Plants display a large number of traits which are reflected in physiological and ecological functions (functional traits). Leaf traits are amongst the most important functional traits. However, a great challenge in measuring leaf traits in the field is that direct methods are limited by the cost of the instruments and the time and work required by direct measurements, which are often destructive. As an alternative, we developed and tested a non-destructive methodology to assess a suite of leaf traits using different digital photographic approaches, with the intimate aim to develop a rapid, robust and cheap protocol for leaf trait measurements in the field. The proposed digital photographic approaches were tested in broadleaved tree species Digital photography allowed to assess a morphological foliar trait (leaf area; LA) and physiological foliar traits (leaf reflectance in red (R), green (G) and blue (B) bands; leaf venation attributes). Leaf area derived from photography significantly agreed with that directly measured with a leaf area meter (LAPHOTO=0.98 LAAREA METER+0.84, R2=0.99, p < 0.001); leaf reflectance in the R, G, B channels derived from photography significantly agreed with that directly measured with a field spectroradiometer (SPEC) (RPHOTO=0.77 RSPEC+0.05, R2=0.61, p < 0.001; GPHOTO=0.79 GSPEC+0.06, R2=0.58, p < 0.001; BPHOTO=0.56 BSPEC+0.00, R2=0.51, p < 0.001). Leaf venation traits estimated from photography agreed to within±20% measurements obtained in cleared leaves of the same species. Based on the obtained results, we demonstrated that digital photography can be an effective tool to obtain a fast, cheap, reliable and non-destructive assessment of morphological and physiological leaf traits in broadleaf tree species, being highly suitable for use in long-term research and monitoring programs.

Development of digital photographic approaches to assess leaf traits in broadleaf tree species / Francesco Chianucci, Carlotta Ferrara, Martina Pollastrini, Piermaria Corona. - In: ECOLOGICAL INDICATORS. - ISSN 1470-160X. - ELETTRONICO. - 106:(2019), pp. 1-5. [10.1016/j.ecolind.2019.105547]

Development of digital photographic approaches to assess leaf traits in broadleaf tree species

Martina Pollastrini;
2019

Abstract

Plants display a large number of traits which are reflected in physiological and ecological functions (functional traits). Leaf traits are amongst the most important functional traits. However, a great challenge in measuring leaf traits in the field is that direct methods are limited by the cost of the instruments and the time and work required by direct measurements, which are often destructive. As an alternative, we developed and tested a non-destructive methodology to assess a suite of leaf traits using different digital photographic approaches, with the intimate aim to develop a rapid, robust and cheap protocol for leaf trait measurements in the field. The proposed digital photographic approaches were tested in broadleaved tree species Digital photography allowed to assess a morphological foliar trait (leaf area; LA) and physiological foliar traits (leaf reflectance in red (R), green (G) and blue (B) bands; leaf venation attributes). Leaf area derived from photography significantly agreed with that directly measured with a leaf area meter (LAPHOTO=0.98 LAAREA METER+0.84, R2=0.99, p < 0.001); leaf reflectance in the R, G, B channels derived from photography significantly agreed with that directly measured with a field spectroradiometer (SPEC) (RPHOTO=0.77 RSPEC+0.05, R2=0.61, p < 0.001; GPHOTO=0.79 GSPEC+0.06, R2=0.58, p < 0.001; BPHOTO=0.56 BSPEC+0.00, R2=0.51, p < 0.001). Leaf venation traits estimated from photography agreed to within±20% measurements obtained in cleared leaves of the same species. Based on the obtained results, we demonstrated that digital photography can be an effective tool to obtain a fast, cheap, reliable and non-destructive assessment of morphological and physiological leaf traits in broadleaf tree species, being highly suitable for use in long-term research and monitoring programs.
2019
106
1
5
Francesco Chianucci, Carlotta Ferrara, Martina Pollastrini, Piermaria Corona
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1160770
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