Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming
Data files
Apr 16, 2026 version files 2.09 MB
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11-Dec-2025_R_Script_for_Plots_and_Analysis_-_Revised.R
67.13 KB
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Estimates_of_Photosynthetic_Capacity_CLEANED_PRN.xlsx
30.76 KB
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Experiment_1_Licor_Data_CLEANED_PRN.xlsx
1.46 MB
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README.md
22.63 KB
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Supplementary_Information.pdf
517.68 KB
Abstract
Rising night temperatures pose a significant threat to wheat productivity, yet the physiological basis of wheat adaptation to nocturnal warming remains poorly understood. We evaluated leaf photosynthetic and respiratory traits in ten Australian wheat cultivars released between 1901 and 2012 to warm nights under temperature-controlled environments. When exposed to warmer nights, rates of leaf net CO2 assimilation measured at 25 °C (Anet25) remained stable across cultivar release date despite declines in photosynthetic capacity (Vcmax and J1500) in newer cultivars. In most cultivars leaf respiratory CO2 release in the dark (Rdark) exhibited divergent thermal responses: warm nights suppressed temperature-normalised night Rdark (Rdark_night) but stimulated or maintained Rdark in the daytime (Rdark_day). The results suggest that a century of yield-focused breeding may have inadvertently maintained Anet25 under warmer nights in modern cultivars. This likely reflects the selection of genotypes with more efficient photosynthetic capacity (i.e. greater return per protein investment) under warm nights. It is also likely that modern cultivars exhibit reduced respiratory demand for maintenance of processes such as Rubisco protein turnover and synthesis. Our findings highlight trait-based targets for enhancing energy efficiency and climate resilience in wheat and opportunities to improve the parameterization of Rdark in Earth system models.
This README file was last updated on: 2026-04-15 (updated to address Dryad curation queries)
Corresponding author: Onoriode Coast (ocoast@une.edu.au)
Corresponding author institution: University of New England, Armidale, NSW, Australia
GENERAL INFORMATION
- Title of Dataset: Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming
- Citation for this dataset:
Rana Shahi, P., Scafaro, A. P., Thistlethwaite, R. J., Atkin, O. K., Trethowan, R. M., Rader, R., Burns, A., & Coast, O. (2025). Data from: Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming. Dryad Digital Repository. - Link to related publication:
Rana Shahi, P., Scafaro, A. P., Thistlethwaite, R. J., Atkin, O. K, Trethowan, R. M., Rader, R., Burns, A., & Coast, O. (2026) Wheat leaf dark respiration acclimates more strongly at night than in the day when responding to nocturnal warming. Journal of Experimental Botany, erag106, https://doi.org/10.1093/jxb/erag106.
DATA & FILE OVERVIEW
File List
Experiment_1_Licor_Data_CLEANED_PRN.xlsx(Main physiological data from LI-COR measurements)Estimates_of_Photosynthetic_Capacity_CLEANED_PRN.xlsx(Derived photosynthetic capacity parameters)11-Dec-2025_R_Script_for_Plots_and_Analysis_-_Revised.R(R script for reproducing all figures and statistical analyses)Supplementary_Information.pdf(Supplementary information)README.md(This file)
Relationship between files
- The R script (
\*.R) loads and processes data directly from the two Excel files. - The Excel files are structured to be machine-readable for the provided R script. Modifying their format (e.g., converting to .csv, removing sheets) would break the script and hinder re-analysis.
DATA-SPECIFIC INFORMATION FOR: Experiment_1_Licor_Data_CLEANED_PRN.xlsx
Important Note on File Format:
This file is intentionally provided as a formatted Excel workbook (.xlsx) with multiple sheets. This structure preserves the logical connections between different data types (e.g., photosynthesis An, dark respiration R_d, night respiration R_n) that are essential for re-analysis. Converting to multiple CSV files would break these connections and invalidate the accompanying R script. The minimal formatting present (e.g., multiple sheets) is essential for re-analysis with the provided code.
Handling of Empty Cells:
Empty cells in this file indicate no data available (NA) for that specific measurement (e.g., a failed measurement, a non-applicable variable, or an unmeasured replicate). These cells are intentionally left blank (rather than filled with "null" or "n/a") to ensure full compatibility with the provided R script, which is designed to handle NA values natively. Adding text strings to these cells would cause the R script to fail.
Sheets in this file:
Main sheet: contains all data
An: photosynthesis data
R_d: dark respiration during the day
R_n: dark respiration during the nights
A-Ci: photosynthesis at different intercellular CO2 concentration
LMA & N: Leaf mass per unit area or weight, leaf nitrogen and plant biomass
Common identified variables (present in most sheets)
| Variable Name | Description | Units |
|---|---|---|
Experiment |
Experimental treatment (Control or High Night) |
- |
Date |
Date of measurement | - |
Licor Name |
Licor instrument ID | - |
PID |
Individual plant identification number | |
Genotype |
Wheat genotype/cultivar name (e.g., Federation, Gabo, Suntop) | - |
Year_Release |
Year of cultivar release | Gregorian year |
Rep |
Biological replicate number | - |
Growth Chamber |
Growth chamber identification number | |
Trait |
Trait measured - being one of An, R_d, R_n or A_Ci | |
Leaf Mass Fresh (g) |
Fresh mass of the leaf sample | g |
Leaf Area (A) m2 |
Leaf area | m² |
Dry Biomass (M) g-sample leaf |
Dry biomass of the leaf sample | g |
LMA (M/A) (gm-2) |
Leaf mass per area (calculated) | g m⁻² |
Total Fresh Wt. |
Total fresh weight of sample | g |
Total Dry Wt. |
Total dry weight of sample | g |
Nitrogen_% |
Nitrogen concentration as percentage of dry mass | % |
N_mg |
Total nitrogen mass | mg |
Rd_A |
Day respiration rate (Rday) at 25°C | µmol CO₂ m⁻² s⁻¹ |
Leaf nitrogen per mass (mg/g) |
Leaf nitrogen concentration on a mass basis | mg N g⁻¹ |
Leaf nitrogen per area (g/m2) |
Leaf nitrogen concentration on an area basis | g N m⁻² |
Obs |
Observation number | - |
HHMMSS |
Time of measurement (hour:minute:second) | HH:MM:SS |
FTime |
Fluorescence time | - |
EBal? |
Energy balance flag | - |
Photo |
Net photosynthetic rate (same as Anet_A) |
µmol CO₂ m⁻² s⁻¹ |
Cond |
Stomatal conductance | mol H₂O m⁻² s⁻¹ |
Ci |
Intercellular CO₂ concentration | µmol CO₂ mol⁻¹ |
Trmmol |
Transpiration rate | mmol H₂O m⁻² s⁻¹ |
VpdL |
Vapor pressure deficit based on leaf temperature | kPa |
CTleaf |
Leaf thermocouple temperature | °C |
Area |
Leaf area enclosed in chamber | cm² |
BLC_1 |
Boundary layer conductance for H₂O | mol m⁻² s⁻¹ |
StmRat |
Stomatal ratio | - |
BLCond |
Boundary layer conductance (alternative) | - |
Tair |
Air temperature inside chamber | °C |
Tleaf |
Leaf temperature (calculated) | °C |
TBlk |
Block temperature | °C |
CO2R |
CO₂ concentration in reference IRGA | µmol CO₂ mol⁻¹ |
CO2S |
CO₂ concentration in sample IRGA | µmol CO₂ mol⁻¹ |
H2OR |
H₂O concentration in reference IRGA | mmol H₂O mol⁻¹ |
H2OS |
H₂O concentration in sample IRGA | mmol H₂O mol⁻¹ |
RH_R |
Relative humidity of reference IRGA | % |
RH_S |
Relative humidity of sample IRGA | % |
Flow |
Flow rate through chamber | µmol s⁻¹ |
PARi |
Photosynthetic photon flux density inside chamber | µmol m⁻² s⁻¹ |
PARo |
Photosynthetic photon flux density outside chamber | µmol m⁻² s⁻¹ |
Press |
Atmospheric pressure | kPa |
CsMch |
CO₂ concentration at leaf surface (matching) | - |
HsMch |
H₂O concentration at leaf surface (matching) | - |
StableF |
Stability flag | - |
BLCslope |
Boundary layer conductance slope | - |
BLCoffst |
Boundary layer conductance offset | - |
f_parin |
Fraction of PAR entering chamber | - |
f_parout |
Fraction of PAR exiting chamber | - |
alphaK |
Leaf absorptance factor | - |
Status |
Measurement status flag | - |
fda |
Fluorescence decay parameter | - |
Trans |
Transmittance | - |
Tair_K |
Air temperature in Kelvin | K |
Twall_K |
Wall temperature in Kelvin | K |
R(W/m2) |
Net radiation | W m⁻² |
Tl-Ta |
Leaf minus air temperature difference | °C |
SVTleaf |
Saturation vapor pressure at leaf temperature | kPa |
h2o_i |
Intercellular H₂O concentration | - |
h20diff |
H₂O concentration gradient | - |
CTair |
Air thermocouple temperature | °C |
SVTair |
Saturation vapor pressure at air temperature | kPa |
CndTotal |
Total conductance | - |
vp_kPa |
Vapor pressure | kPa |
VpdA |
Vapor pressure deficit based on air temperature | kPa |
CndCO2 |
CO₂ conductance | - |
Ci_Pa |
Intercellular CO₂ partial pressure | Pa |
Ci/Ca |
Ratio of intercellular to ambient CO₂ | - |
RHsfc |
Relative humidity at leaf surface | % |
C2sfc |
CO₂ concentration at leaf surface | - |
AHs/Cs |
Ratio of absolute humidity to CO₂ at leaf surface | - |
Leaf # |
Leaf | - |
Specific to sheet An and A-Ci:
Photo = Net photosynthetic rate per unit leaf area (µmol CO₂ m⁻² s⁻¹)
Specific to sheet R_d:
Photo = Dark respiration rate during the day (µmol CO₂ m⁻² s⁻¹)
Specific to sheet R_n:
Photo = Respiration rate at night (µmol CO₂ m⁻² s⁻¹)
Specific to sheet LMA & N:
| S.N | Serial number | |
|---|---|---|
Leaf Mass (M) g |
Fresh mass of the leaf sample | g |
Leaf Area (A) m2 |
Leaf area | m² |
LMA (M/A) (gm-2) Fresh |
Leaf mass per area calculated from fresh mass | g m⁻² |
Dry Biomass (M) g-sample leaf |
Dry biomass of the leaf sample after drying | g |
Total Fresh Wt. |
Total fresh weight of sample (if multiple leaves) | g |
Total Dry Wt. |
Total dry weight of sample after drying | g |
Nitrogen (%) |
Nitrogen concentration as percentage of dry mass | % |
DATA-SPECIFIC INFORMATION FOR: Estimates_of_Photosynthetic_Capacity_CLEANED_PRN.xlsx
Important Note on File Format:
As with the main data file, this Excel workbook is provided in its native format to maintain compatibility with the R script. The single sheet contains calculated parameters derived from A-Ci curves.
Handling of Empty Cells:
Empty cells indicate missing data (NA) for that specific parameter and replicate (e.g., failed model fit for Jmax). Cells are left blank to ensure R's na.rm = TRUE functions correctly.
Sheet: Photo\_Capacity
| Variable Name | Description | Units |
|---|---|---|
PID |
Individual plant identification number | - |
curve |
LI-COR measurement curve ID | - |
Treatment |
Control or High Night |
- |
Genotype |
Wheat genotype/cultivar name | - |
Year\_Release |
Year of cultivar release | Gregorian year |
Night\_temp |
Night temperature treatment | °C |
Rep |
Biological replicate number | - |
Tleaf |
Leaf temperature during measurement | °C |
Vcmax |
Maximum Rubisco carboxylation rate at 25°C | µmol CO₂ m⁻² s⁻¹ |
corVcmax |
Correlation coefficient for Vcmax fit | - |
Jmax |
Maximum electron transport rate for RuBP regeneration at 25°C (J1500) | µmol e⁻ m⁻² s⁻¹ |
corJmax |
Correlation coefficient for Jmax fit | - |
TPU |
Triose phosphate utilization rate at 25°C | µmol CO₂ m⁻² s⁻¹ |
corTPU |
Correlation coefficient for TPU fit | - |
CODE-SPECIFIC INFORMATION FOR: 11-Dec-2025_R_Script_for_Plots_and_Analysis_-_Revised.R
| Variable | Description |
|---|---|
| File name | 11-Dec-2025_R_Script_for_Plots_and_Analysis_-_Revised.R |
| Software required | R (version 4.2.3 or later) |
| Required R packages | readxl, ggplot2, dplyr, gridExtra, ggsignif |
| Purpose | Reproduces all figures (Figures 1-6) and supplementary figures from the associated publication; performs two-way ANOVAs; fits linear/polynomial models to trait-year relationships; generates all plots; saves outputs as high-resolution JPEG and PDF files |
| How to run | 1. Place the R script and both .xlsx data files in the same working directory. 2. Open the script in RStudio or any R environment. 3. Run the script line-by-line or source the entire file (source("11-Dec-2025_R_Script_for_Plots_and_Analysis_-_Revised.R")) |
| Expected output | Console outputs (ANOVA summaries, model coefficients); saved figure files (JPEG and PDF) in the working directory |
| Key notes | The script contains commented sections allowing users to optionally filter data (e.g., excluding Year_Release = 1901). Empty cells in Excel files are handled correctly via na.rm = TRUE. |
SUPPLEMENTARY INFORMATION FOR: Supplementary_Information.pdf
| Variable | Description |
|---|---|
| File name | Supplementary_Information.pdf |
| Contents | This document contains supplementary materials referenced in the main publication, including but not limited to: detailed methodological protocols, supplementary tables (e.g., full ANOVA results, model comparison statistics), supplementary figures not included in the main manuscript, and a complete list of references cited only in the supplementary information |
| Relationship to data files | Supplementary tables and figures referenced in this document are derived from the analysis of the provided Excel data files using the provided R script |
SHARING/ACCESS INFORMATION
- This data is published under a Creative Commons Zero (CC0) waiver.
- Links to other publicly accessible locations of the data: None
- Was data derived from another source? No
- Related data not included: Rubisco protein extracted from wheat leaves using Bradford assays (available from corresponding author upon reasonable request).
ADDITIONAL NOTES FOR DATA USERS
- The R script contains commented sections (e.g.,
# Option to exclude Year\_Release = 1901) that allow users to optionally filter the data for sensitivity analyses. - All statistical outputs (ANOVA summaries, model coefficients) are printed to the R console when the script is run.
- The script automatically saves all publication-ready figures to the working directory.
- Empty cells in the Excel files are intentional and represent
NAvalues; do not replace them with text strings as this will break the analysis script.
Materials and methods
The experiment was conducted in controlled-environment facilities (glasshouses and growth chambers) at the University of New England (UNE) in Armidale, Australia (30.48°S, longitude 151.63°E, elevation 1021.5 m a.s.l.) in 2022.
Plant materials and growth conditions
A set of 10 wheat genotypes (Supplementary Table 1) were used in this experiment. The genotypes included commercial Australian wheat varieties spanning over a century (1901-2012) of breeding. Seeds of ten Australian wheat cultivars were planted in 4.5 L plastic pots (18 cm diameter and 60 cm height) containing Professional premium potting mix with slow-release fertiliser (J.C. & A.T. Searle Pty. Ltd., Qld. Australia). Potted plants were raised in glasshouse bays set to day/night temperatures of 20/12 °C, 70% relative humidity and a natural photoperiod of 12 hours. The plants were grown for four weeks in the glasshouse until the tillering stage (Zadok 20-29) (Zadoks et al., 1974). During this period, watering was provided manually, and standard operating protocols used for plant husbandry in the glasshouse applied. At tillering, when all plants had a fully extended third leaf, wheat plants were moved into growth chambers (Conviron, Conviron Inc., Winnipeg, Canada), and raised for three weeks till their booting stage (Zadok 30-49).
The three growth chambers were equipped with incandescent and fluorescent lamps, and set to a 14-hour photoperiod with photosynthetic photon flux density (PPFD) of 800-850 µmol m-2, and relative humidity of 60%. The experiment was a complete randomised design with two treatments and three replicates. However, each cultivar had six technical replicates (i.e. two pots per chamber per treatment). The treatments were the control temperature (25/12 °C, maximum day/minimum night) and high night temperature (25/22°C, maximum day/minimum night). The experiment was conducted in two sequential batches, with all control plants grown first, followed by all high night temperature plants. Each batch used the same three growth chambers, serving as biological replicates, to ensure consistent environmental conditions across treatments. Maximum and minimum temperatures were maintained for 8 hour each in all growth chambers with a transition period of 4 hour between maximum day/minimum night temperatures. Temperature and relative humidity (RH) at canopy level were recorded every five minutes using Tiny-tag Ultra 2 Hasting temperature/RH data loggers (Gemini Data Loggers UK LTD, UK) in all growth chambers during both treatments.
Photosynthesis and respiration
Gas exchange measurements were conducted on recently fully developed flag leaves on tagged main tillers in each treatment using portable infrared gas analyser (IRGA) units (Li-6400XT, LI-COR Inc., Lincoln, NE, USA). The net CO2 assimilation (Anet25) measurements were taken with Li-6400XT units with 6 cm leaf chamber and block temperatures set to 25 °C, CO2 fixed at 400 ppm with a flow rate of 500 μmol s−1 and light intensity of 1500 μmol m−2 s−1 of Photosynthetically Active Radiation (PAR). Dark-adapted temperature-normalised Rday and Rnight were recorded with the same Li-6400XT units. Each chamber’s head block temperature was set to 25 °C for Rday, and 20 °C for Rnight. The set chamber temperature resulted in average leaf temperature of 25.5 °C for Anet25 and Rday and 21.3 °C for Rnight. Measurements of Anet25 and Rday (after at least 20 minutes of dark adaptation) were completed during the day (between 09:00 and 17:30 h) and Rnight measured at night (after 20:00 h).
Maximum Rubisco activity and electron transport rate
Two Li-6400XT units were used to assess photosynthetic capacity of the ten wheat genotypes. Photosynthetic CO2 response curves (A:Ci curves) were generated, at constant irradiance of 1500 μmol photons m−2 s−1, by varying the CO2 inside the Li-6400XT leaf chambers as follows: 400, 40, 60, 100, 150, 250, 400, 400, 600, 800, 1000, 1200, 1400 and 400 μmol mol−1. Relative humidity within the chamber was maintained between 40 and 70% for all measurements. The maximum Rubisco activity at 25 °C, Vcmax25, and electron transport rate at PAR of 1500 μmol m−2 s−1 and measured at 25 °C, J150025 were calculated using the leaf biochemical model of photosynthesis (Farquhar et al., 1980) with kinetic constants derived for wheat (Silva-Perez et al., 2018). Response curves of Anet25 to the intercellular CO2 concentration (Ci) were measured in the mid-section of the flag leaf when the plants reached Zadoks stage (40-49). The relationship between Anet25 and CO2 followed the FvCB model (Farquhar et al., 1980; von Caemmerer & Farquhar, 1981) with a simple function for limitation by triose phosphate utilization (TPU) (Sharkey et al., 2007). The approach of Gu and Jerome (2010) was used where all possible carboxylation limitation-state combinations were tested, given the required order of limitation states along the Ci axis (Rubisco limited <electron transport limited < TPU limited) and the minimum number of data necessary for each limitation state (n≥2 when Michaelis Menten constants for Rubisco catalysis of carboxylation, Kc, and oxygenation reactions, Ko; and the photosynthetic CO2 compensation point in the absence of mitochondrial respiration in the light, Γ*, are fixed). The R Language and Environment function optim (R Core Team, 2023) was used to minimize the distribution-wise cost function, and the model with the lowest cost function value was accepted after checking for admissibility and, if necessary, testing for co-limited ‘swinging points’ (Gu & Jerome, 2010). These measurements were taken within a day between 09:00 and 17:30 hr (~40 min before sunset) for each plant.
Determination of leaf mass per area and nitrogen content
Leaf area (cm2) was calculated using the same leaf used for gas exchange measurements. Leaves were dried at 65 °C for 72 h or until constant dry weight was achieved then used to calculate leaf dry mass per unit area (LMA, g m-2). Then, 1 mg of dry leaf section of each sampled tissue was weighed and analysed to calculate leaf N (%) using an automatic element analyser (Sercon Control “Callisto CF-IRMS” Version 30.0.11, Sercon Integra 2) coupled to a mass spectrometer (Elemental microanalysis LTD, United Kingdom). Using determined N content (%) and LMA, we estimated leaf nitrogen per area (Narea, g m-2) and leaf nitrogen per dry mass (Nmass, mg g-1).
Supplementary Table S1. Pedigrees, year of introduction, and susceptibility traits of the wheat cultivars used in this study.
| Year released | Variety | Notes | References1 | |
|---|---|---|---|---|
| 1 | 1901 | Federation | AH (Australian Hard), Bred by William Farrer, first Australian variety with both rust and drought resistance. Cold stress tolerant | Paull et al. (1998) |
| 2 | 1945 | Gabo | First variety released by University of Sydney, widely planted, Early maturing, short to medium height straw, susceptible to flat smut and rust, successful grown in most districts. | Reeves (1963) |
| 3 | 1955 | Koda | APH (Australian Prime Hard), grown on heavy land for short season | Parish & Stone, (1965) and Reeves (1963) |
| 4 | 1965 | Gamut | ASW (Australian Standard White), spring wheat, rust resistant, | Snape et al. (1979), |
| 5 | 1975 | Songlen | Australian spring wheat with white grain colour | Mares (1983), Wellings et al. (2005) and Snape et al. (1979) |
| 6 | 1986 | Sunco | AH. Moderately resistant to rust. Rot and sprouting resistance. Commercial variety. | Salman et al. (2009) |
| 7 | 1996 | Sunlin | AH, excellent sprouting tolerance and grain retention in the head at harvest. Moderately resistant to stripe, stem and leaf rust. Moderately susceptible–susceptible to crown rot. Resistant–moderately susceptible to common root rot, moderately resistant–moderately susceptible to yellow leaf spot and Septoria tritici blotch. Very susceptible to root-lesion nematode (Pratylenchus thornei). Some frost tolerance. | Wellings et al., (2005) and Amjad (2001) https://www.grainland.com.au/seed-sales-information |
| 8 | 2001 | Braewood | AH. Susceptible to yellow spot. Moderately resistant to rust. Medium height and suitable for production of high protein and high volume of breads and wanton dumpling skins. | Wellings et al. (2005), and Zaicou et al., (2010) |
| 9 | 2007 | Merinda | AH. Rust resistant. Most suitable to grow in NSW. Released as a Carinya and Janz replacement. | Wellings et al., (2005) |
| 10 | 2012 | Suntop | APH (Australian Prime Hard). Origin in northern NSW. Suitable to all environments across NSW and Queensland. Highest yields in independent trials. Best disease resistance variety. AGT Seeds. | Zeeshan et al., (2020) https://www.grainland.com.au/seed-sales-information |
1References
Amjad, M. (2001). Yield and falling numbers of new wheat cultivars on the south coast of Western Australia.
Mares, D. J. (1983). Preservation of dormancy in freshly harvested wheat grain. Australian Journal of Agricultural Research, 34(1), 33-38.
Parish, J. A., & Stone, R. F. (1965). Premium wheat in Western Australia. Journal of the Department of Agriculture, Western Australia, Series 4, 6(9), 575-578.
Paull, J. G., Chalmers, K. J., Karakousis, A., Kretschmer, J. M., Manning, S., & Langridge, P. (1998). Genetic diversity in Australian wheat varieties and breeding material based on RFLP data. Theoretical and Applied Genetics, 96(3), 435-446.
Reeves, J. T. (1963). Cereal variety trials, 1961-62. Journal of the Department of Agriculture, Western Australia, Series 4, 4(1), 21-29.
Salman, H., Blazek, J., Lopez-Rubio, A., Gilbert, E. P., Hanley, T., & Copeland, L. (2009). Structure–function relationships in A and B granules from wheat starches of similar amylose content. Carbohydrate Polymers, 75(3), 420-427.
Snape, J. W., Chapman, V., Moss, J., Blanchard, C. E., & Miller, T. E. (1979). The crossabilities of wheat varieties with Hordeum bulbosum. Heredity, 42(3), 291-298. Wellings, C., Bariana, H., & Park, R. (2005). Cereal Rust Report.
Zaicou, C., Penny, S., Shackley, B., Ellis, S., Miyan, S., Dhammu, H., Shankar, M., & Sharma, D. (2010). Wheat variety guide 2010 Western Australia.
Zeeshan, M., Lu, M., Naz, S., Sehar, S., Cao, F., & Wu, F. (2020). Resemblance and difference of seedling metabolic and transporter gene expression in high tolerance wheat and barley cultivars in response to salinity stress. Plants, 9(4), 519.
References
Farquhar, G. D., & Sharkey, T. D. (1982). Stomatal conductance and photosynthesis. Annual Review of Plant Physiology, 33(1), 317-345.
Gu, Y., & Jerome, F. (2010). Glycerol as a sustainable solvent for green chemistry. Green Chemistry, 12(7), 1127-1138.
Sharkey, T. D., Bernacchi, C. J., Farquhar, G. D., & Singsaas, E. L. (2007). Fitting photosynthetic carbon dioxide response curves for C3 leaves. Plant, Cell & Environment, 30(9), 1035-1040.
Silva-Perez, V., Molero, G., Serbin, S. P., Condon, A. G., Reynolds, M. P., Furbank, R. T., & Evans, J. R. (2018). Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat. Journal of Experimental Botany, 69(3), 483-496.
von Caemmerer, S. V., & Farquhar, G. D. (1981). Some relationships between the biochemistry of photosynthesis and the gas exchange of leaves. Planta, 153(4), 376-387.
Zadoks, J. C., Chang, T. T., & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed Research, 14(6), 415-421.
