Salinity Stress Elicits Genotype‐Dependent Responses of Turf and Forage Performance and Seasonal Dormancy Across Multiple Harvests in Orchardgrass ( Dactylis glomerata L.)

Limited water availability coupled with increasing soil salinity poses a major challenge to sustainable turfgrass growth and performance. Dactylis glomerata L. (orchardgrass) is a widely distributed cool‐season perennial grass traditionally valued for forage production, with increasing interest in its potential as an alternative low‐input turf‐type species for water‐ and salt‐limited environments. However, despite its adaptability and stress tolerance, information on the salinity resilience and turf‐related performance of orchardgrass genotypes under field conditions remains limited. To address this gap, a worldwide collection of orchardgrass genotypes was evaluated for salinity tolerance, forage yield, agro‐morphological traits and turf quality. Field assessments were conducted across five harvests during the 2022 and 2023 growing seasons under both normal and saline stress conditions, providing comprehensive insights into their morphological and agronomic responses. On average, salinity reduced dry forage yield, colour, ground coverage and turf density by 53.39%, 47.90%, 52.49% and 37.35%, respectively. Considerable genetic variation was observed for the measured traits under both conditions. Broad‐sense heritability ranged from 0.29 to 0.67 under normal irrigation and from 0.35 to 0.54 under salinity stress. Under both salinity conditions, the summer harvest produced the lowest forage yield and turf quality compared with spring and autumn cuts, consistent with seasonal growth suppression and possible partial summer dormancy with considerable variation among genotypes in the panel. Positive correlations among crown diameter, plant height, leaf length, colour, coverage, density and stress tolerance index with forage yield suggest the potential for simultaneous selection targeting both forage productivity and turf quality within this germplasm. Multivariate analysis enabled the identification of suitable genotypes offering promising candidates for future breeding programmes aimed at developing new cultivars.