%0 Journal Article %A M. M. Ali and Ahmed Al-Ani and Derek Eamus and Daniel K. Y. Tan %D 2015 %J International Journal of Agricultural and Biosystems Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 106, 2015 %T Image-Based (RBG) Technique for Estimating Phosphorus Levels of Crops %U https://publications.waset.org/pdf/10002856 %V 106 %X 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. %P 1125 - 1128