agriculture

Article The Crucial Role of Organic Matter in Satisfying the Phosphorus Requirements of Olive Trees (Olea europaea L.)

Niki Christopoulou 1, Theocharis Chatzistathis 2,*, Efimia M. Papatheodorou 3 , Vassilis Aschonitis 2 and Nikolaos Monokrousos 1,*

1 Laboratory of Molecular Ecology, International Hellenic University, 57001 Thessaloniki, Greece; [email protected] 2 Institute of Soil and Water Resources, Hellenic Agricultural Organization-Demeter, 57001 Thessaloniki, Greece; [email protected] 3 Department of Ecology, School of Biology, Aristotle University, 54124 Thessaloniki, Greece; [email protected] * Correspondence: [email protected] (T.C.); [email protected] (N.M.); Tel.: +30-2310-473429 (T.C.); +30-2310-807572 (N.M.)

Abstract: Under high organic matter content, even under low extractable soil P concentrations, sufficient or over-sufficient foliar P levels may be found. This multi-year study aimed at examining the effects of organic matter content and irrigation management on (a) soil fertility, (b) P-cycle related soil enzymes (acid and alkaline phosphatase, pyrophosphatase) and (c) foliar nutrient concentrations. Irrigated and non-irrigated groves of fully productive trees of the cultivar “Chondrolia Chalkidikis” with low organic matter (LOM < 1.5%), medium organic matter (1.5% < MOM < 2.5%) and high   organic matter (HOM > 2.5%) were selected for the experimentation. It was hypothesized that olive groves receiving high inorganic fertilization and irrigation inputs (usually with medium to relatively Citation: Christopoulou, N.; low organic matter content) would show higher soil and foliar P concentrations compared to the Chatzistathis, T.; Papatheodorou, non-irrigated groves with higher organic matter content receiving manure applications. Most of the E.M.; Aschonitis, V.; Monokrousos, N. soil variables (including the three enzymes’ activities) were affected by differences in organic matter The Crucial Role of Soil Organic Matter in Satisfying the Phosphorus content. However, organic matter content did not show a significant influence on foliar nutrient Requirements of Olive Trees (Olea concentrations. Olive trees, especially those cultivated in with high organic matter content europaea L.). Agriculture 2021, 11, 111. (receiving organic fertilization), can over-satisfy their P nutritional needs, even though soil analyses https://doi.org/10.3390/agriculture show low soil extractable P concentrations, probably due to the high enzymatic activity of acid and 11020111 alkaline phosphatases. The practical conclusion of this study is that P fertilizer recommendations should be primarily based on foliar P rather than on extractable soil P. Academic Editor: Elizabeth Baggs Received: 24 December 2020 Keywords: acid phosphatase; alkaline phosphatase; irrigation regime; pyrophosphatase Accepted: 27 January 2021 Published: 1 February 2021

Publisher’s Note: MDPI stays neutral 1. Introduction with regard to jurisdictional claims in In recent decades, olive tree cultivation has shifted from traditional, widely spaced and published maps and institutional affil- rain-fed orchards to intensive, irrigated orchards, with higher fertilization rates and tree iations. density supported by mechanical harvesting to maximize productivity and profitability [1]. Enhanced yields and increased nutrient demands make nutrition and fertilization a vital part of the management of olive orchards [2]. Of all the essential nutrients, Nitrogen (N), Phosphorus (P), and Potassium (K) are the most crucial for olive trees’ nutrition. Copyright: © 2021 by the authors. Of these macronutrients, P is of high importance, since it plays a major role in nu- Licensee MDPI, Basel, Switzerland. merous physiological processes. Insufficient P availability may significantly depress This article is an open access article the photosynthetic rate, root growth and other functions related to plant growth; thus, P distributed under the terms and deficiency may become a limiting factor to the support of crop yields [3,4]. Soil P can be conditions of the Creative Commons Attribution (CC BY) license (https:// found in various organic or inorganic dynamic pools; nevertheless, P availability for creativecommons.org/licenses/by/ is controlled by physical and chemical reactions, including desorption, precipitation and 4.0/).

Agriculture 2021, 11, 111. https://doi.org/10.3390/agriculture11020111 https://www.mdpi.com/journal/agriculture Agriculture 2021, 11, 111 2 of 14

biological processes, such as the immobilization of P by other plants and soil microorgan- isms [5]. Despite its relative abundance, a high percentage of P becomes immobile and unavailable for plant uptake [6]. Thus, to overcome phosphate limitation in soils, extended use of inorganic fertilizers has become a common practice, especially in intensive olive groves. Nevertheless, due to the recognized lack of response of olive trees to P application, most fertilization programs overestimate the recommended rates of the applied P [7]. Ex- cessive fertilization in many European countries has led to a build-up of an unavailable P for plant uptake, accumulating soil P pools at unacceptable environmental levels due to the risk of P transfer to aquatic ecosystems [8]. Thus, with the aim of decreasing the high (often unnecessary) P fertilization rates, discussions have recently increased regarding the role and importance of soil organic matter (SOM) on the P nutritional needs of crops. High SOM content in agricultural soils is required to improve several physicochem- ical properties [9]. Additionally, increasing numbers of studies have indicated that soil fertility is significantly improved under increased SOM [10]. This effect is attributed to the positive effect that SOM exerts on soil microbial biomass and activity, as well as on soil enzyme activities, which are closely related to soil fertility [11,12]. Soil enzymes cat- alyze several biochemical reactions, such as the decomposition of soil organic matter and transition between different forms of nutrients [13]. Enzyme activities reflect the magni- tude of these biochemical processes and are considered good indicators of soil quality. Since there is a strong correlation between soil enzyme activities, fertility and nutrient uptake, many researchers have studied the effect of fertilization management on plants’ nutritional status by investigating soil enzymatic activity [7]. A significant part of soil P can be found in several organic or inorganic chemical compounds, which are comprised of polyphosphates, orthophosphates, pyrophosphates, phosphonates, orthophosphate monoesters and diesters [14]. These forms of P can be used as a source of P for plant uptake after the release of phosphate, which is promoted by enzyme activity. Phosphatases are a broad group of enzymes that are produced by , fungi and plant roots and play a crucial role in organic P cycling, since they transform bounded and unavailable forms of organic P into assimilable phosphate, available for plant uptake [15]. However, under P deficiency, soil biota can enhance the production of extracellular phosphatases, while under high P concentrations, phosphatase production tends to be inhibited [16]. Inorganic pyrophosphatase also plays an important role in soil processes, since it catalyzes the hydrolysis of pyrophosphate to orthophosphate, which enables the absorption of P by plants [17]. Pyrophosphate is abundant in soils and it is mainly originated from soil , especially fungi [18]. However, due to the difficulties in the quantification of pyrophosphate in soil solutions, its role in remains poorly understood. Although the influence of P application/fertilization on olive trees’ nutrition and physiology has been studied extensively [7,19,20], no attention has been paid to the com- binational effect of soil organic matter content and irrigation on the satisfaction of the P nutritional needs of olive trees. According to our knowledge, only Chatzistathis et al. [21] indicated the beneficial influence of organic matter on the satisfaction of P nutritional needs in fully productive olive trees; however, in their study, the effect of irrigation on foliar P nutrition was not included, and different SOM levels were not included. Thus, the novelty of this study consists of the combinational investigation of three organic matter levels (low, medium and high) and irrigation on soil and foliar P in mature olive trees. We hypothesized that olive groves receiving high inorganic fertilization and irrigation inputs (with a medium to relatively low organic matter content) would show higher soil and foliar P concentrations compared to the non-irrigated groves with higher organic matter content receiving manure applications. To investigate this, we determined soil and foliar P, and we also evaluated the activities of acid and alkaline phosphatases as well as those of pyrophosphatase, since they are all strongly involved in the P cycle and are indicators of soil quality. The present study aimed at primarily investigating how soils with different organic matter contents (low, medium and high) under different fertilization (inorganic or organic Agriculture 2021, 11, 111 3 of 14

fertilization) and irrigation (rain-fed and irrigated) regimes affect both soil and foliar P concentrations. Finally, another objective of this study was to investigate whether the determination of extractable soil P is sufficient for properly evaluating the nutritional status of olive trees to set the guidelines for proper fertilization recommendations, or if foliar P determination should be also included.

2. Materials and Methods 2.1. Olive Groves’ Management, Study Area and Experimental Design The multi-year field experimentation was conducted in intensively managed, irrigated olive groves as well as in traditional, non-irrigated groves. All groves had been planted into a 6 × 6 or a 7 × 7 m system and were grown on soils with alkaline pH (varying from 7 to 8.2) and a texture varying from Loam to Sandy Clay Loam. Irrigation was performed with a drip irrigation system (with approximately 300–500 mm water, in five equal doses, during the period from May to September). Furthermore, weed cut and pruning material was left on the soil surface to enrich organic C and nutrient recycling [21,22]. The altitude of the experimental groves varied from 0 to 600 m above sea level. The climate type of the study area is characterized as sub-Mediterranean with hot, dry summers and rainy, mild winters. The mean annual precipitation is approximately 700 mm, with a maximum recorded in November (around 55 mm) and the minimum in August (less than 20 mm) [23]. Regarding the mean monthly temperature, the highest was recorded in August (24.1 ◦C), while the lowest was found in February (4.7 ◦C) (Technical Chamber of Greece, Athens, Greece, 2010). For the needs of the study, six fully productive olive groves (25-year-old trees) of the cultivar “Chondrolia Chalkidikis” were selected, whose size ranged from 1 to 1.6 ha. The irrigated and non-irrigated olive groves of the studied area received either in- organic fertilizers or manures. The groves receiving manure applications showed high soil organic matter (HOM) content (>2.5%) compared to the others (OM < 2.5%) receiving inorganic fertilization. In the case of fields receiving inorganic fertilizers, there were also differences in soil organic matter, due to differences in soil texture (heavier soils have slower rates of mineralization due to lower aeration and thus higher values of organic matter compared to light soils). Thus, the fields receiving inorganic fertilizers were further divided into two groups, based on the OM content: low organic matter (LOM < 1.5%) fields and medium organic matter (1.5% < MOM < 2.5%) fields. The trees in the LOM and MOM fields were approximately fertilized for many years with 50–90 units of N, 3–10 units of −1 P2O5, 80–150 units of K2O ha and 6–12 units of B (borax 11.5%). Each of the three olive grove categories (LOM, MOM and HOM) was split into eight different plots, and each plot included at least 10 trees. From each plot, seven soil samples were collected randomly in the projection of the canopy of olive trees. After the soil samples were collected, they were intermingled, so that a single composite sample was formed for each replicate plot (eight mixed genuine samples). Leaf samples were also collected from the same plots from which soil samples were obtained. The leaves were also mixed so that a single composite sample was formed for each replicate plot. Samplings were conducted approximately three months after the application of inorganic fertilizers or manures.

2.2. Soil Chemical Analyses Soil samples from the upper 60 cm layer were sieved to pass a 2 mm mesh to remove stones, roots and organic debris and were left to dry for 48 h at room temperature and then transferred to the laboratory. The chemical analysis included soil texture analysis, pH, CaCO3, organic matter, nitrate N (NO3-N), available P and concentrations of K, Ca, and Mg macronutrients as well as B, Fe and Zn micronutrients. The above-mentioned parameters were determined as follows [24]: soil texture analysis was conducted according to the Bouyoucos method, pH was measured in a soil-distilled water paste (1:1), % CaCO3 was determined with the acid neutralization method, organic matter was evaluated with potassium dichromate, nitrate (NO3)-N was determined by using KCl 0.5 mol/L, while Agriculture 2021, 11, 111 4 of 14

extractable P (Pext) was measured according to the Olsen method. The concentrations of Ca, Mg, K, Fe, B and Zn were determined by ICP (Perkin Elmer Optical Emission Spectrometer, OPTIMA 2100 DV, Waltham, MA, USA) [25].

2.3. Leaf Chemical Analyses Leaf samples were thoroughly washed both with tap and distilled water and then put into an oven at 75 ◦C for 48 h to dry. Afterwards, they were shuttered and placed in porcelain bowls and incinerated in a furnace at 515 ◦C for 5 h. The ash was then dissolved with 3 mL HCl 6 N and finally diluted with distilled water to reach the volume of 50 mL. Foliar P, K, Ca, Mg, Fe and Zn concentrations were determined by the ICP method [25]. Total N was evaluated by the method of Kjeldahl, while B was determined according to the method of azomethine-H [26]. Foliar macronutrient (N, P, K, Ca and Mg) concentrations were expressed in % dry weight (d.w.), while those of micronutrients (Fe, Zn, and B) were expressed in mg/kg d.w.

2.4. Determination of Acid, Alkaline and Pyrophosphatase Activity For the determination of acid, alkaline and pyrophosphatase activities, fresh soil samples from the upper 30 cm were collected from all the experimental plots and transferred to the laboratory. The soil samples were stored at 4 ◦C and the enzyme activities were measured within a week. Acid (ACP) and alkaline (ALP) phosphatase activities were determined according to the method in [27] in 96-well microplates and 5 mM p-nitrophenyl- phosphate (185.6 mg/100 mL) was used as a substrate solution. A 50 mM sodium acetate buffer with a pH of 5 was used for the determination of ACP, whereas a 50 mM sodium acetate buffer with a pH of 11 was used for ALP. For the colorimetric determination of the product concentrations, we used a spectrophotometer (absorbance at 405 nm). Pyrophosphatase activity was determined as described by Dick and Tabatabai [17], and we used 50 mM pyrophosphate as a substrate solution. For the colorimetric determination of the product concentrations, we used a spectrophotometer at a wavelength of 700 nm.

2.5. Statistical Analysis The overall full factorial experimental design consisted of three “SOM content” levels, with two irrigation regimes and eight replicates per treatment. The two-way ANOVA method was used to determine the effect of soil organic matter, irrigation and their in- teraction on soil physicochemical variables and enzyme activities, as well as on foliar nutrients. In the case of statistically significant effects, the Fisher least significant difference (LSD) post-hoc test was performed at p < 0.05. Furthermore, to examine the relationships among soil enzyme activities and foliar P to soil Pext, regression and Spearman correlation analyses were performed; these analyses served to identify the trends between explanatory and response variables. To further explore whether the organic matter concentration or the irrigation regime exerted the greatest influence on soil and foliar variables, we applied a Principal Component Analysis (PCA). Before analyses, the data were transformed ap- propriately when considered necessary to meet the assumptions of the ANOVA. Statistical analyses were performed by STATISTICA 9 software.

3. Results The effects of soil organic matter (OM), irrigation (I) and their interaction on soil physicochemical variables and enzyme activities are presented in Table1. The results indicated that the effect of irrigation, as well as the interactive effect (OM × I), had no significant impact on any of the estimated soil physicochemical variables. In contrast, most of the soil variables, including the concentrations of Mg, Ca, Fe, Zn and Pext as well as the enzyme activity of acid phosphatase (ACP), alkaline phosphatase (ALP) and py- rophosphatase (PYP), were significantly different under the effect of OM variation. Because irrigation had an insignificant impact on the measurements, the analysis mainly focused on how soil organic matter per se affected enzyme activities and Pext. The enzymatic Agriculture 2021, 11, 111 5 of 14

activity of acid and alkaline phosphatase in the three soil types with low (LOM), medium (MOM) and high (HOM) organic matter content was evaluated (Figure1a,b). The results of the one-way ANOVA revealed that ACP (Figure1a) and ALP (Figure1b) activities showed a similar pattern, presenting statistically significant lower activity values in LOM and MOM soil samples compared to HOM. PYP activity values also increased with the increase in organic matter, where MOM and HOM showed significantly higher values compared with LOM (Figure2). Further analysis also focused on the effect of different organic matter contents on soil extractable phosphorus (Pext), where it was observed that Pext concentration was significantly higher in MOM than in LOM, while Pext in HOM was lower for both LOM and MOM (Figure3). Figure1:

Figure1:Figure1:

Figure 1. (a,b). Acid (ACP) and alkaline phosphatase (ALP) activities (±SE) in different soil organic matter contents.

Different lettersFigure2: refer to statistically significant differences between treatments, revealed by ANOVA and Fischer least significant difference (LSD) test comparisons. (**: p ≤ 0.01; ***: p ≤ 0.001). LOM: low organic matter; MOM: medium organic matter; HOM: highFigure2:Figure2: organic matter.

Figure 2. Pyrophosphatase activity (±SE) in different soil organic matter contents. Different letters

refer to statistically significant differences between treatments, revealed by ANOVA and Fischer LSD Figure3:Figure3: test comparisons. (***: p ≤ 0.001).

Figure3:

Figure 3. Extractable phosphorus (Pext) concentration (±SE) under different soil organic matter

contents. Different letters refer to statistically significant differences between the treatments, as

11revealed by ANOVA and Fischer LSD test comparisons. (***: p ≤ 0.001).

1

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Table 1. Mean values (± SE) of the soil nutrient concentrations and enzymatic activity at various treatments. +I and -I refer to irrigation and non-irrigation; OM: organic matter; ACP: Acid phosphatase; ALP: Alkaline phosphatase; PYP: pyrophosphatase. (ANOVA, ns: non-significant; *: p ≤ 0.05; **: p ≤ 0.01; ***: p ≤ 0.001).

LOM +I LOM -I MOM +I MOM -I HOM +I HOM -I OM I OM × I − NO3 (ppm) 132.60 (86.89) 64.12 (21.04) 203.91 (50.25) 79.41 (25.65) 47.92 (13.28) 62.84 (7.34) F = 1.14 p = ns F = 1.61 p = ns F = 0.73 p = ns K (ppm) 254.72 (39.46) 272.50 (67.55) 384.25 (74.33) 416.12 (81.33) 271.01 (125.11) 343.57 (89.52) F = 1.36 p = ns F = 0.30 p = ns F = 0.04 p = ns Mg (ppm) 512.27 (81.44) 577.01 (114.52) 620.81 (127.68) 717.87 (258.70) 371.50 (167.99) 199.85 (24.59) F = 3.67 p = * F = 0.01 p = ns F = 0.49 p = ns Ca (ppm) 101.10 (0.00) 101.02 (0.00) 299.40 (135.39) 787.01 (268.98) 316.75 (215.75) 219.57 (118.57) F = 4.43 p = ** F = 0.99 p = ns F = 2.09 p = ns Fe (ppm) 4.20 (0.49) 5.45 (1.48) 14.29 (4.09) 22.03 (4.32) 20.25 (5.45) 21.20 (3.37) F = 9.30 p = *** F = 1.07 p = ns F = 0.53 p = ns Zn (ppm) 0.84 (0.13) 1.04 (0.20) 1.02 (0.11) 1.08 (0.09) 2.16 (0.29) 1.48 (0.20) F = 12.21 p = *** F = 0.57 p = ns F = 3.06 p = ns B (ppm) 1.52 (0.44) 1.71 (0.40) 1.42 (0.27) 2.71 (1.30) 9.10 (7.18) 2.01 (1.34) F = 2.88 p = ns F = 1.82 p = ns F = 3.28 p = ns Pext (ppm) 10.45 (1.67) 9.32 (2.37) 12.56 (2.30) 11.04 (2.17) 5.94 (1.21) 5.70 (0.91) F = 4.29 p = * F = 0.33 p = ns F = 0.05 p = ns ACP (mmol 0.25 (0.03) 0.45 (0.04) 0.33 (0.04) 0.49 (0.06) 0.71 (0.16) 0.63 (0.04) F = 17.50 p = *** F = 4.48 p = * F = 3.44 p = ns Kg−1h−1) ALP (mmol 0.32 (0.03) 0.42 (0.04) 0.33 (0.05) 0.54 (0.10) 0.54 (0.04) 0.60 (0.05) F = 4.89 p = ** F = 5.98 p = * F = 0.77 p = ns Kg−1h−1) PYP (mmol 0.27 (0.02) 0.30 (0.03) 0.39 (0.04) 0.60 (0.05) 0.55 (0.09) 0.53 (0.03) F = 20.18 p = *** F = 4.56 p = * F = 4.35 p = ns Kg−1h−1) Agriculture 2021, 11, 111 7 of 14

Regarding the foliar nutrient concentrations, factorial ANOVA results indicated that there was no significant difference between the treatments, with the exceptions of N, K Figure4:and Mg (Table2). The one-way ANOVA analysis of leaf P concentrations also verified that there was no significant difference between LOM, MOM and HOM soil samples (Figure4).

Agriculture 2021, 11, x FOR PEER REVIEWFigure 4. Foliar phosphorus (P) concentrations (±SE) under different soil organic matter contents.9 of 14 No statistically significant differences between the treatments were revealed by the ANOVA (ns: non-significant).

Furthermore,Furthermore, Spearman Spearman rank (r) correlationscorrelations werewere performed performed to to describe describe the the relation- rela- tionshipship between between (i) (i) ACP, ACP, (ii) (ii) ALP, ALP, (iii) (iii) PYP PYP and and (iv) (iv) foliar foliar P versusP versus soil soil Pext Pext (Figure (Figure5a–d). 5a– d).The The results results showed showed that that the the Spearman Spearman r r valuesvalues forfor ACP,ACP, ALPALP and foliar P P versus versus Pext Pext werewere statistically statistically significant. significant. The The activity activity values values of of ACP ACP and and ALP ALP enzymes enzymes were were reduced reduced (Figure(Figure 5a,b),5a,b), whereas whereas foliar foliar P P values values were were increased increased with with the the increase increase of of Pext Pext (Figure (Figure 5b).5b). InIn contrast, contrast, PYP PYP values values were were found found to to be be independent independent of of Pext Pext changes changes (Figure (Figure 5c).5c).

FigureFigure 5. 5. (a(–ad–).d ).Spearman Spearman correlations correlations and and regression regression analyses analyses of acid of acid and and alkaline alkaline phosphatase, phosphatase, pyrophosphatasepyrophosphatase activity activity and and foliar foliar P P concentration concentration in in relation relation to to soil soil available available P P (Pext) (Pext) (Spearman (Spearman correlationcorrelation coefficient: coefficient: ns ns = =non-significant; non-significant; **: **: p p≤ ≤0.01;0.01; ***: ***: p ≤p 0.001).≤ 0.001). 2 To obtain an overall visualization of the multivariable interactions, a Principal Com- ponent Analysis (PCA) was also conducted. The ordination of soil treatments and soil variables on the PCA biplot is depicted in Figure 6. The first two axes of the PCA ac- counted for 46.1% of the data variability (the first axis explained 31.22% of the variability, while the second explained 14.88%). Samples from the HOM fields were ordinated within the left side of the biplot, while the LOM and MOM samples occupied the right side of the biplot irrespective of the irrigation regime. The high soil ACP, ALP and PYP enzyme ac- tivities were the main soil variables characterizing the HOM samples, while LOM and MOM samples were mostly characterized by the increased Pext concentrations. In relation to the second axis, the LOM samples were ordinated at the upper part and were separated from the MOM samples (bottom part). The PCA results indicated that the organic matter effect masked the effect of the irrigation management regime on soil biochemical varia- bles. It is also clear that the HOM samples were much more coherent than the other two groups. The ordination of treatments based on leaf nutrient variables is presented in Figure 7. The first two axes explained 38.39% of the variability (35.57% and 12.82%, respectively). The pattern of ordination differs in comparison to the PCA graph of the soil variables, as the treatments were not as clearly differentiated and mainly ordinated towards the center of the biplot. Pext was not among the variables that significantly affected the ordination of the leaf samples.

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Table 2. Mean values (±SE) of foliar nutrient concentrations at various treatments. +I and -I refer to irrigation and non-irrigation; OM: organic matter. (ANOVA, ns: non-significant; *: p ≤ 0.05; **: p ≤ 0.01).

LOM +I LOM -I MOM +I MOM -I HOM +I HOM -I OM I OM × I Ntotal % 1.59 (0.06) 1.55 (0.04) 1.50 (0.07) 1.17 (0.10) 1.22 (0.18) 1.29 (0.08) F = 6.24 p = * F = 1.92 p = ns F = 2.79 p = ns P % 0.36 (0.03) 0.34 (0.04) 0.38 (0.03) 0.38 (0.03) 0.37 (0.07) 0.29 (0.03) F = 1.07 p = ns F = 1.22 p = ns F = 0.81 p = ns K % 0.72 (0.04) 0.73 (0.05) 0.77 (0.05) 0.95 (0.06) 0.89 (0.06) 0.89 (0.05) F = 3.93 p = * F = 1.25 p = ns F = 2.02 p = ns Ca % 2.07 (0.12) 1.94 (0.22) 2.03 (0.21) 1.40 (0.22) 1.59 (0.17) 1.55 (0.11) F = 2.46 p = ns F = 2.80 p = ns F = 1.49 p = ns Mg % 0.25 (0.02) 0.25 (0.02) 0.24 (0.03) 0.22 (0.03) 0.17 (0.01) 0.16 (0.01) F = 5.18 p = ** F = 0.29 p = ns F = 0.08 p = ns B (ppm) 28.66 (3.10) 28.15 (1.95) 26.68 (2.72) 22.08 (1.40) 20.04 (0.80) 23.26 (1.41) F = 3.04 p = ns F = 0.08 p = ns F = 1.09 p = ns Zn (ppm) 13.77 (1.40) 15.79 (1.05) 13.06 (0.88) 11.59 (1.09) 12.22 (0.96) 13.53 (0.96) F = 2.23 p = ns F = 0.36 p = ns F = 1.21 p = ns Fe (ppm) 67.90 (7.55) 61.82 (2.11) 68.64 (4.47) 85.88 (11.13) 65.29 (11.27) 92.28 (9.58) F = 1.27 p = ns F = 2.65 p = ns F = 1.51 p = ns Agriculture 2021, 11, 111 9 of 14

To obtain an overall visualization of the multivariable interactions, a Principal Com- ponent Analysis (PCA) was also conducted. The ordination of soil treatments and soil variables on the PCA biplot is depicted in Figure6. The first two axes of the PCA accounted for 46.1% of the data variability (the first axis explained 31.22% of the variability, while the second explained 14.88%). Samples from the HOM fields were ordinated within the left side of the biplot, while the LOM and MOM samples occupied the right side of the biplot irrespective of the irrigation regime. The high soil ACP, ALP and PYP enzyme activities were the main soil variables characterizing the HOM samples, while LOM and MOM samples were mostly characterized by the increased Pext concentrations. In relation to the second axis, the LOM samples were ordinated at the upper part and were separated from the MOM samples (bottom part). The PCA results indicated that the organic matter effect Agriculture 2021, 11, x FOR PEER REVIEW 10 of 14 masked the effect of the irrigation management regime on soil biochemical variables. It is also clear that the HOM samples were much more coherent than the other two groups.

FigureFigure 6. 6. OrdinationOrdination of of the the soil soil samples samples according to the soil physicochemical variablesvariables andandenzyme en- zymeactivities activities on a PCAon a PCA biplot. biplot. Each Each point point corresponds corresponds to the to meanthe mean value value of the of the loadings loadings of theof the eight eightsamples samples belonging belonging to the to same the treatment,same treatment, at the firstat the and first the and second the second axis; the axis; first the symbol first correspondssymbol correspondsto the organic to matter the organic content matter (LOM: content low, MOM: (LOM: medium, low, MOM: HOM: medium, high), and HOM: the high), second and to the the specific sec- ondirrigation to the specific regime (+:irrigation irrigation, regime -: no (+: irrigation). irrigation, -: Error no irrigation). bars indicate Erro standardr bars indicate errors standard for both axes errors for both axes (n = 8). (n = 8).

The ordination of treatments based on leaf nutrient variables is presented in Figure7. The first two axes explained 38.39% of the variability (35.57% and 12.82%, respectively). The pattern of ordination differs in comparison to the PCA graph of the soil variables, as the treatments were not as clearly differentiated and mainly ordinated towards the center of the biplot. Pext was not among the variables that significantly affected the ordination of the leaf samples.

Figure 7. Ordination of the leaf samples according to the leaf nutrient variables on a PCA biplot. Each point corresponds to the mean value of the loadings of the eight samples belonging to the same treatment for the first and the second axis; the first symbol corresponds to the organic matter content (LOM: low, MOM: medium, HOM: high) and the second to the specific irrigation regime (+: irrigation, -: no irrigation). Error bars indicate standard errors for both axes (n = 8).

4. Discussion Previous studies have indicated that irrigation favors several biochemical and bio- logical soil properties that are correlated with increased olive tree yields [28]. However, our results showed that irrigation did not significantly affect most of the estimated pa- rameters, including soil and foliar P concentrations (Tables 1 and 2). Our findings agree with those of Ding et al. [29] for wheat plants. The results regarding the effect of irrigation may seem controversial as they depend on the climatic conditions and the precipitation in the study area. Kavvadias et al. [30] studied the effect of organic amendments and irri- gation management on the soil chemical and microbial properties of olive groves in the region of Crete, with a mean annual precipitation of 460 mm. Most of the soil properties

Agriculture 2021, 11, x FOR PEER REVIEW 10 of 14

Figure 6. Ordination of the soil samples according to the soil physicochemical variables and en- zyme activities on a PCA biplot. Each point corresponds to the mean value of the loadings of the eight samples belonging to the same treatment, at the first and the second axis; the first symbol corresponds to the organic matter content (LOM: low, MOM: medium, HOM: high), and the sec- Agriculture 2021, 11, 111 10 of 14 ond to the specific irrigation regime (+: irrigation, -: no irrigation). Error bars indicate standard errors for both axes (n = 8).

Figure 7. Ordination of the leaf samples according to the leaf nutrient variables on a PCA biplot. FigureEach point 7. Ordination corresponds of the to leaf the samples mean value according of the to loadings the leaf ofnutrient the eight variables samples on belonginga PCA biplot. tothe Each point corresponds to the mean value of the loadings of the eight samples belonging to the same treatment for the first and the second axis; the first symbol corresponds to the organic matter same treatment for the first and the second axis; the first symbol corresponds to the organic matter content (LOM: low, MOM: medium, HOM: high) and the second to the specific irrigation regime (+: content (LOM: low, MOM: medium, HOM: high) and the second to the specific irrigation regime (+:irrigation, irrigation, -: no-: no irrigation). irrigation). Error Error bars bars indicate indicate standard standard errors errors for for both both axes axes (n =(n 8).= 8). 4. Discussion 4. Discussion Previous studies have indicated that irrigation favors several biochemical and biologi- cal soilPrevious properties studies that have are correlatedindicated that with irrigation increased favors olive treeseveral yields biochemical [28]. However, and bio- our logicalresults soil showed properties that irrigation that aredid correlated not significantly with increased affect most olive of tree the yields estimated [28]. parameters, However, ourincluding results soil showed and foliar that Pirrigation concentrations did not (Tables significantly1 and2). Ouraffect findings most of agree the estimated with those pa- of rameters,Ding et al. including [29] for wheatsoil and plants. foliar The P concentr resultsations regarding (Tables the effect1 and of2). irrigation Our findings may agree seem withcontroversial those of Ding as they et al. depend [29] for on wheat the climatic plants. conditionsThe results and regarding the precipitation the effect of in irrigation the study mayarea. seem Kavvadias controversial et al. [30 as] studied they depend the effect on ofthe organic climatic amendments conditions andand irrigationthe precipitation manage- inment the study on the area. soil chemicalKavvadias and et microbialal. [30] studie propertiesd the effect of olive of organic groves amendments in the region and of Crete, irri- gationwith a management mean annual on precipitation the soil chemical of 460 mm.and microbial Most of the properties soil properties of olive including groves in total the − regionnitrogen, of Crete, inorganic with nitrogen a mean (NOannual3 ), precipitation exchangeable of K, 460 Pext, mm. soil Most microbial of the respirationsoil properties and microbial biomass were favored by irrigation. Meanwhile, Kavvadias et al. [31] conducted a similar study in the south-western Peloponnese with an annual precipitation of 1.100 mm (AQUASTAT, 2017). In that case, due to the high loads of rain in the study area, any irrigation effect on the soil properties was masked, and no significant differences among the studied soil properties were recorded. Our study area, located in Chalkidiki (Central Macedonia, Northern Greece), also receives sufficient loads of rainfall, since the annual precipitation rate during the last 30 years is higher than 700 mm [23]. This could possibly explain our findings that there was practically no differentiation between irrigated and non-irrigated (rain-fed) plots. Most of the estimated soil variables, including Pext concentration, were significantly higher in MOM and LOM soil samples compared to the HOM samples (Table1, Figure3). Since LOM and MOM fields received external inputs of inorganic P fertilizers, which is a direct way to increase the available P pools, Pext was expected to be higher in these than HOM, where only organic inputs were applied. Chatzistathis et al. [21] also studied the response of olive trees to P mineral fertilization and found that inorganic and total P, as well as Pext, were significantly increased compared to the non-fertilized trees. The foliar analysis (Figure4) showed that the trees grown in HOM fields presented over-sufficient P concentrations, similar to those found in the LOM and MOM sites. Similarly, Ferreira et al. [7] reported that low levels of soil Pext do not necessarily mean low leaf P content, showing that the P nutritional status of olive trees was adequate even in fields showing soil P inadequacy. Our initial hypothesis seems to be partially verified since soils receiving high inorganic fertilization inputs showed higher concentration of soil Pext but not higher foliar P concentrations. This means that foliar nutrient determination may be a more Agriculture 2021, 11, 111 11 of 14

representative procedure than soil analysis to evaluate the nutritional status of olive trees. These results are in accordance with those of Ferreira et al. [7] and Chatzistathis et al. [21] and verify the second objective of the study, suggesting that soil analysis is not sufficient to provide reliable results about proper fertilization guidelines. Many researchers have also investigated the influence of soil organic matter on phos- phorus availability; however, there are still controversial results in the literature, depending on the nature of organic amendments, plant systems, management practices and spe- cific soil properties. Yusran [32] showed that phosphate was significantly higher in soils amended with organic materials than in unamended soil; other researchers [33] reported that organic amendments significantly increased the desorption of P from the soil, thus in- creasing P availability. The addition of organic amendments in soil may increase phosphate availability by abiotic processes, such as ligand-exchange effects on phosphate adsorption or biotic processes such as the decomposition and mineralization of organic P [34]. To interpret the effect of organic matter content and inorganic P fertilization on P availability, the enzymatic activity of acid and alkaline phosphatases and pyrophosphatase was also estimated. ANOVA results (Figure1) revealed that acid and alkaline phosphatase activities were significantly higher in HOM samples, while their activity was suppressed in soils with low organic matter content (LOM and MOM). It is generally accepted that soil or- ganic matter and microbial biomass are strongly associated with soil enzyme activities [35]. Many authors agree that soils treated with various types of organic amendments (e.g., plant residues, manure and vermicompost) showed higher phosphatase activity than soils treated only with inorganic fertilizers [36,37]. Reddy et al. [38] reported that the activities of acid and alkaline phosphatases among soils with different levels of soil organic carbon (SOC) were in the order of high SOC > medium SOC > low SOC soils. Tejada and Benítez [39] also studied the effect of three organic wastes on several enzymatic activities, including phosphatases, in an olive grove, and their results indicated that the stimulation of biochem- ical properties and phosphatase activity was higher in the organically amended soils. In this study, pyrophosphatase activity was also significantly higher in HOM (Figure2) , and this fact is also supported by earlier studies, indicating that pyrophosphatase activity is suppressed by decreased organic matter content [17]. The application of Spearman correlations indicated that acid and alkaline phos- phatases followed the same pattern, showing a negative correlation to Pext (Figure5a,b). These results are in agreement with those of Song et al. [40], who also found a negative correlation between acid and alkaline phosphatase activity with available P, thus indicating that Pext estimation may depict only the current status of available P but not the latent capa- bility of the system to release P through phosphatase activity [21]. However, they found a positive correlation between phosphatase activity and organic P and suggested that organic P fractions may be more useful tools to evaluate phosphatase activity and the capacity of the system to obtain labile P. In our study, inorganic fertilization inputs in the LOM plots possibly suppressed the activity of phosphatases. Chatzistathis et al. [21] also reported that inorganic P fertilizers suppressed the activities of acid and alkaline phosphatase to much lower levels than those found in non-fertilized soil samples. On the other hand, it is widely accepted that soil P deficiency can significantly alter the composition of root exudates, leading to an increase in phosphatase production by plant roots and microorganisms [41]. Yadav and Tarafdar [42] revealed that, under P-deficient conditions, the secretion of acid phosphatase was found in several crops, including cereals, legumes and oilseed crops. In contrast, pyrophosphatase values practically remained constant and independent from Pext concentration variations (Figure5c). Reitzel et al. [ 43], after testing the activity of pyrophosphatase with three inorganic and 14 different organic P compounds, found that pyrophosphatase was very specific to the target substrate (pyrophosphate). These results, in combination with the results of this study, indicate that the role of pyrophosphatase may be of great importance in soil; however, it is a poor indicator to evaluate biologically available phosphorus. Agriculture 2021, 11, 111 12 of 14

The PCA results in soil (Figure6) showed that soil organic matter content was a factor that strongly affected most of the estimated soil variables. The ordination of the samples also revealed that HOM soils are characterized by high enzymatic activity, while MOM and LOM present a higher availability of Pext and N. Regarding leaf nutrient concentrations, PCA results (Figure7) revealed that leaves presented a similar pattern, but the effect of the soil organic matter concentrations was not as strong as it was in relation to the soil physicochemical properties. This could be justified by the fact that foliar nutrient concentrations, and especially P, did not present high fluctuations, which was also verified by other studies [7,21]. These results partially verified the initial hypothesis that soils receiving inorganic fertilizer inputs can be expected to have higher soil and foliar P concentrations than organically amended soils.

5. Conclusions Our study showed that LOM and MOM fields that received external inputs of inor- ganic P fertilizers presented greater soil Pext concentrations than HOM fields receiving only organic fertilization. On the contrary, olive trees grown in HOM fields presented over- sufficient foliar P concentrations, similar to those found in the LOM and MOM sites. These results could be attributed to the high enzymatic activity of acid and alkaline phosphatases in the HOM fields. Overall, our results indicate that soil analysis may underestimate the P nutritional needs of olive trees, in comparison to foliar P analysis; in that case, the oversup- ply of phosphate fertilizers is a common practice. Phosphorus fertilizer recommendations should be primarily based on foliar rather than on soil analysis. In addition, maintaining or even increasing soil organic matter should be a priority for farmers to support sustainable soil P management and production in olive groves. Furthermore, the effect of irrigation management in fields receiving sufficient rainfall rates is expected not to significantly affect soil chemical variables.

Author Contributions: Conceptualization, N.M., and T.C.; investigation, N.C.; data analysis, N.M.; writing—original draft preparation, N.C. and N.M.; writing—review and editing, T.C., E.M.P., and V.A. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable for studies not involving humans or animals. Informed Consent Statement: Not applicable for studies not involving humans. Data Availability Statement: The data presented in this study are available on request from the corresponding author. Conflicts of Interest: The authors declare no conflict of interest.

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