# Data on transgenerational memory effects of photosynthetic efficiency of twelve wheat varieties under elevated carbon dioxide concentration and reduced soil water availability

## TL;DR

This study provides data on how the photosynthetic efficiency of wheat is affected across generations when exposed to high CO2 and drought conditions.

## Contribution

The study introduces a novel method for measuring photosynthesis and investigates transgenerational memory effects under controlled environmental conditions.

## Key findings

- Photosynthetic parameters like Vcmax, Jmax, and Rd were measured under different CO2 and soil water conditions.
- The study shows how parental environmental conditions influence offspring photosynthetic efficiency.
- Environmental and morphological data are provided to support a mechanistic understanding of transgenerational effects.

## Abstract

This data [1] represents ACi curves of twelve winter wheat varieties, which were grown under elevated and ambient CO2 concentrations within a FACE experiment and the subsequent F1 generation was exposed to ambient and elevated CO2 concentrations in a highly controlled environment using climate chambers. The 12 winter wheat genotypes (Triticum aestivum L.) were selected based on their susceptibilty to leaf rust (Puccinia triticina Eriks.) and Fusarium head blight (Fusarium graminearum Schwabe) according to the descriptive variety list of the German Federal Office of Plant Varietes (Beschreibende Sortenliste, Bundessortenamt 2024). The aim was to obtain a diverse set of varieties with the widest possible range of susceptibilities to leaf rust and fusarium head blight. Photosynthesis was measured using the novel Dynamic Assimilation Technique, thus not with the common steady-state approach. The individual wheat plants were measured twice, once under saturating soil water availability (θFC) and once under reduced soil water availability (θcsoil). θcsoil represents the gravimetric water content when the soil matric potential drops below the root matric potential, thus the onset of plant drought stress (sensu Cai et al. [2]). The photosynthesis data was used to fit ACi curves and extract the maximum Rubisco carboxylation rate [Vcmax], maximum rate of electron transport [Jmax] and dark respiration [Rd]. At both measurements we determined BBCH and plant height to quantify plant morphological development, as well as leaf water potential to quantify plant ecohydrologic status. At the end of the experiment, biomass was harvested and reported. Further, we provide environmental data of the climate chambers in use.

Within the data repository, we provide comprehensive experimental data on the investigation of transgenerational memory effects on photosynthetic efficiency. We provide photosynthetic raw data as well as processed (merged) and derived (extracted ACi fit) data. Additionally, we provide the R-code to reproduce the calculation of the derived parameters.

Data on transgenerational memory effects (that is, the influence of the parental environment on offspring phenotype and performance) are scarce, i.e. on the adaptive capacity of the photosynthetic apparatus. Thus, the data provided here can contribute to closing this gap. The highly controlled environment allows to closely investigate cause-effect relationships, thereby contributing to a mechanistic understanding of the transgenerational memory effects on photosynthetic efficiency and how this is altered by reduced soil water availability. By using a recently developed methodological approach, the data contributes to further investigate the quality of the method and establish it within the field of plant ecophysiology.