Image-Based (RBG) Technique for Estimating Phosphorus Levels of Crops

Authors: M. M. Ali, Ahmed Al-Ani, Derek Eamus, Daniel K. Y. Tan

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.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109932

References:

[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.