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Physiological responses of apricot and peach cultivars under progressive water shortage: Different crop signals for anisohydric and isohydric behaviours

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  • Losciale, Pasquale
  • Gaeta, Liliana
  • Corsi, Mariadomenica
  • Galeone, Ciro
  • Tarricone, Luigi
  • Leogrande, Rita
  • Stellacci, Anna Maria

Abstract

The knowledge about the behaviour of different fruit tree species when subjected to water shortage is pivotal to pair correctly the species with the environment, as well as to choose the most reliable index for monitoring the plant water status. Net photosynthesis (Pn) and stomatal conductance (gs) are considered some of the most reliable variables describing the plant water status, functionality and potential productivity, but their measurement are actually time consuming, complex and expensive. The aims of the present study were to investigate the effect of a progressive water stress on leaf functioning and plant water status of two stone fruit trees species; to study the water relations within the Soil-Plant-Atmosphere Continuum; to assess a pool of indices for estimating Pn and gs by means of other variables quick to be measured, potentially through less expensive and user-friendly sensors. The trial was carried out on an early ripening apricot variety (Prunus armeniaca L. cv. Primius) and on a late ripening peach variety (Prunus persica (L.) Batsch cv. Calred) subjected to progressive dry down. Trees were monitored for stem water potential, leaf temperature, chlorophyl fluorescence, Pn and gs. “Primius” and “Calred” behaved as near anisohydric and near-isohydric plants, respectively. In “Primius” Pn and gs were more affected by soil water content than vapour pressure deficit (VPD) and the opposite occurred in “Calred”, suggesting a different approach to be used for managing water in the two cultivars. Chlorophyll fluorescence variables and leaf to air temperature difference (ΔT), combined properly by means of stepwise multiple regression analysis approach, were selected as good predictors of Pn for both the species. ΔT and VPD were selected to estimate gs, using the same approach. The prediction performance of the models resulted good suggesting their possible use for driving irrigation in a more sustainable and plant-based way.

Suggested Citation

  • Losciale, Pasquale & Gaeta, Liliana & Corsi, Mariadomenica & Galeone, Ciro & Tarricone, Luigi & Leogrande, Rita & Stellacci, Anna Maria, 2023. "Physiological responses of apricot and peach cultivars under progressive water shortage: Different crop signals for anisohydric and isohydric behaviours," Agricultural Water Management, Elsevier, vol. 286(C).
    • Handle: RePEc:eee:agiwat:v:286:y:2023:i:c:s0378377423002494
    DOI: 10.1016/j.agwat.2023.108384
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    References listed on IDEAS

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    1. Levidow, Les & Zaccaria, Daniele & Maia, Rodrigo & Vivas, Eduardo & Todorovic, Mladen & Scardigno, Alessandra, 2014. "Improving water-efficient irrigation: Prospects and difficulties of innovative practices," Agricultural Water Management, Elsevier, vol. 146(C), pages 84-94.
    2. Soulis, Konstantinos X. & Elmaloglou, Stamatios & Dercas, Nicholas, 2015. "Investigating the effects of soil moisture sensors positioning and accuracy on soil moisture based drip irrigation scheduling systems," Agricultural Water Management, Elsevier, vol. 148(C), pages 258-268.
    3. Cardenas-Lailhacar, B. & Dukes, M.D., 2010. "Precision of soil moisture sensor irrigation controllers under field conditions," Agricultural Water Management, Elsevier, vol. 97(5), pages 666-672, May.
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