In semi-arid regions, almond orchards face significant challenges from climate change, necessitating sustainable irrigation strategies and advanced monitoring methods to enhance water use efficiency. This study investigated key ecophysiological variables to identify the most relevant physiological variables for future threshold definition in irrigation management (Prunus dulcis Mill., cv. Guara). The experiment included three irrigation treatments during the kernel-filling phase: 100 % (CTRL), 80 % (MRDI), and 60 % (SRDI) of crop evapotranspiration (ETc), with full irrigation provided during fruit growth and post-harvest periods. Key physiological variables, including stomatal conductance (gs), stem water potential (Ψs), photosynthesis (Pn), and PKO/KC (reflecting electron flux from PSII and RuBisCO carboxylative activity) were monitored weekly during a single growing season and showed clear seasonal dynamics: peaking during fruit growth, declining during kernel filling, and partially recovering post-harvest. During kernel filling, MRDI values for gs, Ψs, Pn, and PKO/KC were lower than CTRL but higher than SRDI. Strong correlations were observed between Pn and gs, PKO/KC, as well as between gs and Ψs. Pn, gs, and PKO/KC were significantly influenced by air temperature and vapor pressure deficit, whereas Ψs was more closely linked to soil water content. Yield, fruit fresh weight, and seed dry weight were similar across treatments, although SRDI produced a higher proportion of tight-hull fruits. Variables such as gs, Ψs, Pn, and PKO/KC effectively captured plant water status and microclimatic variations. The MRDI treatment achieved significant water savings while maintaining yield and fruit quality, suggesting that Ψs, Pn, gs, and PKO/KC are reliable indicators of plant performance under reduced irrigation, with potential to inform the development of simplified, decision-support tools for growers. Advances in sensor technologies could facilitate the adoption of plant-based irrigation thresholds, improving water resource efficiency.

Scouting ecophysiological variables to monitor regulated deficit irrigation in almond

Conti, Leonardo;Gaeta, Liliana;D'Onghia, Anna;Montesano, Francesco Fabiano;Losciale, Pasquale
2025-01-01

Abstract

In semi-arid regions, almond orchards face significant challenges from climate change, necessitating sustainable irrigation strategies and advanced monitoring methods to enhance water use efficiency. This study investigated key ecophysiological variables to identify the most relevant physiological variables for future threshold definition in irrigation management (Prunus dulcis Mill., cv. Guara). The experiment included three irrigation treatments during the kernel-filling phase: 100 % (CTRL), 80 % (MRDI), and 60 % (SRDI) of crop evapotranspiration (ETc), with full irrigation provided during fruit growth and post-harvest periods. Key physiological variables, including stomatal conductance (gs), stem water potential (Ψs), photosynthesis (Pn), and PKO/KC (reflecting electron flux from PSII and RuBisCO carboxylative activity) were monitored weekly during a single growing season and showed clear seasonal dynamics: peaking during fruit growth, declining during kernel filling, and partially recovering post-harvest. During kernel filling, MRDI values for gs, Ψs, Pn, and PKO/KC were lower than CTRL but higher than SRDI. Strong correlations were observed between Pn and gs, PKO/KC, as well as between gs and Ψs. Pn, gs, and PKO/KC were significantly influenced by air temperature and vapor pressure deficit, whereas Ψs was more closely linked to soil water content. Yield, fruit fresh weight, and seed dry weight were similar across treatments, although SRDI produced a higher proportion of tight-hull fruits. Variables such as gs, Ψs, Pn, and PKO/KC effectively captured plant water status and microclimatic variations. The MRDI treatment achieved significant water savings while maintaining yield and fruit quality, suggesting that Ψs, Pn, gs, and PKO/KC are reliable indicators of plant performance under reduced irrigation, with potential to inform the development of simplified, decision-support tools for growers. Advances in sensor technologies could facilitate the adoption of plant-based irrigation thresholds, improving water resource efficiency.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/551720
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