We examined photosynthetic capacity of newly-developed and pre-existing flag leaves of four wheat genotypes under three night temperatures (15, 20 and 25 °C) and common day temperature of 26 °C in two controlled environment experiments. In newly-developed leaves which acclimated (i.e. maintained or increased) the maximum rate of net CO₂ assimilation (A_n) to long-term (9–13 weeks) nocturnal warming, acclimation was underpinned by greater capacity of Rubisco carboxylation (V_cmax) and photosynthetic electron transport (J). This indicates a night-dependent temperature sensitivity of the activation state of Rubisco. Metabolite profiling linked acclimation of A_n to greater accumulation of monosaccharides and saturated fatty acids in leaves, suggesting roles for osmotic adjustment of leaf turgor pressure and maintenance of cell membrane integrity. By contrast, warm night-induced inhibition of A_n was related to reductions in stomatal conductance of CO₂ and J, despite higher basal electron transport thermal stability: T_crit 51 of 45–46.5 °C in non-acclimated versus T_crit of 43.8–45 °C in acclimated leaves. Pre-existing leaves exposed to short-term nocturnal warming (5–7 nights) showed no change in instantaneous temperature responses of A_n and photosynthetic capacity, except for an elite heat-tolerant genotype. These findings can be used to support strategies for developing climate-resilient wheat.

T_crit: leaf discs were excised during the day from the middle section of detached dark-adapted and were exposed to a temperature ramp at a constant rate of 1°C min⁻¹ from 20 to 65 °C with simultaneous continuous measurement of F0 taken. T_crit was calculated as the intersection point of two regression lines extrapolated from the flat and steep portion of the F0–temperature response curve.

Leaf gas exchange and An-Ci curves: Five LI-COR portable photosynthesis systems (LI-6400XT, LI-COR Inc., Lincoln, NE, USA) were used for gas exchange measurements. The LI-COR units were fitted with 6 cm2 leaf chambers with red-blue light source (6400-18 RGB Light Source, LI-COR). Leaves were exposed to saturating irradiance of 1500 μmol photons m⁻² s⁻¹ within the LI-COR leaf chamber, with both the LI-COR leaf chamber/block, and the whole plants were placed within the temperature-controlled cabinet. The LI-COR leaf chamber was initially set to 20°C, reference line atmospheric [CO₂] of 400 ppm, a flow rate of 500 μmol s⁻¹, and relative humidity maintained between 40 and 75%. photosynthetic [CO₂] response curves (A:C_i curves) were generated, at constant irradiance of 1500 μmol photons m⁻² s⁻¹, by varying the [CO₂] inside the LI-COR leaf chambers as follows: 30, 50, 100, 150, 250, 400, 400, 600, 800, 1000, 1200, 1400 and 400 μmol mol⁻¹. The A:C_i curves were repeated with the leaves exposed to measurement temperatures of 25, 30, 35, 40 and 50 °C.

Modelling photosynthetic capacity: Model parameters for each growth and measurement temperature were estimated following the FvCB model and using the Plantecowrap package (Stinziano et al., 2018) in the R computing environment (R-Development-Core-Team, 2021). 

The kinetic parameters used in modelling photosynthetic capacity for wheat were: mesophyll conductance at 25°C (g_m = 5.5 mmol m⁻² s⁻¹ Pa^-1); activation energy of mesophyll conductance (E_a = 47.65 kJ mol^-1); apparent Michaelis-Menten constant for Rubisco carboxylation in 21% oxygen (K_air = 772 µmol mol^-1); activation energy of K_c (93.72 kJ mol^–1); photorespiratory CO2 compensation point or Gamma star at 25°C (Γ* = 37.74 µmol mol^–1, equivalent to µbar bar^–1); and Gamma star activation energy (24.42 kJ mol^–1). The temperature response of V_cmax, J₁₅₀₀ and TPU were modelled using non-linear least squares fit of the Arrhenius temperature response function accounting for deactivation (Medlyn et al., 2002, Kattge and Knorr, 2007). The deactivation energy (E_d) was assumed to be 200 kJ mol^–1, the activation energy (E_a) and entropy factor (DS) were estimated from iterative fits of the model.

Metabolites: Metabolite extraction was conducted using a gas chromatography coupled to mass spectrometry (GC-MS) procedure.

MS Excel and R/R Studio.