BackgroundMitochondrial respiration in the dark (R dark) is a critical plant physiological process, and hence a reliable, efficient and high-throughput method of measuring variation in rates of R dark is essential for agronomic and ecological studies. However, currently methods used to measure R dark in plant tissues are typically low throughput. We assessed a high-throughput automated fluorophore system of detecting multiple O2 consumption rates. The fluorophore technique was compared with O2-electrodes, infrared gas analysers (IRGA), and membrane inlet mass spectrometry, to determine accuracy and speed of detecting respiratory fluxes.ResultsThe high-throughput fluorophore system provided stable measurements of R dark in detached leaf and root tissues over many hours. High-throughput potential was evident in that the fluorophore system was 10 to 26-fold faster per sample measurement than other conventional methods. The versatility of the technique was evident in its enabling: (1) rapid screening of R dark in 138 genotypes of wheat; and, (2) quantification of rarely-assessed whole-plant R dark through dissection and simultaneous measurements of above- and below-ground organs.DiscussionVariation in absolute R dark was observed between techniques, likely due to variation in sample conditions (i.e. liquid vs. gas-phase, open vs. closed systems), indicating that comparisons between studies using different measuring apparatus may not be feasible. However, the high-throughput protocol we present provided similar values of R dark to the most commonly used IRGA instrument currently employed by plant scientists. Together with the greater than tenfold increase in sample processing speed, we conclude that the high-throughput protocol enables reliable, stable and reproducible measurements of R dark on multiple samples simultaneously, irrespective of plant or tissue type.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-017-0169-3) contains supplementary material, which is available to authorized users.

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 generated a large dataset of leaf Rdark for wheat (1380 samples) from 90 genotypes, multiple growth stages, and growth conditions to generate models for Rdark. Leaf Rdark (per unit leaf area, fresh mass, dry mass or nitrogen, N) varied 7‐ to 15‐fold among individual plants, whereas traits known to scale with Rdark, leaf N, and leaf mass per area (LMA) only varied twofold to fivefold. Our models predicted leaf Rdark, N, and LMA with r2 values of 0.50–0.63, 0.91, and 0.75, respectively, and relative bias of 17–18% for Rdark and 7–12% for N and LMA. Our results suggest that hyperspectral model prediction of wheat leaf Rdark is largely independent of leaf N and LMA. Potential drivers of hyperspectral signatures of Rdark are discussed.

Nitrogen (N) and phosphorus (P) have key roles in leaf metabolism, resulting in a strong coupling of chemical composition traits to metabolic rates in field-based studies. However, in such studies, it is difficult to disentangle the effects of nutrient supply per se on trait-trait relationships. Our study assessed how high and low N (5 mM and 0.4 mM, respectively) and P (1 mM and 2 μM, respectively) supply in 37 species from six plant functional types (PTFs) affected photosynthesis (A) and respiration (R) (in darkness and light) in a controlled environment. Low P supply increased scaling exponents (slopes) of area-based log-log A-N or R-N relationships when N supply was not limiting, whereas there was no P effect under low N supply. By contrast, scaling exponents of A-P and R-P relationships were altered by P and N supply. Neither R : A nor light inhibition of leaf R was affected by nutrient supply. Light inhibition was 26% across nutrient treatments; herbaceous species exhibited a lower degree of light inhibition than woody species. Because N and P supply modulates leaf trait-trait relationships, the next generation of terrestrial biosphere models may need to consider how limitations in N and P availability affect trait-trait relationships when predicting carbon exchange.