Abstract
Midday stem water potential (SWP) is rapidly becoming adopted as a standard tool for plant-based irrigation management in many woody perennial crops. A reference or “baseline” SWP has been used in some crops (almond, prune, grape, and walnut) to account for the climatic influence of air vapor pressure deficit (VPD) on SWP under non-limiting soil moisture conditions. The baseline can be determined empirically for field trees maintained under such non-limiting conditions, but such conditions are difficult to achieve for an entire season. We present the results of an alternative survey-based approach, using a large set of SWP and VPD data collected over multiple years, from irrigation experiments in olive orchards located in multiple countries [Spain, United States (California), Italy, and Argentina]. The relation of SWP to midday VPD across the entire data set was consistent with an upper limit SWP which declined with VPD, with the upper limit being similar to that found in Prunus. A best fit linear regression estimate for this upper limit (baseline) was found by selecting the maximum R2 and minimum probability for various upper fractions of the SWP/VPD relation. In addition to being surprisingly similar to the Prunus baseline, the olive baseline was also similar (within 0.1 MPa) to a recently published mechanistic olive soil-plant-atmosphere-continuum (SPAC) model for “super high density” orchard systems. Despite similarities in the baseline, the overall physiological range of SWP exhibited by olive extends to about −8 MPa, compared to about −4 MPa for economically producing almond. This may indicate that, despite species differences in physiological responses to low water availability (drought), there may be convergent adaptations/acclimations across species to high levels of water availability. Similar to its use in other crops, the olive baseline will enable more accurate and reproducible plant-based irrigation management for both full and deficit irrigation practices, and we present tentative SWP guidelines for this purpose.
Introduction
Crop productivity is closely linked to crop water use (e.g., ) and improving the efficiency of water use in agriculture has been an ongoing focus of research worldwide (e.g., ). For some woody perennial crops, reducing or eliminating irrigation during specific periods of development (e.g., ) has been shown to produce economically beneficial effects, such as an improved fruit drying ratio in prunes (), decreased fruit drop in peach (), and increased control of hull rot disease in almonds (). Hence, these crops may be good candidates for deficit water management strategies to increase overall water use efficiency. In woody perennial crops, however, the effect of any given deficit irrigation regime can depend strongly on soil conditions (e.g., ). Hence, the plant-based approach of midday stem water potential (SWP; ) has become a widely accepted tool for deficit irrigation management.
Olive (Olea europaea L.) is considered to be a drought resistant species () and also exhibits a wide range of SWP under cultivated conditions. However, olive also exhibits differential sensitivity of yield to SWP at different periods of crop development. Olive trees are an evergreen species most often grown in Mediterranean climate regions with shoot growth and bloom occurring during spring in mature orchards. Fruit set occurs as evaporative demand increases, with fruit growth and oil accumulation occurring under fairly high evaporative demand conditions in the summer and fall, and with harvest varying from the end of summer to early winter. In addition to occurring under different environmental conditions, all of these processes exhibit different levels of sensitivity to low SWP. Shoot growth and flowering are very sensitive to water limited conditions, and while these processes normally occur at a time in the season when soil water is not limiting, supplemental irrigation may be needed under drought conditions or in locations with delayed growth cycles (; ). SWP of around −2 MPa reduced fruit size due to reduced endocarp growth (; ) with more severe SWP deficits (−4 MPa at predawn) affecting bud development and reducing next season bloom (). Once endocarp growth finishes, the number of fruits is relatively constant and pit hardening occurs (). After this phase, the sensitivity of yield to water stress is reduced (; ; ; ; ; ). Even under very severe water stress conditions (SWP below −5 MPa) yield may only be slightly reduced, particularly if there is an adequate recovery in SWP before harvest (; ; ). Oil accumulation prior to harvest is usually coincident with autumn rains under Mediterranean climate conditions, but several authors have suggested that moderate water stress does not substantially reduce oil accumulation (; ; ) and improves oil extractability. Reduction in oil accumulation is likely to occur only with SWP values consistently below −2 MPa (). Postharvest irrigation is not commonly studied, but reported no significant differences in next season yield over a wide range of postharvest water stress conditions.
The above values provide some guidance for an allowable lower range of SWP, but from a practical as well as scientific standpoint it is important to understand this physiological range in the context of both upper and lower limits. were the first to propose SWP as a reliable physiological indicator of water stress, in part because a stable relation over much of the growing season was found between SWP and vapor pressure deficit (VPD) under non-limiting soil moisture conditions. This relation enabled a reliable prediction of SWP for a “fully irrigated state or condition” (i.e., from an irrigation perspective). In essentially all previous and many current irrigation studies, the highest irrigation level is simply assumed to be non-water-limiting. However, localized water application systems (e.g., micro-irrigation) create zones of wet and dry soil, and, particularly for woody perennials, there are typically roots present in both zones throughout the season. If roots in dry soil influence overall plant water relations, then irrigation at 100% of crop evapotranspiration (ETc) in the wetted soil zones may not establish a physiologically non-soil-water-limited condition for the plant. To the authors knowledge, other than the study in Prunus, there has only been one study in olive () in which the entire soil volume was maintained at a high moisture content over the growing season. measured leaf rather than SWP in olive trees, but also did not report any relation of water potential to VPD. A number of studies in olive have found a linear relation of SWP to VPD (; , ; ), indicating that a relationship exists, but may be influenced by a number of factors, potentially including unintended effects of dry soil areas.
Based on the principle that the majority of water movement in soils and plants is driven primarily by differences in water potential (e.g., ), it is expected that SWP will depend on a large number of independent physical and biological factors such as soil, root, and stem hydraulic properties as well as plant transpiration as determined by stomatal and atmospheric conditions. Hence, it is not clear that an upper limit to SWP should exist, that it should be largely independent of soil and tree conditions, and that it should have a reproducible relation simply to VPD. However, the experimentally determined upper limit reported by produced a robust estimate for an upper limit of SWP that was supported by further studies in both prune () and almond () orchards. The objective of the current study in olive was to determine if a large survey of SWP and VPD values from olive orchards in multiple countries might produce an upper limit reference SWP baseline.
Materials and Methods
Survey Sites and Measurements
Much of the data used for this survey study was obtained from previous publications, and Table 1 summarizes the locations and additional characteristics of each of the survey sites. All orchards were managed commercially and drip irrigated. The multi-year and multi-location studies provided a large data set with variable ranges in VPD and SWP. References are listed in Table 1 where further information on particular sites may be obtained. Five different table (Manzanillo, Noceralla de Belice, and Olivo di Mandanici) and oil (Arbequina and Cornicabra) cultivars were used in these experiments in Argentina, Italy, Spain, and United States (California). Most data were from Arbequina and Manzanillo cvs but in different locations and management systems. Orchard age ranged from 2 to more than 10 years-old, but most orchards would be considered mature based on yield. Only the youngest in Coria del Rio (Spain) and Sciacca (Italy) were orchards with less yield than mature conditions and could be considered young. Tree density varied from high density (HD; around 300–350 trees per ha) to super high density (SHD), hedgerow orchards (>1000 trees per ha).
TABLE 1
| Country | Site | References | GPS | Year | CV | AGE | Soil | Density | Use |
| Argentina | Aimogasta (La Rioja) | 28°33′S, 66°49′W | 2005–2007 | Manzanillo | 6 | Loamy sand | 8 × 4 | Table | |
| Argentina | Aimogasta (La Rioja) | 28°35′S, 66°42′W | 2009–2010 | Manzanillo | 10 | Loamy sand | 8 × 4 | Table | |
| Argentina | Chilecito (La Rioja) | Unpublished | 29°09′S, 67°26′W | 2017–2018 | Arbequina | 4 | Gravelly sand | 4 × 1.5 | Oil |
| Spain | Ciudad Real | Unpublished | 39°N, 5°6′W | 2012–2015 | Cornicabra | 14 | Shallow clay loam | 7 × 4.76 | Oil |
| Spain | Coria del Rio (Seville) | 37°N, 6°3′W | 2014–2016 | Manzanillo | 43 | Sandy loam | 7 × 5 | Table | |
| Spain | Dos Hermanas (Seville) | 37°25′N,5°95′W | 2015–2017 | Manzanillo | 30 | Sandy loam | 7 × 4 | Table | |
| Spain | Carmona (Seville) | Unpublished | 37.5°N, 5.7°W | 2017–2019 | Arbequina | 11 | Sandy loam | 4 × 1.5 | Oil |
| Spain | Coria del Rio (Seville) | Unpublished | 37°N, 6°3′W | 2015 | Manzanillo | 2 | Sandy loam | 4 × 1.5 | Table |
| Italy | Marsala | 37°46′28″N, 12°30′19″E | 2008–2009 | Arbequina | 4 | Sandy clay loam | 1.5 × 3.5 | Oil | |
| Italy | Sciacca | , | 37°32′N, 13°02′E | 2014–2015 | Nocellara del Belice and Olivo di Mandanici | 3–4 | Sandy clay loam | 5 × 3, 5 × 2, 7 × 7 | Oil, table |
| United States (CA) | Genoa | Unpublished | 39°54′16.04″N, 122°17′14.20″W | 2011 | Manzanillo | >10 | Loam, gravelly loam | 7.7 × 3.6 | Table |
| United States (CA) | Haro | Unpublished | 39°49′N, 122°23′W | 2011 | Manzanillo | >10 | Gravelly loam, sandy loam | 9.0 × 5.8 | Table |
| United States (CA) | Nielsen | Unpublished | 39°44′59.36″N, 122°8′51.97″W | 2009, 2011 | Manzanillo | 6, 8 | Sandy loam | 3.6 × 5.5 | Table |
Description of the sites used in the survey.
Stem water potential was typically measured over multiple years as part of irrigation experiments. SWP was determined on individual trees as described previously (). Briefly, a shaded leaf or short stem located near the main trunk within the tree canopy was covered with a reflective plastic bag for longer than 10 min (typically 1–2 h) to allow equilibration with the water potential of the stem at the point of attachment. A Scholander-type pressure chamber was then used to measure SWP. Olive trees are a Mediterranean species, typically growing under hot and dry summer and relatively warm winter conditions. However, even in these regions, climatic conditions can be very different. For instance, the experiments in Ciudad Real (central Spain, ) are in a production zone with a shorter and cooler summer than that in Dos Hermanas (south Spain, ). In all experiments, hourly climatic data were measured with automated stations either at the experimental plots, or in nearby locations with the same environment as the experimental plots. Hourly, mid-afternoon climatic measurements were used to calculate hourly air VPD () that coincided with the period of SWP measurement.
Data Assumptions and Analysis
Based on the hypothesis that there may be a practical upper limit to SWP at a given level of VPD for trees under non-soil-water-limited conditions (i.e., the “baseline” relation of ), a total of 837 (SWP, VPD) values over all sites, years, and experimental treatments, were divided into groups based on 0.5 kPa classes of VPD. Assuming that each class would contain SWP values that were at or near the upper limit (i.e., if rain or irrigation had resulted in non-soil-water-limited conditions for that site and date) as well as SWP values below this limit, a range of uppermost (least negative) fractions (0.02–0.16) of SWP and the corresponding VPD values were averaged, and the average points used in a regression analysis of SWP on VPD. Since there was only one average (SWP, VPD) point per VPD class, each fraction contained the same number of (SWP, VPD) points, so the uppermost fraction which exhibited the highest regression R2 and lowest probability was used as the best fit estimate of the non-water-limited (“baseline”) relation of SWP to VPD. All statistical analyses were conducted in SAS 9.4 (SAS institute, Cary, NC, United States).
Comparison to Data From the Literature
First, the baseline estimate for olive was compared to that found in prune and almond (). Second, a set of SWP and VPD values obtained from a multi-compartment hydraulic model for olive under simulated non-soil-water-limiting conditions for two contrasting planting densities () was kindly provided by the authors. The relation of SWP to VPD for this set of data was determined and compared to the baseline estimate for olive. Lastly, previously published data of leaf conductance (Gs) to SWP in almond () was also compared to data in olive as reported by and . The raw data for each was kindly provided by the authors and fitted using a smoothed spline function (Proc Transreg, SAS 9.4) in order to avoid any a priori assumptions regarding the functional form of the (Gs, SWP) relation.
Results
Relation of Stem Water Potential to Vapor Pressure Deficit
Olive SWP values from the entire data set varied over a wide range (−0.5 to about −6 MPa), but the highest (least negative) values exhibited a pattern of decline with increasing VPD that was similar to the previously reported Prunus baseline (; Figure 1). Overall, SWP values in Spain tended to be closest to the Prunus baseline, but some SWP values from other countries were also close to this baseline. The maximum midday air VPD in this data set was about 6.5 kPa, which allowed for a total of 13 groups of 0.5 kPa classes in VPD, having a mode of 2.5 kPa (inset, Figure 1). Because there were relatively few SWP values in each VPD group below 1.5 and above 3.5 kPa (inset, Figure 1), in order to obtain a comparable upper fraction sample from every group, only data from the five central VPD groups (1.5–3.5 kPa) were further analyzed. A regression analysis of average SWP on average VPD for the upper 0.02–0.16 fractions (2–16%) of SWP values exhibited a relatively linear decrease in SWP with increasing VPD regardless of the fraction selected (Figure 2). As expected, selecting greater fractions of the upper SWP values in each VPD group resulted in a progressive decrease in the regression intercept, but no clear trend was apparent in the regression slope (Figure 2). For all fractions from 0.02 to 0.16, the regression R2 was maximum and the P-value minimum for fractions of 0.07 and 0.08, with a clear decline in R2 and increase in P-value as fractions increased above about 0.09 (Figure 3). It should be noted that these R2 and P-values are only used for purposes of comparison, and even though the total number of observations increased with higher fractions, since the regression analysis was performed on the mean (SWP, VPD) values, the number of points (5) for each regression was constant (as shown in Figure 2). Since a decrease in the regression intercept was expected as the fraction of upper SWP values increased, the relation corresponding to an upper fraction of 0.07 was considered the most appropriate estimate for a linear upper limit of olive SWP to air VPD. The slope and intercept for this relation (−0.18 and −0.34, Figure 2), were similar to those reported for Prunus (−0.12 and −0.41, respectively, Figure 1).
FIGURE 1
FIGURE 2
FIGURE 3
Comparison to Model Data
The soil-plant-atmosphere-continuum (SPAC) model of , which was not based on an explicit link between SWP and VPD, exhibited a clear negative overall relation between SWP and VPD under non-soil-water-limiting conditions, with a similar shape for both HD and SHD orchard conditions (Figure 4). The relation of SWP to VPD was well fit by a smoothed spline function, which involves no a priori assumption about the shape of the relation but cannot be easily parameterized, and equally well fit by an exponential decay to a linear dependence of SWP on VPD for both HD and SHD (Figure 4). The residuals to the exponential + linear fit for HD and SHD exhibited a relatively low variation (0.038–0.047 MPa) and a normal distribution (Shapiro–Wilk P = 0.37 and 0.74), respectively, and the slope (change in SWP per 1 kPa change in VPD) of the linear component for SHD (−0.13, m in Table 2) was in the same range as that for the strictly linear olive (−0.18, Figure 2) and Prunus (−0.12, Figure 1) baselines. One conceptual advantage of the model over a strictly linear model is that it allows SWP values to approach 0 as VPD’s approach 0, which would be expected for non-soil-water-limited conditions. The relation of SWP to various temperatures and relative humidities for the exponential + linear fit of the SHD model is presented in Table 3.
FIGURE 4
TABLE 2
| Density | Equation parameters | Fit statistics | |||||
| A | B | C | m | TSS | Model SS | Fit | |
| HD | 0.556 | 2.47 | 0.0266 | −0.096 | 6.81 | 6.59 | 0.97 |
| SHD | 0.613 | 1.37 | 0.0685 | −0.13 | 9.57 | 9.25 | 0.97 |
Parameters and fit statistics for combined linear + exponential fit shown in Figure 4.
.
TABLE 3
| Air temperature (°C) | Air relative humidity (%) | |||||
| 10 | 20 | 30 | 40 | 50 | 60 | |
| 5 | −0.30 | −0.27 | −0.23 | −0.19 | −0.16 | −0.11 |
| 10 | −0.41 | −0.37 | −0.33 | −0.28 | −0.23 | −0.18 |
| 15 | −0.54 | −0.50 | −0.44 | −0.39 | −0.33 | −0.26 |
| 20 | −0.69 | −0.63 | −0.57 | −0.51 | −0.44 | −0.36 |
| 25 | −0.84 | −0.78 | −0.71 | −0.64 | −0.56 | −0.47 |
| 30 | −1.00 | −0.93 | −0.86 | −0.78 | −0.69 | −0.59 |
| 35 | −1.19 | −1.11 | −1.02 | −0.93 | −0.83 | −0.72 |
| 40 | −1.40 | −1.30 | −1.20 | −1.10 | −0.98 | −0.86 |
Baseline SWP (MPa) for various combinations of air temperature and relative humidity, based on the equation and parameters for SHD density shown in Table 2.
The data used for the olive survey included a wide range of planting densities (Table 1), but the linear estimate for the baseline was much closer to the SHD than to the HD model (Figure 4). All individual survey values that contributed to the upper 0.07 fraction for the linear estimate were categorized based on orchard density, and the least squares mean SWP (i.e., SHD model adjusted mean) for each density was compared (Figure 5). There were no statistically significant differences in the adjusted SWP means from different densities (ANCOVA not shown) but the trend was for an increase in SWP at higher densities (Figure 5), rather than the decrease predicted by the
FIGURE 5

Relation of SWP to VPD for all individual points of the upper 0.07 fraction, classified into groups representing different orchard tree densities, and the adjusted SWP means corresponding to each group. Also shown for reference is the linear/exponential fit for the
Within the context of the overall range in SWP exhibited by olive under field conditions, the difference between the empirical linear fit and the SHD model fit can be considered relatively minor (Figure 6), with both being surprisingly close to the Prunus linear relation (Figure 1). Based on data from the literature, a similar overall relation of Gs to SWP in almond and olive was also found for the upper range of SWP, with close to a linear increase in Gs from about −1.1 to −0.5 MPa in almond and a similar linear increase in Gs from about −1.6 to −0.9 MPa in olive (Figure 7). However, a clear difference between the species was apparent in the lower range of SWP, with almond exhibiting a Gs close to 0 by about −3 MPa, whereas olive maintaining a measurable Gs to about −7 MPa (Figure 7).
FIGURE 6

Pooled relation of SWP to midday VPD for all countries, as in Figure 2, showing the combined linear/exponential relation for the SHD data of
FIGURE 7

Relation of leaf conductance to SWP for almond reported by
Discussion
As originally proposed (
Independently of its use as a baseline index of soil water limitations, SWP itself should be a measure of physiological water limitations, although this assumption has not been without controversy (e.g.,
In woody perennials, crop yield and quality are the result of growth, developmental, and biochemical processes that occur over relatively long time frames (seasonal or multi-seasonal). Hence, appropriate target or threshold SWP levels for irrigation management in these crops will depend on which processes contribute to yield and quality at which times, as well as the sensitivity of each process to deficit levels of SWP. Table 4 summarizes the range of SWP for regulated deficit irrigation in olive and the observed crop response during different phenological stages. These threshold values may serve as an approximate guide, but it is recognized that the duration of a given water stress is also likely to be important (
TABLE 4
| Phenological stage | Response | SWP range | References |
| PHASE I | |||
| Vegetative growth | Maximum growth | At or near baseline, (> about −1 MPa) | |
| Significant growth reduction | −1.0 to −1.2 MPa | ||
| Strong growth reduction | −2 Mpa | ||
| Flower/inflorescence development | Maximum inflorescence development and flowering | At or near baseline, (> about −1 MPa) | |
| Significant reduction in flowers and inflorescences | −2 MPa | ||
| Fruit set/endocarp growth | Maximum fruit set | At or near baseline, (> about −1 MPa) | |
| Little or no effect on endocarp growth | −2 MPa | ||
| Reduction in endocarp growth and fruit size at harvest | −3 MPa | ||
| Reduction in endocarp growth and fruit size at harvest; possible effect on the flower induction of next season | Lower than −3 MPa; −4 MPa (predawn stem water potential values) | ||
| PHASE II | |||
| Endocarp schlerification (pit hardening) | No significant yield reduction with rehydration next phase. Negligible fruit drop. | −2 to −3 MPa | |
| Significant yield reduction. Fruit drop. | −3 to −4 MPa | ||
| Fruit shrinkage. Permanent injury to table olives. | Below −4 MPa | ||
| PHASE III | |||
| Fruit growth due to cell expansion (table and oil olives) | No significant yield reduction. No significantly lower fruit size. | At or near baseline, (> about −1.5 MPa) | |
| Oil quantity and quality (oil olives) | No significant effect on oil accumulation | >−2 MPa | |
| Increase in phenolic compounds | Linear increase from −2 to −3 MPa | ||
| Increase in oil extractability | −3 MPa | ||
| Decrease phenolic compounds | Below −3 MPa | ||
Guidelines for the use of SWP for deficit irrigation management in olive trees.
Phenological phases are based on
Although differences may occur by region, the irrigation season is commonly divided into three phases in mature orchards. Phase I is the most water-sensitive part of the season because shoot growth and flower development occur. For both processes, irrigation scheduling should be performed such that SWP is near the baseline. Even under such conditions, vegetative growth may not be optimal due to the high water stress sensitivity of growth to reductions in SWP (
Endocarp sclerification occurs during Phase II (
During the last phase, fruit growth occurs principally due to cell expansion and oil accumulation. In this period, different irrigation strategies for table and oil cultivars are necessary, especially if harvesting is done for green table olives. Fruit size is one of the main quality features of table olives and optimum water status is desirable if previous deficit irrigation has been applied (
Conclusion
Across multiple sites and years, an upper limit of olive midday SWP, presumably corresponding to non-limiting soil moisture (i.e., baseline) conditions in the field, was found to have a negative linear relation with midday air VPD for VPD’s above about 1.5 kPa. This relation was very close (within 0.1 MPa) to that of a recently published olive hydraulic model for non-limiting soil moisture and VPD’s above about 2 kPa. This relation was also remarkably similar across the entire range of VPD’s (0 to 6 kPa) to the SWP baseline in Prunus. This similarity between Prunus and olive, despite many fundamental physiological differences (e.g., Prunus being deciduous and olive being evergreen), may indicate a convergence in woody perennial plant adaptations/acclimations that impact the balance between plant water demand on one hand and soil water supply on the other, at least under high levels of soil water availability. The proposed baseline should serve as a reference for olive SWP under non-limiting soil moisture conditions, and it may be important for irrigation management to maintain trees near this reference during stress sensitive periods (e.g., spring). Tentative SWP guidelines for irrigation management during potentially less stress sensitive periods are also presented.
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Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
KS, AM, GM, MC, and PS substantially contributed to the conception and design of the study. KS wrote the manuscript with assistance from AM, GM, and PS. KS analyzed the full data set from the four countries. DP-L, MM-P, TC, FPM, LMA, LM, RR, and AF were all involved in field measurements, data processing, and supervision of these tasks in the different countries. All authors contributed to the article and approved the submitted version.
Funding
In addition to the authors institutions, this research was supported by the Olive Oil Commission of California and the California Olive Committee.
Acknowledgments
We would like to thank Omar García Tejera for sharing his model output of SWP and VPD. Samuel Ortega-Far as kindly provided leaf conductance data for olive.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
Agüero-AlcarasL. M.RousseauxM. C.SearlesP. S. (2021). Yield and water productivity responses of olive trees (cv Manzanilla) to postharvest deficit irrigation in a non-Mediterranean climate.Agric. Water Manag.245:106562. 10.1016/j.agwat.2020.106562
2
Ahumada-OrellanaL. E.Ortega-FariasS.SearlesP. S.RetamalesJ. B. (2017). Yield and water productivity responses to irrigation cut-off strategies after fruit set using stem water potential thresholds in a super-high density olive orchard.Front. Plant Sci.8:1280. 10.3389/fpls.2017.01280
3
Ahumada-OrellanaL.Ortega-FaríasS.Poblete-EcheverríaC.SearlesP. S. (2019). Estimation of stomatal conductance and stem water potential threshold values for water stress in olive trees (cv. Arbequina).Irrig. Sci.37461–467. 10.1007/s00271-019-00623-9
4
Ben-GalA.RonY.YermiyahuU.ZiporiI.NaoumS.DagA. (2021). Evaluation of regulated deficit irrigation strategies for oil olives: a case study for two modern Israeli cultivars.Agric. Water Manag.245:106577. 10.1016/j.agwat.2020.106577
5
Beyá-MarshallV.HerreraJ.FichetT.TrestaconteE. R.KremerC. (2018). The effct of water status on productive and flowering variables in young “Arbequina” olive trees under limited irrigation water availability in a semiarid region of Chile.Hortic. Environ. Biotechnol.59815–826.
6
BradfordK. J.HsiaoT. C. (1982). “Physiological responses to moderate water Stress,” in Encyclopedia of Plant Physiology, Physiological Plant Ecology B. Water Relations and Photosynthetic Productivity, edsLangeO. L.NobelP. S.OsmondC. B.ZieglerH. (Berlin: Springer Verlag).
7
ChalmersD. J.MitchellP. D.van HeekL. (1981). Control of peach tree growth and productivity by regulated water supply, tree density, and summer pruning.J. Am. Soc. Hortic. Sci.106307–312.
8
ConnorD. J. (2005). Adaptation of olive (Olea europaea L.) to water-limited environments.Aust. J. Agric. Res.561181–1189.
9
CorellM.Martín-PalomoM. J.GirónI.AndreuL.GalindoA.CentenoA.et al (2020). Stem water potential-based regulated deficit irrigation scheduling for olive table trees.Agric. Water Manag.242:106418. 10.1016/j.agwat.2020.106418
10
CorellM.Pérez-LópezD.Martín-PalomoM. J.CentenoA.GirónI.GalindoA.et al (2016). Comparison of the water potential baseline in different locations: usefulness for irrigation scheduling of olive orchards.Agric. Water Manag.177308–316.
11
Correa-TedescoG.RousseauxM. C.SearlesP. S. (2010). Plant growth and yield responses in olive (Olea europaea) to different irrigation levels in an arid region of Argentina.Agric. Water Manag.971829–1837. 10.1016/j.agwat.2010.06.020
12
FernándezJ. E.Perez-MartinA.Torres-RuizJ. M.CuevasM. V.Rodriguez-DominguezC. M.Elsayed-FaragS.et al (2013). A regulated deficit irrigation strategy for hedgerow olive orchards with high plant density.Plant Soil372279–295. 10.1002/jsfa.7828
13
FernándezJ. E.Torres-RuizJ. M.Diaz-EspejoA.MonteroA.AlvarezR.JimenezM. D.et al (2011). Use of máximum trunk diameter measurements to detect wáter stress in mature “Arbequina” olive trees under deficit irrigation.Agric. Water Manag.981813–1821. 10.1016/j.agwat.2011.06.011
14
FultonA.BuchnerR.OlsonB.SchwanklL.GillesC.BertagnaN.et al (2001). Rapid equilibration of leaf and stem water potential under field conditions in almonds, walnuts, and prunes.HortTechnology11609–615. 10.21273/horttech.11.4.609
15
GarcíaJ. M.CuevasM. V.FernandezJ. E. (2013). Production and oil quality in “Arbequina” olive (Olea europaea, L) trees under two deficit irrigation strategies.Irrig. Sci.31359–370. 10.1007/s00271-011-0315-z
16
García-TejeraO.Lopez-BernalA.OrgazF.TestiL.VillalobosF. J. (2021). The pitfalls of water potential for irrigation scheduling.Agric. Water Manag.243:106522. 10.1093/jxb/erh213
17
GirónI. F.CorellM.Martín-PalomoM. J.GalindoA.TorrecillasA.MorenoF.et al (2015). Feasibility of trunk diameter fluctuations in the scheduling of regulated deficit irrigation for table olive trees without reference trees.Agric. Water Manag.161114–126. 10.1016/j.agwat.2015.07.014
18
GoldhamerD. A. (1999). Regulated deficit irrigation for California canning olives.Acta Hortic.474369–372. 10.17660/actahortic.1999.474.76
19
Gómez del CampoM. (2013). Summer deficit-irrigation strategies in a hedgerow olive orchard cv “Arbequina”: effect on fruit characteristics and yield.Irrig. Sci.31259–269. 10.1007/s00271-011-0299-8
20
Gómez del CampoM.Perez-ExpositoM. A.HammamiS. B. M.CentenoA.RapoporrtH. F. (2014). Effect of varied summer déficit irrigation on components of olive fruit growth and development.Agric. Water Manag.13784–91. 10.1016/j.agwat.2014.02.009
21
GrattanS. R.BerenguerM. J.ConnellJ. H.PolitoV. S.VossenP. M. (2006). Olive oil production as influenced by different quantities of applied water.Agric. Water Manag.85133–140. 10.1016/j.agwat.2006.04.001
22
GucciR.CarusoG.GennaniC.EspostoS.UrbaniS.ServiliM. (2019). Fruit growth, yield and oil quality changes induced by deficit irrigation at different stages of olive fruit development.Agric. Water Manag.21288–98.
23
HowellT. A. (1990). “Relationships between crop production and transpiration, evaporation, and irrigation,” in Irrigation of Agricultural Crops, Chap. 14, edsStewartE. B.NielsenD. (Madison, WI: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America), 391–434. 10.1016/j.scitotenv.2018.11.176
24
HuesoA.CamachoG.Gomez-del-CampoM. (2021). Spring deficit irrigation promotes significant reduction on vegetative growth, flowering, fruit growth and production in hedgerow olive orchards (cv Arbequina).Agric. Water Manag.248:106695. 10.1016/j.agwat.2020.106695
25
HuesoA.TrentacosteE. R.JunqueraP.Gomez-MiguelV.Gomez del CampoM. (2019). Differences in stem wáter potential during oil synthesis determine fruit characteristics and production but not vegetative growth or return bloom in an olive hedgerow orchard (cv Arbequina).Agric. Water Manag.223:105589. 10.1016/j.agwat.2019.04.006
26
KramerP. J.BoyerJ. S. (1995). Water Relations of Plants and Soils.Cambridge, MA: Academic Press Inc.
27
LampinenB. D.ShackelK. A.SouthwickS. M.OlsonW. H. (2001). Deficit irrigation strategies using midday stem water potential in prune.Irrig. Sci.2047–54. 10.1007/s002710000028
28
LampinenB. D.ShackelK. A.SouthwickS. M.OlsonB.YeagerJ. T.GoldhamerD. (1995). Sensitivity of yield and fruit quality of French prune to water deprivation at different fruit growth stages.J. Am. Soc. Hortic. Sci.120139–147. 10.21273/jashs.120.2.139
29
LaveeS.HanochE.WodnerM.AbramowitchH. (2007). The effect of predetermined deficit irrigation on the performance of cv Muhasan olives (Olea europaea L) in the eastern coastal plain of Israel.Sci. Hortic.112156–163.
30
LiS. H.HuguetJ. C.SchochP. G.OrlandoP. (1989). Response of peach tree growth and cropping to soil water deficit at various phenological stages of fruit development.J. Hortic. Sci.61531–552.
31
MarinoG.CarusoT.FergusonL.Paolo MarraF. (2018). Gas exchanges and stemwater potential define stress thresholds for efficient irrigation management in olive (Olea europea L.).Water10:342. 10.3390/w10030342
32
MarinoG.PerniceF.MarraF. P.CarusoT. (2016). Validation of an online system for the continuous monitoring of tree water status for sustainable irrigation managements in olive (Olea europaea L.).Agric. Water Manag.177298–307.
33
MarinoG.ScalisiA.Guzmán-DelgadoP.CarusoT.MarraF. P.Lo BiancoR. (2021). Detecting mild water stress in olive with multiple plant-based continuous sensors.Plants10:131. 10.3390/plants10010131
34
MarraF. P.MarinoG.MarcheseA.CarusoT. (2016). Effects of different irrigation regimes on a super-high density olive grove cv. ‘Arbequina’: vegetative growth, productivity and polyphenol content of the oil.Irrig. Sci.34313–325.
35
Martin-PalomoM. J.CorellM.GirónI.AndreuL.GalindoA.CentenoA.et al (2020). Absence of yield reduction after controlled water stress during preharvest period in table olive trees.Agronomy10:258.
36
McCutchanH.ShackelK. A. (1992). Stem-water potential as a sensitive indicator of water stress in prune trees (Prunus domestica L. cv. French).J. Am. Soc. Hortic. Sci.117607–611. 10.21273/jashs.117.4.607
37
Morales-SilleroA.GarcíaJ. M.Torres-RuizJ. M.MonteroA.Sánchez-OrtizA.FernándezJ. E. (2013). Is the productive performance of olive trees under localized irrigation affected by leaving some roots in drying soil?Agric. Water Manag.12379–92.
38
MorianaA.OrgazF.FereresE.PastorM. (2003). Yield responses of a mature olive orchard to water deficits.J. Am. Soc. Hortic. Sci.128425–431. 10.21273/jashs.128.3.0425
39
MorianaA.Pérez-LópezD.PrietoM. H.Ramírez-Santa-PauM.Pérez-RodriguezJ. M. (2012). Midday stem water potential as a useful tool for estimating irrigation requirements in olive trees.Agric. Water Manag.11243–54. 10.1016/j.agwat.2012.06.003
40
NaorA. (2006). Irrigation scheduling and evaluation of tree water status in deciduous orchards.Hortic. Rev.32111–165. 10.1002/9780470767986.ch3
41
RapoportH. F.Pérez-LópezD.HammamiS. B. M.AgueraJ.MorianaA. (2013). Fruit pit hardening: physical measurements during olive growth. Ann. Appl. Biol.163, 200–208. 10.1111/aab.12046
42
Pérez-LópezD.RibasF.MorianaA.OlmedillaN.De JuanA. (2007). The effect of irrigation schedules on the water relations and growth of a young olive (Olea europaea L.) orchard.Agric. Water Manag.89297–304. 10.1016/j.agwat.2007.01.015
43
PierantozziP.TorresM.TivaniM.ContrerasC.GentiliL.PareraC.et al (2020). Spring deficit irrigation in olive (cv. Genovesa) growing under arid continental climate: effects on vegetative growth and productive parameters.Agric. Water Manag.238:106212. 10.1016/j.agwat.2020.106212
44
RapoportH. F.HammamiS. B. M.MartinsP.Perez-PriegoO.OrgazF. (2012). Influence of water deficits at different times during olive tree inflorescence and flower development.Environ. Exp. Bot.77227–233. 10.1016/j.envexpbot.2011.11.021
45
Sánchez-RodríguezL.KranjacM.MarijanovicZ.JerkovicI.CorellM.MorianaA.et al (2019). Quality attributes and fatty acid, volatile and sensory profiles of “Arbequina” hydroSOStainable olive oil.Molecules24:2148. 10.3390/molecules24112148
46
ShackelK. A. (2011). A plant-based approach to deficit irrigation in trees and vines.Hortic. Sci.46173–177. 10.21273/hortsci.46.2.173
47
ShackelK. A.AhmadiH.BiasiW.BuchnerR.GoldhamerD.GurusingheS.et al (1997). Plant water status as an index of irrigation need in deciduous fruit trees.HortTechnology723–29. 10.21273/horttech.7.1.23
48
ShackelK. A.BuchnerR.ConnellJ.EdstronJ.FultonA.HoltzB.et al (2010). “Midday stem water potential as a basis for irrigation scheduling,” in Proceedings of the 5th National Decennial Irrigation Conference, 5-8 December 2010, Phoenix Convention Center, (Phoenix, ARI). 10.1093/treephys/28.8.1255
49
SinclairT. R.LudlowM. M. (1985). Who taught plants thermodynamics? The unfulfilled potential of plant water potential.Aust. J. Plant Physiol.12213–217.
50
SpinelliG. M.SnyderR. L.SandenB. L.ShackelK. A. (2016). Water stress causes stomatal closure but does not reduce canopy evapotranspiration in almond.Agric. Water Manag.16811–22.
51
StewartW. L.FultonA. E.KruegerW. H.LampinenB. D.ShackelK. A. (2011). Regulated deficit irrigation reduces water use of almonds without affecting yield.Calif. Agric.6590–99. 10.1016/j.scitotenv.2021.146148
52
TetensV. O. (1930). Uber einige meteorolgische.Begriffe Z. Geophys.6297–309.
53
TeviotdaleB. L.GoldhamerD. A.ViverosM. (2001). Effects of deficit irrigation on hull rot disease of almond trees caused by Monilinia fructicola and Rhizopus stolonifer.Plant Dis.85399–403. 10.1094/PDIS.2001.85.4.399
54
TrentacosteE. R.CalderónF. J.Contreras-ZanessiO.GalarzaW.BancoA. P.PuertasC. M. (2019). Effect of regulated deficit irrigation during the vegetative growth period on shoot elongation and oil yield components in olive hedgerows (cv. Arbosana) pruned annually on alternate sides in San Juan, Argentina.Irrig. Sci.37533–546. 10.1007/s00271-019-00632-8
55
Velasco-MuñozJ. F.Aznar-SánchezJ. A.Belmonte-UreñaL. J.Román-SánchezI. M. (2018). Sustainable water use in agriculture: a review of worldwide research.Sustainability10:1084. 10.3390/su10041084
Summary
Keywords
deficit irrigation, Olea europaea, stem water potential, vapor pressure deficit, baseline
Citation
Shackel K, Moriana A, Marino G, Corell M, Pérez-López D, Martin-Palomo MJ, Caruso T, Marra FP, Agüero Alcaras LM, Milliron L, Rosecrance R, Fulton A and Searles P (2021) Establishing a Reference Baseline for Midday Stem Water Potential in Olive and Its Use for Plant-Based Irrigation Management. Front. Plant Sci. 12:791711. doi: 10.3389/fpls.2021.791711
Received
08 October 2021
Accepted
01 November 2021
Published
26 November 2021
Volume
12 - 2021
Edited by
Thorsten M. Knipfer, University of British Columbia, Canada
Reviewed by
Maria Isabel Hernández Pérez, EAFIT University, Colombia; Eduardo Rafael Trentacoste, Instituto Nacional de Tecnología Agropecuaria, Argentina
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Copyright
© 2021 Shackel, Moriana, Marino, Corell, Pérez-López, Martin-Palomo, Caruso, Marra, Agüero Alcaras, Milliron, Rosecrance, Fulton and Searles.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ken Shackel, kashackel@ucdavis.edu
This article was submitted to Plant Biophysics and Modeling, a section of the journal Frontiers in Plant Science
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