Promising photosynthetic parameters Y(II) and NPQ for predicting barley drought tolerance

Abstract

The purpose of the current work was to identify photosynthetic parameters that are predictors of barley drought tolerance, determined at early stages of development, and to verify the results obtained in field conditions. The study was carried out with the barley varieties ‘Leon’, ‘Ratnik’ and ‘Foks 1’, used in mutation breeding to develop drought-resistant genotypes. Drought was modeled by stopping irrigation. Plant resistance was estimated by changes in chlorophyll fluorescence (Fv /Fm, Y(II), NPQ) and morphometric parameters (leaf length, wet and dry weight) compared to the control group with normal water supply. Under stress-free conditions, the variety ‘Leon’ demonstrated a statistically significantly lower efficiency of photosynthesis in terms of Y(II) and Fv /Fm (0.535 ± 0.005 and 0.776 ± 0.004, respectively) in comparison with other varieties (0.577 ± 0.005 and 0.788 ± 0.001 for the variety ‘Foks 1’; 0.574 ± 0.004 and 0.787 ± 0.001 for the variety ‘Ratnik’). When modeling drought, there has been established a decrease in all morphometric indicators for all varieties relative to the control, with the highest degree of inhibition for the variety ‘Ratnik’ (70.16 ± 3.88 %; 8.09 ± 0.73 %; 68.50 ± 4.42 % for leaf length, wet and dry weight, respectively) and with the lowest degree for the variety ‘Leon’ (88.06 ± 7.83 %; 26.51 ± 7.11 %; 79.32 ± 11.17 %, respectively). A decrease in the photosynthesis intensity was manifested in the suppression of Fv /Fm and Y(II) and an increase in NPQ, with the earliest changes in the parameters Y(II) and NPQ in the varieties ‘Foks 1’ and ‘Ratnik’ (on the 4th and 5th day, respectively), compared to the variety ‘Leon’ (on the 7th day). In the field conditions, there has been estimated productivity of the varieties and its dependence on precipitation. A positive correlation between the difference in yield of two varieties ‘Leon’ and ‘Ratnik’, contrasting in their response to drought, and the amount of precipitation during the active vegetation period in 2014–2017 and 2022 (Pearson’s R2 = 0.77, p < 0.05) has been identified. The most sensitive parameters of photosynthesis, which can be used to predict resistance to moisture deficiency, were Y(II) and NPQ.