Abstract

The effect of addition of organic materials (shredded pruning residues, composted olive mill by-products) on spatial distribution of soil chemical and microbial properties in irrigated and rainfed olive groves was investigated. Most of the soil parcels were subjected to reduced tillage or no tillage practices. Soil sampling took place in 40 olive groves in the region of Messinia, south-western Peloponnese, Greece during a 5-year period (2012–2017). The results showed significant increases in soil organic matter, humic acids and nitrate content at the end of the study period, compared to the first year of the soil sampling campaign. On the other hand, the relatively low amount of fresh organic materials that was applied to the soil produced unfavorable results. Differences between irrigated and rainfed soil parcels were not significant, for most of the soil properties, since the area receives much higher loads of rain than the average rainfall, as registered in the main olive growing regions of Greece. The area underneath the tree canopy favors an environment that enhances soil fertility, compared to the area out of the tree canopy. Changes of soil properties according to depth showed that the surface soil in olive orchards has the potential to sequester carbon and nutrients.

INTRODUCTION

Olive (Olea europaea L.) is an extensively cultivated tree crop in the Mediterranean basin. Intensive cultivation practices are associated with low soil fertility and degradation of water resources. Excessive tillage, the lack of use of organic fertilizers, the burning of olive pruning residues and intensive orchard management in combination with the Mediterranean climate of Greece have a strong negative influence on the content of soil organic matter. On the other hand, the cultivation of olive trees produces a large quantity of biomass, such as branches of different thickness and leaves. At the same time, high loads of both liquid and solid olive mill wastes are being produced during the procedures for olive oil extraction. The management of olive tree pruning can affect nitrogen and carbon dynamics in soils (Gómez-Muñoz et al. 2016). Mulch using plant residues is becoming increasingly popular by farmers, because it reduces both the need for weed control measures (Calatrava & Franco 2011) and soil and nutrient losses (Rodríguez-Lizana et al. 2008). Mulching helps to ensure partial weed control because it forms a physical barrier and produces allelopathic substances when the mulch decomposes (International Olive Oil Council (IOOC) 2007).

The use of compost produced by agricultural activities for the fertilization of crops is considered a promising alternative option for waste management. Bartzas et al. (2015) carried out a life cycle assessment (LCA) study to assess the effect of application of treated or untreated agricultural wastes on crop land in open field and greenhouse cultivations. The importance of application of organic fertilizers in agriculture towards promotion of sustainability was displayed. In fact, reusing and recycling of agricultural residues not only reduce the environmental footprint of the harvested crop, but also provide an additional income to farmers (Bartzas et al. 2015; Bartzas & Komnitsas 2017). In addition, materials such as oil mill wastes, leaves and chopped branches have been assessed in the past for their suitability for composting, with encouraging results. Montanaro et al. (2012) reported that when the long-term recycling of plant residues is combined with the application of compost in Mediterranean tree crops, then organic matter is substantially increased. The success of soil management in maintaining its quality depends on understanding the way that soil responds in agricultural practices (Grebrekidan & Negassa 2006).

Olive orchards are traditionally managed as rainfed crop. In recent years the water demand of olive orchards has increased in the Mediterranean basin, particularly with reference to the plantations of high-density olive orchards. Irrigation, although favoring the productivity of trees, can often have an adverse effect on soil properties and hence the productivity (Henry & Hogg 2003). The adverse effects result from the quality of the irrigation water, the application method and soil properties (IOOC 2007).

A positive influence of sustainable orchard management practices on soil properties has been reported by many authors (Hernandez et al. 2005; Moreno et al. 2009; Montanaro et al. 2012; Koubouris et al. 2017) during recent years. However, their implementation in olive groves under different irrigation regimes has not been systematically tested under the prevailing Mediterranean conditions (Kavvadias et al. 2018). A LIFE+ project was initiated (oLIVE-CLIMA; LIFE 11/ENV/000942) aiming to introduce alternative management practices in olive tree crops. The objective of this work was to study the effect of organic matter input techniques (recycling of shredded pruning residue, returning of olive mill wastes to the field via compost and soil incorporation of weeds) and irrigation conditions (irrigated and rainfed olive orchards) on spatial distribution of main soil chemical (total organic carbon, total nitrogen, inorganic nitrogen, humic and fulvic acids, available P, and exchangeable K and Mg) and microbial properties (soil basal microbial respiration and microbial biomass carbon).

METHODS

Study site and soil analysis

The area of study is located in the region of Messinia, south-western Peloponnese, Greece.

Messinia is well known for both its rich olive agriculture and its water availability. It receives relatively large amounts of rainfall (mean annual rainfall 1,100 mm) compared to an average of 653 mm over the entirety of Greece (AQUASTAT 2017). Most of the annual rainfall falls in winter, in autumn and spring. Mean temperature is around 11 °C in winter and 27 °C in summer.

Forty soil parcels were selected. The size of soil parcels varied between 0.5 and 3 hectares. Cultivation practices (CP) related to organic matter addition (addition of shredded pruning residue, olive mill by-products compost, weed control) were applied to half of the irrigated and rainfed soil parcels (treated soil parcels), while the remaining ones (20) were used as control soil parcels without organic amendments. However, in most of the control parcels reduced tillage or no tillage was practiced. Irrigation was implemented from May to September according to evapotranspiration through drippers (five per tree), each with a discharge rate of 4 L h−1 and wetting a ∼1.0 m wide strip along the in-row. With regard to CP, soil was supplemented with chopped pruning residues from the same grove at approximately 1.36 t/ha (f.w.) each year of the period 2013–2017. Pruning residues comprised of olive tree leaves and wood pieces of variable size up to 7 cm in length. Compost derived from recycling by-products of a three-phase olive mill mixing olive pomace, leaves and chopped pruning residue at a ratio of 1:1:2, with 2 kg CO (NH2)2 per m3 of mixture was added. The compost was applied once every autumn of the years 2013–2017 at a rate of approximately 1.12 t ha–1. The compost dose applied depended on the available amount of the materials derived as by-products by the cultivation of olive groves. Composting took place for a period of 5–7 months in a suitable soil parcel in terms of water supply, soil gradient, shade, handling of organic materials, etc. The compost was loaded on a transport platform and dispersed by workers among the tree rows of each field. In addition, weeds were maintained and cut before spring every year of the period 2013–2017 and were left on the soil. The cover vegetation was estimated approximately to 11.35–11.51 t/ha/year. Table 1 shows the chemical composition of the added materials. Reduced tillage or no tillage practices were also applied. Detailed guidelines for the implementation of the above cultivation practices can be found at the website of oLIVE-CLIMA project (http://www.oliveclima.eu/en/).

Table 1

Chemical analysis of organic materials

 C (%) N (%) C/N P (%) K (%) Mg (%) 
Mean values ± st deva 
Thin branches 54 ± 1.20 0.75 ± 0.09 73 ± 7.68 0.23 ± 0.26 0.78 ± 0.17 0.10 ± 0.04 
Leaves 53 ± 1.28 1.65 ± 0.15 32 ± 2.48 0.29 ± 0.32 0.94 ± 0.17 0.20 ± 0.03 
Thick branches 55 ± 1.27 0.39 ± 0.02 143 ± 5.41 0.17 ± 0.20 0.33 ± 0.10 0.02 ± 0.01 
Compost 43.4 ± 8.3 2.00 ± 0.47 21.2 ± 2.5 0.18 ± 0.06 0.63 ± 0.19 0.30 ± 0.11 
 C (%) N (%) C/N P (%) K (%) Mg (%) 
Mean values ± st deva 
Thin branches 54 ± 1.20 0.75 ± 0.09 73 ± 7.68 0.23 ± 0.26 0.78 ± 0.17 0.10 ± 0.04 
Leaves 53 ± 1.28 1.65 ± 0.15 32 ± 2.48 0.29 ± 0.32 0.94 ± 0.17 0.20 ± 0.03 
Thick branches 55 ± 1.27 0.39 ± 0.02 143 ± 5.41 0.17 ± 0.20 0.33 ± 0.10 0.02 ± 0.01 
Compost 43.4 ± 8.3 2.00 ± 0.47 21.2 ± 2.5 0.18 ± 0.06 0.63 ± 0.19 0.30 ± 0.11 

aStandard deviation.

A soil sampling campaign took place during the 5-year 2012–2017 period of study and particularly in December 2012–February 2013 (Year 1), January 2015–February 2015 (Year 3), and December 2016–January 2017 (Year 5). There was no addition of organic materials in the first year of soil sampling (Year 1). In each soil parcel six composite soil samples were taken at 0–10 cm of depth, at equal intervals along a straight line joining the trunk of the tree with the middle of the distance from the nearest tree of the next tree series. The first three samples were under the tree canopy (UTC) and the next three were outside of the canopy (OuTC). It was decided to proceed to the above soil sampling methodology because many researchers had noted that in arid and semi-arid ecosystems soils had an increased content of organic matter, nutrients, water and higher biological activity under tree canopies (Isichei & Muoghalu 1992; Sanchez et al. 1997; Bouhafa et al. 2015). Soil management practices should take into account the effect of the distance from olive tree on soil fertility. Soil samples were collected from 0–10 cm, since surface soil is the main part of what organic matter inputs contribute to soil organic matter and is more sensitive to changes in the content of organic matter. In addition, about half of the microbial biomass is located in the surface (10 cm of a soil profile) and most of the nutrient release also occurs here. Furthermore, a general assessment of soil fertility below 10 cm took place by taking a composite soil sample at the depth of 10–40 cm close to the active olive roots.

Soil analysis was carried out via standard methodologies (Page et al. 1982). Total N (TN) was determined by the Kjeldahl method (ISO 11261; ISO 1995); soil organic matter (OM) was determined by sulfochromic oxidation (ISO 14235; ISO 1998); available P (Pavail) was determined by sodium hydrogen carbonate extraction (ISO 14263; ISO 1994), and exchangeable K (Kexch) and exchangeable Mg (Mgexch), using BaCl2 extraction (ISO 11260; ISO 1994). Determination of NH4+-N, NO3, was performed in 1:10 water extracts using Dionex-100 Ionic Chromatography (DX 1–03, USA). Humic acids (HA) and fulvic acids (FA) in soil samples were determined according to Metson et al. (1979). The microbial activity in soil samples was measured by the amount of CO2 evolved from moist (50–60% of water-holding capacity) soil samples incubated at 22 ± 2 °C, for 24 h. The CO2 evolved was determined by titrating 10 mL of the NaOH solution with 0.1 N HCl (Ohlinger 1995). The basal respiration (BR) was expressed as mg CO2–C kg–1 soil h–1 on a soil dry weight basis (105 °C, 24 h). Microbial biomass C (MB-C) was determined by substrate-induced respiration, after the addition of 1% glucose (Anderson & Domsch 1990) and expressed as mg C kg–1 dry soil. Main soil properties in control soil parcels are presented in Table 2.

Table 2

Main soil properties (means ± st deva) in soil parcels before initiation of organic matter inputs

 Mean ± st dev
 
Sampling location Clay,b (%) Silt, (%) Sand, (%) pH EC, (mS cm–1CaCO3, (%) OM, (%) TN, (mg g–1NH4+, (mg kg–1
UTCc 31 ± 4.6 39 ± 6.6 31 ± 6.2 7.3 ± 0.4 2.0 ± 1.0 16.7 ± 1.7 5.1 ± 1.1 2.3 ± 0.4 13.0 ± 5.6 
OuTC 28 ± 3.7 35 ± 5.0 37 ± 6.5 7.1 ± 0.3 1.5 ± 0.7 16.4 ± 4.6 4.1 ± 1.0 1.7 ± 0.3 21.9 ± 6.9 
10–40 cm 30 ± 4.3 39 ± 5.4 31 ± 2.0 6.9 ± 0.4 1.0 ± 0.9 17.5 ± 8.2 1.9 ± 0.6 0.9 ± 0.2 12.1 ± 4.2 
Sampling location NO3, (mg kg–1Pavail, (mg kg–1Kexch, (cmolc kg–1Caexch, (cmolc kg–1Mgexch, (cmolc kg–1HA, (mg g–1FA (mg g–1BR, (mg CO2–C kg–1 soil h–1MB-C, (mg C kg–1 soil) 
UTC 45 ± 7.9 52.4 ± 4.8 0.95 ± 0.23 25.5 ± 1.0 2.4 ± 0.3 3.1 ± 0.5 1.6 ± 0.3 0.169 ± 0.047 1.372 ± 0.298 
OuTC 38 ± 4.3 10.6 ± 1.5 0.64 ± 0.14 23.0 ± 1.3 1.6 ± 0.2 2.6 ± 0.3 1.3 ± 0.3 0.140 ± 0.045 1.122 ± 0.252 
10–40 cm 25 ± 3.8 28.8 ± 2.8 0.53 ± 0.26 17.0 ± 0.8 2.1 ± 0.4 2.2 ± 0.4 1.0 ± 0.2 0.087 ± 0.038 0.862 ± 0.337 
 Mean ± st dev
 
Sampling location Clay,b (%) Silt, (%) Sand, (%) pH EC, (mS cm–1CaCO3, (%) OM, (%) TN, (mg g–1NH4+, (mg kg–1
UTCc 31 ± 4.6 39 ± 6.6 31 ± 6.2 7.3 ± 0.4 2.0 ± 1.0 16.7 ± 1.7 5.1 ± 1.1 2.3 ± 0.4 13.0 ± 5.6 
OuTC 28 ± 3.7 35 ± 5.0 37 ± 6.5 7.1 ± 0.3 1.5 ± 0.7 16.4 ± 4.6 4.1 ± 1.0 1.7 ± 0.3 21.9 ± 6.9 
10–40 cm 30 ± 4.3 39 ± 5.4 31 ± 2.0 6.9 ± 0.4 1.0 ± 0.9 17.5 ± 8.2 1.9 ± 0.6 0.9 ± 0.2 12.1 ± 4.2 
Sampling location NO3, (mg kg–1Pavail, (mg kg–1Kexch, (cmolc kg–1Caexch, (cmolc kg–1Mgexch, (cmolc kg–1HA, (mg g–1FA (mg g–1BR, (mg CO2–C kg–1 soil h–1MB-C, (mg C kg–1 soil) 
UTC 45 ± 7.9 52.4 ± 4.8 0.95 ± 0.23 25.5 ± 1.0 2.4 ± 0.3 3.1 ± 0.5 1.6 ± 0.3 0.169 ± 0.047 1.372 ± 0.298 
OuTC 38 ± 4.3 10.6 ± 1.5 0.64 ± 0.14 23.0 ± 1.3 1.6 ± 0.2 2.6 ± 0.3 1.3 ± 0.3 0.140 ± 0.045 1.122 ± 0.252 
10–40 cm 25 ± 3.8 28.8 ± 2.8 0.53 ± 0.26 17.0 ± 0.8 2.1 ± 0.4 2.2 ± 0.4 1.0 ± 0.2 0.087 ± 0.038 0.862 ± 0.337 

aStandard deviation.

bElectrical conductivity (EC), soil organic matter (OM), total nitrogen (TN), inorganic nitrogen (NO3 and NH4+), available P-Olsen (Pavail), exchangeable K (Κexch), exchangeable Ca (Caexch), exchangeable Mg (Mgexch), humic acids (HA), fulvic acids (FA), soil basal microbial respiration (BR), microbial biomass carbon (MB-C).

cUC: under tree canopy 0–10 cm, OuTC: outside tree canopy 0–10 cm; 10–40 cm: composite sample in the vicinity of active tree roots.

Statistical analysis

It is critical to increase our understanding of the multiple factors affecting the variability of soil properties by applying the univariate general linear model (GLM). Data were analyzed using SPSS (SPSS Inc., Chicago, USA) and were subjected to multifactorial analysis of variance (ANOVA) using the GLM procedure using soil sampling period (T), irrigation practices (IP), cultivation practices-organic matter inputs (CP) and sampling location (SL) as factors (Table 3). Data were first tested for homogeneity of variance and normality and then were subjected to a multifactorial analysis of variance, followed by Duncan's multiple range test (DMRT) (a = 0.05) as a post hoc test, to measure specific differences between pairs of means within each main factor. In addition, due to the large number of complex interactions, we cited in figures only ‘very significant’ interactions (P < 0.001), which provided insights into cultivation practices in olive orchards. Data were subjected to one-way analysis of variance and DMRT.

Table 3

Factors considered in the experimental site

Factors Levels Properties considered 
Sampling period (T) Year 1 December 2012–February 2013 
Year 3 January 2015–February 2015 
Year 5 December 2016–January 2017 
Irrigation practices (IP) Irrigated soil parcels 
  • Drip irrigation, five drippers per tree each one with a discharge rate of 4 L h−1 and wetting a ∼1.0 m wide strip along the in-row

 
Rainfed soil parcels 
  • Mean annual rainfall 950 mm in the period considered for the trial (local station Filiatra, region of Messinia)

 
Cultivation practices (CP) Without addition of OM 
  • Reduced tillage/no-tillage

 
With addition of OM 
  • Reduced tillage/no-tillage

  • Compost at the dose of 1.12 t ha–1 (f.w.)

  • Chopped pruning residues at the dose of 1.36 t ha–1 year–1 (f.w.).

  • Incorporation of weeds, 11.35–11.51 t ha–1 year–1

 
Sampling location (SL) UTC Under tree canopy, soil depth 0–10 cm 
OuTC Outside tree canopy, soil depth 0–10 cm 
10–40 cm Composite sample from soil depth 10–40 cm in the close vicinity of active roots 
Factors Levels Properties considered 
Sampling period (T) Year 1 December 2012–February 2013 
Year 3 January 2015–February 2015 
Year 5 December 2016–January 2017 
Irrigation practices (IP) Irrigated soil parcels 
  • Drip irrigation, five drippers per tree each one with a discharge rate of 4 L h−1 and wetting a ∼1.0 m wide strip along the in-row

 
Rainfed soil parcels 
  • Mean annual rainfall 950 mm in the period considered for the trial (local station Filiatra, region of Messinia)

 
Cultivation practices (CP) Without addition of OM 
  • Reduced tillage/no-tillage

 
With addition of OM 
  • Reduced tillage/no-tillage

  • Compost at the dose of 1.12 t ha–1 (f.w.)

  • Chopped pruning residues at the dose of 1.36 t ha–1 year–1 (f.w.).

  • Incorporation of weeds, 11.35–11.51 t ha–1 year–1

 
Sampling location (SL) UTC Under tree canopy, soil depth 0–10 cm 
OuTC Outside tree canopy, soil depth 0–10 cm 
10–40 cm Composite sample from soil depth 10–40 cm in the close vicinity of active roots 

RESULTS AND DISCUSSION

Changes of soil properties with time (T)

The soil properties seem to be altered over time by the sustainable management practices. Soil OM significantly increased at the third sampling period (Year 5) compared to the first two (Year 3 and 1), while TN was significantly reduced (Table 4). The increase of OM may be partially attributed to the relatively lower microbiological activity and therefore low rate of C mineralization (Dersch & Bohm 2001). In fact, during the soil sampling campaign, BR and MB-C were significantly reduced and the reduction was more evident on surface soils than on subsoil (10–40 cm), as indicated by the significant TxTC interactions (F values = 8.301 and 8.325 respectively, P < 0.001) (data not shown). The reduced levels of soil TN are ascribed to the immobilization process due to a high C:N ratio of plant residues. In our study the C:N ratios of residues from olive tree pruning and olive leaves (Table 1) are 30–35 for leaves, 62–80 for small branches and 136–146 for thick branches indicating the immobilization process. Chen et al. (2014) concluded that the empirical critical C:N ratio of plant residues which cause the immobilization process should be greater than 44. Nitrogen in plant residues with high C:N ratios (>30) is retained by the microbial biomass during decomposition and released slowly (Ocio et al. 1991; Bremer & van Kessel 1992).

Table 4

Main factors (sampling period, irrigation practices, cultivation practices, sampling location) effects, using GLM procedure, on soil organic matter (OM), total nitrogen (TN), inorganic nitrogen (NO3 and NH4+) soil basal microbial respiration (BR) and microbial biomass carbon (MB-C)

Sourcea df F value
 
OMb TN ΝΟ3 ΝΗ4+ BR MB-C 
Sampling period (T) 30.209*** 6.708** 7.329** 29.172*** 111.833*** 49.945*** 
Irrigation practices (IP) 0.405 NS 0.608 NS 0.033 NS 2.235 NS 0.531 NS 1.112 NS 
Cultivation practices (CP) 2.581 NS 2.101 NS 1.268 NS 0.297 NS 0.110 NS 5.990 NS 
Sampling location (SL) 59.938*** 81.898*** 13.938*** 3.190* 100.170*** 112.723*** 
Main factor. Mean values ± sec 
Year 1 4.48 ± 0.23 a 1.93 ± 0.085 b 42.4 ± 7.01 a 18.1 ± 1.26 b 0.151 ± 0.004 c 1.23 ± 0.025 c 
Year 3 4.73 ± 0.14 a 2.04 ± 0.053 b 70.4 ± 8.62 b 7.7 ± 0.85 a 0.127 ± 0.003 b 0.92 ± 0.016 a 
Year 5 5.99 ± 0.15 b 1.86 ± 0.057 a 78.2 ± 3.77 b 5.5 ± 0.75 a 0.073 ± 0.003 a 1.14 ± 0.017 b 
IP Irrigated fields 4.87 ± 0.13 1.77 ± 0.05 60.9 ± 6.67 7.7 ± 0.72 0.100 ± 0.002 1.02 ± 0.015 
Rainfed fields 4.72 ± 0.14 NS 1.82 ± 0.05 NS 59.8 ± 4.95 NS 8.2 ± 0.75 NS 0.102 ± 0.003 NS 0.99 ± 0.015 NS 
CP Without OM addition 4.72 ± 0.12 1.81 ± 0.047 54.1 ± 5.0 9.4 ± 0.70 0.107 ± 0.002 1.05 ± 0.014 
OM inputs 4.90 ± 0.14 NS 1.77 ± 0.054 NS 68.8 ± 7.0 NS 5.9 ± 0.77 NS 0.093 ± 0.003 NS 0.95 ± 0.016 NS 
SL UTCd 5.87 ± 0.12 c 2.34 ± 0.045 c 84.1 ± 3.98 c 10.53 ± 0.71 b 0.138 ± 0.002 c 1.23 ± 0.013 c 
OuTC 4.70 ± 0.12 b 1.73 ± 0.045 b 57.4 ± 5.11 b 8.12 ± 0.69 b 0.108 ± 0.002 b 1.03 ± 0.013 b 
10–40 cm 3.63 ± 0.23 a 1.33 ± 0.085 a 36.1 ± 12.07 a 5.42 ± 1.33 a 0.069 ± 0.004 a 0.80 ± 0.025 a 
Sourcea df F value
 
OMb TN ΝΟ3 ΝΗ4+ BR MB-C 
Sampling period (T) 30.209*** 6.708** 7.329** 29.172*** 111.833*** 49.945*** 
Irrigation practices (IP) 0.405 NS 0.608 NS 0.033 NS 2.235 NS 0.531 NS 1.112 NS 
Cultivation practices (CP) 2.581 NS 2.101 NS 1.268 NS 0.297 NS 0.110 NS 5.990 NS 
Sampling location (SL) 59.938*** 81.898*** 13.938*** 3.190* 100.170*** 112.723*** 
Main factor. Mean values ± sec 
Year 1 4.48 ± 0.23 a 1.93 ± 0.085 b 42.4 ± 7.01 a 18.1 ± 1.26 b 0.151 ± 0.004 c 1.23 ± 0.025 c 
Year 3 4.73 ± 0.14 a 2.04 ± 0.053 b 70.4 ± 8.62 b 7.7 ± 0.85 a 0.127 ± 0.003 b 0.92 ± 0.016 a 
Year 5 5.99 ± 0.15 b 1.86 ± 0.057 a 78.2 ± 3.77 b 5.5 ± 0.75 a 0.073 ± 0.003 a 1.14 ± 0.017 b 
IP Irrigated fields 4.87 ± 0.13 1.77 ± 0.05 60.9 ± 6.67 7.7 ± 0.72 0.100 ± 0.002 1.02 ± 0.015 
Rainfed fields 4.72 ± 0.14 NS 1.82 ± 0.05 NS 59.8 ± 4.95 NS 8.2 ± 0.75 NS 0.102 ± 0.003 NS 0.99 ± 0.015 NS 
CP Without OM addition 4.72 ± 0.12 1.81 ± 0.047 54.1 ± 5.0 9.4 ± 0.70 0.107 ± 0.002 1.05 ± 0.014 
OM inputs 4.90 ± 0.14 NS 1.77 ± 0.054 NS 68.8 ± 7.0 NS 5.9 ± 0.77 NS 0.093 ± 0.003 NS 0.95 ± 0.016 NS 
SL UTCd 5.87 ± 0.12 c 2.34 ± 0.045 c 84.1 ± 3.98 c 10.53 ± 0.71 b 0.138 ± 0.002 c 1.23 ± 0.013 c 
OuTC 4.70 ± 0.12 b 1.73 ± 0.045 b 57.4 ± 5.11 b 8.12 ± 0.69 b 0.108 ± 0.002 b 1.03 ± 0.013 b 
10–40 cm 3.63 ± 0.23 a 1.33 ± 0.085 a 36.1 ± 12.07 a 5.42 ± 1.33 a 0.069 ± 0.004 a 0.80 ± 0.025 a 

aGLM model: main factors, values of F: *P< 0.05; **P< 0.01; ***P< 0.001; NS: no significant differences.

bOM in % TN mg g–1 soil, NO3 in mg kg–1 soil, NH4+- in mg kg–1 soil; BR in CO2–C kg–1 soil h–1, BM-C in mg C kg–1 soil.

cMean values for each measured parameter within factors, (T, IP, CP, SL) with the same letter are not significantly different (P < 0.05) according to Duncan's multiple range test; se: standard error.

dUTC: under tree canopy 0–10 cm, OuTC: outside tree canopy 0–10 cm, 10–40 cm: composite sample in the vicinity of active tree roots.

It is notable that no tillage practices or reduced tillage were applied to the soil parcels. Many researchers have reported that these practices can substantially increase carbon sequestration in soils (Álvaro-Fuentes et al. 2008), as a reflection of the greater accumulation of organic residues at, or near, the soil surface. This management practice improves soil water retention and reduces the temperature at the soil surface, all of which act to reduce the OM mineralization rate (Guimarães et al. 2013).

With regard to humic fractions, HA and the HA/FA ratio were significantly increased in Year 5 compared to Year 1 and particularly in control fields, being indicated by the significant TxCI interactions (F values = 14.119 and 15.647 respectively, P < 0.001) (Figure 1). On the other hand, no significant differences among sampling periods were registered for FA, indicating a relatively higher humification process in control fields at the last year of the experimental period. More humic acids than fulvic acids indicate the potentially low mobility of carbon accumulated in soil (Guimarães et al. 2013). A greater biological activity in control soils due to conventional tillage increases organic carbon (OC) mineralization and the production of soluble phenolic compounds and via polycondensation, the HA fraction is generated (Souza et al. 2016). According to some authors (Bayer et al. 2002; Ding et al. 2002), higher humification degrees were determined in surface soils under conventional tillage in comparison with those under no tillage.

Figure 1

Effects of sampling period (T) and cultivation practices (CP) on humic to fulvic acid ratio (HA/FA) and concentration of humic acids (HA) in soil. Mean values with the same letter are not significantly different (P < 0.05) according to Duncan’s multiple range test.

Figure 1

Effects of sampling period (T) and cultivation practices (CP) on humic to fulvic acid ratio (HA/FA) and concentration of humic acids (HA) in soil. Mean values with the same letter are not significantly different (P < 0.05) according to Duncan’s multiple range test.

Nitrate concentration was significantly increased in Year 3 and 5 compared to Year 1 while concentration of NH4+ was decreased indicating higher nitrification rates with increasing sampling period. Furthermore, NH4+ content was substantially higher in rainfed fields than in irrigated fields in the first year of soil sampling, while differences were diminished in the rest of the sampling periods as indicated by the significant TxIP interaction (F value = 11.151, P < 0.001) (Figure 2). These results showed that CP offered conditions that are more favorable for nitrification in rainfed soil parcels during the following years. As such, information on soil moisture conditions and the method of adding organic materials is vital towards generating management strategies, which can reduce the use of fertilizers, while offering less environmental degradation.

Figure 2

Effects of sampling period (T) and irrigation practices (IP) on ammonium concentration (NH4+) in soil. Mean values with the same letter are not significantly different (P < 0.05) according to Duncan's multiple range test.

Figure 2

Effects of sampling period (T) and irrigation practices (IP) on ammonium concentration (NH4+) in soil. Mean values with the same letter are not significantly different (P < 0.05) according to Duncan's multiple range test.

Considering exchangeable cations, K and Mg and available P, their concentrations reduced in Years 3 and 5 compared to Year 1. This is a reflection of the sustainable fertilization program for at least half of the olive fields, where alternative cultivation techniques have been applied. Furthermore, the accumulation of organic matter in soil during the experimental period contributes to the enhancement of soil cation exchange capacity (CEC), therefore increasing potassium fixation capacity and magnesium can form complexes with organic matter (Bertol et al. 2005). Organic amendments added to soils may also negatively influence P solubility (Iyamuremye & Dick 1996). Zhao et al. (2006) and Yu et al. (2013) reported that for soils with a pH > 6.0, the organic matter in the soil increased P-adsorption. In our study, mean levels (±standard deviation) of soil pH were 6.90 (±0.28), 7.01 (±0.21) and 7.12 (±0.22) in Years 1, 3 and 5 respectively (data not shown).

Effect of cultivation practices (CP)

Cultivation practices (CP) did not have a significant effect on ΟΜ, ΤΝ, inorganic nitrogen and microbial properties. In contrast, the long-term recycling of plant residues in combination with compost application can substantially increase OM (Montanaro et al. 2012). It seems that the relatively low amount of residues and compost applied to soil parcels may affect decomposition. Ordóñez-Fernández et al. (2015) pointed out that the largest percentage of loss of fine olive pruning biomass was recorded under treatment which involves the least amount of residues (2.65 t ha–1). Rui et al. (2016) noticed that the difficulty in increasing soil C by crop residue input may be related to the decrease of microbial carbon use efficiency. This is due to the fact that although microbial respiration should increase linearly with the addition of increased amounts of fresh organic matter, the response of the microbial biomass may not be significant, due to insufficient inorganic nutrients to form new biomass.

On the other hand, carbon inputs significantly reduced humic and fulvic fractions which is partially ascribed to the fact that OM and HA/FA did not significantly change by cultivation treatments. Humification depends on OM contents (González et al. 2003). The result may be the cause of accumulation of a greater proportion of non-humic substances, also called the light fraction, probably due to the recalcitrant compounds not being easily degradable by soil microorganisms in the source material. Adani et al. (2007) reported accumulation of no humic substances for soil treated with organic compost for four years.

With regard to Kexch, application of organic material significantly increased Kexch, due to the large proportion of woody plant material which was rich in K (Table 5). On the other hand, available P significantly decreased. During organic matter decomposition, macronutrients N, P and S are converted into inorganic forms and subsequently are either immobilized and used in the synthesis of new microbial tissues, or mineralized (Baldock & Nelson 2000). According to Ordóñez-Fernández et al. (2015) the application of the largest amount of fine residues, <8 cm in diameter (53.10 t ha–1), increases soil N, P and K with regard to the control sample, while the application of the least amount of fine residues (2.65 t ha–1) increases N and decreases P content. They suggested occurrence of phosphorus immobilization by microorganisms (Ngoran et al. 2006). Crop residues with higher P content (>0.24%) increased net P mineralization, while crop residues with low P content (<0.07%) resulted in net P immobilization (Nziguheba et al. 1998). In our study, the concentration of P in organic materials was lower than the upper limit, indicating low P mineralization. In addition, fresh plant litter can increase microbial activity and P demand, decreasing the labile P concentration and increasing the desorption and microbial uptake of inorganic P bound to Al- and Fe-oxides (Kunito et al. 2018). The microbial uptake rate of P might have been greater than the mineralization rate of the organic labile P fraction during this period. Thus, when microbial P increases available P decreases (Bünemann et al. 2013). As regards Mgexch, it was not significantly influenced by the cultivation practices.

Table 5

Main factors (sampling period, irrigation practices, cultivation practices, sampling location) effects, using GLM procedure, on humic:fulvic acids ratio (HA/FA), humic acids (HA), fulvic acids (FA), exchangeable K (Κexch), exchangeable Mg (Mgexch) and available P (Pavail)

Sourcea df F value
 
HA /FAb HA FA Kexch Mgexch Pavail 
Sampling period (T) 4.502** 7.185** 10.470*** 8.995*** 5.074** 9.494*** 
Irrigation practices (IP) 0.774 NS 0.450 NS 1.364 NS 0.128 NS 6.206** 0.556 NS 
Cultivation practices (CP) 3.462 NS 18.093*** 11.604** 8.850** 0.747 NS 4.413* 
Sampling location (SL) 0.896 NS 27.344*** 89.835*** 73.733*** 22.302*** 129.618*** 
Main factor. Mean values ± sec 
Year 1 1.86 ± 0.09 a 2.62 ± 1.36 a 1.44 ± 0.41 b 0.73 ± 0.24 2.01 ± 0.139 b 34.1 ± 3.34 b 
 Year 3 2.24 ± 0.06 b 2.65 ± 0.087 a 1.25 ± 0.03 a 0.55 ± 0.20 a 1.64 ± 0.079 a 22.3 ± 2.08 a 
 Year 5 2.15 ± 0.05 b 3.10 ± 0.092 b 1.44 ± 0.28 b 0.62 ± 0.20 b 1.84 ± 0.085 b 31.8 ± 2.31 b 
IP Irrigated fields 2.20 ± 0.06 2.75 ± 0.81 1.26 ± 0.02 0.58 ± 0.02 1.86 ± 0.074 b 28.4 ± 1.96 
 Rainfed fields 2.12 ± 0.06 NS 2.67 ± 0.81 NS 1.31 ± 0.02 NS 0.60 ± 0.02 NS 1.66 ± 0.077 a 26.8 ± 2.04 NS 
CP Without OM addition 2.18 ± 0.05 2.88 ± 0.08 b 1.33 ± 0.02 b 0.57 ± 0.15 a 1.78 ± 0.070 30.3 ± 1.86 b 
 OM inputs 2.12 ± 0.06 NS 2.47 ± 0.088 a 1.22 ± 0.03 a 0.62 ± 0.20 b 1.75 ± 0.081 NS 23.6 ± 2.18 a 
SL UTCd 2.06± 0.05 3.24 ± 0.07 c 1.59 ± 0.02 c 0.80 ± 0.18 b 2.18 ± 0.067 b 51.2 ± 1.79 c 
 OuTC 2.15 ± 0.05 2.67 ± 0.07 b 1.27 ± 0.02 b 0.49 ± 0.18 a 1.54 ± 0.067 a 10.3 ± 1.78 a 
 10–40 cm 2.24 ± 0.09 NS 2.20 ± 0.14 a 1.02 ± 0.04 a 0.52 ± 0.36 a 1.63 ± 0.128 a 19.9 ± 3.40 b 
Sourcea df F value
 
HA /FAb HA FA Kexch Mgexch Pavail 
Sampling period (T) 4.502** 7.185** 10.470*** 8.995*** 5.074** 9.494*** 
Irrigation practices (IP) 0.774 NS 0.450 NS 1.364 NS 0.128 NS 6.206** 0.556 NS 
Cultivation practices (CP) 3.462 NS 18.093*** 11.604** 8.850** 0.747 NS 4.413* 
Sampling location (SL) 0.896 NS 27.344*** 89.835*** 73.733*** 22.302*** 129.618*** 
Main factor. Mean values ± sec 
Year 1 1.86 ± 0.09 a 2.62 ± 1.36 a 1.44 ± 0.41 b 0.73 ± 0.24 2.01 ± 0.139 b 34.1 ± 3.34 b 
 Year 3 2.24 ± 0.06 b 2.65 ± 0.087 a 1.25 ± 0.03 a 0.55 ± 0.20 a 1.64 ± 0.079 a 22.3 ± 2.08 a 
 Year 5 2.15 ± 0.05 b 3.10 ± 0.092 b 1.44 ± 0.28 b 0.62 ± 0.20 b 1.84 ± 0.085 b 31.8 ± 2.31 b 
IP Irrigated fields 2.20 ± 0.06 2.75 ± 0.81 1.26 ± 0.02 0.58 ± 0.02 1.86 ± 0.074 b 28.4 ± 1.96 
 Rainfed fields 2.12 ± 0.06 NS 2.67 ± 0.81 NS 1.31 ± 0.02 NS 0.60 ± 0.02 NS 1.66 ± 0.077 a 26.8 ± 2.04 NS 
CP Without OM addition 2.18 ± 0.05 2.88 ± 0.08 b 1.33 ± 0.02 b 0.57 ± 0.15 a 1.78 ± 0.070 30.3 ± 1.86 b 
 OM inputs 2.12 ± 0.06 NS 2.47 ± 0.088 a 1.22 ± 0.03 a 0.62 ± 0.20 b 1.75 ± 0.081 NS 23.6 ± 2.18 a 
SL UTCd 2.06± 0.05 3.24 ± 0.07 c 1.59 ± 0.02 c 0.80 ± 0.18 b 2.18 ± 0.067 b 51.2 ± 1.79 c 
 OuTC 2.15 ± 0.05 2.67 ± 0.07 b 1.27 ± 0.02 b 0.49 ± 0.18 a 1.54 ± 0.067 a 10.3 ± 1.78 a 
 10–40 cm 2.24 ± 0.09 NS 2.20 ± 0.14 a 1.02 ± 0.04 a 0.52 ± 0.36 a 1.63 ± 0.128 a 19.9 ± 3.40 b 

aGLM model. Main factors, values of F: *P< 0.05; **P< 0.01; ***P< 0.001; NS: no significant differences.

bHA and FA in mg g–1 soil Kexch in cmolc kg–1 soil, Mgexch in cmolc kg–1 soil Pavail in mg kg–1 soil.

cMean values for each measured parameter within factors, (T, IP, CP, SL) with the same letter are not significantly different (P < 0.05) according to Duncan's multiple range test; se: standard error.

dUTC: under tree canopy 0–10 cm, OuTC: outside tree canopy 0–10 cm, 10–40 cm: composite sample in the vicinity of tree roots.

Effect of irrigation practices (IP)

The overall effect of IP was not significant for most of the soil parameters except Mgexch, the content of which in irrigated fields was higher compared to rainfed fields and particularly in soil parcels treated with organic amendments, as indicated by the significant IPxCP interaction (F value = 16.720, P < 0.001) (data not shown). This is due to the addition of organic materials and to the improved mobility of Mg in soil. Unlike other cations, Mg is very mobile in soils because it is less bound to the soil charges (Senbayram et al. 2015). High correlation coefficients with soil moisture were observed for Mg, in soil solution (Misra & Tyler 2000).

It is evident that irrigation practices did not affect soil fertility, due to the fact that the area under study receives high loads of rain and this masked any irrigation effect on soil properties. The adoption of irrigation best practices to local soil climatic conditions will increase yield of olive groves and water productivity and minimize yearly fluctuations in yield, and losses through evaporation or drainage will be reduced. It is also worth mentioning that most of the olive production areas receive much lower rainfall. Karyotis et al. (2014) concluded that irrigation significantly affected the chemical and microbial properties of soils. Ronchail et al. (2014) concluded that in Andalucía, Spain, by 2030–2050 a 15–30% rainfall reduction in the fall combined with a 7–9% annual reduction will cause a decrease of yields by 7% and 3.5% for rainfed and irrigated olive trees, respectively. Considering the climate change impacts on soil water balance, it is necessary to improve local irrigation practices in order to adapt to the climate changes. Consequently, irrigation frequency and load should be optimized based on monitoring precipitation and water storage in soil within the tree's root zone (Kourgialas et al. 2016).

Effect of sampling location (SL)

Soil chemical and microbial properties were significantly increased under the tree canopy (UTC) as compared to outside the canopy (OuTC). The area under the tree is richer in organic residues compared to the area that lies out of the tree canopy (Soria et al. 2005), owing to the accumulation of olive litter and because the impact of machinery passing up and down is much less. Moreover, the greater amount of soil surface residue favors an environment more suitable for microbial activity (Souza et al. 2016). In addition, nutrients in soils out of the tree canopy are subjected to leaching due to rainfall, while the replenishment of nutrient loss is limited. Soil management practices should consider the spatial distribution of soil properties in relation to the distance from the tree trunk.

As regards changes of soil properties according to depth, significant differences between soil depths 0–10 cm, under or out of the tree canopy and 10–40 cm were registered for most of the soil parameters, indicating that the potential of surface soil in olive groves to sequester carbon and nutrients is high. Maximum values of organic matter and nitrogen were also reported in surface soil layers (up to 10 cm) of olive groves (Nieto et al. 2011; Marquez-Garcia et al. 2013).

Our results conclusively showed that a combination of yearly olive residue amendments with reduced or no-tillage practices can constitute an effective way of sequestering carbon and promote nitrogen availability. Unfavorable results were recorded by CP. Organic amendments did not significantly alter ΟΜ, ΤΝ, inorganic nitrogen and microbial properties, while CP significantly reduced humic fractions, available P and favored exchangeable K. The main difficulty in increasing soil organic matter is the relatively low amount of organic materials applied to soil parcels each year and the addition of fresh organic matter, which is poor in nutrients and thus could result in poor response of the microbial biomass to form new biomass. Irrigation did not have substantial influence on soil fertility compared to rainfed olive orchards. The relatively high rainfall in the olive production region of south-western Peloponnese masked any irrigation effect on soil properties. Adjustments of soil management practices to the local soil climatic conditions should be made, in order to improve soil fertility and control environmental impact. Levels of soil chemical and microbial properties were significantly increased under the tree canopy as compared to outside the canopy indicating a more favorable environment for soil processes underneath the tree canopy. Moreover, changes in soil properties with depth showed that surface soil in olive orchards has the potential to sequester carbon and nutrients.

ACKNOWLEDGEMENTS

This work was supported by the European Commission in the framework of the LIFE11 ENV/GR/942 project entitled ‘Introduction of new oLIVE crop management practices focused on CLIMAte change mitigation and adaptation-oLIVE CLIMA’.

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