Management of Residues from Fruit Tree Pruning: A Trade-Off between Soil Quality and Energy Use

Abstract

In the EU, bioenergy is by far the most significant renewable energy source and more than two thirds of biomass utilized for energy conversion consists of forestry and agricultural residues, such as fruit tree pruning. Although still underutilized, biomass from pruning is a relevant energy feedstock that does not generate additional demand for land, nor negative impact on the environment and biodiversity. On the other hand, previously shredded pruning left in the field may sustain agricultural processes and help provide beneficial ecological services. In the latter case, the most relevant result is the increase in soil organic carbon, an essential factor for improving soil quality and promoting climate regulation. As a result, a “dilemma” arises for farmers over two conflicting pruning management options: “pruning to energy” vs. “pruning to soil”, respectively. The present study, performed in the frame of the Horizon 2020 project “uP_running”, is offering a straightforward evaluation tool to assess weather biomass resulting from fruit tree pruning could be removed from the field and used as energy feedstock without compromising both soil quality and the provision of important ecosystem services.

1. Introduction

A fruit tree plantation is a human-driven agricultural ecosystem where the farmer is managing its ecological functions to get a productive outcome. Ecosystems can provide services conceived as those benefits that people obtain from the proper functioning of ecosystems [1,2,3] through processes that support and satisfy important needs of human life [4]. In addition to delivering goods, i.e., the so-called “provisioning” services, ecosystems may also offer life “supporting” and “regulating” services, such as cleaning and purification, recycling and renewal, protection and control, also conferring several intangible aesthetic and cultural benefits [5].

The structure and the properties of the farming system (i.e., the integration of physical, chemical, and biological components forming the ecosystem) give origin to several functions. These functions, in turn, may provide several services, thus offering a wide range of benefits, either monetary or not-monetary, finally improving the quality of human life [6]. Therefore, a kind of “cascade effect” is activated: ecosystem structure → ecosystem functions → ecosystem services → human well-being.

When considering a fruit tree plantation managed according to sustainability criteria, a wide range of ecosystem services can be detected. Indeed, these services may include, apart from fruit production, also climate change mitigation by reducing GHG emissions, fossil fuel consumption and increasing carbon sequestration [7,8,9,10], soil nutrient recovery and cycling [7,8,11,12], improving water use efficiency and water regulation, preventing run-off and controlling erosion [7,8,13,14], biological control of pests and diseases, biodiversity, pollination, and many others [7,8,15,16,17,18]. The cultivation of a fruit tree plantation should maintain a suitable production while preserving natural resources and providing stable ecosystem services [17,18]. Managing multiple ecosystem services appears to be a great challenge [19] and requires a good knowledge about the underlying ecological functions and the effects of agricultural operations on these functions [17]. Farming management may affect ecosystem services positively or negatively; in the latter case, farming produces a “disservice” [19]. Sustainable agricultural management can mitigate or offset possible conflicts between “provisioning” services, on the one hand, and “regulating” or “supporting” services, on the other.

Within the agricultural system, the soil component encompasses a rich and complex soil biota. The soil ecosystem is marked by a wide range of functions, such as sustaining biological activity, diversity, and productivity; regulating and partitioning water and solute flows; filtering and buffering, degrading, immobilizing, detoxifying organic and inorganic materials (including industrial and municipal by-products) and atmospheric deposition; storing and cycling nutrients, etc. [20,21]. High soil quality refers to the full capacity of soil to perform all the array of functions assigned to it. Soil quality entails sustaining biological productivity, maintaining good environmental conditions, and promoting plant and animal health [22].

Soil ecosystem services are highly affected by the agricultural soil use [23]. Several authors [24,25,26] reported that soil management can be very influential on soil properties, in regulating the soil functions and services. With reference to fruit tree plantation, several soil management operations and agronomic practices are available to farmers: conventional, reduced or no-tillage; fallow soil or grass covering; mineral or organic fertilization; tree pruning and pruning residues management.

Pruning residues, when removed from the cultivated field, can be directed to energy conversion to obtain renewable forms of energy (heat and power), thus offering a supplemental “provisioning” service. This option is of particular relevance considering that replacing the use of fossil fuels with renewables is a relevant international goal, within the frame of the former Kyoto protocol (from 2005 to 2020) and the Paris agreement thereafter (from 2020 to 2030 and 2050). Conversely, pruning can be shredded and left on the soil surface to form a mulching, or alternatively incorporated into the soil top layer as manuring. Therefore, two contrasting, although complementary, pruning management options could be considered:

(a)

A provisioning service is delivered by converting biomass into a renewable form of energy. We can define this option as “pruning to energy” (PtE) and the service is provided outside the ecosystem from where pruning is sourced.

(b)

A regulating service is delivered when pruning residues are not removed but remains on the soil. This option can be defined as “pruning to soil” (PtS) and the service provided is aimed at preserving soil quality and fertility, thus maintaining the flow of supporting ecosystem services. These latter services are delivered inside the ecosystem from where pruning is sourced although the resulting benefits can also be useful outside.

Considering the “pruning to energy” option, new energy value chains are set up in the region, fossil fuels are displaced by renewable energy sources, and the concentration of carbon dioxide is gradually reduced from the atmosphere due to the “carbon neutrality” of biomass feedstock, thus mitigating climate change. In this regard, renewable energy is the final goal provided by the system, while the avoided or saved GHG emissions through renewables is the ecological service offered. Conversely, considering the benefits resulting from the “pruning to soil” option, a soil conservation management is performed and a range of regulating ecological services is, therefore, delivered. Particularly, atmospheric carbon (CO₂) is sequestered in the form of soil organic matter (SOM), soil fertility is promoted and, in the long run, agricultural productivity should result enhanced.

An impressive, unexpected and largely distributed amount of renewable energy is potentially obtainable from pruning biomass in Europe, although still largely underused. The theoretical potential of pruning from permanent crop in Europe is 252.0 PJ yr⁻¹ [27]. The surfaces of fruit tree cultivation in EU are 11.33 Mha, which corresponds to a theoretical potential of pruning availability approximately equal to 25 Mt yr⁻¹ (dry matter) if no other possible alternative uses are considered. This available biomass corresponds to 8.9 Mtoe yr⁻¹ of potential gross energy content that can be converted into a potential power generation of 23.9 TWh yr⁻¹. Alternatively, but still considering all the available biomass, a potential heat generation of 57.9 TWh yr⁻¹ can be obtained (our estimates).

Biomass from pruning, being a residual material, does not create any additional demand for land and can deliver substantial greenhouse gas emission savings compared to fossil fuels. According to the RED [28,29], no GHG emissions or energy consumptions should be assigned to the agricultural phase of a bioenergy value chain if crop residues, such as pruning, are removed from the agricultural land with the purpose of energy conversion. Clearly, this assumption is a very rough simplification and does not consider possible direct and indirect drawbacks related to a systematic withdrawal of crop residues [30,31]. A vast literature identifies several positive effects of crop residues on the physical, chemical and biological soil characteristics [30,31,32,33,34,35,36,37,38,39,40]. Among these benefits, soil organic matter increases, atmospheric carbon is sequestered, mineral nutrients are cycled, soil particle aggregation and soil structuring are improved, erosion can be controlled, and soil water infiltration and retention are raised.

Therefore, a “dilemma” arises for farmers regarding the option to choose, and a trade-off between the two alternatives becomes needed. Reconciling or combining these two contrasting pruning management operations is possible, thus obtaining renewable energy while preserving soil quality, its health status and fertility. Particularly, the conservation of SOM should be a precondition. Soil properties and functions should remain favorable and stable, not jeopardized by a decreasing trend in soil quality, leading to soil degradation and inadequate SOM turnover.

This study was performed in the frame of the H2020 project “uP_running” and it was aimed at working out an easy-to-apply empirical tool to assess whether pruning residues from a fruit tree plantation can be removed or should be retained in the field. Through a minimum set of properly selected indicators, soil properties were identified, together with information on local climate conditions, thus developing an evaluation tool that checks the prevailing soil quality conditions and their possible trends with respect to pruning management options. Based on the soil quality assessment, guidelines are recommended in selecting proper management operations to prevent soil degradation and ensure its long-term fertility, addressing the right destination for pruning residues.

2. Materials and Methods

2.1. Concept and Rationale of the Work

A multi-criteria procedure was developed to assess the suitability of removing pruning without causing a significant impact on soil quality and compensating for possible negative effects through proper agricultural management. The overall aim was to provide an easy-to-use but reliable procedure to assist farmers or agricultural professionals in making the right decision regarding pruning management. Three consecutive steps were considered (Figure 1).

Step 1.

Assessing the soil/climate conditions through the detection of only four indicators. A score is assigned to each indicator and the total score is given by their weighted average.

Step 2.

According to the resulting score, the appropriate soil management strategy is selected; it should be effective in maintaining or improving soil quality and preserving its organic content.

Step 3.

Applying the technical operations foreseen by the selected soil management strategy allowing the energy use of pruning while preserving soil quality.

In Section 2.2 and Section 2.3, the first two steps of the procedure are presented. In Section 2.4, the third step is accounted for, dealing with the agronomical operations suggested to develop a proper strategy to favor energy extraction from pruning. In Section 2.5, the experimental setup applied to test the sensitivity of the empirical model is described, and these results are presented in Section 3. In Section 4, a discussion is developed on the two compared alternatives, i.e., pruning “to soil” or “to energy”, respectively. Finally, in Section 5 concluding remarks about this “dilemma” are offered.

2.2. Assessing Soil and Climate Conditions

Proper soil and climate conditions should prevent any risk of soil quality degradation due to the pruning removal. In Step 1, a minimum set of soil properties and local climate conditions is considered. Only four indicators were selected. Soil organic matter (SOM) content is assumed the pivotal soil property directly influencing the pruning management strategy to be applied. The other indicators are related to SOM and can significantly affect its content. Soil texture, soil slope and erodibility, climatic conditions of the place are, respectively, the other selected variables [41,42].

Moreover, soil quality and its health status can be strongly affected by farming management [23]. To this respect, a sustainable soil management appears to play a crucial role in regulating a wide range of soil functions from which, in turn, services offered by a fruit tree plantation depend [43,44]. This range of soil functions is mainly associated with the soil organic matter and its carbon pool (SOC). Therefore, SOM (or SOC) content is the most relevant feature to assess soil conditions and its ability to lead most of the soil related functions (Figure 2).

Soil under cultivation should maintain its organic content that constitutes a stock of material and potential energy for the entire ecosystem biocenosis. When mineralization takes place, microorganisms use this energy, partly dissipated through respiration, while the released mineral nutrients become available to plant growth. The residual organic substances, more recalcitrant to mineralization, are “condensed” into polymeric humic compounds that improve soil quality and promote those microbial activities involved in many biogeochemical processes. Soil organic matter may be considered the “second engine” (i.e., an energy source) of every natural and agricultural ecosystem, the “first engine” being the sun.

With reference to SOM content, expressed as percentage of the soil dry weight, only the stable and humified compounds should be considered. The Carbon fraction is approximately 58% in weight with respect to SOM. Therefore, the conventional factor applied to convert soil organic carbon (SOC) to SOM should be equal to 1.724, although considering it a fixed factor may seem a simplification [45]. As a general indication, poor soils are those with a SOM value lower than 1.5%; moderately supplied are the soils with a SOM value in the range of 1.5–2.5%; finally, well supplied are the soils with a SOM value higher than 2.5% [46]. To be more accurate, it should be considered that soil texture significantly affects the SOM content [41,42]. SOM mineralization rate is higher in coarse- than fine-textured soils, therefore the SOM thresholds reported in

Table 1. Soil contents in organic matter (SOM), expressed as percentage of the soil dry weight and with respect to the main soil texture USDA categories.

Soil Texture Categories	Sandy Soils (1)	Loamy Soils (2)	Clay and Silty Soils (3)	General Guidelines
Very Low	<0.80	<1.00	<1.20	<1.00
Low	0.80–1.40	1.00–1.80	1.20–2.20	1.00–1.50
Moderate	1.40–2.00	1.80–2.50	2.20–3.00	1.50–2.50
High	>2.00	>2.50	>3.00	>2.50

⁽¹⁾ Sandy soils = Sand, Loamy Sand; Sandy Loam. ⁽²⁾ Loamy soils = Loam, Silt Loam, Clay Loam, Sandy Clay Loam. ⁽³⁾ Clay and Silty soils = Clay, Silty Clay, Silty Clay Loam, Sandy Clay, Silt. According to the United State Department of Agriculture (USDA).

gradually decrease as the clay fraction increases and the sand fraction decreases.

SOM content is also strictly affected by the prevailing climatic conditions (temperature and rainfall) of the considered agricultural zone. In this respect, warmer and more arid climatic zones allow for a significant lower amount of SOM as compared to colder and humid zone [41,42]. This is strictly related to the mineralization rate of SOM, assuming equal the amount of organic feedstock returning to the soil (raw organic input) in both climates. The effect of climate can be accounted for by the De Martonne aridity index (AI—see further on in this section). A correction factor, depending on the De Martonne index, considers that in more arid climates the potential value of SOM content is below the potential value observed in more humid climates. This factor compares the reference value AI = 24 to the actual value obtained from the climatic analysis. The assigned score related to SOM content (SCORE_1) can be calculated according to the following formula:

SCORE_1 = MIN [3; (γi + C × (24-AI)) × SOM]

(1)

Considering that the MIN [a;b] function returns the smallest value of numbers within brackets, SCORE_1 may range from 0 to 3. SOM is expressed as %, C is an empirical coefficient (C= 0.03), AI is the value of the De Martonne aridity index and γi is another empirical coefficient depending on soil texture, as specified below:

• γi = 1.65 if i = Sandy soil (Sand, Loamy Sand; Sandy Loam);
• γi = 1.25 if i = Loamy soil (Loam, Silt Loam, Clay Loam, Sandy Clay Loam);
• γi = 1.00 if i = Clay Silty (Clay, Silty Clay, Silty Clay Loam, Sandy Clay, Silt).

Soil texture strongly correlates with soil water holding capacity, water permeability and conductivity, aeration, compaction and mechanical workability. All these physical soil characteristics significantly affect SOM dynamic and its turnover [41,42]. Very coarse textured soils, characterized by higher sand fraction, are prone to SOM mineralization, while heavy textured soils, characterized by higher clay fraction, result in hard and compact soils, difficult to cultivate and highly prone to waterlogging. The best conditions are detected when loamy soils are available. Considering the procedure we are presenting, if clay percentage was between 10–30%, while silt and sand percentages are both below 50%, soil optimal conditions were assumed (Score_2 = 3). Conversely, still considering the soil clay content between 10–30%, while silt or, alternatively, sand were above 50%, then the soil conditions were considered moderately good (Score_2 = 2). Finally, if clay percentage was below 10% or above 30% then soil difficult conditions should be predicted (and the corresponding Score_2 = 1).

Concerning soil slope, the higher its value, the higher the risk of soil erosion when heavy rains occur. Soil texture and SOM are, in turn, also very influential in controlling soil erosion due to water runoff. Due to erosion, soil loss together with SOM depletion could be considerable. Soil erodibility (K) refers to soil’s inherent susceptibility to erosion. The K value of soil erodibility is taken from the Revised Universal Soil Loss Equation (RUSLE) approach and is obtained from an empirical equation [47]. The K value is proportional to the following formula:

K ∝ 0.21 × 10⁻³ × M^1.14 × (12 − a) + 3.25 × (b − 2) + 3.3 × (c − 3) × 10⁻³

(2)

Being: M = (Silt + Sand very fine) × (100 − Clay)

(3)

where M is the particle-size parameter, Silt, Sand very fine and Clay are expressed as percentage (%). Coefficient a is the percentage of SOM content. Coefficient b is the soil structure code (1 = very fine granular; 2 = fine granular; 3 = medium or coarse granular; 4 = blocky, platy or massive). Coefficient c reports the permeability class of the soil vertical profile, to be correlated to the saturated hydraulic conductivity (1 = rapid or ≥150 mm h⁻¹; 2 = moderate to rapid, in the range 50–150 mm h⁻¹; 3 = moderate, in the range 12–50 mm h⁻¹; 4 = slow to moderate, in the range 5–15 mm h⁻¹; 5 = slow, in the range 1–5 mm h⁻¹; 6 = very slow, <1 mm h⁻¹). It should be noted that the size of soil particles for very fine sand fraction ranges between 0.05 and 0.10 mm. The default value for b and c are 2 and 3, respectively.

Standard conditions were set in order to obtain a reference K₀ value. For this purpose, the following values were assumed: clay 20%, silt 40%, very fine sand 10% of the sand percentage (=4%), a = 1.5% (SOM content), b = 2 and c = 3.

Soil slope inclination (%) was then adjusted considering the following formula:

S_adj = S × K/K₀

(4)

If the adjusted soil inclination (S_adj) is lower than 9%, the cultivated soil can be considered flat or moderately flat. If the slope is between 9 and 20%, the cultivated soil can be considered markedly sloping. Finally, if the slope is higher than 20%, the cultivated soil can be considered strongly sloping. The assigned score related to soil slope (SCORE_3) can be calculated according to the following formula:

SCORE_3 = MAX [3–10 × sen φ; 1]

(5)

being φ the soil tilt angle (expressed in radians or degrees) equal to:

φ = arctan (Sadj/100);

(6)

Finally, the local climatic conditions can be characterized by applying the De Martonne’s annual aridity index [41] a climatic variable that refers to the mean values of temperature and rainfall over a proper representative period. The applied formula is the following: P/(T + 10); where P is the annual average precipitation (mm) and T is the annual average temperature (°C) of the considered place. The World Meteorological Organization recommends that climate averages are computed over a 30-year period of consecutive records [48]. The aridity index is clearly correlated with the SOM mineralization rate since higher temperatures and lower soil water availability promote SOM decomposition [41,42]. Using this index, climate can be classified as arid (AI < 10); semi-arid (10 ≤ AI < 20); Mediterranean (20 ≤ AI < 24); semi-humid (24 ≤ AI < 28); humid (28 ≤ AI < 35); very humid (35 ≤ IDM < 55); extremely humid (AI > 55) [32].

The assigned score related to climate (SCORE_4) can be calculated according to the following formula:

SCORE_4 = MIN [AI ÷ 10; 3]

(7)

2.3. Selecting the Proper Soil Management Strategy

Once the soil/climate conditions have been evaluated by assigning a score to each indicator, a comprehensive evaluation is obtained through the weighted average value of the four scores (SCORE_AVR) according to the following formula:

SCORE_AVR = ½ SCORE_1 + ⅙ SCORE_2 + ⅙ SCORE_3 + ⅙ SCORE_4

SCORE_1 is given the highest weight (½) considering that SOM content is the pivotal and more influencing variable. Moreover, a certain redundancy is associated with this variable since SOM is already affected by both soil texture (explicitly considered in SCORE_2) and climate conditions (accounted for by SCORE_4).

Observing the flowchart represented in Figure 1, if the total score is higher than 2.5, soil conditions are good or even optimal. If the calculated average score is in the range 1.5–2.5, soil conditions are not optimal but still good. Finally, if the calculated average score is lower than 1.5, soil conditions are bad or very bad. The average score can be associated with information about the proper strategy to be applied pertaining to soil and pruning management (

Table 2. Soil management strategies consequent to the average score assigned to soil quality conditions.

Average Score Value	Management Strategies
	“Green Light” Soil conditions are good or even optimal ⇒ full possibility to remove pruning from the soil, ⇒ no specific adjustment of soil management practices are needed, although… ⇒ a set of maintenance options of soil quality should be assured
	“Yellow Light” Soil conditions are not optimal but still good; surely not critical ⇒ pruning can be removed from the soil, but… ⇒ specific soil management strategy are requested, ⇒ an integration strategy of soil management should be applied, i.e., a mix of (at least) three “increasing” and other two “maintenance” options
	“Red Light” Soil conditions are bad or very bad ⇒ no possibilities to remove pruning from the soil, unless… ⇒ a strong readjustment of soil management practices is applied, ⇒ a set of increasing options of soil quality should be assured

).

When the average score is higher than 2.5, “minimum” soil quality conditions are fully met and a “green light” is turned on indicating that pruning removal is possible addressing its use to energy conversion. Therefore, no specific adjustments are necessary to improve the soil management currently applied, if at least the “SOM maintenance” operations are implemented. When the average score is in the range from 1.5 to 2.5, the “minimum” soil quality conditions are not fully met. A “yellow light” is turned on and specific management operations are suggested in order to counteract to soil quality degradation, thus establishing good agronomic practices that allow for residues to be removed and soil quality to be preserved. The prescribed “SOM integration” strategy is a combination of at least three “SOM increasing” and two “SOM maintenance” operations. Finally, if the average score is lower than 1.5, the “minimum” soil quality conditions are far from the optimal, a “red light” is turned on and pruning removal should be avoided. This time, a deep adjustment of current soil management practices is needed to establish better soil conditions with respect to SOM content. Therefore, a set of “SOM increasing” operations must be implemented if pruning is to be removed from the soil.

Moreover, whatever the initial soil conditions, management operations that risk decreasing soil quality should be avoided in any case, even if pruning residues are not going to be removed from the fruit-tree plantation (“precautionary principle”). Conversely, independently from the starting soil conditions, farmers should be encouraged to apply a soil quality increasing strategy, whatever the destination of pruning, both if it remains or is removed from the field (“best option principle”).

2.4. Management Strategies and Farming Operations

According to the identified soil management strategy, with the third step of the procedure (Figure 1) prescriptions are implemented. In this regard, soil management should take into account a set of technical options preserving soil quality and its ecological services. Sustainable soil management is focused on improving its organic fraction, i.e., maintaining, protecting and possibly increasing the SOM content by applying the best agronomic decisions. Such operations can be the following:

(i)

Supply organic fertilizers, manure, compost or soil improvers to increase the SOM level, counteracting its mineralization rate and also conferring better physical and structural properties to soil;

(ii)

Maintain, as long as possible, a year-round soil cover through organic mulching, with either living or dead biomass, provided by crop residues properly shredded or by a cover crop mowed at the end of its growth cycle and left at the soil surface;

(iii)

Apply minimum tillage or no-tillage to minimize soil disturbance and avoid the rapid SOM mineralization due to: the mechanical mixing of the active topsoil; the progressive loss of soil structure; the high soil compaction from heavy tractors.

According to these guidelines, organic fertilization, soil cover by grass and soil mechanical processes, together with operations on pruning residues, shall be considered the main influential soil management options.

A set of technical options, related to “SOM maintenance”, “SOM integration” and “SOM increasing” strategies, ensures that removing pruning from the fruit tree plantation does not compromise soil quality and its fertility in the long term. A list of technical options corresponding to each management strategy is reported in

Table 3. Technical management options to apply according to soil management strategies.

Management Strategies	Technical Options
	Organic Fertilization	Soil Cover in Space in Time		Soil Tillage	Mechanical Trafficability
SOM increasing strategy	organic fertilization and green manuring	total cover	permanent annual cover	absent (no-tillage)	low
SOM integration strategy	organic fertilization or green manuring	total or partial cover	permanent annual cover or extended winter cover	absent or significantly reduced	low or moderate
SOM maintenance strategy	possibly, green manuring	possibly partial cover	at least, winter cover	reduced tillage	moderate

.

In theory, no particular actions should be requested in applying a “maintenance” strategy, although Table 3 shows a set of good agronomic operations to prevent a decreasing trend in the SOM content. Differently, when an “integration” SOM strategy is recommended, farmers should apply soil operations allowing for pruning removal from the field without causing possible negative side effects. According to Table 3, a mix of good practices should be applied, such as 3 suggested operations to increase soil quality (“SOM increasing” strategy) and 2 operations to preserve soil quality (“SOM maintaining” strategy). Finally, when the soil conditions are very unfavorable the removal of pruning is not in line with the target of preserving soil quality. By default, in this case, pruning may have a major role as a carbon source to be added to the soil, and farmers should be recommended to use pruning as a carbon agronomic input, unless strong and persistent improving operations are implemented. Indeed, “pruning to energy” could be promoted only under the condition that farmers will drastically apply good practices including all the five available operations to improve soil quality (“SOM increasing” strategy).

2.5. Experimental Design and Model Sensitivity

An extensive analysis was performed applying different environmental conditions to the evaluation model. In total, 188 soil types were selected, spanning from coarse- to fine-textured soils according to a factorial combination of sand and clay (both sand and clay in the 5–95% range and a 5% increase). A wide variability in soil texture was therefore accounted for. Increasing conditions of SOM content (from 0 to 4%) were tested, as well as increasing values of aridity index, covering semi-arid conditions (AI = 16), Mediterranean climate conditions (AI = 20 and 24) to reach sub-humid (AI = 28) and humid (AI = 32) climate conditions. According to this choice, a representative range of climate conditions was taken into account to provide an adequate understanding of the effects that soil/climate factors have on the evaluation score, which in turn will direct towards a particular soil management strategy.

3. Results

Considering that SOM content is the pivotal soil variable, affected by both the aridity index (AI) and soil texture, the effect of these two factors on the SOM score (SCORE_1) was initially examined. Threshold scores of 1.5 and 2.5 were taken as a reference, respectively, because they separate “red” from “yellow”, and “yellow” from “green” soil/climate conditions. Considering 188 soil samples with different textures (but with fixed SOM, Slope and Aridity Index), the results show that the scores follow a statistical distribution. The mean score of this distribution (Mean_SCORE) can be targeted or, alternatively, the minimum score (Min_SCORE). If the minimum score in the distribution of 188 soil samples is to be greater than 1.5 or 2.5, the soil and climate conditions (relative to SOM, Slope or AI) must show much better quality compared to the conditions of soil and climate relative to the mean score of the same distribution. Therefore,

Table 4. SOM content (%) corresponding to threshold values of the SOM score (1.5 and 2.5, respectively), considering the mean and the minimum values of 188 soil textures. The effect of an increasing value of the aridity index (AI from 16 to 32) is taken into account.

De Martonne AI	16	20	24	28	32
Mean SOM_SCORE = 1.5	1.08	1.18	1.30	1.44	1.63
Min SOM_SCORE > 1.5	1.21	1.34	1.50	1.44	1.71
Mean SOM_SCORE = 2.5	1.80	1.98	2.20	2.47	2.81
Min SOM_SCORE > 2.5	2.10	2.30	2.60	2.90	3.30

reports the SOM content (%) related to these threshold scores with respect to increasing AI values. In general, SOM content must obviously increase in order to improve both the average and the minimal score. The shifting from “red” to “yellow” SOM conditions (i.e., SOM score > 1.5) needs SOM values in the range 1.08–1.71, while the shifting from “yellow” to “green” SOM conditions (i.e., SOM score > 2.5) needs SOM values in the range 1.80–3.3, whatever the AI value. As expected, the increase in AI values causes a progressive increase in the SOM transition values because soil environmental conditions are in favor of SOM accumulation as AI gets larger, while in arid and semi- arid climates (i.e., lower AI) the SOM mineralization rate is faster. Under Mediterranean climate conditions (AI 20–24) a SOM in the range 1.34–2.20% will ensure prevailing non-critical and acceptable soil conditions (“yellow light”). Conversely, a SOM below 1% should be considered a critical soil condition (“red light”) requiring extraordinary soil management interventions (Table 2 and Table 3).

Soil slope and soil erodibility are other relevant features to be carefully tested. SOM has the ability to stabilize soil structure and prevent erosion while the soil tilt angle increases soil erosion because it favors water run-off. The effects of these two factors on the Slope score (SCORE_3) are reported in

Table 5. Soil slope (%) corresponding to threshold values of the Slope score (1.5 and 2.5, respectively), considering both the mean and the minimum values of 188 soil textures. The effect of an increasing value of SOM content (from 0.5 to 2.5) is taken into account.

SOM (%)	0.50	1.00	1.50	2.00	2.50
Mean Slope_SCORE = 1.5	19.60	20.49	21.46	22.54	23.72
Min Slope_SCORE > 1.5	4.51	4.72	4.94	5.19	5.46
Mean Slope_SCORE = 2.5	4.40	5.65	6.04	6.33	6.67
Min Slope_SCORE > 2.5	1.49	1.56	1.63	1.71	1.80

. Again, the two threshold scores of 1.5 and 2.5 were taken as reference. For each soil texture, in order to have a score greater than 1.5 (“yellow light”) the soil must have a slope no higher than 4.5–5.5%, while for a score higher than 2.5 (“green light”), the soil slope should be lower than 1.49–1.80%, considering the different SOM contents.

The overall weighted average score (SCORE_AVR) was calculated for all 188 soils textures. The scores were aggregated and averaged according to the USDA soil texture categories. An Analysis of variance (ANOVA) was performed considering 12 USDA texture categories, three levels of SOM (1.0, 1.5 and 2.0%) and three levels of Slope (0, 5, 10 degree) in factorial combination, while AI was set constant and equal to 20. The applied ANOVA model is represented in

Table 6. Analysis of variance performed considering soil texture categories, soil organic matter and soil slope in factorial combination (total data number = 108).

Source of Variation	DF (3)	SS (4)	F (5)	Prob (6)
SOIL TEXTURE (1)	11	46.61	717.41	<0.0001	**
SOM (2)	2	41.56	3517.50	<0.0001	**
SOIL SLOPE	2	1.98	167.30	<0.0001	**
TEXTURE × SOM	22	1.08	8.30	<0.0001	**
TEXTURE × SLOPE	22	3.32	25.59	<0.0001	**
SOM × SLOPE	4	0.00	0.11	0.978	ns
TEXTURE × SOM × SLOPE	44	0.00	0.02	1.000	ns

⁽¹⁾ Soil texture classes according to the USDA categories; ⁽²⁾ SOM: Soil Organic Matter; ⁽³⁾ DF: Degree of freedom; ⁽⁴⁾ SS: Sum of squares; ⁽⁵⁾F: F-Fisher statistics; ⁽⁶⁾ Prob: Probability level (** highly significant; ns. not significant).

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Figure 3 shows the obtained scores. The effect of SOM on the scores is quite evident comparing the three graphs. When SOM is lower (SOM = 1.0%) approximately half of the soil classes are in the “yellow zone” (SCORE_AVR > 1.5), while the remaining are in the “red zone”. When higher SOM values are considered (SOM = 1.5%), all the soil classes are definitively in the “yellow zone” and some loamy soil classes are even approaching the “green zone” (SCORE_AVT > 2.5) when the SOM value is set to 2.0%. As expected, coarse and loam textured soils received the higher score, while clay and silty textured soils the lower. The observed ranking is, on average, the following: Loam; Sandy Loam; Loamy Sand; Sand; Sandy Clay Loam; Clay Loam; Silt Loam; Silt; Sandy Clay; Clay; Silty Clay Loam; Silty Clay. The effect of the soil tilt angle on the score values is generally limited but still effective, specifically in some soil classes rather than others. Interactions between SOM and Texture, as well as between Slope and Texture played, indeed, a significant role (Table 6). According to the aforementioned sequence of texture classes, from Loam to Sandy soils a higher SOM contents strongly favored the score; conversely, from Sandy Clay Loam to Silt soils a lower SOM contents further penalized the score; finally, the increasing score due to higher SOM contents was significantly attenuated in soils from Sandy Clay to Silty Clay.

With respect to soil slope, the significant interaction observed with soil texture can be described as follows. In loam and silty textured soils, the increase in the soil tilt angle further penalized the score more than the average effect, while in sandy and clay textured soils the opposite was observed, meaning that the decreasing score due to soil tilt was significantly attenuated. In the former case, this effect is particularly relevant in Silt and Silt Clay soil classes; in the latter case, Clay and Silty Clay soil classes showed the most pronounced leveling effect (Figure 3).

4. Discussion

4.1. Agronomic Operations Preserving SOM and Allowing for Pruning Removal

Farmers can apply different technical options to ensure sustainable soil management and to preserve or increase SOM content. The application of manure and compost to soil is the factor directly affecting soil carbon supply and its SOM balance. Composting is the aerobic process through which raw organic matter (such as tree residues from pruning, cereal straws, animal manures or the organic fraction of solid urban waste) is progressively decomposed and partially converted into stabilized humus. A useful soil amendment is obtained and different values of the C/N ratio characterize the subsequent stages of manure technological readiness. As composting proceeds, the C/N ratio gradually decreases from 30:1 to 10–15:1 for the finished product ready to be used [49,50]. This is due to the “condensation” of humified substances while carbon is partially converted to CO₂ through mineralization. The farming operations of organic fertilizing and/or compost supply are generally very effective in establishing a rapid and progressive increase in the SOM content and boosting soil fertility because of a large array of benefits [8,9,51]. For this reason, manuring or compost application are highly recommended, not only considering the supply of organic matter to the soil, but also because considered an even better alternative to pruning incorporation into the soil.

Soil covering, obtained by either sowing grass or preserving the grass naturally established (by self-seeding crops or weed plants), has two different ways to exert its soil protective action. One is related to “space” (the extent of soil actually covered), while the other is related to “time” (the period of the year when soil cover is established). The greater the covered surface fraction, both in space and time, the greater the benefit in terms of protecting the soil from erosion. The microclimatic conditions experienced by a covered soil are very positive to reduce evaporation from soil, preserve soil water, increase water infiltration, avoiding surface run-off and soil erosion, mitigate extreme temperatures (both max and min values), promoting bacterial and mycorrhizal activities, humification and nutrient cycling [12,52,53]. Green cover is becoming particularly common in vineyard, orchard and tree crop systems, by planting a non-crop species or allowing weed species to grow in inter-rows. Grass cover in inter-rows solves many problems of sustainability in exporting pruning for energy use. Soil cover by grasses provides an alternative carbon source for soil microorganisms and favor the buildup of humic substance into the soil [12,54]. Negative interactions between cover crop and fruit tree plantation should be controlled and minimized. Considering Mediterranean climate, autumn-winter season is the one mostly characterized by rainfalls, while spring-summer season is generally almost arid or semi-arid. During the rainy season, a large, dense and effective soil cover is useful to preserve soil from erosion. Moreover, tree activity in winter is slower or absent. Conversely, during the dry season, cover crops can compete with fruit trees for the limited available water, unless irrigation is applied and this competition is largely reduced or completely zeroed. Periodic mowing in the summertime may soften water competition between fruit trees and cover crops [55,56]. Therefore, a soil cover with grass is considered more effective in winter than in summer.

Intensive soil tillage, based on frequent machine passing to control weed, incorporate fertilizers, remove soil crusting or cracking due to drying, leads to a considerable soil structural degradation and soil loss due to erosion [38,57]. Moreover, tillage accelerates SOM decomposition as a result of the break-up of soil aggregates [39,58,59] and the consequent loss of organic carbon together with possible nutrient leaching. Generally, soil compaction, waterlogging, anoxic conditions are the resulting consequences of intense mechanical tillage and machine traffic. Soil management techniques that apply reduced tillage or no-tillage cultivation systems, in combination with cover crops, is an effective way for improving soil properties, reducing soil disturbance, diminishing GHG emissions by storing carbon in the form of organic matter, also protecting SOM from rapid decomposition [39,60,61].

Several approaches and procedures are available in the literature to perform a “soil quality assessment” based on a limited number of physical, chemical and biological soil indicators (“minimum data set”) [62,63,64,65]. In this respect, frequently a statistical “principal component analysis” is performed in order to extract a limited, coherent, non-redundant and representative set of indicators. These procedures can be used routinely in rural planning applications (“soil capacity” and “soil suitability” evaluation) and in supporting farmers’ management. As far as we know, the evaluation tool we have developed should be the first application specifically focused on pruning management by comparing the two options PtE and PtS, respectively.

An evaluation approach similar to the one we have applied in this work was developed in the frame of the EU project Europruning” [66]. Through an extensive carbon balance analysis performed on fruit tree plantations in different agricultural regions, the following “rule of thumb” was proposed: pruning removal should be avoided when soil cover in the tree inter-rows does not reach at least 80% of the soil surface or, alternatively, the biomass of the vegetation cover does not reach at least 3 t ha⁻¹ of fresh matter. According to these guidelines [66], pruning should be mulched (i.e., left on the soil surface once shredded) in poorly structured soil conditions, subject to compaction, water runoff and erosion. Otherwise, pruning should be shredded and lightly buried in the soil if soils are subject to waterlogging and anoxic conditions prevail.

Soil C sequestration refers to the increase in C stored in the soil by capturing atmospheric CO₂ because of changes in farming management. Carbon balance and soil organic carbon (SOC) dynamics should be considered the “litmus test” to check soil “quality” resulting from a change in soil management. Several reviews summarize the effects of different agricultural practices on soil C stocks compared to conventional practices. On this respect, the application of SOC simulation models to a series of experimental data, long-term data of soil properties in particular, can be very useful for targeting the best management strategies. Results obtained from the RothC simulation model [39,67] showed that mulching with shredded pruning significantly improved SOC content as compared to conventional tillage. An increase in SOC (13.2–14.4 t C ha⁻¹ yr⁻¹), a reduction in CO₂ emissions from soil (2.0–2.1 t CO₂ ha⁻¹ yr⁻¹, and a potential carbon sequestration (0.5–0.6 t C ha⁻¹ yr⁻¹) was observed according to soil type. From these results, it was concluded that preserving pruning at the soil surface, coupled with no-tillage and cover cropping, represented and optimal strategy for improving soil “quality”. Benefits on the SOC content derived from mulching with shredded pruning were observed in several other field experimental trials, not only in comparison with bare soil, but also with respect to a weed cover that farmers often allow to develop under no-tillage soil management regime [68]. The fine shredding of pruning sped up organic decomposition and the formation of a stabilized SOC fraction, the most active in improving soil fertility [68]. While pruning left on the soil is progressively degraded, an immobilization of soil Nitrogen should be expected due to the high C/N ratio of pruning, together with a CO₂ “priming effect”, at least temporarily [69].

4.2. The “Trade-Off” between “Pruning to Energy” and “Pruning to Soil”

As previously reported, there is no doubt that the shredding of pruning and its release in the field must be considered a good agronomic practice; however, at least so far, no explicit comparison has been made with the alternative energy use of pruning. The point, in fact, is whether it is better to target the “PtS” option or, the alternative one, i.e., “PtE”; in other words, if the environmental advantages on the front of fossil fuels substitution with renewable forms of energy can offset possible environmental disadvantages on the front of soil degradation (and consequent food insecurity).

Interestingly, this issue was expressly addressed by conducting a comprehensive LCA (“Life Cycle Assessment”) of the two contrasting paths: traditional mulching of pruning vs. their energy utilization [66,70]. Considering an apple orchard in Poland, results showed that the GHG emissions (Greenhouse Gases—measured in CO₂-eq) assigned to the PtE scenario were 200 kg CO₂-eq ha⁻¹, whereas for the PtS scenario the estimated emissions were 2360 kg CO₂-eq ha⁻¹. Therefore, an impressive GHG emission savings can be assigned to PtE as compared to PtS (2160 kg CO₂-eq ha⁻¹). This result was almost entirely dependent on the overwhelming effect of “fossil displacement” (i.e., the substitution of fossils by renewables) estimated to be 2340 kg CO₂ ha⁻¹, which benefited the PtE solution exclusively, but becoming an absolute burden on the PtS solution. When you consider that the energy mix of the Polish economy is largely based on energy obtained from coal (the most carbon-intensive fossil fuel), this striking gap becomes more intelligible. If natural gas were considered instead of coal, the PtS burden would be halved. Furthermore, if the country’s energy mix shared low-emission energy carriers (such as wind or photovoltaic power), the burden on the PtS would be further reduced. Therefore, the PtS solution largely depends on the country’s energy mix.

Observing Figure 4, the climate mitigation strategy based on “PtE” is focused on the concept that biogenic carbon flows (obtained from biomass) counteract the anthropogenic flows of fossil carbon. In this way, the linear flow of fossil carbon (coming from the earth’s crust and directed into the atmosphere) should be replaced by a circular flow of biogenic carbon (from the atmosphere to biomass and vice versa).

An effective mitigation strategy (resulting in the reduction of the atmospheric CO₂ concentration) is actually achieved on condition that fossil displacement is real (i.e., the use of fossil fuels is truly replaced). Moreover, the carbon “neutrality” condition (only theoretically assumed) should be met or at least approached as close as possible. The latter is a very crucial condition and it means that the unavoidable GHG emissions associated to the entire biomass-bioenergy conversion process are significantly lower than those linked to the fossil fuels they replace. In short, two conditions must be met: a real replacement of fossil fuels and a significant GHG saving with respect to fossils.

Alternatively, the “pruning to soil” climate mitigation strategy is totally relying on the soil carbon sinking capacity, i.e., the rate at which CO₂ is removed from the atmosphere through soil carbon sequestration via biomass released to the soil. This represents a “carbon negative” approach to climate change mitigation.

Referring to the “traffic light” analogy that we have previously developed, when soil/climate conditions are favorable (“green light”), the PtE pathway can be followed. Otherwise, when soil/climate conditions are prohibitive (“red light”), the PtS pathway should be prioritized (until “red” light is turned into “yellow”, at least). However, what to do when soil/climate conditions show an intermediate score (“yellow light”)? A trade-off is needed, in this case; it means sustain SOM and soil quality while allowing for an energy utilization of pruning. Observing Figure 4, one possible option is to alternate PtE and PtS at a frequency considered the most appropriate and, for example, targeting pruning to energy once every two or three years, or some other rate, moving soil conditions to turn from “yellow” to “green”.

Just one last comment. Considering the opposite although complementary mitigation strategies (“pruning to soil” vs. “pruning to energy”), there are two significant constraints that should be taken into account. These constraints progressively restrict the efficiency of climate mitigation (i.e., the GHG saving rate) to the extent they achieve a good degree of implementation.

(a) The efficiency of fossil displacement will decrease over time as the average carbon intensity of the produced energy mix (made of both fossil and renewable energy) will be reduced thanks to fossil replacement itself. In fact, the emission factor linked to energy use gradually decreases over time thanks to the increasing share of renewables in the energy mix.

(b) The efficiency of carbon soil sequestration will be reduced over time as the SOC content is approaching a saturation threshold depending on soil and climate conditions as well as soil management operations. When these conditions of soil carbon saturation are met, only carbon maintenance can be performed, but no further carbon sinking will occur. Furthermore, the closer the soil to carbon saturation, the lower the annual amount of sequestered atmospheric CO₂.

Therefore, it should be evident that estimating the trade-off between “pruning to energy” and “pruning to soil” is not an easy task since it also depends on the historical trend of market penetration made by renewable energies and their technological maturity as well as in the soil evolutional trend in carbon sink and sequestration.

5. Conclusions

Under the stressful urgency of reducing GHG emissions and mitigate global warming is the threat of “sacrificing” the ecological sustainability of agriculture in pursuit of greater sustainability of the energy sector. This condition identifies a trade-off close to zero with “energy prevailing over the soil”. Conversely, the sustainability concept should be considered as a whole. It means pursuing energy sustainability without compromising agricultural sustainability or jeopardizing the natural capital and the ecological services delivered by it. Therefore, the agroecosystem management should address the following “trade-off” criteria: soil quality, its health and fertility are preconditions and necessary requirements in performing a sustainable form of agriculture. The setting up of a bioenergy value chain based on the use of crop residues requires that pruning removal from the soil is allowed only if correctly carried out (i.e., in the proper annual amounts according to sustainable extraction rate criteria) and provided that the quality of the soil is not negatively affected. Good agricultural and environmental conditions should be applied in the cultivation of the orchard, according to a well-defined operational strategy. The rationale behind this strategy is to apply compensatory interventions able to fully counteract possible deteriorating effects on soil and the whole agroecosystem functioning. This strategy should be intended as a “minimum level of maintenance” requested to allow for pruning extraction. The concept refers to the “good agricultural and environmental conditions” (GAEC) addressed by the EU Common Agricultural Policy (CAP).

The proposed approach is a multi-criteria assessment procedure based on just a few soil characteristics (organic matter content and texture), information about the cultivated field (soil slope) and about the climate (temperature and rainfall) of the place where the fruit tree plantation is located. This information is generally accessible to farmers; therefore, the proposed method can be applied directly to help farmers in managing pruning residues correctly and achieve the greatest environmental benefits.