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Agriculture & Food 2020, 8th International Conference
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Agriculture & Food, Volume 3, 2015

Mahdi Ali, Ahmed AL-Ani, Daniel Tan, Derek Eamus, Ian Rochester
Pages: 234-240
Published: 23 May 2015
Views: 2,282
Downloads: 627
Abstract: In this glasshouse study, we proposed a new image-based non-destructive technique for estimating P levels in cotton leaves. The plants were grown on a nutrient medium containing various P concentrations, i.e. 0%, 50% and 100% of recommended P levels for 10 weeks, and then leaf P contents were analysed using a destructive method. For comparison, we collected leaf images of the leaves using a handheld crop sensor. The RGB (red, green and blue) values of the collected images were used for calculating leaf area and leaf perimeter. This data on leaf growth parameters was used in a linear discriminant analysis (LDA) to estimate leaf P contents. Using LDA, we successfully classified cotton plants into different group based on their leaf P contents indicating that P deficiency in cotton can be estimated using leaf morphological data. Our proposed non-destructive method was efficient in estimating P requirements for cotton.
Keywords: image-based techniques, cotton, leaf p contents, linear discriminant analysis
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