This assessment reveals genetic variability in root traits and water use efficiency among graft combinations, suggesting effective drought mitigation strategies.
Coffee (Coffea arabica) is a major global commodity, yet its productivity is increasingly challenged by water scarcity, especially in rainfed cultivation systems. This study investigated the physiological and morphological responses of 16 grafted coffee combinations and their respective parental lines under 70% water deficit conditions using a rain-out shelter over three consecutive years (2015–2018). Significant genetic variability was observed in root traits, total dry matter (TDM) and water use efficiency (WUE). Among the grafts, S.4538/Sln.6 recorded the highest TDM (112.8 g plant⁻¹), root biomass (27.0 g plant⁻¹) and shoot biomass (44.9 g plant⁻¹). The highest root-to-shoot ratio was found in Sln.6/Sln.10 (1.05), while S.4538/Sln.6 showed the lowest (0.60), indicating diverse carbon allocation patterns under stress.Water use efficiency varied significantly among combinations, with Sln.11/Sln.11 achieving the maximum WUE (5.84 g kg⁻¹), followed closely by Sln.11/Sln.6 (5.82 g kg⁻¹), Sln.10/Sln.6 (5.73 g kg⁻¹) andTaffarikela/Sln.6 (5.61 g kg⁻¹). The highest Net Assimilation Rate (NAR) and Mean Transpiration Rate (MTR) were recorded in Taffarikela/C x R (4.39 g dm⁻² day⁻¹ and 23.27 mg dm⁻², respectively). Z- score-based classification further revealed that grafts like S.4538/Sln.6, Sln.6/Taffarikela and Sln.10/Sln.6 consistently combined high WUE with strong root development. A negative correlation between MTR and WUE (r = –0.68) confirmed that efficient stomatal regulation contributed to water-saving strategies under drought.These findings underscore the potential of grafting drought-sensitive but agronomically elite arabica lines onto physiologically resilient rootstocks. Such combinations offer a dual advantage of improved water acquisition and utilization, providing a viable strategy for enhancing coffee resilience and yield stability under increasing climatic variability.
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Patil et al. (2025) studied this question.
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