Predicting pre-harvest sprouting susceptibility in barley: Looking for “sensitivity windows” to temperature throughout grain filling in various commercial cultivars

Pre-harvest sprouting (PHS) is common in cereals that lack grain dormancy if maturing grain is exposed to rain. This phenomenon leads to immediate loss of seed viability, and since the malting process requires germination, its occurrence is highly undesirable in malting barley crops. Dormancy release rate is genetically and environmentally controlled. We evaluated the effect of temperature during grain filling on the dormancy release pattern (and then on the PHS susceptibility) of grains from five malting barley ( Hordeum vulgare L.) cultivars widely sown in Argentina, with the aim of predicting PHS susceptibility of a barley crop from easy-to-gather data. Barley cultivars (Quilmes Ayelén, Q. Palomar, Q. Painé, B1215 and Scarlett) were sown on different dates over a 3-year period for generating variability in the thermal environment during grain filling. The period from pollination to physiological maturity (PM) was adjusted to a thermal time (TT) scale, which was then arbitrarily divided into 50 °C d intervals. Mean air temperature within each interval and for the whole filling period was calculated for the different sowing dates. Dormancy release pattern was followed by determining a weighed germination index (GI) throughout grain filling and maturation. We sought a linear relationship between temperature during grain filling and GI at some moment after PM. For all barley cultivars, except B1215, a significant ( p < 0.001) and positive correlation was found between the GI of grains with 10–20% moisture content (fresh basis) and mean temperature within TT intervals located at the last stages of seed development. Then, simply temperature-based models for predicting crop PHS susceptibility were generated for each barley cultivar. Moreover, we intended a single, universal prediction model constructed with data from all cultivars. Two general forms were proposed, but the relationships were slightly less tight when each barley cultivar model was used. A preliminary validation for each cultivar model was done for three genotypes with independent data from four sites of the major barley production area in Argentina. When comparing experimental and field data regressions we did not find significant differences in slope for any cultivar ( p > 0.25). However, most of the observed GIs were higher than predicted. This upwards displacement of GI–temperature relationship suggests the role of other environmental factors (i.e. water and soil N availability, day length),