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Australian Journal of Soil Research, 2010, 48, 266–273

Changes in composition and activity of soil microbial communities in peach and kiwifruit Mediterranean orchards under an innovative management system Adriano Sofo A,C, Giuseppe Celano A, Patrizia Ricciuti B, Maddalena Curci B, Bartolomeo Dichio A, Cristos Xiloyannis A, and Carmine Crecchio B A

Dipartimento di Scienze dei Sistemi Colturali, Forestali e dell’Ambiente, Università degli Studi della Basilicata, Via dell’Ateneo Lucano 10, 85100, Potenza, Italy. B Dipartimento di Biologia e Chimica Agroforestale e Ambientale, Università degli Studi di Bari, Via Orabona 4, 70126 Bari, Italy. C Corresponding author. Email: [email protected]

Abstract. The aim of this work was to evaluate the effects of 2 soil management systems, so called ‘innovative’ (INN) and ‘conventional’ (CON), on genetic and metabolic diversity of soil microbial communities of peach and kiwifruit orchards. INN system included minimum tillage, organic matter inputs from compost and cover crops, winter pruning, and adequate irrigation and fertilisation. CON system was characterised by conventional tillage, zero organic input, empirical pruning, strong chemical fertilisation, and excessive irrigation. After 4 years of treatments, soil samples were collected in different orchard sites. In peach and kiwifruit INN orchards, average fruit yields were significantly higher than in CON. INN orchards had a significantly higher total number of bacteria. The patterns of denaturing gradient gel electrophoresis of bacterial 16S rDNA/RNA from peach orchard showed differences between soils under drip emitters and along the inter-rows, whereas those from kiwifruit orchard clearly distinguished between INN and CON for both bacteria (16S rRNA) and fungi (18S rDNA/RNA). Shannon’s substrate diversity index, evaluated by Biolog® metabolic assay, was affected by soil treatment in peach orchard and by soil depth in kiwifruit orchard. Principal component analysis of Biolog® values clearly discriminated INN and CON soils of both orchards. The results revealed qualitative and quantitative changes of soil microbial communities in response to an innovative and sustainable soil management. Additional keywords: Actinidia deliciosa, Biolog®, DGGE, Prunus persica, soil fertility, sustainable soil management.

Introduction The loss of soil quality is a process that mostly affects areas where intensive agriculture and an indiscriminate use of external energetic inputs (fertilisers, pesticides, water) are adopted (Lal 1997). For this reason, the optimisation and innovation of agricultural techniques with a low negative environmental impact can allow recovery of the normal levels of total fertility in agro-ecosystems and have positive effects on both soil and yield quality (Gruhn et al. 2000). In semi-arid Mediterranean agricultural lands, conventional, non-sustainable techniques, such as frequent and intensive cultivation, zero organic matter input, and use of excessive water and chemical fertilisers, can reduce soil organic matter and increase groundwater contamination, soil accumulation of mineral elements (in particular phosphorus and nitrogen), alkalinisation/salinisation, and nutritional imbalances in plants (Lal 1997; Gruhn et al. 2000). To obtain high yields of good quality and preserve environmental sustainability, chemical and biological soil fertility should be maintained through the choice of innovative, sustainable agricultural techniques (Kushwaha et al. 2000; Jagadamma et al. 2008). Agricultural management practices such as minimum tillage or no tillage, recycling of the  CSIRO 2010

carbon sources internal to the fruit grove (pruning material, spontaneous or/and seeded cover crops, compost amendments), and adequate irrigation, fertilisation, and pruning are recommended to save conventional water, restore soil organic matter, reduce erosion and environmental pollution, and increase the CO2 sequestration processes from the atmosphere into the soil (Lal 2004). These practices also have positive effects on soil microbiota, increasing microbial biomass, activity, and complexity (Kushwaha et al. 2000; Widmer et al. 2006). Soil microbiota, in turn, influence soil fertility and plant growth by regulating nutrient availability and increasing their turnover (Gruhn et al. 2000; Borken et al. 2002; Govaerts et al. 2008). Whereas an improvement of soil physicochemical properties is more evident in long-term (>10 years) adequate soil treatments (Brady and Weil 2008), molecular and biochemical patterns, microbial biomass, and metabolism of soil microbial communities change significantly in response to both long-term and short-term soil management (Bending et al. 2002; Marschner et al. 2003). One of the most useful molecular techniques to reveal qualitative changes in the structure of soil bacterial and fungal communities is based on the characterisation of conserved and 10.1071/SR09128

0004-9573/10/030266

Molecular and metabolic fingerprinting of soil microbial community

variable regions of the bacterial 16S rRNA gene (16S rDNA) and fungal 18S rRNA gene (18S rDNA) by denaturing gradient gel electrophoresis (DGGE). Metabolic diversity of a soil bacterial community can be estimated using the Biolog® EcoMicroplates metabolic assay (Insam 1997), based on the ability of microbial isolates to oxidise different carbon sources with a high discriminatory power among soil communities (Zak et al. 1994). The community-level physiological profile (CLPP) obtained by the Biolog® method is used to differentiate microbial populations from various soil environments or from soil subjected to various treatments (Calbrix et al. 2005). In the Mediterranean area, 16% of the total cultivable land is used for fruit orchards (Olesen and Bindi 2002). In Italy alone, peach (Prunus persica L.) and kiwifruit (Actinidia deliciosa cv. Hayward) groves cover an area of ~1.0  105 and 2.0  104 ha, respectively (ISTAT 2000). Peach and kiwifruit are 2 of the most economically important fruit species of the Mediterranean basin but most of the recent studies have focused on plant physiological behaviour (Montanaro et al. 2006; Dichio et al. 2007), without considering molecular and metabolic aspects of soil microbial community at orchard level. A new approach in fruit orchard management is imposed by environmental issues such as soil degradation as a result of erosion and desertification, water shortage, and the greenhouse effect (Hochstrat et al. 2006). Sustainable and innovative soil management systems in fruit growing can determine optimal plant nutritional equilibrium, avoid nutrient accumulation and leaching risks, improve irrigation efficiency, and prevent soil erosion and root asphyxia (Xiloyannis et al. 2005; Montanaro et al. 2006; Dichio et al. 2007). However, research into the definition of appropriate agricultural techniques and soil management in order to preserve soil quality, positively affect soil microbial activity and composition, and maintain high yields of high quality in Mediterranean fruit orchards is scarce. Therefore, the aim of this study was to explore the short-term effects of 2 different management systems on microbial genetic, functional, and metabolic diversity, evaluated by a combination of culture-dependent and culture-independent methods. Materials and methods Experimental design The study was conducted in peach (Prunus persica (L.) Batsch Nectarine cv. Supercrimson grafted on GF677) and kiwifruit (Actinidia deliciosa C.F. Liang et A.R.Ferguson var. deliciosa, own-rooted plants) orchards located in Bernalda (Southern Italy, Basilicata Region; 408240 N, 168480 E). Peach trees were trained to vase (500 plants/ha) with a north–south row orientation, whereas kiwifruit plants were trained onto pergolas (494 plants/ha). The climate was semi-arid (UNESCO-FAO classification), with an average annual rainfall of 525 mm. For 7 years (2003–07), each orchard was divided in 2 parts subjected to 2 different soil management and cropping systems, so called ‘innovative’ (INN) and ‘conventional’ (CON). CON orchards included conventional soil tillage, annual chemical fertigation (100 kg N, 10 kg P, 20 kg K/ha), empirical irrigation (without considering soil moisture and evapotranspiration, using excessive amounts of water), and empirical pruning (without considering soil nutrient levels

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and plant nutrient requirements) based on grower experience, and removal of pruning residues from the field. In contrast, INN orchards were subjected to a management system consisting of minimum tillage, cover crops (30 kg/ha of Trifolium subterraneum seeds and spontaneous grass), compost application (15 t/ha fresh weight; Eco-Pol SpA, VR, Italy; see Table 1 for compost characteristics) over the whole soil surface in the kiwifruit orchard and along the tree row tilled area in the peach orchard, winter pruning based on the selection of shoots with a high number of floral buds and on a better light interception in the canopy, and fertigation based on plant nutrient demand evaluated by leaf mineral analyses and on soil measured NO3– levels. At INN sites, the endogenous organic carbon inputs (cover crops and pruning residues) were chopped and mulched on the soil, whereas compost was buried into the soil by a light harrowing (depth 0.10 m) in autumn. The INN peach orchard was irrigated by 3 drip emitters per plant along the tree lines with capacity of 4 L/h each, while the INN kiwifruit orchard was uniformly irrigated by a microjet method (120 L/h) over the whole orchard surface. Irrigation scheduling and volumes were calculated on the basis of the equation ETc = ETo  Kc, where ETc is the evapotranspiration of the system, ETo the Penman–Monteith reference crop evapotranspiration, and Kc the crop coefficient (data from ALSIA Agrometeorological Service, Basilicata). Water balance was updated at 2-day intervals in order to schedule irrigation treatments when available water, calculated on the basis of soil texture parameters reported in Table 2, was 1: in peach orchard, PC 1, PC 2, and PC 3 were 14.51, 9.36, and 7.11, respectively; in kiwifruit, PC 1, PC 2, and PC 3 were 17.00, 8.74, and 5.25, respectively. The biplot in Fig. 4 showed the first 2 components accounted for most variance (77% for peach and 87% for kiwifruit orchard). In the peach orchard, the 4 datasets (2 managements  2 irrigation systems) were quite clearly separated from each other. In particular, PC 1 (accounting for 47% of total variance) separated soils from different locations (drip emitter/inter-row), while PC 2 (30% of the total variance) clearly discriminated soils of the 2 different management systems (INN/CON) (Fig. 4a). In kiwifruit orchard, PC 1 and PC 2 accounted for 59% and 28% of total variability, respectively discriminating the innovative from the conventional managed systems, as well as taking into consideration soil depths; in particular, the conventional cropping system in the deeper soil layer (KC 10/20) was markedly separated from the other 3 treatments (Fig. 4b). Figure 4 also reports the different carbon sources and how they contribute to discriminate among treatments; metabolic diversity of some soil samples (e.g. KI 0/10) is clearly due to the different utilisation of a great number of carbon sources, while metabolic diversity of other microbial communities (e.g. KC 0/10) seems to be affected by few substrates. Discussion Our data reveal significant differences between the innovative, high carbon input soil management system (INN) and the conventional, low carbon input system (CON). In particular, the higher fruit yield of both peach and kiwifruits orchards can be clearly attributed to the INN system (Table 3). On the basis of statistical critical F values, in both peach and kiwifruit orchards, total bacterial number was higher in INN (Fig. 1), likely because soil bacteria rely on external available nutrients and respond promptly to changes in organic nutrient matter (Borken et al. 2002; Peixoto et al. 2006). In contrast, total fungal counts showed no significant differences between soil management systems or sample location/soil depths (Fig. 1b). In a longterm study of the consequences of tillage and residue

Principal component 2 (28%)

Kiwifruit

2

(b)

KI 0/10

–2

2

KC 0/10 KC10/20

KI10/20

–2

Principal component 1 (59%) Fig. 4. Biplot of the principal component analysis of Biolog® EcoMicroplates in soils from (a) peach orchard and (b) kiwifruit orchard (n = 3). The symbols C2 to C32 indicate the 31 different carbon sources. P, Peach; K, kiwifruit; I, Innovative soil management; C, conventional soil management; D, soil along inter-rows; W, soil under drip emitters; 0/10, 0–0.10 m depth; 10/20, 0.10–0.20 m depth.

management on selected micro-flora groups, Govaerts et al. (2008) reported that total bacterial count was generally higher when residue was retained than when residue was removed and minimum tillage occurred. The positive effects of minimum tillage and organic carbon input on soil bacteria are due to increased soil aeration, cooler and wetter conditions, temperature and moisture buffering capacity of the soil, as well as higher carbon content in surface soil (Brady and Weil 2008). The number of cultivable microorganisms isolated from soil samples represents a minimal portion of the total bacteria and fungi inhabiting soil (Nannipieri et al. 2003). For this reason, it is necessary to combine culture-based microbiological methods with molecular techniques. In fact, different soil management systems, such as tillage modalities and organic farming

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practices, can induce a genetic alteration of soil microbial communities and changes in microbial community structure as assessed by DGGE analysis of PCR amplified 16S rDNA (Crecchio et al. 2004). In our study, this behaviour is clear in both 16S rRNA and 18S rDNA/rRNA DGGE dendrograms from kiwifruit orchard, which revealed a clear discrimination between INN and CON systems (Fig. 3b–d). For bacterial counts, the effects on microbial community structures were due to the concomitant effects of crop residue management, cover crops, compost application, and adequate irrigation. It is noteworthy that the fungal community evaluated by DGGE was affected by INN management, although no increase in size was observed (Fig. 1b). In fact, compost amendments strongly influence the composition of soil microbial communities because of the direct influence of the bacteria in the compost and the promoting effect of the compost on the bacterial activity and growth (Pérez-Piqueres et al. 2006; Chu et al. 2007). Differences in DGGE dendrograms of peach orchard soils were less marked, as indicated by the generally high values of similarity Pearson coefficient (Fig. 2). It seems that the irrigation regime is the main factor inducing changes in bacterial communities of sites under drip emitters and of sites 2.5 m from the emitters. Qualitative changes of soil bacterial communities in relation to water availability can be important in Mediterranean peach orchards, where the adoption of appropriate and adequate irrigation techniques, based on drip irrigation, is worthwhile to save water and improve plant water use efficiency (Boland et al. 2000; Dichio et al. 2007). These qualitative differences were less clear for fungal communities (Fig. 2c, d), as 18S DGGE dendrograms showed a lower discrimination among the 4 different soil treatments/locations combinations. Lower response of fungal communities to different soil treatments was also observed by Marschner et al. (2003), who demonstrated that bacterial diversity was affected by different organic and inorganic soil amendments, while no changes occurred in fungal community structure. Crop residue retention in the field and changes in soil organic matter can affect the metabolic diversity of the soil microbial communities evaluated by Biolog® CLPP (Bending et al. 2002; Govaerts et al. 2008). Mäder et al. (1996) observed low microbial diversity in long-term, conventionally managed areas, leading to the predominance of few groups of microorganisms. Soil bacterial metabolic diversity indices, as indicated by carbon substrate utilisation patterns, were also higher in sustainable than in conventional farms (Mäder et al. 1996). Our results show that in peach orchard, Shannon’s diversity index (H’) was significantly increased by INN management, whereas in kiwifruit orchard it was influenced by soil depth (Table 4). In addition to compost and available water, cover crops could be an important discriminating element for bacterial substrate utilisation between peach orchard INN and CON treatments, as recently observed by Carrera et al. (2007). Considering that univariate measures such as CLPP indices reduce the complexity to a single number, multivariate measures have been necessary to take into account the complexity of the datasets. So, visualisation of the scores and loadings by PCA biplot (Fig. 4) allowed us to highlight significant differences in the metabolic capability of soil microbial communities subjected to the 2 different management practices (INN or CON) in both the orchards.

A. Sofo et al.

Our study revealed qualitative (genetic and metabolic) and quantitative changes in soil microbial communities in response to an innovative, sustainable agricultural management. In Mediterranean orchards, under semi-arid climatic conditions, the adoption of exogenous (compost) and endogenous (cover crops, cultural and pruning residues) sources of organic matter and the measures used to slow down its mineralisation, as well as a correct water management, can be key factors for preserving or restoring soil bacterial metabolic diversity, so enhancing soil quality and fertility. At the same time, adoption of sustainable practices could help to obtain good-quality fruits, to preserve natural resources, mainly soil and water, and to avoid detrimental effects on the environment. Acknowledgments This research was supported by the national research projects FISRMESCOSAGR and BRIMET.

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Manuscript received 17 July 2009, accepted 21 October 2009

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