wong, H. S. Miranda, I.
R. Wright, and J. H. C. Gash, and Jn. McIntyre “A simple calibrated
model of Amazon rainforest productivity based on leaf biochemical
properties” Plant, Cell Environ., Vol. 18, 1995, pp. 1129-1145.
[2] D. Rodríguez, W. G. Keltjens, and J. Goudriaan, “Plant leaf area
expansion and assimilate production in wheat (Triticum aestivum L.)
growing under low phosphorus conditions” Plant Soil, Vol. 200, 1998,
pp. 227-240.
[3] M. W. Shane, M. E. McCully, and H. Lambers, “Tissue and cellular
phosphorus storage during development of phosphorus toxicity in Hakea
prostrata (Proteaceae)” J. Exp. Bot., Vol. 55, 2004, pp. 1033-1044.
[4] R.. Sui, J. B. Wilkerson, W. E. Hart, L. R. Wilhelm, and D. D. Howard,
“Multi - spectral sensor for detection of nitrogen status in cotton”. App.
Eng. Agric. Vol. 21, 2005, pp. 167-172.
[5] B. Gérard, P. Hiernaux, B. Muehlig-Versen, and A. Buerkert,
“Destructive and non-destructive measurements of residual crop residue
and phosphorus effects on growth and composition of herbaceous fallow
species in the Sahel” Plant Soil, Vol. 228, 2001, pp. 265-273
[6] J. W. Radin, and M. P Eidenbock, “Hydraulic conductance as a factor
limiting leaf expansion of phosphorus-deficient cotton plants” Plant
Physiol., Vo. 75, 1984, pp. 372-377.
[7] I. Lopez‐Cantarero, F. A. Lorente, and L. Romero, “Are chlorophylls
good indicators of nitrogen and phosphorus levels?” J. Plant Nutr., Vol.
17, 1994, pp. 979-990.
[8] S. Zhang, and Y. K. Lei, “Modified locally linear discriminant
embedding for plant leaf recognition” Neurocomputing, Vol. 74, 2011,
pp. 2284-2290.
[9] D. Casanova, J. J. de Mesquita Sa Junior, and O. M. Bruno, “Plant leaf
identification using Gabor wavelets” Int. J. Imag. Sys. Technol., Vol.
19,2009, pp. 236-243.
@article{"International Journal of Biological, Life and Agricultural Sciences:71345", author = "M. M. Ali and Ahmed Al-Ani and Derek Eamus and Daniel K. Y. Tan", title = "Image-Based (RBG) Technique for Estimating Phosphorus Levels of Crops", abstract = "In this glasshouse study, we developed a new imagebased
non-destructive technique for detecting leaf P status of
different crops such as cotton, tomato and lettuce. The plants were
grown on a nutrient solution containing different P concentrations,
e.g. 0%, 50% and 100% of recommended P concentration (P0 = no P,
L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P). After 7 weeks
of treatment, the plants were harvested and data on leaf P contents
were collected using the standard destructive laboratory method and
at the same time leaf images were collected by a handheld crop image
sensor. We calculated leaf area, leaf perimeter and RGB (red, green
and blue) values of these images. These data were further used in
linear discriminant analysis (LDA) to estimate leaf P contents, which
successfully classified these plants on the basis of leaf P contents.
The data indicated that P deficiency in crop plants can be predicted
using leaf image and morphological data. Our proposed nondestructive
imaging method is precise in estimating P requirements of
different crop species.", keywords = "Image-based techniques, leaf area, leaf P contents,
linear discriminant analysis.", volume = "9", number = "10", pages = "1121-4", }