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Predicting dark respiration rates of wheat leaves from hyperspectral reflectance

Coast, Onoriode; Shah, Shahen; Ivakov, Alexander; Gaju, Oorbessy; Wilson, Pip; Posch, Bradley; Bryant, Callum; Negrini, Ana; Evans, John; Condon, Anthony; Silva-Pérez, Viridiana; Reynolds, Matthew P.; Pogson, Barry; Millar, A Harvey; Furbank, Robert; Atkin, Owen

Description

Greater availability of leaf dark respiration (Rdark) data could facilitate breeding efforts to raise crop yield and improve global carbon cycle modelling. However, the availability of Rdark data is limited because it is cumbersome, time consuming, or destructive to measure. We report a non‐destructive and high‐throughput method of estimating Rdark from leaf hyperspectral reflectance data that was derived from leaf Rdark measured by a destructive high‐throughput oxygen consumption technique. We...[Show more]

CollectionsANU Research Publications
Date published: 2019
Type: Journal article
URI: http://hdl.handle.net/1885/201959
Source: Plant Cell and Environment
DOI: 10.1111/pce.13544
Access Rights: Open Access

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