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Article

Drought-Stressed Apple Tree Grafted onto Different Rootstocks in a Coastal Sandy Soil: Link between Fast Chlorophyll a Fluorescence and Production Yield

by
Andrea Colpo
1,2,
Sara Demaria
1,
Marzio Zaccarini
2,
Alessandro Forlani
2,
Antonia Senatore
1,2,
Elena Marrocchino
1,
Angela Martina
1 and
Lorenzo Ferroni
1,*
1
Department of Environmental and Prevention Sciences, University of Ferrara, Corso Ercole I d’Este 32, 44121 Ferrara, Italy
2
Consorzio Italiano Vivaisti Soc. Consortile A.R.L., Stat. Romea n. 116, S. Giuseppe di Comacchio, 44020 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Agronomy 2024, 14(6), 1304; https://doi.org/10.3390/agronomy14061304
Submission received: 11 May 2024 / Revised: 11 June 2024 / Accepted: 12 June 2024 / Published: 16 June 2024
(This article belongs to the Special Issue Qualitative and Quantitative Plant Screening Measurements for Yield and Quality Enhancement)
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Abstract

:
Domesticated apple is a drought-sensitive species that spread from continental to Mediterranean temperate regions, where it can particularly experience prolonged water stress. One strategy to improve drought resistance in apple is engrafting on selected rootstocks. This study explores the potential of fast chlorophyll a fluorescence for the comparison of rootstock sensitivity to drought, looking for significant correlations with fruit productivity. The experiment was conducted in a field located in the coastal Po River Plain, Northern Italy, characterized by a loamy sandy soil, particularly prone to drought (86% sand). Mature plants of apple cv. Superchief® Sandidge engrafted on three different rootstocks (CIVP21pbr, MM106, M26) were monitored throughout the summer of 2021 and compared between irrigated and non-irrigated parcels, and at the end of the season, fruit production was evaluated. Despite soil water tension only reaching −13 kPa, the non-irrigated plants experienced a small but consistent loss of Photosystem II (PSII) activity and a lesser capacity of light energy conservation in the photosynthetic electron transport chain. The fruit weight correlated with PSII photochemical indexes recorded during early drought, particularly FV/FM and PIABS; a correlation emerged between fruit number per plant and median values of electron transport parameters, including PITOT. Although all rootstocks underwent a 40% loss of productivity, the fluorescence parameters revealed a graded susceptibility to drought, M26 > CIVP21pbr > MM106, which matched well with the plant vigour. The least drought-sensitive MM106 produced less numerous but heavier fruits than the other two rootstocks.

1. Introduction

Rising temperatures, precipitation anomalies, heat waves, soil erosion, and infertility are a few examples of undesirable impacts of global climate change [1]. The regions that are already prone to recurrent drought periods are going to be further challenged by water stress and heat waves, with consequent reductions in crop yields [2]. The breeding of tolerant crop varieties against prolonged water scarcity is one of the main challenges in the Mediterranean basin, which is characterized by hot, dry summers and is predicted to suffer from increasingly severe droughts together with higher temperatures [3]. Additionally, in Mediterranean coastal regions, groundwater, serving as the primary irrigation source, frequently suffers degradation primarily due to salinization [4]. Increased salinity can mainly depend on seawater intrusion or be due to the mobilization of saline paleo-waters caused by the inadequate management of coastal aquifers [5].
The domesticated apple (Malus domestica Borkh.) is one of the most important continental fruit tree crops, spread from cool to temperate regions, including the Northern part of Mediterranean countries. The drought susceptibility of the apple tree prompts the research of more resistant varieties [6,7,8] or rootstocks that can help the plant respond to water scarcity and ensure more stable productivity [9,10,11,12]. Grafting apple scion onto drought-resistant rootstocks can be especially important in sandy soils. Soil type is a major irrigation criterion, and particularly, soil texture directly affects water retention and availability to plants: the higher the proportion of sand compared to clay, the shorter the drying time [13,14,15]. By dominating water uptake, soil texture influences photosynthesis because water availability is crucial for optimal stomatal function and carbon assimilation [16]. With larger pore spaces and lower cation exchange capacity than clay soils, sandy soils offer better aeration but may suffer from rapid nutrient leaching and experience larger temperature fluctuations, which can impair enzymatic activities involved in photosynthesis [17]. The soil water tension at which a plant potentially starts to be exposed to xylem cavitation and loss of cell turgor is extremely variable and ultimately depends on experience with a specific crop in each region [15]. A comprehensive literature review by Shock and Wang exemplifies some crops requiring irrigation in sandy soils already at around −10 kPa [15]. The use of non-invasive, near-instantaneous tools to monitor the physiological status of apple trees can help timely decisions on field irrigation and enable rational water use.
Photosynthesis is one of the primary physiological targets of water deficiency. Early effects depend on the limitations of CO2 diffusion caused by lower stomatal and mesophyll conductance, though with varying importance based on the duration of stress [18,19,20]. Despite drought having no direct influence on individual metabolic reactions, a reduced CO2 supply to the Calvin–Benson–Bassham cycle causes the downregulation in the photosynthetic electron transport chain [21]. If drought persists, the light energy absorbed in excess of its use in photosynthesis and dissipative pathways leads to the generation of reactive oxygen species, which impair the photosynthetic machinery, particularly Photosystem II (PSII) [22]. The damage severity induced by drought on the photosynthetic membrane tends to increase upon exposure to other concomitant stresses, such as high temperature, high irradiance, or fluctuating light [23,24,25]. PSII is the complex enzymatic machinery that allows electron extraction from the water molecule to feed the photosynthetic electron transport chain from plastoquinone to Photosystem I (PSI) and its downstream acceptors, thus supporting the need for reducing power by the carbon assimilation metabolism [26].
The fast kinetics of chlorophyll a fluorescence emission, also known as the OJIP transient, is an elective method to investigate structural and functional aspects of PSII and, therefore, it provides a powerful tool for monitoring a variety of stress conditions in plants [27,28,29,30,31,32,33]. The use simplicity of portable OJIP fluorometers, their accessible cost, and the availability of a consistent theoretical framework for data interpretation (so-called “JIP test”, [31,32,33]) have made fast chlorophyll a fluorescence one of the most popular tools in plant phenomics [34]. According to a recent literature review by Swoczyna et al. [35], in woody plants, drought stress is the most common problem dealt with using chlorophyll a fluorescence analysis. Several chlorophyll fluorescence parameters have been proposed as endpoints to detect drought stress in woody plants, including those linked to the PSII photochemical activity (mainly FV/FM) or probing the PSII donor and acceptor sides (related to fluorescence at 0.3 or 2 ms, respectively), or more complex and comprehensive indexes (for review, [35]). The sensitivity of parameters is very variable depending on species and cultivars, and some variations might result from compensatory mechanisms rather than reflect damage to the photosynthetic machinery [35,36,37]. Moreover, recent important advances in the relationship between PSII functioning and fluorescence emission challenge the common interpretation of the OJIP transient [38].
In this study, the potential of fast chlorophyll a fluorescence in monitoring the behaviour of apple rootstocks under water stress has been explored in an experimental field of the “Consorzio Italiano Vivaisti” (C.I.V.; www.civ.it, accessed on 13 June 2024) located in the coastal region of the Po River Plain in Northern Italy. C.I.V. is a private research centre engaged in the selection of rootstocks that enhance the apple’s performance, including its tolerance to water stress in sandy coastal soils. Inference about specific rootstock features, such as drought tolerance, is obtained during the selection phase, but expectations are not necessarily met in productive orchards. While productivity evaluations of drought-stressed mature apple trees require the completion of the seasonal life cycle, chlorophyll a fluorescence indices might reveal the early and poorly evident effects of drought stress. To verify this hypothesis, three rootstocks were monitored season-long and comparatively between irrigated and non-irrigated (non-irrigated) mature plants. The objectives of the study were (i) to identify the best chlorophyll fluorometric parameters to detect water stress early, even if it is mild, and (ii) to differentiate rootstocks according to their resistance to water stress.

2. Materials and Methods

2.1. Plant Material and Experimental Design

This study was performed on Malus domestica Borkh cv. Superchief® Sandidge trees engrafted on CIVP21pbr, M26, and MM106 rootstocks. CIVP21pbr is a deep-rooting, semi-dwarfing C.I.V. proprietary rootstock, potentially suitable for poor soils subjected to water shortage. Rootstocks M26 and MM106 were selected in the East Malling (Kent, UK) breeding program. M26 is a very popular semi-dwarfing rootstock, originally proposed to confer an advantage during periods of low soil water availability [39], although its drought tolerance seems not very high based on accumulating evidence [40,41,42]. MM106 is one of the most used semi-vigorous rootstocks, among other reasons, because of its claimed tolerance to a wide range of soils, including poor ones. The vigour allowed by CIVP21pbr is considered intermediate between M26 and MM106. Table 1 reports comparative data of Superchief® Sandidge apple engrafted on the three rootstocks under standard conditions.
The experiment was performed in 2021 on 10-years-old plants distributed in the same orchard espalier at one of the experimental fields of C.I.V. (San Giuseppe di Comacchio, Ferrara, Northern Italy; 44°46′01.14″ N–12°11′42.72″ E, altitude −1 m a.s.l.). The 220 m long espalier is oriented north–south; the planting size is 4 m × 1 m; the plant height is kept at ca. 2.5 m. During the vegetation period, the field was fertilized as appropriate and treated against diseases and pests according to common agricultural practices. Soil nutrient levels are typically sufficient or low, except for high levels of phosphorous and copper (Table A1). The source of water is the Po River through the irrigation system managed by the local water management agency (Consorzio di Bonifica Pianura di Ferrara, www.bonificaferrara.it, accessed on 13 June 2024). As per the characteristics reported in Table A2, water is slightly alkaline, quite hard, and moderately saline but does not pose a sodium risk and is, therefore, suitable for irrigation of most crops. The experimental field is equipped with a drip irrigation system, which allows for independent irrigation regimes in different parcels of the orchard. The dripline has a flow rate of 3.2 L h−1 m−1; nozzles are spaced 0.25 m so as to irrigate an area of approx. 1 m2, and irrigation is scheduled at 10:00 a.m. with a duration of one hour per day. The irrigation regime provides 6.4 mm of water per day, roughly corresponding to the daily evapotranspiration.
Within the row, two experimental parcels were identified; the distance between the two parcels was approx. 80 m. In each parcel, 3–5 plants per rootstock type were available. Season-long recordings of soil water tension (SWT) were performed at intervals of 30 min with a Watermark sensor (Irrometer, Riverside, CA, USA), and volumetric water content was monitored with a TriSCAN® probe (Sentek Technologies, Stepney, SA, Australia). Both sensors were connected online with a DAVIS Gateway EnviroMonitor (www.weatherlink.com, accessed on 13 June 2024) during 68 days of monitoring. A preliminary one-week analysis (first week of June) revealed in both parcels a stable water content of ca. 39% vol. at a depth of 30 cm without differences between the two parcels. Moreover, all plants were preliminarily analysed for chlorophyll fluorescence parameters revealing the uniformity of plants independent of the rootstock and parcel (Table A3).
One parcel was chosen as the control with full irrigation and the other as the treated (hereafter named “non-irrigated”), in which the irrigation was interrupted on the 9th of June 2021 until the end of the vegetation period. For the entire experiment, the chlorophyll a fluorescence emission was monitored at intervals of 7–10 days. At the end of the season, fruit production and quality parameters were collected.

2.2. Soil Analysis

To classify the soil, the methods reported by Marrocchino et al. were used [43]. Soil samples, after being quartered to obtain a representative amount to be analysed [44], were subjected to oxidation using a low concentration (16 vol) of H2O2 to break down organic matter and ensure thorough dispersion of clasts until the effervescence effect subsided entirely. Subsequently, soil samples underwent wet sieving to separate sandy material from muddy sediment using a 63 μm mesh. The obtained sandy fractions were oven-dried at 105 °C in glass beakers for a minimum of 24 h. After drying, the samples were weighed using a precision balance. Each sample was further quartered to obtain approx. 3 g for grain size analysis. This analysis was conducted using a sedimentation balance, which consists of a 2 m long sedimentation tube filled with water and topped with a lid. The lid served to hold the material, while the bottom contained a balance plate submerged in water. The sample was released from above, with larger particles settling on the plate first, followed by smaller ones. Weight accumulation on the plate was automatically recorded and correlated with particle size using the principle of Stokes’ Law via computer software. The analysis results were presented cumulatively, with the percentage of each individual particle size fraction determined by the difference in weight.
The volatile fraction was determined in 0.6 g aliquots of soil powder upon treatment for loss on ignition (L.O.I.) at 1000 °C in a muffle for 12 h [43]. L.O.I. allows estimation of the organic matter content in sediment (plant debris, microbial biomass, and other organic materials). To validate the L.O.I. procedure, calcimetric analyses were also carried out with a gas volumetric method [45]. The dried soil samples (105 °C, 24 h) were grounded to powder using an agate mortar grinder (Laarmann LMMG 100, Roermond, The Netherlands). The CaCO3 content was determined based on the chemical reaction between 0.5 g of sample with 10% HCl:
CaCO3 + 2HCl → CO2 + H2O + CaCl2
The percentage of CaCO3 in each sample was determined by measuring the quantity of CO2 developed; for each mole of CaCO3, one mole of CO2 is generally formed in the L.O.I. procedure, and the loss of weight is due only to volatile elements. In the case of the presence of carbonate, the procedure is only able to measure the loss of CO2. All soil analyses have been performed at the Department of Physics and Earth Sciences of the University of Ferrara.

2.3. Chlorophyll a Fluorescence Analysis

A continuous excitation Handy-PEA portable fluorometer was used to record the fast chlorophyll a fluorescence kinetics in the field using leaf clips (Hansatech Instruments, King’s Lynn, Norfolk, UK). Measurements were performed on the 4th–5th leaf from the branch apex at 10:00–13:00. After at least 20 min of dark acclimation in the leaf clip, the fluorescence transient was induced by a 1s-long saturating pulse of red light (wavelength 650 nm provided by the LEDs incorporated in the probe) at an irradiance of 3500 μmol photons m−2 s−1. The resulting OJIP transient was basically characterized according to the “JIP-test” concept [31,32,33]. The JIP-test is modelled on the “theory of energy fluxes”, which includes many technical and derived parameters; the validity of the latter is based on many assumptions (see, particularly, [33]). For the phenotyping purpose of this work, the use of basic structural parameters descriptive of the OJIP transient was preferred, and only a few selected JIP-test-derived parameters were included [46].
FO is the minimum chlorophyll fluorescence in the dark-acclimated state at step O sampled at 20 μs; FM is the maximum chlorophyll fluorescence in the dark-acclimated state at the plateau of the fluorescence transient (step P); FV is their difference FM − F0 and corresponds to PSII variable fluorescence. FV/FM and FV/FO were calculated as PSII photochemical indexes.
Upon double normalization of the OJIP transient between O and P, relative fluorescence values were calculated at noticeable time points: VK of the K band at 0.3 ms, VJ of the J step at 2 ms, VI of the I step at 30 ms. Although the actual position of the J and I steps can change depending on environmental conditions [47,48], for the treatment of large data sets, the fluorescence values were always sampled at 0.3, 2, and 30 ms, considering this an acceptable approximation in the phenotyping experiment.
The initial slope MO of the relative variable fluorescence (within 0.3 ms) was used to calculate the apparent antenna size of PSII, i.e., the light absorption flux per PSII reaction centre, ABS/RC [32]. The area comprised between the transient and FM was normalized on FV to obtain the Sm parameter. The performance indexes PIABS (performance index on absorption basis) and PITOT (performance index for energy conservation from exciton to the reduction of PSI terminal acceptors) were calculated as integrative parameters according to Strasser et al. [32,49].

2.4. Production Parameters

The pome fruits produced by each plant were counted and weighed. The level of fruit firmness was measured with an FTA-Fruit Texture Analyzer (Güss Manufacturing, Strand, South Africa). The starch degradation level was evaluated with a starch–iodine test according to Laimburg scale. For analysis of sweetness and acidity, the juice was obtained from ten randomly chosen apples per sample. Sweetness was expressed as Brix measured with an Atago Palette PR-32α refractometer (Atago Italia, Merlino, Italy); acidity was titrated with 0.1 N NaOH using a Titralab® TIM 840 Radiometer (Hach Lange, Düsseldorf, Germany) and converted to malic acid concentration.

2.5. Statistical Data Treatment

Data organisation, sorting, and descriptive statistics were performed with Microsoft Excel. OriginPro version 2024 (OriginLab Corporation, Northampton, MA, USA) was used for further statistical analyses and graphing. Soil texture was classified based on ternary graphs with sand, clay, and silt coordinates of 17 replicated samples. For chlorophyll fluorescence, 15 to 45 leaves were analysed per rootstock type and time point. A preliminary comparison of parameter time courses showed that any difference potentially due to drought stress was somehow hidden behind variations induced by other environmental factors. For a clearer presentation and to help disentangle the effect of drought stress, the average parameters for each rootstock were normalized on the corresponding irrigated control at each time point of monitoring; therefore, the latter was assigned the constant value of 1. Normalized average parameters recorded throughout the season, i.e., pooling all measurement points per treatment, were checked for significant differences from 1 using a one-sample Student’s t-test with a threshold set at p = 0.05. Quantitative production data were analysed by two-way ANOVA for the two variables “rootstock” and “irrigation regime” by setting the significance threshold at p = 0.05. For multivariate analysis, 11 fluorescence parameters (FV/FM was not included because it was redundant with FV/FO) and 7 production parameters were subjected to principal component analysis (PCA). PCA was run based on Pearson’s r correlation matrix and by setting the extraction of two components, which explained more than 75% of data variability. Eigenvalues and Eigenvectors were reported in a biplot graph. Correlation matrixes were built based on Pearson’s r coefficient, and the significance threshold was set at p = 0.05.

3. Results

3.1. Without Irrigation in a Sandy Soil, Apple Trees Were Exposed to Slight Chronic Water Shortage

In the ternary diagram in Figure 1a, the soil samples collected in the experimental field all clustered together, indicating the lack of significant heterogeneity. The soil mainly constituted of sandy fractions (86%, of which 8% was medium sand, 70% was fine sand, and 8% was very fine sand), while silt and clay contents represented less than 15% of the grain size distribution. The soil can be classified as loamy sand, according to the USDA-NRCS Soil Texture Classes (Figure 1a). It is part of the cartographic unit CER1 according to the Emilia Romagna Region Soil Map (1:50,000) [50] and belongs to the paleo-coastal dune sediments developed during the Po River Delta progradation [51,52,53].
The volatile and carbonate contents are two further crucial components to characterize sediments. The volatile content expressed as L.O.I. value was 6.28 ± 1.14%, higher than the CaCO3 content (5.0 ± 2.1%), resulting in an L.O.I./carbonate ratio of 1.5 ± 0.7 (average values with SD of N = 8 samples). The discrepancy between L.O.I. and carbonate was due to the presence of bivalve shells, primarily consisting of CaCO3 (calcite and aragonite). Because the organic matrix and shell structure of bivalves can contribute less to the LOI compared to other organic materials, the LOI/carbonate ratio was higher than 1 in the coastal sediments of the study area. Accordingly, the soil was scarce in organic matter (1.0 ± 0.6%) and subalkaline (pH ca. 8.0) (see also Table A1).
The interruption of irrigation in the treated parcel resulted in a progressive increase in SWT for 24 days. Three temporary drops in SWT corresponded to as many rainfall events (days 25, 34–37, and 53; Figure 1b and Figure A1), although rainfall was never sufficient to restore the water-saturated condition (0 kPa). The non-irrigated parcel received about 41 mm of rain, compared with the equivalent of 440 mm for the irrigated parcel. In the irrigated parcel, at a depth of 30 cm, the volumetric water content was approximately constant (39%) throughout the monitoring period. Conversely, in the non-irrigated parcel, it decreased to 33% until early July and then recovered very slowly (Figure 1b). Over the monitoring period, SWT was lower than −10 kPa for 40 days in the non-irrigated parcel. Therefore, for the entire season, the treated plants were exposed to a slight but chronic water shortage. No visual signs of leaf epinasty or wilting occurred.

3.2. A Small Loss of PSII Activity Occurred in the Non-Irrigated Plants

Examples of chlorophyll a fluorescence transients, both absolute and normalized, are shown in Figure 2 with reference to average curves recorded at day 21 when the lowest water content of the season was reached in the non-irrigated parcel (see Figure 1b). The fast kinetics of chlorophyll a fluorescence showed the typical features repeatedly reported in the literature [27,28,29,30,31,32,33,49]. Starting at step O from the minimal value F0, fluorescence increased progressively to its maximum at P, reaching FM in less than 1 s (Figure 2a). On a logarithmic timescale, the transients showed a first inflection after ca. 2–3 ms corresponding to the J step; the very fast O-J increase in fluorescence corresponds to the so-called “photochemical phase”, which is followed by the slower J-I-P rise during the “thermal phase” [47]. The second slope change after 30–40 ms corresponded to the I step (Figure 2b). In the graph, the approximate position of the K band is also shown at ca. 0.3 ms.
Fluorescence parameters normalized on the irrigated controls are shown in Figure 3. F0 and FM are the simplest parameters often used to monitor the onset of drought stress [54]. The water deficit did not have any significant effect on F0 throughout the experiment, while FM tended to be lower in the treated plants (Figure 3a,b). The simultaneous variation of F0 and FM characterizes the photochemical activity and structural dynamics of PSII in a complex way [36]. The photochemical FV/FM index varied significantly but minimally for all rootstocks; FV/F0 contains the same basic information as FV/FM but is more sensitive to stress [55,56], therefore making the loss of PSII functioning more evident in all treated rootstocks, especially in M26 (Figure 3c,d).
The functional state of the PSII donor side was probed using the VK/VJ ratio [57,58]. Higher average VK/VJ characterised all non-irrigated rootstocks, but particularly M26, quite closely matching the changes in SWT (Figure 3e). PSII photoinhibition or photodamage is usually accompanied by changes in the apparent PSII antenna size; for this reason, the JIP-test parameter ABS/RC can be an informative index to monitor the progression of drought stress. An increase in ABS/RC was evident in the first 20 days after irrigation was discontinued in the treated parcel, particularly in M26. Subsequently, the parameter fluctuated only slightly around the reference of the control parcel (Figure 3f). The variations in VK/VJ and ABS/RC were overall very similar to each other.

3.3. Drought Stress Lowered the Leaf’s Capacity of Light Energy Conservation

Energy flux theory assigns special importance to the relative fluorescence at the J and I steps, indicated as VJ and VI [31,32,33]. Such parameters, usually reported in the form of their complement to one, are related to the operation of the electron transport chain from PSII to the end acceptors of PSI and are additional candidates for monitoring drought stress. The 1 − VJ parameter monitors the PSII acceptor side and reflects the availability of oxidised plastoquinone for the reoxidation of QA− [59]. Despite statistical significance, 1 − VJ was negligibly lower in the treated parcel plants than in the corresponding controls (Figure 4a). 1 − VI is related to the reduction of the entire electron transport chain up to the acceptor side of PSI [47,60] and was consistently lower only in non-irrigated CIVP21pbr than the corresponding irrigated controls (Figure 4b). The variations of the (1 − VI)/(1 − VJ) ratio did not prove very informative with respect to the effect of drought stress (Figure 4c). Likewise, Sm, which is related to the general capacity of electron transport in the photosynthetic membrane [33,45], did not evidence statistically significant results (Figure 4d). However, two opposite trends could be observed, i.e., Sm values were generally higher than controls within 30–40 days without irrigation but subsequently lower.
In the JIP-test, various fluorescence parameters are combined into synthetic indices, providing comprehensive information on the potential photosynthetic performance of a plant. The PIABS performance index relates to the energy conservation from the photon absorption events to the reduction of the plastoquinone pool [32]. The incorporation of energy conservation events until the reduction of PSI end electron acceptors results in the PITOT performance index [49]. Notwithstanding their high variability, in the non-irrigated plants both indexes were lower than in the irrigated controls already during the first days of water shortage (Figure 4e,f). Focusing on the first 30 days, the monotonic decrease in PIABS in M26 allowed a clear segregation of this rootstock from the other two. PITOT was consistently and significantly lower in all three rootstocks under the non-irrigated condition but without any obvious differentiation among them (Figure 4f).

3.4. Drought Stress Severely Lowered Productivity

A marked loss in total fruit weight harvest per plant occurred for all rootstocks under the non-irrigated condition, ca. 40% less than in the irrigated controls without differences among the rootstocks (Table 2). The number of fruits produced per plant decreased for all rootstocks, although the loss was more marked for CIVP21pbr and MM106 (ca. 30% less) than M26 (ca. 10% less). Two-way ANOVA indicated the significant effect of the watering regime only, but not of rootstock or the interaction between the two factors. A very significant decrease in the single fruit weight occurred under the non-irrigated condition (p < 10−4); the significance of the rootstock also emerged (p < 0.05), with M26 producing the heaviest fruits and CIVP21pbr the lightest. However, the decrease in average fruit weight under drought was greater in M26 (about 30% less) than in the other two rootstocks (about 20% less). For a more complete description, some qualitative parameters were also surveyed and reported in Table A4. The rootstock influenced the pome firmness (p < 0.05) and marginally the starch content (p = 0.057) without any significant effect of the watering regime. Brix and malic acid were minimally variable among the sample types.

3.5. Relationships between Chlorophyll Fluorescence and Productivity

To find the fluorescence parameters more closely linked to the productivity results, a PCA analysis was conducted. Given the wide oscillations in parameters during the monitoring period and the rejection of the normality hypothesis for most parameters (Shapiro–Wilk test with a threshold set at 5%), we used the medians obtained for each parameter (Table A5, Table A6, Table A7 and Table A8). The biplot in Figure 5a neatly separates the irrigated rootstocks in the right quadrants from the non-irrigated ones in the left quadrants, therefore showing that the horizontal principal component, explaining more than 50% of the variability, was related to the watering regime. This component, associated with productivity parameters, was dominated by the comprehensive performance indexes, PIABS and PITOT. The fruit number per plant and PITOT were almost perfectly aligned and close to the vectors related to the electron transport capacity (1 − VJ, 1 − VI, Sm). The fruit ponderal parameters were instead more related to the PSII function (FV/F0). The vertical component, explaining ca. 26% of the variability, included the qualitative parameters; based on the sample distribution, this component reflected the rootstock specificity.
To analyse the predictive potential of chlorophyll a fluorescence in revealing diverging rootstock sensitivities to drought stress, PCA analysis was repeated using the values obtained just after two weeks from the interruption of irrigation (Figure 5b). This time point may be of particular interest to growers: although the −10 kPa SWT threshold that often requires the start of irrigation in sandy soil was not yet reached [15], the sensitivity of the fluorescence parameters could already allow revealing the different susceptibilities of the rootstocks to water shortage. Even at this early stage, the vector of the average fruit weight was close to FV/F0 and, moreover, completely overlapped with PIABS. The association between PITOT and the fruit number per plant was also present, but it was unrelated to electron transport parameters.
The matrixes reported in Figure A2 allow one to appreciate the consistent significant correlation between fruit weight and FV/F0. A smaller fruit number per plant corresponds to an increased F0 at an early stage of monitoring; with the whole dataset, significant positive correlations emerge with electron transport capacity parameters. The performance indexes followed these changes: PIABS showed an early but temporary good correlation with the fruit weight, while PITOT became a good predictor of the fruit number later on. The average fruit weight correlated negatively with the pulp sweetness expressed as Brix.

4. Discussion

A soil with an SWT equal to or slightly below −10 kPa is generally considered nearly saturated with water and does not require irrigation [15]. However, the SWT irrigation criterion is highly variable depending on the specific combination of crop and soil type [15]. For example, in silty loam soil, an SWT threshold for apple tree irrigation was reported to be around −30 kPa [61]. Very different is the situation in the study area, which is characterized by loamy sandy soil without significant heterogeneity (Figure 1a). The sandy soil texture is characterised by relatively high permeability, i.e., a high capacity for the soil to allow the passage of water [13,17,62]. A coarse-textured soil, due to the presence of sand particles, allows rapid water drainage, which prevents waterlogging, reduces the risk of standing water, and promotes good aeration. The presence of some silt and clay (14%) provides the soil with enough cohesion to resist erosion by wind and water [62]. Moreover, a significant carbonate mineral store in bivalve shells can have a stabilising effect on the soil, preventing acidification and fostering plant growth [63]. Altogether, the analysed coastal sandy soil is suitable for agriculture but only if productivity can be maintained by an efficient use of irrigation and fertilizers [62]. Field management, based on the experience of C.I.V. growers, consists of maintaining the STW above −10 kPa by seamless drip irrigation throughout the summer. Although under the non-irrigated regime, the soil was sufficiently wet, with SWT decreasing at most down to −13 kPa (Figure 1b), empiric knowledge appears well grounded, as confirmed by the strong losses in fruit production with all rootstocks (Table 2). Lower plant performance under water deficit is very likely due to a combination of direct carbon losses (stomata closure) and energy-consuming hydraulic and photosynthetic adjustments [42]. However, the absence of any visible drought stress symptom (e.g., epinasty) makes it very challenging to drive decisions about irrigation plans or the selection of rootstocks. Considering the weakness of the SWT criterium for apple cultivated in sandy soil, this report explores the use of plant-based indicators obtained by fast chlorophyll a fluorescence and looks for links with fruit productivity. The selection of fluorescence parameters as endpoints for monitoring drought stress is more complex than for other abiotic stresses because water shortage does not have early direct effects on PSII, and, moreover, physiological adjustments may enhance PSII resistance [64,65].

4.1. The Fruit Weight Is Related to PSII Photochemical Indexes during Early Drought

Ideally, a good candidate parameter should allow early predictions of end-of-season productivity, and the PSII photochemical index FV/F0 can be one of them with respect to the fruit weight (Figure 5). For many years, the sister parameter FV/FM has been more popular than FV/F0 mainly because, in the pure “QA model” of the OJIP transient, it is interpreted as the maximum quantum yield of PSII (for review [33]). Recently, the results obtained by Garab’s group made it very clear that FV/FM cannot be equated with the quantum efficiency of PSII, albeit it can still be used to monitor PSII functioning [38,66]. Considering the meaning redundancy of FV/FM and FV/F0, the wider variation range of the latter makes it preferable to the former [55,56], as it also emerges in this report (Figure 3c,d). The literature is not consistent about the responsivity of these photochemical indices to drought in woody plants [35]. The PSII photoinhibition meant by a decrease in FV/FM and FV/F0 is generally a late effect of drought, not triggered directly by drought but by other co-occurring environmental stresses, such as intense light and high temperature [28,35,67]. This is almost certainly the case for non-irrigated apple monitored during the warmest months in Northern Italy. Other early predictors of productivity are directly linked to the PSII photochemical indices. The partial loss of activity of a PSII population corresponds to a larger apparent PSII antenna size (ABS/RC), basically because an unchanged antenna bed serves less abundant active PSII [31]. Less straightforward was VK/VJ, whose increase was previously suggested to offer a tool to monitor the occurrence of and the recovery from drought stress [68] and was indeed sometimes applied in woody species [35]. Nonetheless, Brestič and Živčak demonstrated that VK/VJ is completely insensitive to drought stress (pp. 41–43 in [28]). An increase in VK/VJ during drought is explained by the deactivation of the oxygen-evolving complex caused by co-occurring heat stress [57]. In this experiment with apple, the obviously parallel variations of ABS/RC and VK/VJ suggest that both parameters reflect the changes in the OJIP curve slope within 0.3 ms, and, therefore, it is not possible to reliably disentangle a genuine disrupting effect of drought on PSII donor side from the concomitant increase in the apparent PSII antenna size (Figure 3e,f).
PIABS is another good endpoint for monitoring apple plants’ early response to drought (Figure 4e). Because this integrative parameter is calculated by combining FV/F0, ABS/RC, and VJ, the last being poorly sensitive to drought in this experiment (Figure 4a), it is not surprising that PIABS tends to be more sensitive than simpler photochemical indices [29,69]. Overall, the early loss of PSII functionality means that in apple a slight water deficit decreases the electrons made available to the carboxylation phase of photosynthesis. Such a response can represent a short-term acclimation response against a lower electron sink capacity of the Calvin–Benson–Bassham cycle, which is a very well-known consequence of the stomatal closure [18].

4.2. The Fruit Number per Plant Relates to Late Changes in Electron Transport Parameters

The predictability of the fruit number per plant from early fluorescence parameters is quite weak. Only F0 has some potential in this respect. Using continuous excitation fluorometers, the absolute fluorescence values, i.e., not combined in unitless ratios, depend on a variety of instrumental and biological factors, including leaf structure and composition [27]. Nevertheless, F0 found some applications to monitor early drought stress, for example, in the Eurasian grapevine (Vitis vinifera L.) [70].
More interestingly, the correlations involving the fruit number emerge from the study of the medians, pointing especially to PITOT (Figure 5a and Figure A2, Table A8). A superior sensitivity of PITOT to detect plant tolerance to drought has been shown [28,66,71], and Mihaljević et al. have indeed used PITOT to compare the drought stress sensitivity of some apple cultivars [6]. The parameter incorporates into PIABS the efficiency of electron transports up to the acceptors downstream of PSI [32]. In non-irrigated apple trees, the lower PITOT is linked to a lower transport efficiency from the plastoquinone pool to the end acceptors of PSI (Figure 5a and Figure A2a). The negative impact of drought stress on the I-P phase amplitude has been evidenced in the literature, e.g., in barley, the decrease in 1 − VI was shown to depend on the cultivar sensitivity to drought [60]. The I-P phase has been associated with the relative PSI activity and amount [60,72] or, more comprehensively, with the relative pool of PSI end electron acceptors [46,73]. The median Sm, which is a proxy for the electron transporters per PSII-PSI chain [33], was likewise negatively correlated with the fruit number per plant, which is quite interesting if compared with the complex time course of this parameter. A slight Sm excess is an expected consequence of the decreased proportion of functional PSII centres (lower FV/F0). However, especially after 35 days without irrigation, Sm tended to stabilise at lower values (Figure 4d). In woody plant species like apple, the leaf life extends throughout the entire season, which can allow the leaf to recover from the drought-induced damage and to adjust the electron transport chain components on the long-term [35], in this case, the relative amount of PSI and its downstream electron acceptors. Therefore, despite the season-long water deficit, the apple plants succeeded in keeping FV/F0 and PITOT relatively stable, though somewhat lower than in controls (Figure 3d and Figure 4f).

4.3. The Chlorophyll a Fluorescence Parameters Allow Rootstock Differentiation Based on Drought Sensitivity

Based on the ponderal production per plant, the three rootstocks appear roughly equivalent to each other with respect to drought stress susceptibility, each undergoing a loss of yield per plant by 40%. However, interestingly, the scores assigned in PCA highlight the highest irrigated-to-non-irrigated distance for M26 and the lowest for MM106: M26 (2.38) > CIVP21pbr (2.03) > MM106 (1.62) (Figure 5a). Based on chlorophyll a fluorescence, drought stress was indeed more challenging for the Superchief® Sandidge apple engrafted on M26 than on the other two rootstocks, particularly MM106. Such a graded susceptibility to drought corresponds well to the known decreasing vigour from MM106 to CIVP21pbr to M26. Han et al. have recently tried to link the drought susceptibility of apple rootstocks to integrated changes in leaf gas exchange and hydraulic conductance, including modulations of the symplastic water flows mediated by root and leaf aquaporins [42]. Compared to apple dwarfing rootstocks (M9, SH6, GM256) and semi-dwarfing M26, the more vigorous MM106 was found to preserve high net photosynthesis under water deficit conditions [42]. The drought tolerance of MM106 could primarily depend on a distinctively lower root hydraulic conductance than in M26 [42], which can limit vessel cavitation and is associated with a higher shoot vigour [74]. This advantage of MM106 can explain its success in limiting the PIABS decrease from even the first weeks of water deficit (Figure 4e). MM106 also appears as the most efficient rootstock in supporting the adjustment of the photosynthetic machinery. The overall cost of regulation in MM106 seems to be the loss of some fruits. In contrast to MM106, PIABS is consistently lower in drought-stressed M26 throughout the season. With a higher and not drought-responsive root hydraulic conductance [42], M26 must rely more on short-term responses, particularly stomatal closure under water deficit [42]. The consequence of the expected permanent limitation of CO2 supply to photosynthesis is the chronic loss of PSII photochemical activity observed in our study (Figure 3d). Interestingly, obvious compensative adjustments of the photosynthetic electron transport chain do not emerge in M26. We can tentatively hypothesise that a less efficient overall regulation under drought makes M26 less prone to fruit loss, yet with the consequence that fruits are lighter than in the irrigated parcel. With respect to the fruit productivity under drought, CIVP21pbr is more similar to MM106 than M26.

5. Conclusions

The application of fast chlorophyll a fluorescence method in the field is challenged by the continuous variability of environmental variables, which can make it difficult to discern specific drought-responsive parameters to support apple rootstock selection programmes. Nevertheless, in this report, we have shown the feasibility of this approach, providing evidence for significant correlations between fluorescence and production parameters. With respect to the objective of identifying the best parameters to detect water stress, particularly interesting is the use of the comprehensive indices PIABS and PITOT. As regards the objective of differentiating rootstocks according to their resistance to water stress, the multivariate analysis of fluorescence parameters, which encompass the fundamental steps of energy conservation from light absorption to final electron acceptors reduction, allowed an unambiguous ordering of rootstocks based on drought susceptibility. In particular, the drought tolerance series MM106 > CIVP21pbr > M26 closely matched the increasing vigour of the rootstocks. The effectiveness of chlorophyll a fluorescence appears promising for the scope of rootstock characterisation and selection aimed at the cultivation of apple in marginal lands, such as coastal sandy fields, which are predicted to be increasingly used for agriculture under the current and future scenarios of climate change.

Author Contributions

Conceptualization, A.C., L.F. and M.Z.; methodology, L.F. and E.M.; formal analysis, S.D. and L.F.; investigation, A.C., L.F., M.Z., A.F., A.S., E.M. and A.M.; resources, M.Z. and A.F.; data curation, A.C., S.D. and A.M.; writing, L.F. and E.M.; supervision, L.F.; project administration, L.F.; funding acquisition, L.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Camera di Commercio, Industria, Artigianato e Agricoltura di Ferrara (Bando 2019), and by the University of Ferrara.

Data Availability Statement

Raw data that support the findings of this study are made available upon request.

Acknowledgments

The authors are grateful to Lucrezia Felletti (C.I.V.) for the careful technical support during fruit analyses.

Conflicts of Interest

This research used rootstock CIVP21pbr developed, patented, and owned by C.I.V. (UK Patent n. 18974, released on the 11th of March 2019). The C.I.V. personnel (A.C., M.Z., A.F., A.S.) participated in the design of the study and in the collection of the data and their analysis.

Appendix A

Table A1. Typical ranges of soil nutrients in the experimental field before the experiment. Analyses were outsourced to the external Company LabGhedini (Ferrara, Italy) to be compared with reference agronomic ranges. Values are expressed in mg kg−1.
Table A1. Typical ranges of soil nutrients in the experimental field before the experiment. Analyses were outsourced to the external Company LabGhedini (Ferrara, Italy) to be compared with reference agronomic ranges. Values are expressed in mg kg−1.
ParameterField ValuesReference Range
Total Nitrogen600–7001000–2000
Assimilable Phosphorus40–5010–20
Exchangeable Potassium70–10080–160
Exchangeable Magnesium68–120120–180
Assimilable Iron21–235–130
Assimilable Manganese5.4–6.21.6–30
Assimilable Copper3.8–4.41–6
Assimilable Zinc2.2–2.41–30
Assimilable Boron0.2–0.30.3–0.8
Organic matter %0.7–1.01.5–3.0
pH8.0–8.2
Table A2. Physical and chemical properties of the irrigation water in the experimental site. Typical values based on routine analyses during the summer period (outsourced to the external Company LabGhedini, Ferrara, Italy).
Table A2. Physical and chemical properties of the irrigation water in the experimental site. Typical values based on routine analyses during the summer period (outsourced to the external Company LabGhedini, Ferrara, Italy).
Parameter
pH8.2
Electrical conductivity (μS cm−1)855
Total dissolved solids (mg L−1)600
Chloride as NaCl (mg L−1)292
Calcium (mg L−1)53
Magnesium (mg L−1)25
Potassium (mg L−1)7.8
Sodium (mg L−1)72
Sodium adsorption ratio (SAR)2.0
Hardness (°F)23.5
Table A3. Selected chlorophyll fluorescence parameters measured in plants before the interruption of irrigation. These parameters were compared for the three rootstocks in parcels 1 and 2; values are means with standard deviations of N = 18–40 measurements. ANOVA did not highlight significant differences (threshold at p < 0.05). After this preliminary check, the irrigation was interrupted in parcel 2.
Table A3. Selected chlorophyll fluorescence parameters measured in plants before the interruption of irrigation. These parameters were compared for the three rootstocks in parcels 1 and 2; values are means with standard deviations of N = 18–40 measurements. ANOVA did not highlight significant differences (threshold at p < 0.05). After this preliminary check, the irrigation was interrupted in parcel 2.
RootstockParcelFV/FMFV/F0PIABSPITOT
CIVP21pbr1 (irrigated)0.826 ± 0.0224.33 ± 0.666.52 ± 2.317.78 ± 1.85
2 (non-irrigated)0.818 ± 0.0174.09 ± 0.526.11 ± 2.278.07 ± 1.84
MM1061 (irrigated)0.830 ± 0.0124.39 ± 0.386.09 ± 1.707.53 ± 1.89
2 (non-irrigated)0.827 ± 0.0124.32 ± 0.396.56 ± 1.557.63 ± 1.49
M261 (irrigated)0.821 ± 0.0254.16 ± 0.706.08 ± 2.377.61 ± 2.57
2 (non-irrigated)0.822 ± 0.0184.17 ± 0.556.12 ± 2.157.21 ± 1.62
F(5184)
p		 1.941.490.320.73
0.090.190.900.60

Appendix B

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Figure A1. Precipitation (bars) and average daily air temperature (line) during the monitoring season (June–August 2021).
Figure A1. Precipitation (bars) and average daily air temperature (line) during the monitoring season (June–August 2021).
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Appendix C

Table A4. Pome qualitative parameters in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. For firmness and starch level, the values are means with standard errors of N = 10 randomly chosen fruits per treatment. The same fruits were pooled and homogenized, and the homogenate was analysed for Brix and titrated for malic acid concentration.
Table A4. Pome qualitative parameters in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. For firmness and starch level, the values are means with standard errors of N = 10 randomly chosen fruits per treatment. The same fruits were pooled and homogenized, and the homogenate was analysed for Brix and titrated for malic acid concentration.
RootstockTreatmentFirmness
kg cm−2		Starch Level
(Laimburg Scale) 		BrixMalic Acid
g L−1
CIVP21pbrIrrigated8.82 ± 0.151.80 ± 0.0813.33.87
Non-irrigated8.70 ± 0.181.85 ± 0.1513.14.37
MM106Irrigated8.35 ± 0.232.35 ± 0.2412.14.08
Non-irrigated8.79 ± 0.222.05 ± 0.6413.44.60
M26Irrigated7.99 ± 0.171.90 ± 0.1011.54.56
Non-irrigated8.38 ± 0.171.95 ± 0.1213.34.19

Appendix D

Table A5. Minimum (F0) and maximum (FM) chlorophyll a fluorescence in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type).
Table A5. Minimum (F0) and maximum (FM) chlorophyll a fluorescence in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type).
RootstockTreatmentF0FM
CIVP21pbrIrrigated[453] 476 [513][2360] 2528 [2689]
Non-irrigated[460] 483 [517][2326] 2498 [2654]
MM106Irrigated[466] 488 [521] [2469] 2613 [3792]
Non-irrigated[465] 493 [518] [2430] 2580 [2704]
M26Irrigated[472] 494 [536] [2550] 2698 [2882]
Non-irrigated[472] 496 [521] [2307] 2498 [2654]
Table A6. Chlorophyll a fluorescence parameters related to PSII function in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
Table A6. Chlorophyll a fluorescence parameters related to PSII function in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
RootstockTreatmentFV/F0VK/VJABS/RC
CIVP21pbrIrrigated[3.85] 4.34 [4.68][0.085] 0.092 [0.104][1.37] 1.45 [1.59]
Non-irrigated[3.72] 4.13 [4.45][0.090] 0.098 [0.108][1.40] 1.52 [1.61]
MM106Irrigated[4.00] 4.40 [4.71][0.089] 0.097 [0.108][1.40] 1.49 [1.61]
Non-irrigated[3.80] 4.25 [4.61][0.090] 0.098 [0.109][1.40] 1.50 [1.61]
M26Irrigated[4.05] 4.48 [4.71][0.089] 0.097 [0.106][1.42] 1.50 [1.61]
Non-irrigated[3.62] 3.99 [4.31][0.094] 0.103 [0.114][1.46] 1.56 [1.68]
Table A7. Chlorophyll a fluorescence parameters related to photosynthetic electron transport in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
Table A7. Chlorophyll a fluorescence parameters related to photosynthetic electron transport in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
RootstockTreatment1 − VJ1 − VI(1 − VJ)/(1 − VJ)Sm
CIVP21pbrIrrigated[0.661] 0.685 [0.703][0.344] 0.371 [0.394][0.504] 0.543 [0.584][31.1] 33.1 [36.6]
Non-irrigated[0.650] 0.674 [0.697][0.322] 0.353 [0.385][0.485] 0.525 [0.575][29.2] 32.3 [35.7]
MM106Irrigated[0.656] 0.676 [0.698][0.329] 0.360 [0.382][0.490] 0.533 [0.570][28.4] 31.9 [34.7]
Non-irrigated[0.648] 0.672 [0.693][0.314] 0.346 [0.371][0.464] 0.516 [0.560][27.6] 30.3 [34.2]
M26Irrigated[0.659] 0.679 [0.699][0.338] 0.363 [0.389][0.495] 0.530 [0.574][28.4] 32.1 [35.1]
Non-irrigated[0.646] 0.666 [0.689][0.324] 0.356 [0.387][0.482] 0.535 [0.585][28.1] 31.7 [35.7]
Table A8. Chlorophyll a fluorescence-based performance indexes in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
Table A8. Chlorophyll a fluorescence-based performance indexes in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are medians with 1st and 3rd quartile in brackets (N = 248–417 per sample type). For definitions, see the main text.
RootstockTreatmentPIABSPITOT
CIVP21pbrIrrigated[4.95] 6.48 [7.98][6.27] 7.69 [8.83]
Non-irrigated[4.41] 5.73 [6.87][5.00] 6.36 [7.48]
MM106Irrigated[4.90] 6.18 [7.48][5.64] 6.95 [8.22]
Non-irrigated[4.56] 5.89 [7.20][4.98] 6.17 [7.15]
M26Irrigated[5.19] 6.33 [7.53][6.05] 7.22 [8.68]
Non-irrigated[4.17] 5.18 [6.27][4.84] 6.01 [7.20]
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Figure A2. Correlation matrixes with chlorophyll a fluorescence and productivity parameters. For the former, the medians obtained with the entire dataset or the values on the 14th day after watering interruption are shown in (a) and (b), respectively. The graded colour scales are based on Pearson’s r. Asterisks mark significant correlations with p < 0.05. Parameter definitions are given in the main text.
Figure A2. Correlation matrixes with chlorophyll a fluorescence and productivity parameters. For the former, the medians obtained with the entire dataset or the values on the 14th day after watering interruption are shown in (a) and (b), respectively. The graded colour scales are based on Pearson’s r. Asterisks mark significant correlations with p < 0.05. Parameter definitions are given in the main text.
Agronomy 14 01304 g0a2

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Figure 1. (a) Classification of the soil in the experimental field according to the USDA-NRCS Soil Texture Classes (N = 17 samples). (b) Soil water tension in the non-irrigated parcel during the monitoring season and comparative volumetric water content at a depth of 30 cm in irrigated and non-irrigated parcels.
Figure 1. (a) Classification of the soil in the experimental field according to the USDA-NRCS Soil Texture Classes (N = 17 samples). (b) Soil water tension in the non-irrigated parcel during the monitoring season and comparative volumetric water content at a depth of 30 cm in irrigated and non-irrigated parcels.
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Figure 2. Examples of chlorophyll a fluorescence induction curves in Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26, either irrigated or not (drought). (a) Average curves from data recorded on the 30th of June 2021 (21 days without irrigation in the treated parcel). Position of F0 and FM are indicated. (b) The same curves as in (a) after double normalization between F0 and FM. The noticeable steps of the fluorescence induction are indicated.
Figure 2. Examples of chlorophyll a fluorescence induction curves in Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26, either irrigated or not (drought). (a) Average curves from data recorded on the 30th of June 2021 (21 days without irrigation in the treated parcel). Position of F0 and FM are indicated. (b) The same curves as in (a) after double normalization between F0 and FM. The noticeable steps of the fluorescence induction are indicated.
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Figure 3. Variation of chlorophyll a fluorescence parameters related to PSII activity in non-irrigated Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26. Relative variations in parameters are shown compared to the irrigated control, which was assigned the value 1. (a) Minimum fluorescence F0. (b) Maximum fluorescence FM. (c) PSII photochemistry index FV/FM. (d) PSII photochemistry index FV/F0. (e) PSII donor side integrity parameter VK/VJ. (f) Absorption flux per PSII reaction centre ABS/RC. Means of N = 15–45 leaves per rootstock with standard deviations represented as coloured bands. p values were obtained from one-sample Student’s t test, with H0 stating that the parameter was not different from 1 value assigned to the irrigated controls.
Figure 3. Variation of chlorophyll a fluorescence parameters related to PSII activity in non-irrigated Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26. Relative variations in parameters are shown compared to the irrigated control, which was assigned the value 1. (a) Minimum fluorescence F0. (b) Maximum fluorescence FM. (c) PSII photochemistry index FV/FM. (d) PSII photochemistry index FV/F0. (e) PSII donor side integrity parameter VK/VJ. (f) Absorption flux per PSII reaction centre ABS/RC. Means of N = 15–45 leaves per rootstock with standard deviations represented as coloured bands. p values were obtained from one-sample Student’s t test, with H0 stating that the parameter was not different from 1 value assigned to the irrigated controls.
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Figure 4. Variations of chlorophyll a fluorescence parameters related to the light energy conservation in the photosynthetic electron transport chain in non-irrigated Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26. Relative variations in parameters are shown compared to the irrigated control, which was assigned the value 1. (a) Complement to relative fluorescence at step J, 1 − VJ. (b) Complement to relative fluorescence at step I, 1 − VI. (c) (1 − VI)/(1 − VJ) ratio. (d) Normalized area Sm between the OJIP transient and FM. (e) Performance index on absorption basis, PIABS. (f) Total performance index on absorption basis, PITOT. Means of N = 15–45 leaves per rootstock with standard deviations represented as coloured bands. p values were obtained from one-sample Student’s t test, with H0 stating that the parameter was not different from 1 value assigned to the irrigated controls.
Figure 4. Variations of chlorophyll a fluorescence parameters related to the light energy conservation in the photosynthetic electron transport chain in non-irrigated Superchief® Sandidge apple trees engrafted on rootstocks CIVP21pbr, MM106, M26. Relative variations in parameters are shown compared to the irrigated control, which was assigned the value 1. (a) Complement to relative fluorescence at step J, 1 − VJ. (b) Complement to relative fluorescence at step I, 1 − VI. (c) (1 − VI)/(1 − VJ) ratio. (d) Normalized area Sm between the OJIP transient and FM. (e) Performance index on absorption basis, PIABS. (f) Total performance index on absorption basis, PITOT. Means of N = 15–45 leaves per rootstock with standard deviations represented as coloured bands. p values were obtained from one-sample Student’s t test, with H0 stating that the parameter was not different from 1 value assigned to the irrigated controls.
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Figure 5. Principal components analysis of chlorophyll a fluorescence and productive parameters of Superchief® Sandidge apple engrafted on the three rootstocks CIVP21pbr, MM106, M26 under two watering regimes (w, irrigation; d, drought stress). (a) Biplot built using the median fluorescence parameters measured during the entire season. (b) Biplot built using the fluorescence parameters measured during the 14th after the interruption of irrigation. The vectors of the fluorescence or productive parameters are coloured in blue or purple for fluorescence or productive parameters, respectively.
Figure 5. Principal components analysis of chlorophyll a fluorescence and productive parameters of Superchief® Sandidge apple engrafted on the three rootstocks CIVP21pbr, MM106, M26 under two watering regimes (w, irrigation; d, drought stress). (a) Biplot built using the median fluorescence parameters measured during the entire season. (b) Biplot built using the fluorescence parameters measured during the 14th after the interruption of irrigation. The vectors of the fluorescence or productive parameters are coloured in blue or purple for fluorescence or productive parameters, respectively.
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Table 1. Main features of Superchief® Sandidge apple engrafted on the three rootstocks analysed in this study (Consorzio Italiano Vivaisti, comparison trial with apple planted in 2009).
Table 1. Main features of Superchief® Sandidge apple engrafted on the three rootstocks analysed in this study (Consorzio Italiano Vivaisti, comparison trial with apple planted in 2009).
RootstockTrunk Cross Section
(cm2)		Fruit Yield per Trunk Section
(kg cm−2)		Cumulative Production
(kg plant−1)		Average Fruit Weight
(g)		Plant Height
(m)
CIVP21pbr24.650.3720.712852.37
MM10616.340.3716.092702.37
M2614.570.4214.402742.21
Table 2. Productivity at the end of the season in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are means with standard errors of N = 3–5 plants per treatment.
Table 2. Productivity at the end of the season in Superchief® Sandidge apple engrafted on the three rootstocks under two watering regimes. Values are means with standard errors of N = 3–5 plants per treatment.
RootstockTreatmentFruit Number
per Plant		Harvest Weight per Plant (kg)Fruit Weight
(kg)
CIVP21pbrIrrigated63.0 ± 4.213.6 ± 1.00.215 ± 0.008
Non-irrigated44.8 ± 7.07.8 ± 1.40.172 ± 0.010
MM106Irrigated55.6 ± 6.313.7 ± 1.70.245 ± 0.006
Non-irrigated35.7 ± 13.77.9 ± 4.10.201 ± 0.027
M26Irrigated54.8 ± 8.014.8 ± 2.40.267 ± 0.006
Non-irrigated49.3 ± 6.59.1 ± 1.80.182 ± 0.018
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Colpo, A.; Demaria, S.; Zaccarini, M.; Forlani, A.; Senatore, A.; Marrocchino, E.; Martina, A.; Ferroni, L. Drought-Stressed Apple Tree Grafted onto Different Rootstocks in a Coastal Sandy Soil: Link between Fast Chlorophyll a Fluorescence and Production Yield. Agronomy 2024, 14, 1304. https://doi.org/10.3390/agronomy14061304

AMA Style

Colpo A, Demaria S, Zaccarini M, Forlani A, Senatore A, Marrocchino E, Martina A, Ferroni L. Drought-Stressed Apple Tree Grafted onto Different Rootstocks in a Coastal Sandy Soil: Link between Fast Chlorophyll a Fluorescence and Production Yield. Agronomy. 2024; 14(6):1304. https://doi.org/10.3390/agronomy14061304

Chicago/Turabian Style

Colpo, Andrea, Sara Demaria, Marzio Zaccarini, Alessandro Forlani, Antonia Senatore, Elena Marrocchino, Angela Martina, and Lorenzo Ferroni. 2024. "Drought-Stressed Apple Tree Grafted onto Different Rootstocks in a Coastal Sandy Soil: Link between Fast Chlorophyll a Fluorescence and Production Yield" Agronomy 14, no. 6: 1304. https://doi.org/10.3390/agronomy14061304

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