Next Article in Journal
Yield Performance of Organic Sweetpotato Varieties in Various Mulches
Next Article in Special Issue
Refining Irrigation Strategies in Horticultural Production
Previous Article in Journal
Microbial Effects on the Production of Aquaponically Grown Lettuce
Previous Article in Special Issue
Remote Sensing for Irrigation of Horticultural Crops
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Horticulturae
Volume 3
Issue 3
10.3390/horticulturae3030047
horticulturae-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Plant Water Status Indicators for Irrigation Scheduling Associated with Iso- and Anisohydric Behavior: Vine and Plum Trees

by
Fernando Blanco-Cipollone
1,
Sónia Lourenço
2,
José Silvestre
3,4,
Nuno Conceição
2,3,
María José Moñino
1,
Antonio Vivas
1 and
Maria Isabel Ferreira
2,3,*
1
Departamento de Hortofruticultura, Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Finca La Orden, Junta de Extremadura, Autovía A-V, Km 372, 06187 Guadajira (Badajoz), Spain
2
Instituto Superior de Agronomia (ISA), Universidade de Lisboa (ULisboa), Tapada da Ajuda, 1349-017 Lisboa, Portugal
3
Linking Landscape, Environment, Agriculture and Food (LEAF), Instituto Superior de Agronomia (ISA), Universidade de Lisboa (ULisboa), Tapada da Ajuda, 1349-017 Lisboa, Portugal
4
Instituto Nacional de Investigação Agrária e Veterinária, Pólo de Dois Portos, 2565-191 Dois Portos, Torres Vedras, Portugal
*
Author to whom correspondence should be addressed.
Horticulturae 2017, 3(3), 47; https://doi.org/10.3390/horticulturae3030047
Submission received: 8 May 2017 / Revised: 20 July 2017 / Accepted: 7 August 2017 / Published: 12 August 2017
(This article belongs to the Special Issue Refining Irrigation Strategies in Horticultural Production)
Browse Figures
Versions Notes

Abstract

:
Plant water status indicators have been increasingly used for scheduling irrigation. Different variables may be used to do this, depending on personal preferences and the resources available. Many studies have suggested that selection of an indicator should take into account plant behavior in relation to isohydricity. In two Iberian studies, deficit irrigation (DI) was applied in a vineyard and in a plum orchard while plant water status and fluxes were monitored. These case-studies are discussed with special focus on the use of predawn leaf water potential (Ψpd) versus stem water potential (Ψst) to determine whether Ψst performed better and would therefore be the preferred stress indicator for plants exhibiting anisohydric behavior. In contrast, in plants with isohydric behavior, Ψpd would be generally preferred. This hypothesis seems to be supported by the present results obtained and by prior studies. The cultivars used and the intensity of stress applied have an important influence on the results. This suggests that, if no specific information is available from the existing literature, daily preliminary studies would be recommended prior to application in order to select the most appropriate plant water stress indicators.

1. Introduction

Scheduling deficit irrigation (DI) in commercial fields traditionally requires knowledge of stress coefficient functions (Ks) in order to estimate soil water depletion (SWD) via the water balance, using estimated actual evapotranspiration (ETa) as input. This enables users to anticipate the required irrigation depths (how much water to apply). The use of water stress indicators to schedule irrigation requires the selection of which variables should be used as well as their threshold values for different objectives concerning marketable yields (when to irrigate). Finally, the coordinated use of these approaches or steps can lead to a self-learning process, as proposed by Ferreira [1]. The use of soil water content (θs) can directly serve both purposes (when and how much), and is considered the ideal variable in low continuous crops though it presents several challenging difficulties when applied to woody crops. Application to woody crops is especially critical when plants present a significantly active part of their root systems in deep layers, as in agroecosystems found in regions with Mediterranean type climates. Under such conditions, plant water status has often been preferred.
The use of plant water status to schedule irrigation has been advocated since the 1980s by many researchers [2,3] and has seen a continuous rise in its use [4,5,6]. A risk of using this approach in DI is that water status needs to be accurately maintained within a fairly narrow range as described by Jones [7]. Any excess application loses the benefit of the regulated deficit applied and any sub-application can lead to severe losses in yield or quality. Indeed, if water stress indicators, such as those based on plant water status, are used without estimating SWD, the exact amounts of water to be applied must be calculated from various tests that may result in an excessive or deficient amount of irrigation water, until the desired amount is found (trial and error [1,8]).
In both situations mentioned above, i.e., either estimating SWD or not, plant water status [see 8] is often quantified by using leaf water potential (Ψl), generally at predawn (Ψpd), or stem water potential, measured generally around or shortly after solar noon (Ψst). A common alternative is the use of stem diameter variations (SDV) and derived indexes. These last indexes are calculated based on easy, affordable and automatable measurements made with linear variable displacement transducers (LVDT, e.g., [9,10,11,12,13]).
The values of Ks have been related to either soil or plant water status. The variables generally used include (i) SWD [14,15], usually expressed in total depth (mm) or (ii) plant water potential (Ψpd or Ψst) [16,17]. Though numerous studies have used SDV, results relating Ks with SDV-derived indexes are unfortunately not frequent or have not been successful.
Plant water status does not depend solely on atmospheric conditions and the availability of water in the soil, in general. Plants are able to modify the architecture of their canopies to acclimate to the environment [18] and have several strategies to deal with it including the avoidance of excessive losses by dehydration [19]. In this sense, lowering stomatal conductance (gs) is one of the most effective mechanisms [20,21,22].
Plants that preferentially put into action effective mechanisms to regulate their water content have a behavior known as isohydric [23,24], whereas those in which the mechanisms referred to above are less effective or non-existent are called anisohydric.
Several studies based mainly on forest species have considered two categories in which species can be classified (e.g., related to xylem type). In this paper, we prefer to use the word “behavior”, which can be ‘more’ or ‘less’ isohydric, or speak about levels of isohydricity. Indeed, many cases have been observed with cultivars displaying different behaviors, notably with grapevines (Vitis vinfera L.) [18,25], or even different behaviors for the same cultivar depending on environmental conditions [26,27,28] or crop stage [29].
Physiological mechanisms associated with isohydricity have been analyzed, as well as their consequences for SDV and plant water potential or the role of stomatal closure. Simonneau et al. [30], when studying SDV in different organs in relation to the water storage rate in 3- to 5-year-old peach (Prunus persica) trees, showed that SDV is closely related to total water stored in the shoots, without any important lag. In spite of changes in the volume of water stored (capacitance), which are more or less proportional to the changes in organ volume depending on tissue elasticity [31,32], the changes in plant organ capacitance have been related to SDV, either in the trunk or in branches.
It might be expected that organs from plants with less effective stomatal closure would tend to exhibit anisohydric behavior and change their volume more expressively than plants under conditions of isohydric behavior. However, according to Meinzer et al. [33], such an analysis requires consideration of the effect of using stored water (plant capacitance) in preventing decreases in Ψl.
Meinzer et al. [34] found contrasting behaviors of Juniperus monosperma and Passiflora edulis which reflect differences in their capacity for homeostatic regulation of turgor that could represent aniso- and isohydric behavior. Furthermore, Meinzer et al. [35] evaluated metrics of stomatal regulation of Ψl during soil drying in eight woody species and assessed whether easily determined leaf pressure—volume traits could serve as proxies for their degree of iso- vs. anisohydric behaviour. According to Garcia-Forner et al. [36], and contrary to their expectations, both of these species (J.  monosperma and P.  edulis) exhibited similar stomatal temporal dynamics in response to drought, with little embolism in J.  monosperma due to its conservative stomatal regulation. This contributed to refuting the concept that very low water potentials during drought are associated with loose stomatal control and with the hypothesis that anisohydric species are more prone to hydraulic failure than isohydric species.
In a review on the relationship between stomatal behaviour, water potential regulation and hydraulic transport, in relation to isohydric and anisohydric classification, Martínez-Vilalta and Garcia-Forner [37] also observed that a tight regulation of Ψl (isohydric) is not necessarily associated with greater stomatal control during drought. A continuous range of stomatal sensitivities to water stress in grapevines, closely linked with rootstock, was observed by Lavoie-Lamoreaux et al. [38]. They found that isohydric and anisohydric behavior defined in terms of Ψl regulation cannot be used as an indicator of a specific mechanism of drought-induced mortality or as a proxy for overall plant vulnerability to drought.
In spite of the controversy on the importance of stomatal control in this regard, or even the controversy as to which type of behavior corresponds to less drought vulnerability, the analysis by McDowell et al. [39] supports a connection between isohydric behaviour and tighter stomatal control. In addition, their analysis reinforces the hypothesis that the so-called “isohydric species are more likely to die of carbon starvation than hydraulic failure, and that partitioning of mortality between isohydric and anisohydric plants is a function of drought intensity and duration” [39].
Martínez-Vilalta et al. [40] showed that the response of the plant's water potential gradient to declining θs (meaning here soil water availability) is not determined directly by stomatal sensitivity to drought but by the ratio between this sensitivity and the vulnerability of the plant hydraulic system. In their view and words, a plant with highly sensitive stomata closing at relatively high water potentials (less negative) could still show a strict anisohydric behavior, provided its hydraulic system is even more sensitive than its stomata to declining water availability. The same authors also provided a quantitative framework for interpretation of the coordination between stomatal regulation and plant hydraulics in terms of an analysis of isohydricity. Roman et al. [41] described a continuum of isohydric to anisohydric regulation of leaf water potential and Klein [42] also argued that species-specific curves form a continuum, rather than a dichotomy, between isohydric and anisohydric behavior, and suggested the use of water potential at 50% of the maximum gs (Ψgs50) for a quantitative comparison between species.
In the context of irrigation science, given the sometimes limited information directly available on such vulnerabilities and given the restricted aim of identifying critical variables and their thresholds, we hypothesized that the daily or seasonal courses of Ψpd or Ψst in plants under different conditions, together with the relative degree of stomatal closure, can give hints about the behavior of the species or cultivar under given circumstances.
When gs is not measured, the transpiration rate (Tr) may often be available, due to possible automated monitoring. Reductions in Tr could then be used as proxies of gs reductions, even if they are not strictly proportional, due to possible differences in the driving forces. In this context, the daily or seasonal course of Ψpd or Ψst in plants submitted to stress compared to well-watered controls is often a good indication of whether plant behavior is isohydric or anisohydric
This article has the following aims: (1) to identify these two behaviors (isohydric and anisohydric), providing examples that explore relationships between the selected variables and Ks (or relative transpiration, RTr) using two case studies; (2) to use the discussion to verify whether the frequent choice made by researchers of plant stress indicators to express water status is related to the isohydric or anisohydric behavior of plants; and (3) to check whether the usual choice of SDV-derived indexes is related with isohydricity.
We hypothesized that, from this analysis, the arguments for possible orientation in the selection of water stress indicators will be reinforced. The examples shown also serve to explain the criteria used in this study to distinguish between the two behaviors.

2. Materials and Methods

2.1. Experimental Sites, Meteorological Conditions and Crop Characteristics

2.1.1. Experiment 1

Experiment 1 was conducted in a commercial drip-irrigated vineyard, planted with the grape (Vitis vinifera L.) ‘Tempranillo’, grafted on 1103P rootstock, with an area of 6.0 ha (“Herdade de Monte Novo e Figueirinha”), at 38.04972 N, 7.9208 W, 200 m above sea level (a. s. l.), located in the Alentejo region near the city of Beja, the warmest and driest region of Portugal (annual 30-year average for precipitation is 572 mm, 5% of which falls during summer; the climate is temperate of Mediterranean type Csa (http://www.ipma.pt/pt/oclima/normais.clima/1971-2000/002/). The grapevines were planted in 2002 (2350 vines ha−1, row orientation ~ N-S). The training system was vertical shoot positioning. The vines were spur pruned on a bilateral Royat cordon with 16 buds per vine. There was tillage between the rows and no tillage beneath the canopy. The soil type was a shallow clay vertisol with abundant gravel and few stones. Available water capacity in the soil was low. The soil depth was about 0.6 m, but only a very few fine roots could have explored rock fissures down to a depth of 1.5 m. The leaf area index (LAI) measured at veraison was 2.15, and ground cover was 42%. The meteorological conditions for the location and years of Experiment 1 are summarized in Table 1.

2.1.2. Experiment 2

Experiment 2 was carried out in an experimental orchard located at Finca La Orden (Cicytex), in the “Vegas Bajas” area (Badajoz, Spain) at 38.8507 N, 6.6709 W, 184 m a.s.l. The soil type is an alfisol characterized as a young soil with low organic matter and a texture of 19.4% clay, 40.2% silt and 40.4% sand. The climate is temperate of Mediterranean type with Atlantic influence (Csa); annual evapotranspirative demand is 1295 mm, with 428 mm annual rainfall. The plant material was Prunus salicina ‘Angeleno’, a late season plum variety grafted on Marianna pattern 2624 rootstock. The orchard was established during 2005, and the tree formation system is in open-beaker with four branches per tree. The arrangement of the trees was in rows in a 6 × 4 m plantation frame, east-west oriented. The meteorological conditions for the location and years of Experiment 2 are summarized in Table 1.
These two Experiments (1 grapevine, 2 plum orchard) were selected for their respective representation of isohydric and anisohydric behavior.

2.2. Measurements and Irrigation Treatments

2.2.1. Experiment 1

Irrigation treatments. The experimental work reported took place during 2009 and 2010. Irrigation started when vegetative growth stopped and was usually applied once a week, on average. DI treatments were imposed after day of the year (DOY) 175 (approximately two weeks before veraison) until harvest (DOY 238).
During 2009, three DI treatments with three completely randomized repetitions each were applied in the long term. Threshold values of Ψpd defined for the vineyard [43,44] were used to control stress levels corresponding to irrigation depths applied of approximately 70%, 40% and 25% of estimated crop evapotranspiration (ETc). The aim was for the treatments to correspond in the long term roughly to weak (Ψpd > −0.4 MPa), mild (−0.4 MPa < Ψpd > −0.6 MPa) and severe water stress (Ψpd < −0.6 MPa).
In the following year (August 2010), a short water stress cycle (eight days) was conducted for a more detailed characterization of Ψl and stomatal conductance behavior between irrigation events. A control (without water stress (CT)), mild water stress (MS) and moderate water stress (HS) treatments were imposed under field conditions, as follows. Before the beginning of the drought stress (8th August), an irrigation event of 22 mm was applied to CT and MS and of 14 mm to HS. During the water stress period, two irrigation events of 13 mm each were applied to CT (11th and 13th August). Measurements of Ψpd were taken at predawn, and of Ψst and gs in the middle of the morning (10 h), 15 min after solar noon (14 h) and at mid-afternoon (18 h).
Measurements. For the long-term experiment of 2009, meteorological data from a nearby station (http://www.cotr.pt/ema.asp?id=1007, 38. 0375 N, 7.8850 W, ca. 206 m a.s.l.) were used to calculate ETo with the Penman-Monteith equation, using reference crop parameters (grass with a height of 0.12 m, surface resistance of 70 s m−1 and albedo of 0.23 [15]. ETc was initially established with the crop coefficient as a function of leaf area index (LAI).
All measurements of Ψpd and Ψst were performed the day immediately before irrigation with a pressure chamber (Scholander type, PMS Instrument Company, Albany, OR, USA, Model 600) with each leaf for Ψst wrapped in an aluminum bag two hours prior to measurements. The leaves were removed from the vines and measured in a pressure chamber with the precautions described by Shackel et al. [45]. Stomatal conductance was measured with a LI-1600 steady state porometer (LI-COR Inc., Lincoln, NE, USA). At least three measurements were performed per replicate (9 per irrigation treatment). Due to the soil nature (gravel), θs was not measurable.

2.2.2. Experiment 2

Irrigation treatments. For the first part of the experiment, in 2010, two irrigation treatments were established: a Control treatment (C) which was irrigated with 100% of estimated ETc and a Deficit Irrigation (DI) treatment irrigated as C, except from the 7th of June to the 26th of July (48 days) during which there was no irrigation at all (functioning as a stress cycle). The experimental design was four random blocks per treatment, four trees per block. During three consecutive years (2014, 2015, 2016), the same irrigation treatments were maintained. The periods in which irrigation was removed in the stressed (DI) treatment were from 12th May to 11th June in 2014 (30 days), 13th May to 15th June in 2015 (32 days) and 13th May to 22nd June in 2016 (40 days).
Measurements. In 2010, ETc was estimated as the product of ETo obtained with the Penman-Monteith equation and a single Kc according to the values proposed in Allen et al. [15]. In 2014, 2015 and 2016, a soil water balance was used to determine ETc (for C or equivalent). It (ETc WB) was calculated using the law of mass conservation (water balance) as:
ETc WB = P + I − D − R − ΔS
ΔS = Σ (θi − θi−1) z
where P is effective rainfall, I is irrigation, D is drainage, R is runoff, ΔS is the change in soil water storage between two consecutive dates, and z is the depth of each layer. The values of R were considered negligible because the orchard was levelled and no runoff was observed. D was considered null at the maximum observed depth (1.8 m). The values of θs were obtained from neutron probe measurements (CPN 503DR Hydroprobe, CPN International, Inc., Port Chicago Highway, CA, USA), carried out once a week, early in the morning, throughout the irrigation season in the root zone of representative trees of each cultivar. Four access tubes were installed on both sides of a tree at 0.5 m and 1.5 m in a line and, perpendicularly, at 0.5 m and 1.5 m from that line, respectively. Each tube was 3 m long, and measurements were made at intervals of 30 cm, from 30 to 270 cm. The neutron probe readings were calibrated in loco.
In 2010, four times during the season, Ψst was measured from predawn to sunset at different hours. The measurements were taken for eight trees per treatment corresponding to four trees per block, in two blocks. Two leaves per tree were selected from a branch located in the lower part near the trunk and facing north. The same technique was used as in Experiment 1 except that the aluminum bags were placed in the first hour of the morning and the leaves of the first measurement were bagged in the last hour of the previous day.
On the same trees, during 2014, 2015 and 2016 throughout the periods of the water stress cycles, water supply measurements were recorded for both treatments, confirming that the DI treatment did not receive any irrigation water during the stress cycles. The measures of Ψst were also taken at solar noon, using two leaves per tree, two trees per block and per treatment, which resulted in a total of 16 measures per treatment.
On two trees of each treatment, canopy transpiration was measured with a sap-flow system device which was developed and assembled at the IAS in Cordoba and described in Testi and Villalobos [46]. The system uses the compensation heat-pulse method plus the calibrated average gradient technique. Sap velocity was measured following the procedure of Green and Clothier [47], using the theoretical calibrations of Swanson and Whitfield [48], to account for the probe-induced effects of wounding. The temperature signals and the corresponding heat pulse velocities were recorded at 15 min intervals using heat-pulse instrumentation connected to a data logger (CR1000, with a multiplexer AM16/32, Campbell Scientific Inc., Logan, UT, USA).
The value of RTr (similar to Ks) is expressed as the ratio of transpiration of treatment DI to transpiration of treatment C (see irrigation treatments). The value observed in the control treatment the day before the stress cycle started was taken as the baseline reference (for normalization).

2.3. Data Analysis and Statistics

The statistical techniques employed to analyze these data were mainly linear regression and summary statistics. One-way ANOVA was also used (Experiment 1), and significant differences among treatments were evaluated with the Student-Newman-Keuls test with p = 0.05 using the CoStat Statistics Software (CoHort Software, Monterey, CA, USA). This type of analysis is considered not applicable when the aim is only to locate the moment for which the treatments have the largest absolute differences for the variable under analysis (as for data shown from Experiment 2), not to establish when differences between treatments appear.

3. Results

3.1. Experiment 1

Over the experimental period, the different irrigation treatments applied during 2009 to the Beja vineyard could be clearly discriminated by using Ψpd (Figure 1a); statistically significant differences at p = 0.01 and p = 0.0001 were observed respectively after DOY 203 and 217. Conversely, statistically significant differences at p = 0.01 and p = 0.0001 were observed using Ψst only after DOY 226 and DOY 230 (Figure 1b). These results suggest isohydric behavior.
The relationships between Ψpd and gs (Figure 1c) and between Ψst and gs (Figure 1d) also reveal a larger relative variation in the values observed at predawn compared to those observed at noon. A single line can be considered for Ψpd, though with high scattering for upper values of Ψpd which can be explained by the strong influence of atmospheric conditions on gs, when atmospheric stress (atmosphere causing plant stress) dominates edaphic-based stress [49]. As for Ψst, there is a larger scattering of gs for average values, suggesting that initially atmospheric conditions affect both variables (Ψst and gs) but, when edaphic-based stress dominates, Ψst no longer expresses the proportion of the stomatal closure occurring (discrete distance between treatments, Figure 1d). If the degree of isohydricity can also be defined through the slope of the curve Ψl versus gs [50], the high slope in Figure 1d (with Ψst) supports our interpretation.
During the short stress cycle that was imposed in 2010, the range of measured Ψpd (Figure 2a) was in agreement with values found in the literature either in the absence of water stress or with mild and severe water stress. Moreover, Ψpd was very sensitive to any irrigation applied. A strong decrease in Ψpd occurred on 10th August, possibly due to unusually hot and dry conditions during the night (min air temperature = 24.1 °C, min VPD = 1.35 kPa), which may have contributed to nocturnal transpiration.
The evolution of Ψst immediately before and during the drought stress cycle measured at 10 h, 14 h and 18 h (clock or legal time = solar time + ≈1.75 h, during summer) is presented in Figure 2b–d, respectively. Although Ψst at noon is often considered a good indicator of grapevine water status [43,51,52], this experiment suggested that this is not the case for this cultivar and under the conditions of this study, possibly due to isohydric behavior, since (again) Ψst could not discriminate between the treatments that were shown to differ by Ψpd. A similar result was found by Intrigliolo and Castel [53] for the same grapevine cultivar.
The evolution of Ψst during the day and its recovery during the afternoon were faster in CT, as expected. The range of Ψst observed is in strong disagreement with the thresholds indicated by Myburgh [54] for absence and mild water stress intensities. This can be partly attributed to the VPD influence on Ψst [52,55]. In this case, the average VPD at solar noon during the drought cycle was approximately 4.95 kPa. Moreover the high Ψst values observed during 8th August can be attributed not only to a lower VPD (3.10 kPa) but also to the heavy cloud cover observed (with ETo = 4.1 mm, whereas the average ETo during the drought cycle was 6.8 mm).
Transpiration rates and Kc values as well as the relationship between RTr and Ψpd (Ks function) were already presented and discussed in comparison with three other vineyards, mostly rainfed [1,56], where the vineyard described here was the one suffering more stress in spite of being irrigated, with the Ks function (Ks = 1.0011 exp −1.829 Ψpd, r2 = 0.73) distinct from other functions obtained for the rainfed situations (lower Ks for the same Ψpd). In parallel with this Ks function for grapevines, a Ks function from Ψst for the plum orchard of Experiment 2 will be presented below.

3.2. Experiment 2

In the plum orchard at Badajoz, Spain, the minimum Ψst attained was −1.2 MPa for the DI treatment (Figure 3). Although both treatments showed the same trend in Ψst, the differences between both, around −0.2 MPa in the morning, almost doubled at noon. Other authors studying similar situations of water deficit [57,58] observed that the hours for which the differences in Ψst were more varied from day to day depended on the weather, but were usually observed roughly 1–2 h after solar noon. This greater difference does not necessarily correspond to the minimum values. In this case, we distinguished Ψst,noon from Ψst because some Ψst measurements were performed during the day.
Consequently, for this cultivar, Ψpd did not seem to be as useful as Ψst as an indicator of water status. We consider that this example illustrates anisohydric behavior, due to the fact that differences in Ψst at noon were much higher than at pre-dawn, the main criteria we considered.
A strong relationship between Ψst,noon and RTr was observed (Figure 4). The relationship between RTr and Ψst,noon measured in the three years of the study developed between a maximum RTr (=1) until a threshold of −1.0 MPa was attained and, as Ψst,noon decreased to −2.5 MPa, RTr decreased to 20% (RTr = 2.3767 exp −0.874 Ψst, r2 = 0.87). If a linear relation was applied, Ψst,noon would decrease from −1.1 MPa (Ks = 1) to around −2.7 MPa (Ks = 0).

4. Discussion

The results shown, with grapevines and plum trees, illustrated two distinct behaviors. They described the behavior of these cultivars under the environmental conditions and stress levels they experienced. In addition, the examples served to explain the criteria used in this study to distinguish between these two behaviors, isohydric versus anisohydric, which we relate to the level of isohydricity.
In order to have a general perspective of the choices made by researchers about plant stress indicators used to express water status, and their relationship with identified iso/anisohydric behavior of plants, representative studies performed with a perspective relevant for our aims, of perennial, woody agricultural crops, mostly under Mediterranean climate conditions are shown in Table 2. We focused mainly on the variables which are predominantly used in both behaviours, Ψpd, Ψl,noon, and Ψst,noon. Complementary information is provided on SDV-derived variables (measured with LVDT sensors), such as the maximum daily shrinkage (MDS) or its relative value—the relative daily trunk shrinkage (RDTS), the minimum trunk diameter (MNTD), the maximum trunk diameter (MXTD), the trunk or, more generally, organ growth rate (TGR or OGR)—which is the difference between two consecutive MXTD. These are the most common SDV-derived variables, though some variations or combinations thereof have also been used. Other variables considered in these studies are mentioned. Their comparison encourages a general description, identification of general trends and inspires specific comments.
In general, it is claimed that the variables (indicators) most closely related with important biological processes should be selected as they are better indicators in relation to growth processes (e.g., [9]). Ψst in this respect is often recommended. MDS was shown to depend on seasonal changes in trunk growth and both MDS and Ψst were valued by Marsal et al. [9] for accounting for day-to-day variations in diurnal atmospheric demand, expressed in general by ETo.

4.1. Plant Water Status Indicators Versus Water Stress

An increase in ETo, which can possibly cause atmospheric stress, can hardly be solved by irrigation except when there is an important percentage of wet soil surface (e.g., by mini sprinklers), and in stands with low aerodynamic conductance [49]. If Ψst decreases due to changes in ETo, wetting the soil in a drip-irrigated orchard would apparently have a negligible effect on decreasing VPD anyway (and increasing gs and carbon exchanges).
Irrigation aims first at decreasing or preventing edaphic-based stress. Consequently, the value of any variable considered for scheduling irrigation that is heavily influenced by diurnal atmospheric stress can be controversial in its effectiveness for irrigation scheduling decisions.
Several researchers (e.g., [11]) have compared the earliness of water stress detection by different indicators versus soil water content (θs) but have sometimes not related it to the readily available water (RAW) concept. This possibly leads to misinterpreting apparent late reactions of several indicators versus θs (since no water stress is expected while the soil water is within the RAW limits).
Like peach trees, kiwi (Actinidia deliciosa), grapevines, and olive (Olea europea) trees also displayed different behaviors (isohydricity) depending on the particular cultivar in question. However, the simple criteria used here for irrigation scheduling would seem inadequate for the complex interpretation required when dealing with olive tree cultivars. According to Ennajeh et al. [72], even if transpiration can also be significantly reduced under stress due to stomatal closure, Ψl can be extremely low in relation to most other tree species as a result of the ability of olive trees to transfer water from tissues to the xylem sap.

4.2. Use of Water Stress Indicators

A study with peach [63] with an intermediate behavior showed important variations in TGR and MDS, Ψst, Ψl and Ψpd. The authors did not report any stomatal conductance measurements. The way in which these authors and others that followed valued the different indicators was based on relative values. Relative values were relevant in some cases and will be used in this discussion only for flux,conductance and SDV derived variables, but not for potentials. However, there is a limitation in that they require a well-watered control used as reference. For instance, due to the observed effects of environmental atmospheric conditions on MDS, Ferreira et al. [61] did not use MDS directly but RDTS to evaluate water stress in peach.
Some studies [4,67,73] have demonstrated that atmospheric conditions have significant effects on Ψst and/or especially MDS, with relationships that change with the carbon status of the plant, dependent for instance on the pre- or postharvest condition. Intrigliolo and Castel [67] also concluded that MDS should be considered only in relative terms (as RDTS).
A review of a large collection of Spanish studies on the use of SDV, Ψst and Ψleaf for irrigation scheduling related to different environmental variables [13] also implicitly supported this perspective, even suggesting that MDS (or RDTS, later called in that study the MDS signal intensity) should be combined with other water stress indicators. Intrigliolo et al. [68] showed that the MDS difference between treatments, with pomegranate, increased with stress and then tended to stabilize or even decrease. This was also observed by other research [13,61]. The values of Ψst,noon were closely related to other indicators of plant stress [74,75,76,77]. In some cases, this indicator has been related to the reduction in transpiration (RTr or Ks), as in Figure 4. Anisohydric mechanisms apparently caused greater Tr rates at noon, which was reflected in the fact that the most commonly used indicators of stress were expected to be involved with changes in plant tissue volume. The SDV-derived indicators were widely described in the literature as being the most suitable for determination of the water status of plant with anisohydric behavior and therefore for irrigation scheduling [13,78,79]. These indexes seem to be among the most popular plant water stress indicators, with the advantage of providing a continuous data-set over time [5,80]. This applies especially to young trees where OGR is one of the earliest responses to plant water stress [81]. The literature suggests that in plants with anisohydric behavior, MNTD and MDS are the most commonly used indexes, although a combination of trunk and tree organ measurements is also effective [71]. However, MXTD seems inadequate for this purpose [63,82]. By contrast, tests performed on isohydric species showed a lack of use of this type of indicator. Intrigliolo et al. [68] showed how the use of TGR was unsuitable as a measure to determine plant water status in pomegranate [67]. The same conclusion was reached for peach [83].
In summary, water potential measurements have been widely used in many studies. The high levels of measurement repeatability and reliability have made them popular for irrigation scheduling, although some authors [9,63] have pointed out that in anisohydric species these indicators are not as reliable as SDV-derived indexes, especially Ψpd, where no differences were found between species under deficit irrigation treatment. Conversely, Ψpd is the most commonly used and most highly valued variable to quantify plant water status in plants with isohydricbehaviour.
The present discussion focused on authors who use stress indicators for irrigation management (Table 2) and showed that there has been a tendency to use a certain type of indicator according to the behavior of the case-studies considered: (1) all the studies on plants with isohydric behavior whereby were measured Ψpd showed this variable performed well as a water stress indicator; (2) all the studies on species with isohydric behavior which measured Ψst reported that this indicator did not perform well; (3) a few studies on species with isohydric behavior which analyzed SDV reported satisfactory results with RDTS or DMXTD/MXTD (difference of MXTD divided by the value observed for a well-watered control). In relation to anisohydric behavior, there has been a tendency to obtain a better performance using SDV-derived indexes than with isohydric cultivars, especially with MDS. In general, Ψst also performs well with all anisohydric species or in cases where the behavior is not clear. However, Ψst performs badly with isohydric species, with the sole exception of pomegranate [68]. These results confirm our hypothesis. We should stress that apparently the choices made by researchers for measurements or the presentation of results often seem to be made having already taken this concept into account, even when not explicitly.
Ks functions where Ks is estimated from SWD have been used but, there are no studies of relationships between Ks and plant indicators. This may be attributed to the use of plant water status indicators which are often linked to a feed-back approach which does not usually require Ks estimates. Consequently, it is difficult to provide a summary of the use of such Ks functions from plant indicators.

4.3. When to Use Predawn or Noon Stem Water Potential

In conclusion, our results and those of others suggested that Ψst performs better and therefore is a preferred stress indicator in plants with anisohydric behavior, while in plants with isohydric behavior, Ψpd is generally preferred.
It is important to stress that the validity of these indicators depends not only on isohydric versus anisohydric behavior, but also on the stress level to which plants are subjected, as several authors [57,63,64] have demonstrated. Although SDV seemed to provide more interesting indicators for anisohydric species, the sensitivity of the derived indicator also changed as the range of water stress level varied.
It is clear from these observations that the behavior also depends on the cultivar in question, as demonstrated for instance for grapevines and peach (Table 2). Associating isohydricity with species (e.g., ring-porous versus diffuse-porous wood) is apparently not supported by these results.
If the choice of SDV-derived indexes is related to isohydricity, possible guidelines for these indicators could be determined from further in-depth analyses in future studies.
The differences between isohydric and anisohydric behavior complicate the choice and use of a stress indicator in a particular cultivar. A prior study of plant behavior with environmental changes is recommended to establish which variable provides the best information, unless a collection of data on different indicators is already available.

Acknowledgments

Nuno Conceição received a PhD fellowship (SFRH/BD/66967/2009) from the Foundation for Science and Technology (FCT) in Portugal. The Portuguese study was financially supported by the projects PTDC/AGR-AAM/69848/2006 “Estratégias de rega deficitária em vinha—indicadores de carência hídrica e qualidade” (FCT, Portugal) and to a lesser extent by “Uso da teledetección para a recomendaccion e seguimiento de las practicas de riego en el espacio SUDOE” (SOE1/P2/E082). We thank private owners for the vineyard facilities at Herdade de Monte Novo e Figueirinha. Sónia Lourenço has a grant for PhD fees from CGD (Portugal). The Spanish study was supported by the projects INIA (RTA2009-00026-C02-00, RTA2012-00034-C02-02), CCESAGROS, GR15112 (AGA001), FEDER and the Junta de Extremadura. Fernando Blanco received a PhD grant from the National Institute of Agriculture and Food Research and Technology in Spain (CPR-2014-0148), which included a traineeship at ISA, Universidade de Lisboa.

Author Contributions

Vineyard experiments: Maria Isabel Ferreira, José Silvestre and Nuno Conceição conceived, designed, performed and analyzed the data. Plum experiments: conceived and designed by María José Moñino, performed by Antonio Vivas; data processed by María José Moñino, Antonio Vivas and Fernando Blanco-Cipollone Paper conceived by Maria Isabel Ferreira. Fernando Blanco-Cipollone and Maria Isabel Ferreira performed further data processing and wrote the paper with contributions from Nuno Conceição, Sónia Lourenço and José Silvestre.

Conflicts of Interest

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study, in the collection, analyses or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

References

  1. Ferreira, M.I. Stress Coefficients for Soil Water Balance Combined with Water Stress Indicators for Irrigation Scheduling of Woody Crops. Horticulturae 2017, 3, 38. [Google Scholar] [CrossRef]
  2. Katerji, N.; Hallaire, M. Les grandeurs de référence utilisables dans l’étude de l’alimentation en eau des cultures. Agronomie 1984, 4, 999–1008. [Google Scholar] [CrossRef]
  3. Chalmers, D.J.; Mitchell, P.D.; Vanheek, L. Control of peach tree growth and productivity by regulated water supply, tree density and summer pruning. J. Am. Soc. Hortic. Sci. 1981, 106, 307–312. [Google Scholar]
  4. Ortuño, M.F.; Conejero, W.; Moreno, F.; Moriana, A.; Intrigliolo, D.S.; Biel, C.; Mellisho, C.D.; Pérez-Pastor, A.; Domingo, R.; Ruiz-Sánchez, M.C.; et al. Could trunk diameter sensors be used in woody crops for irrigation scheduling? A review of current knowledge and future perspectives. Agric. Water Manag. 2010, 97, 1–11. [Google Scholar] [CrossRef]
  5. Goldhamer, D.A.; Fereres, E. Irrigation scheduling protocols using continuously recorded trunk diameter measurements. Irrig. Sci. 2001, 20, 115–125. [Google Scholar] [CrossRef]
  6. Goldhamer, D.A.; Fereres, E. Irrigation scheduling of almond trees with trunk diameter sensors. Irrig. Sci. 2004, 23, 11–19. [Google Scholar] [CrossRef]
  7. Jones, H.G. Irrigation scheduling: Advantages and pitfalls of plant-based methods. J. Exp. Bot. 2004, 55, 2427–2436. [Google Scholar] [CrossRef] [PubMed]
  8. Fernández, J.E. Plant-Based Methods for Irrigation Scheduling of Woody Crops. Horticulturae 2017, 3, 35. [Google Scholar] [CrossRef]
  9. Marsal, J.; Gelly, M.; Mata, M.; Arbonés, A.; Rufat, J.; Girona, J. Phenology and drought affects the relationship between daily trunk shrinkage and midday stem water potential of peach trees. J. Hortic. Sci. Biotechnol. 2002, 77, 411–417. [Google Scholar] [CrossRef]
  10. Badal, E.; Buesa, I.; Guerra, D.; Bonet, L.; Ferrer, P.; Intrigliolo, D.S. Maximum diurnal trunk shrinkage is a sensitive indicator of plant water, stress in Diospyros kaki (Persimmon) trees. Agric. Water Manag. 2010, 98, 143–147. [Google Scholar] [CrossRef]
  11. Conejero, W.; Mellisho, C.D.; Ortuño, M.F.; Moriana, A.; Moreno, F.; Torrecillas, A. Using trunk diameter sensors for regulated deficit irrigation scheduling in early maturing peach trees. Environ. Exp. Bot. 2011, 71, 409–415. [Google Scholar] [CrossRef]
  12. De Schepper, V.; van Dusschoten, D.; Copini, P.; Jahnke, S.; Steppe, K. MRI links stem water content to stem diameter variations in transpiring trees. J. Exp. Bot. 2012, 63, 2645–2653. [Google Scholar] [CrossRef] [PubMed]
  13. Fernández, J.E.; Cuevas, M.V. Irrigation scheduling from stem diameter variations: A review. Agric. For. Meteorol. 2010, 150, 135–151. [Google Scholar] [CrossRef]
  14. Stegman, E.C.; Schiele, L.H.; Bauer, A. Plant water stress criteria for irrigation scheduling. Trans. ASAE 1976, 19, 0850–0855. [Google Scholar] [CrossRef]
  15. Allen, R.G.; Pereira, L.S.; Raes, D.; Smith, M. Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and Drainage Paper 56; FAO: Rome, Italy, 1998; Volume 300, p. D05109. [Google Scholar]
  16. Jarvis, P.G. The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field. Philos. Trans. R. Soc. Lond. B Biol. Sci. 1976, 273, 593–610. [Google Scholar] [CrossRef]
  17. Hinckley, T.M.; Duhme, F.; Hinckley, A.R.; Richter, H. Water relations of drought hardy shrubs: Osmotic potential and stomatal reactivity. Plant Cell Environ. 1980, 3, 131–140. [Google Scholar]
  18. Hugalde, I.P.; Vila, H.F. Comportamiento isohídrico o anisohídrico en vides…:¿ Una controversia sin fin? RIA Rev. Investig. Agropecu. 2014, 40, 75–82. [Google Scholar]
  19. Jones, H.G. Physiological aspects of the control of water status in horticultural crops. HortScience 1990, 25, 19–26. [Google Scholar]
  20. Lovisolo, C.; Perrone, I.; Carra, A.; Ferrandino, A.; Flexas, J.; Medrano, H.; Schubert, A. Drought-induced changes in development and function of grapevine (Vitis spp.) organs and in their hydraulic and non-hydraulic interactions at the whole-plant level: A physiological and molecular update. Funct. Plant Biol. 2010, 37, 98–116. [Google Scholar]
  21. Chaves, M.M.; Zarrouk, O.; Francisco, R.; Costa, J.M.; Santos, T.; Regalado, A.P.; Lopes, C.M. Grapevine under deficit irrigation: Hints from physiological and molecular data. Ann. Bot. 2010, 105, 661–676. [Google Scholar] [CrossRef] [PubMed]
  22. Domec, J.C.; Johnson, D.M. Does homeostasis or disturbance of homeostasis in minimum leaf water potential explain the isohydric versus anisohydric behavior of Vitis vinifera L. cultivars? Tree Physiol. 2012, 32, 245–248. [Google Scholar] [CrossRef] [PubMed]
  23. Stocker, O. Die Abhängigkeit des transpiration von den unweltfaktoren. In Encyclopedia of Plant Physiology; Ruhland, W., Ed.; Springer-Verlag: Berlin, Germany, 1956; Volume 3. [Google Scholar]
  24. Konings, A.G.; Gentine, P. Global variations in ecosystem-scale isohydricity. Glob. Chang. Biol. 2017, 23, 891–905. [Google Scholar] [CrossRef] [PubMed]
  25. Schultz, H.R. Differences in hydraulic architecture account for near-isohydric and anisohydric behaviour of two field-grown Vitis vinifera L. cultivars during drought. Plant Cell Environ. 2003, 26, 1393–1405. [Google Scholar] [CrossRef]
  26. Rogiers, S.Y.; Greer, D.H.; Hutton, R.J.; Clarke, S.J. Transpiration efficiency of the grapevine cv. Semillon is tied to VPD in warm climates. Ann. Appl. Biol. 2011, 158, 106–114. [Google Scholar] [CrossRef]
  27. Domec, J.C.; Noormets, A.; King, J.S.; Sun, G.E.; McNulty, S.G.; Gavazzi, M.J.; Bloggs, J.L.; Treasure, E.A. Decoupling the influence of leaf and root hydraulic conductances on stomatal conductance and its sensitivity to vapour pressure deficit as soil dries in a drained loblolly pine plantation. Plant Cell Environ. 2009, 32, 980–991. [Google Scholar] [CrossRef] [PubMed]
  28. Lovisolo, C.; Hartung, W.; Schubert, A. Whole-plant hydraulic conductance and root-to-shoot flow of abscisic acid are independently affected by water stress in grapevines. Funct. Plant Biol. 2002, 29, 1349–1356. [Google Scholar] [CrossRef]
  29. Intrigliolo, D.S.; Castel, J.R. Usefulness of diurnal trunk shrinkage as a water stress indicator in plum trees. Tree Physiol. 2006, 26, 303–311. [Google Scholar] [CrossRef] [PubMed]
  30. Simonneau, T.; Habib, R.; Goutouly, J.P.; Huguet, J.G. Diurnal changes in stem diameter depend upon variations in water content: Direct evidence in peach trees. J. Exp. Bot. 1993, 44, 615–621. [Google Scholar] [CrossRef]
  31. Jarvis, P.G. Water transfer in plants. In Heat and Mass Transfer in the Plant Environment; De Vries, D., Afgan, N.H., Eds.; John Wiley & Sons Inc.: New York, NY, USA, 1975; Chapter 1; pp. 369–394. [Google Scholar]
  32. Scholz, F.C.; Bucci, S.J.; Goldstein, G.; Meinzer, F.C.; Franco, A.C.; Miralles-Wilhelm, F. Temporal dynamics of stem expansion and contraction in savanna trees: Withdrawal and recharge of stored water. Tree Physiol. 2008, 28, 469–480. [Google Scholar] [CrossRef] [PubMed]
  33. Meinzer, F.C.; Johnson, D.M.; Lachenbruch, B.; McCulloh, K.A.; Woodruff, D.R. Xylem hydraulic safety margins in woody plants: Coordination of stomatal control of xylem tension with hydraulic capacitance. Funct. Ecol. 2009, 23, 922–930. [Google Scholar] [CrossRef]
  34. Meinzer, F.C.; Woodruff, D.R.; Marias, D.E.; Mcculloh, K.A.; Sevanto, S. Dynamics of leaf water relations components in co-occurring iso- and anisohydric conifer species. Plant Cell Environ. 2014, 37, 2577–2586. [Google Scholar] [CrossRef] [PubMed]
  35. Meinzer, F.C.; Woodruff, D.R.; Marias, D.E.; Smith, D.D.; McCulloh, K.A.; Howard, A.R.; Magedman, A.L. Mapping ‘hydroscapes’ along the iso-to anisohydric continuum of stomatal regulation of plant water status. Ecol. Lett. 2016, 19, 1343–1352. [Google Scholar] [CrossRef] [PubMed]
  36. Garcia-Forner, N.; Adams, H.D.; Sevanto, S.; Collins, A.D.; Dickman, L.T.; Hudson, P.J.; Zeppel, M.J.B.; Jenkins, M.W.; Powers, H.; Martínez-Vilalta, J.; et al. Responses of two semiarid conifer tree species to reduced precipitation and warming reveal new perspectives for stomatal regulation. Plant Cell Environ. 2016, 39, 38–49. [Google Scholar] [CrossRef] [PubMed]
  37. Martínez-Vilalta, J.; Garcia-Forner, N. Water potential regulation, stomatal behaviour and hydraulic transport under drought: Deconstructing the isohydric and anisohydric concept. Plant Cell Environ. 2016, 40, 962–976. [Google Scholar] [CrossRef] [PubMed]
  38. Lavoie-Lamoureux, A.; Sacco, D.; Risse, P.A.; Lovisolo, C. Factors influencing stomatal conductance in response to water availability in grapevine: A meta-analysis. Physiol. Plant. 2017, 159, 468–482. [Google Scholar] [CrossRef] [PubMed]
  39. McDowell, N.; Pockman, W.T.; Allen, C.D.; Breshears, D.D.; Cobb, N.; Kolb, T.; Plaut, J.; Sperry, J.; West, A.; Williams, D.G.; et al. Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought? New Phytol. 2008, 178, 719–739. [Google Scholar] [CrossRef] [PubMed]
  40. Martínez-Vilalta, J.; Poyatos, R.; Aguadé, D.; Retana, J.; Mencuccini, M. A new look at water transport regulation in plants. New Phytol. 2014, 204, 105–115. [Google Scholar] [CrossRef] [PubMed]
  41. Roman, D.T.; Novick, K.A.; Brzostek, E.R.; Dragoni, D.; Rahman, F.; Phillips, R.P. The role of isohydric and anisohydric species in determining ecosystem-scale response to severe drought. Oecologia 2015, 179, 641–654. [Google Scholar] [CrossRef] [PubMed]
  42. Klein, T. The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours. Funct. Ecol. 2014, 28, 1313–1320. [Google Scholar] [CrossRef]
  43. Choné, X.; Van Leeuwen, C.; Dubourdieu, D.; Gaudillère, J.-P. Stem water potential is a sensitive indicator of grapevine water status. Ann. Bot. 2001, 87, 477–483. [Google Scholar] [CrossRef]
  44. Riou, C.; Payan, J.C. Outils de gestion de l’eau en vignoble méditerranéen. Application du bilan hydrique au diagnostique du stress hydrique de la vigne. 12 Journ. GESCO, Journ. Prof. Gest. L’eau Dans Vign. 2001, 125–133. [Google Scholar]
  45. Shackel, K.A.; Ahmadi, H.; Biasi, A.W.; Buchner, R.; Goldhamer, D.; Gurusinghe, S.; Hasey, J.; Kester, D.B.; Krueger, B.; Lampinen, B.; et al. Plant water status as an index of irrigation need in deciduous fruit trees. Hort Technol. 1997, 7, 23–29. [Google Scholar]
  46. Testi, L.; Villalobos, F.J. New approach for measuring low sap velocities in trees. Agric. For. Meteorol. 2009, 149, 730–773. [Google Scholar] [CrossRef]
  47. Green, S.R.; Clothier, B.E. Water use of kiwifruit vines and apple trees by the heat-pulse technique. J. Exp. Bot. 1998, 39, 115–123. [Google Scholar] [CrossRef]
  48. Swanson, R.H.; Whitfield, D.W.A. A numerical analysis of heat pulse velocity theory and practice. J. Exp. Bot. 1981, 32, 221–239. [Google Scholar] [CrossRef]
  49. Ferreira, M.I.; Katerji, N. Is stomatal conductance in a tomato crop controlled by soil or atmosphere? Oecologia 1992, 92, 104–107. [Google Scholar] [CrossRef] [PubMed]
  50. Matheny, A.M.; Mirfenderesgi, G.; Bohrer, G. Trait-based representation of hydrological functional properties of plants in weather and ecosystem models. Plant Divers. 2017, 39, 1–12. [Google Scholar] [CrossRef]
  51. Patakas, A.; Noitsakis, B.; Chouzouri, A. Optimization of irrigation water use in grapevines using the relationship between transpiration and plant water status. Agric. Ecosyst. Environ. 2005, 106, 253–259. [Google Scholar] [CrossRef]
  52. Olivo, N.; Girona, J.; Marsal, J. Seasonal sensitivity of stem water potential to vapour pressure deficit in grapevine. Irrig. Sci. 2009, 27, 175–182. [Google Scholar] [CrossRef]
  53. Intrigliolo, D.S.; Castel, J.R. Evaluation of grapevine water status from trunk diameter variations. Irrig. Sci. 2007, 26, 49–59. [Google Scholar] [CrossRef]
  54. Myburgh, P.A. Response of Vitis vinifera L. cv. Merlot to low frequency drip irrigation and partial root zone drying in the Western Cape Coastal Region—Part I. Soil and plant water status. S. Afr. J. Enol. Vitic. 2011, 32, 89–103. [Google Scholar] [CrossRef]
  55. Williams, L.E.; Baeza, P. Relationships among ambient temperature and vapor pressure deficit and leaf and stem water potentials of fully irrigated, field-grown grapevines. Am. J. Enol. Vitic. 2007, 58, 173–181. [Google Scholar]
  56. Ferreira, M.I.; Silvestre, J.; Conceição, N.; Malheiro, C. Crop and stress coefficients in rainfed and deficit irrigation vineyards using sap flow techniques. Irrig. Sci. 2012, 30, 433–444. [Google Scholar] [CrossRef]
  57. Rodríguez, P.; Mellisho, C.D.; Conejero, W.; Cruz, Z.N.; Ortuno, M.F.; Galindo, A.; Torrecillas, A. Plant water relations of leaves of pomegranate trees under different irrigation conditions. Environ. Exp. Bot. 2012, 77, 19–24. [Google Scholar] [CrossRef]
  58. Girona, J.; Mata, M.; Goldhamer, D.A.; Johnson, R.S.; DeJong, T.M. Patterns of soil and tree water status and leaf functioning during regulated deficit irrigation scheduling in peach. J. Am. Soc. Hortic. Sci. 1993, 118, 580–586. [Google Scholar]
  59. Selles, G.; Berger, A. Physiological indicators of plant water status as criteria for irrigation scheduling. Acta Hortic. 1989, 278, 87–100. [Google Scholar] [CrossRef]
  60. McCutchan, H.; Shackel, K.A. Stem-water potential as a sensitive indicator of water stress in prune trees (Prunus domestica L. cv. French). J. Am. Soc. Hortic. Sci. 1992, 117, 607–611. [Google Scholar]
  61. Ferreira, M.I.; Valancogne, C.; Daudet, F.-A.; Ameglio, T.; Pacheco, C.A.; Michaelsen, J. Evapotranspiration and crop-water relations in a peach orchard. In Proceedings of the International Conference on “Evapotranspiration and Irrigation Scheduling”, San Antonio, TX, USA, 3–6 November 1996; pp. 61–69. [Google Scholar]
  62. Gucci, R.; Massai, R.; Xiloyannis, C.; Flore, J.A. The effect of drought and vapour pressure deficit on gas exchange of young kiwifruit (Actinidia deliciosa var. deliciosa) vines. Ann. Bot. 1996, 77, 605–613. [Google Scholar] [CrossRef]
  63. Goldhamer, D.A.; Fereres, E.; Mata, M.; Girona, J.; Cohen, M. Sensitivity of continuous and discrete plant and soil water status monitoring in peach trees subjected to deficit irrigation. J. Am Soc. Hortic. Sci. 1999, 124, 437–444. [Google Scholar]
  64. Silvestre, J.; Ferreira, M.I. Efects of irrigation on transpiration and water relations of vineyards, in the Teja Valley (central Portugal). Acta Hortic. 2000, 537, 305–312. [Google Scholar] [CrossRef]
  65. Naor, A.; Cohen, S. Sensitivity and variability of maximum trunk shrinkage, midday stem water potencial, and transpiration rate in response to withholding irrigation from field-grown apple trees. HortScience 2003, 38, 547–551. [Google Scholar]
  66. Malheiro, A.C.; Gonçalves, I.N.; Fernandes-Silva, A.A.; Silvestre, J.C.; Conceição, N.S.; Paço, T.A.; Ferreira, M.I. Relationships between relative transpiration of grapevines and plant and soil water status in Portugal's Douro wine region. Acta Hortic. 2011, 922, 261–267. [Google Scholar] [CrossRef]
  67. Intrigliolo, D.S.; Castel, J.R. Effects of regulated deficit irrigation on growth and yield of young Japanese plum trees. J. Hortic. Sci. Biotechnol. 2005, 80, 177–182. [Google Scholar] [CrossRef]
  68. Intrigliolo, D.S.; Puerto, H.; Bonet, L.; Alarcón, J.J.; Nicolas, E.; Bartual, J. Usefulness of trunk diameter variations as continuous water stress indicators of pomegranate (Punica granatum) trees. Agric. Water Manag. 2011, 98, 1462–1468. [Google Scholar] [CrossRef]
  69. Ferreira, M.I.; Conceição, N.; Pacheco, C.A.; Häusler, M. Análise de indicadores de desconforto hídrico durante ciclos de stress num olival intensivo no Alentejo. Atas Port. Hortic. 2012, 21, 217–226. [Google Scholar]
  70. Paço, T.; Ferreira, M.I.; Pacheco, C.A. Scheduling peach orchard irrigation in water stress conditions: Use of relative transpiration and predawn leaf water potential. Fruits 2013, 68, 147–158. [Google Scholar] [CrossRef]
  71. Silva, R.; Ferreira, M.I. A new microdendrometric index to quantify water status in kiwifruit. Acta Hortic. 2014, 1038, 43–50. [Google Scholar]
  72. Ennajeh, M.; Tounekti, T.; Vadel, A.M.; Khemira, H.; Cochard, H. Water relations and drought-induced embolism in olive (Olea europaea) varieties ‘Meski’ and ‘Chemlali’ during severe drought. Tree Physiol. 2008, 28, 971–976. [Google Scholar] [CrossRef] [PubMed]
  73. Fereres, E.; Goldhamer, D. Suitability of stem diameter variations and water potential as indicators for irrigation scheduling of almond trees. J. Hortic. Sci. Biotechnol. 2003, 78, 139–144. [Google Scholar] [CrossRef]
  74. Rieger, M.; Duemmel, M.J. Comparison of drought resistance among Prunus species from divergent habitats. Tree Physiol. 1992, 11, 369–380. [Google Scholar] [CrossRef] [PubMed]
  75. Lankes, C. Effect of water stress on transpiration and CO2 gas exchange of the apple leaf and fruit. Acta Hortic. 1985, 171, 305–314. [Google Scholar]
  76. Jorba, J.; Tapia, L.; Sant, D. Photosynthesis, leaf water potential, and stomatal conductance in Olea europaea under wet and drought conditions. Acta Hortic. 1984, 171, 237–246. [Google Scholar] [CrossRef]
  77. Tan, C.S.; Buttery, B.R. Response of stomatal conductance, transpiration, photosynthesis, and leaf water potential in peach seedlings to different watering regimes. HortScience 1982, 17, 222–223. [Google Scholar]
  78. Doltra, J.; Oncins, J.A.; Bonany, J.; Cohen, M. Evaluation of plant-based water status indicators in mature apple trees under field conditions. Irrig. Sci. 2007, 25, 351–359. [Google Scholar] [CrossRef]
  79. Velez, J.E.; Intrigliolo, D.S.; Castel, J.R. Scheduling deficit irrigation of citrus trees with maximum daily trunk shrinkage. Agric. Water Manag. 2007, 90, 197–204. [Google Scholar] [CrossRef]
  80. Huguet, J.G. Appréciation de l’état hydrique d’une plante à partir des variations micrométriques de la dimension des fruits ou des tiges au cours de la journée. Agronomie 1985, 5, 733–741. [Google Scholar] [CrossRef]
  81. Nortes, P.A.; Pérez-Pastor, A.; Egea, G.; Conejero, W.; Domingo, R. Comparison of changes in stem diameter and water potential values for detecting water stress in young almond trees. Agric. Water Manag. 2005, 77, 296–307. [Google Scholar] [CrossRef]
  82. Li, S.H.; Huguet, J.G.; Bussi, C. Irrigation scheduling in a mature peach orchard using tensiometers and dendrometers. Irrig. Drain. Syst. 1989, 3, 1–12. [Google Scholar] [CrossRef]
  83. Remorini, D.; Massai, R. Comparison of water status indicators for young peach trees. Irrig. Sci. 2003, 22, 39–46. [Google Scholar]
Horticulturae 03 00047 g001 550
Figure 1. Seasonal course (2009) of (a) Ψpd and (b) Ψst, with the relationships between those variables and noon stomatal conductance (gs); respectively (c,d), for the treatments (◊, 70% ETc; □, 40% ETc; ∆, 25% ETc) developing approximately to a weak, mild and severe water stress (see text for corresponding Ψpd ranges). The standard deviations of means are approximately within symbol width. Vineyard (Beja, Portugal).
Figure 1. Seasonal course (2009) of (a) Ψpd and (b) Ψst, with the relationships between those variables and noon stomatal conductance (gs); respectively (c,d), for the treatments (◊, 70% ETc; □, 40% ETc; ∆, 25% ETc) developing approximately to a weak, mild and severe water stress (see text for corresponding Ψpd ranges). The standard deviations of means are approximately within symbol width. Vineyard (Beja, Portugal).
Horticulturae 03 00047 g001
Horticulturae 03 00047 g002 550
Figure 2. Observed Ψpd (a) and Ψst of grapevines at 10:00 a.m. (b); 2:00 p.m. (c) and 6:00 p.m. (d) (solar noon at ≈ 1:45 p.m.) for the treatments described (Low Stress, Medium Stress and High Stress, see text) immediately before and during the 2010 stress cycle (8th to 16th August 2010). Irrigation events during the stress cycle: see text. The standard deviations of means are within symbol width. Vineyard (Beja, Portugal).
Figure 2. Observed Ψpd (a) and Ψst of grapevines at 10:00 a.m. (b); 2:00 p.m. (c) and 6:00 p.m. (d) (solar noon at ≈ 1:45 p.m.) for the treatments described (Low Stress, Medium Stress and High Stress, see text) immediately before and during the 2010 stress cycle (8th to 16th August 2010). Irrigation events during the stress cycle: see text. The standard deviations of means are within symbol width. Vineyard (Beja, Portugal).
Horticulturae 03 00047 g002
Horticulturae 03 00047 g003 550
Figure 3. Plum stem water potential along the day in the control (C, ∆) and stressed plots (DI, □) for four dates: (a) 1 July; (b) 8 July; (c) 14 July; (d) 22 July. Each point represents the average of 8 trees; the vertical bars represent the standard error of each mean. Hours are legal time (solar time = legal time − 2.7 h). Plum orchard (Badajoz, Spain).
Figure 3. Plum stem water potential along the day in the control (C, ∆) and stressed plots (DI, □) for four dates: (a) 1 July; (b) 8 July; (c) 14 July; (d) 22 July. Each point represents the average of 8 trees; the vertical bars represent the standard error of each mean. Hours are legal time (solar time = legal time − 2.7 h). Plum orchard (Badajoz, Spain).
Horticulturae 03 00047 g003
Horticulturae 03 00047 g004 550
Figure 4. Relationship between Ψst measured after solar noon and daily relative transpiration (RTr) of plum. Each point is the average of two trees only for the days when Ψst was measured during the last period of each stress cycle (2014–2016).
Figure 4. Relationship between Ψst measured after solar noon and daily relative transpiration (RTr) of plum. Each point is the average of two trees only for the days when Ψst was measured during the last period of each stress cycle (2014–2016).
Horticulturae 03 00047 g004
Table
Table 1. Meteorological conditions for the studied years in Experiment 1 and 2; data represent the year averages.
Table 1. Meteorological conditions for the studied years in Experiment 1 and 2; data represent the year averages.
YearP (mm)Taverage (°C)HRmax (%)HRmin (%)ETo (mm)
Experiment 1 Beja (Portugal)2009418.017.6693.3340.531311.50
2010734.617.0894.0145.441222.99
Experiment 2 Vegas Bajas (Spain)2010738.716.3188.0440.561317.70
2014506.716.3395.7442.721230.79
2015328.016.4593.0338.651310.50
2016546.016.3599.2542.961236.98
Table
Table 2. Plant indicators used and relationship with isohydricity observed following criteria described.
Table 2. Plant indicators used and relationship with isohydricity observed following criteria described.
Species/CultivarBehaviourPlant Water PotentialSDV Derived IndexesRTrOther IndexesReference
IsoAnisoDoubts ΨpdΨstMDS or RDTSTGROther
Prunus persica ‘Fire-Red’ NC 2 RGGG [59]
Prunus persica ‘French’ NCBG gs 1 [60]
Prunus persica ‘Cal Red’* GB gs, LT 3[58]
Prunus persica ‘H30’* G RDTS Tr, gs relat, θs[61]
Actinidia deliciosa ‘Deliciosa’* G gs, A, Tr[62]
Prunus persica ‘O’Henry’ *GGR MXTD MNTD θs 4[63]
Vitis vinifera ‘Trincadeira’* GB Tr, gs,[64]
Prunus persica ‘Andros’ * GGGG [9]
Malus domestica ‘Golden delicious’* BGG Ggs relat [65]
Vitis vinifera ‘Tempranillo’* GB gs[66]
Prunus salicina ‘Black Gold’ NC GR 5 [67]
Diospyros kaki. ‘Rojo Brillante’ *NC RR gs[10]
Punica granatum ‘Mollar de Elche’* GRB [68]
Prunus persica ‘Flordastar’ NC BG [11]
Olea europea ‘Arbequina’* G B 8B 8DMXTD/MXTD Tr, θs[69]
Punica granatum ‘Mollar de Elche’*,7 GB gs[57]
Prunus persica ‘Silver King’* G Tr[70]
Actinidia deliciosa ‘Hayward’ * BGR MDS (1-OGR) 6 gs, θs[71]
* Apparent behavior from the results presented by authors; 1 A relationship of Ψpd or Ψst difference versus relative gs or RTr was used; 2 NC = Not clear; plant does not have a clear behavior but more anisohydric, or G = good, R = regular, B = bad; 3 LT = leaf temperature; 4 Best is daily variations in θs; 5 SDV regular (RDTS required); 6 In agreement with suggestion [9] of combining both indexes; 7 Tends to anisohydric, towards the end of stress cycle; 8 Implicitly.

Share and Cite

MDPI and ACS Style

Blanco-Cipollone, F.; Lourenço, S.; Silvestre, J.; Conceição, N.; Moñino, M.J.; Vivas, A.; Ferreira, M.I. Plant Water Status Indicators for Irrigation Scheduling Associated with Iso- and Anisohydric Behavior: Vine and Plum Trees. Horticulturae 2017, 3, 47. https://doi.org/10.3390/horticulturae3030047

AMA Style

Blanco-Cipollone F, Lourenço S, Silvestre J, Conceição N, Moñino MJ, Vivas A, Ferreira MI. Plant Water Status Indicators for Irrigation Scheduling Associated with Iso- and Anisohydric Behavior: Vine and Plum Trees. Horticulturae. 2017; 3(3):47. https://doi.org/10.3390/horticulturae3030047

Chicago/Turabian Style

Blanco-Cipollone, Fernando, Sónia Lourenço, José Silvestre, Nuno Conceição, María José Moñino, Antonio Vivas, and Maria Isabel Ferreira. 2017. "Plant Water Status Indicators for Irrigation Scheduling Associated with Iso- and Anisohydric Behavior: Vine and Plum Trees" Horticulturae 3, no. 3: 47. https://doi.org/10.3390/horticulturae3030047

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop