Skip navigation
Skip navigation

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


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
Source: Plant Cell and Environment
DOI: 10.1111/pce.13544
Access Rights: Open Access


File Description SizeFormat Image
01_Coast_Predicting_dark_respiration_2019.pdf3.62 MBAdobe PDFThumbnail

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator