Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table 5-2:** Physico-chemical parameters of the mineral fertilizers NPK 0.32.16 and 15.5.20 and composts used in the study, total content dry weight (DW) measured by alkali fusion and aqua regal and comparison with the limit values of NFU 44-051 regulation. Numbers in brackets correspond to standard deviation (n=2)</caption><thead><tr><th></th><th></th><th>pH<sub>H20</sub></th><th>C</th><th>C/N</th><th>P</th><th>K</th><th>Ca</th><th>Mg</th><th>Fe</th><th>Mn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr><tr><th></th><th></th><th>-</th><th>g.kg<sup>-1</sup></th><th>-</th><th></th><th></th><th></th><th colspan="5">Alkali fusion (mg kg<sub>DW</sub><sup>-1</sup>)</th><th></th><th></th><th></th></tr></thead><tbody><tr><td rowspan="2">Mineral fertilizer</td><td>NPK 0.32.16</td><td>2.9</td><td></td><td></td><td>158 129</td><td>120 384</td><td>89 729</td><td>7 397</td><td>8 186</td><td>776</td><td>23</td><td>40</td><td>34</td><td>175</td></tr><tr><td>NPK 15.5.20</td><td>6.5</td><td></td><td></td><td>24 416</td><td>135 729</td><td>5 636</td><td>18 391</td><td>260</td><td>78</td><td>6</td><td>16</td><td>18</td><td>275</td></tr><tr><td rowspan="3">Compost</td><td>2019</td><td>5.9<br>(0.0)</td><td>218<br>(5)</td><td>9.79</td><td>10 322<br>(116)</td><td>10 495<br>(183)</td><td>22 535<br>(88)</td><td>13 742<br>(211)</td><td>36 080<br>(1 111)</td><td>789<br>(23)</td><td>410<br>(26)</td><td>1 231<br>(207)</td><td>77<br>(3)</td><td>223<br>(9)</td></tr><tr><td>2020</td><td>6.0<br>(0.0)</td><td>208<br>(23)</td><td>8.20</td><td>13 004<br>(30)</td><td>9 536<br>(385)</td><td>22 388<br>(444)</td><td>18 640<br>(526)</td><td>44 142<br>(2 716)</td><td>676<br>(67)</td><td>512<br>(10)</td><td>1 345<br>(17)</td><td>102<br>(5)</td><td>325<br>(21)</td></tr><tr><td>Mean<br>(sd)</td><td>5.9<br>(0.1)</td><td>212<br>(17)</td><td>8.73<br>(0.91)</td><td>12 110<br>(1549)</td><td>9 855<br>(617)</td><td>22 437<br>(326)</td><td>17 007<br>(2852)</td><td>41 454<br>(5 035)</td><td>714<br>(81)</td><td>483<br>(51)</td><td>1 307<br>(67)</td><td>94<br>(15)</td><td>291<br>(61)</td></tr><tr><td rowspan="3">Compost</td><td></td><td></td><td></td><td></td><td colspan="8">Aqua regal (mg kg<sub>DW</sub><sup>-1</sup>)</td><td></td><td></td><td></td></tr><tr><td>2019</td><td></td><td></td><td></td><td>8 029<br>(129)</td><td>7 187<br>(54)</td><td>16 962<br>(370)</td><td>5 005<br>(25)</td><td>19 770<br>(701)</td><td>533<br>(8)</td><td>416<br>(24)</td><td>329<br>(22)</td><td>96<br>(10)</td><td>302<br>(36)</td></tr><tr><td>2020</td><td></td><td></td><td></td><td>13 860<br>(349)</td><td>7 996<br>(483)</td><td>25 318<br>(336)</td><td>19 366<br>(626)</td><td>64 333<br>(6 122)</td><td>613<br>(61)</td><td>457<br>(16)</td><td>421<br>(21)</td><td>96<br>(6)</td><td>315<br>(12)</td></tr><tr><td></td><td>Mean<br>(sd)</td><td></td><td></td><td></td><td>11 916<br>(3 375)</td><td>7 726<br>(579)</td><td>22 533<br>(4 831)</td><td>14 579<br>(8 303)</td><td>49 479<br>(26 090)</td><td>586<br>(63)</td><td>443<br>(26)</td><td>391<br>(55)</td><td>96<br>(4)</td><td>310<br>(11)</td></tr><tr><td colspan="2">NFU 44-051<br>regulation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>60</td><td>120</td><td>300</td><td>600</td></tr></tbody></table>
For the first year, the fertilizers were mixed in the planting hole. From the second year of cultivation, all fertilizer inputs, including composts, were applied on the surface without soil mixing because of surface-root trees. Inputs were divided into two parts along the cropping cycle, i.e., 65 % in July/August for the flowering and fruit setting and 35 % in December for the fruit growing (Table 5-3).

<table><caption>**Table 5-3:** Trace metal input in soils; *mixed in the planting hole** input divided in two parts (65 % in July/August at flowering and fruit setting and 35% in December at fruit growing). Amount of fertilizer applied in soils</caption><thead><tr><th>Crop cycle</th><th>Spreading</th><th>Mineral fertilizer</th><th>Dose 1 compost</th><th>Dose 2 compost</th></tr></thead><tbody><tr><td rowspan="2">Year 1:<br>2019-2020</td><td>Planting</td><td>0.32.16</td><td>3 kg raw matter</td><td>12 kg raw matter</td></tr><tr><td>hole*</td><td>2 kg</td><td>2.16 kg dry matter</td><td>8.63 kg DW</td></tr><tr><td rowspan="4">Year 2:<br>2020-2021</td><td rowspan="4">Surface**</td><td>15.5.20</td><td></td><td>12 kg raw matter</td></tr><tr><td>0.25 kg</td><td></td><td>6.52 kg DW</td></tr><tr><td>15.5.20</td><td></td><td>6 kg raw matter</td></tr><tr><td>0.15 kg</td><td></td><td>2.96 kg DW</td></tr></tbody></table>

Those different fertilization treatments were coupled with two types of soil management, i.e., leguminous cover crop or straw mulching. In November 2019, 20 bales of straw of 250 kg each were applied on the row of the orchard in December 2019 and then 43 and 60 bales in June 2020 and March 2021, respectively. The cover crop, *Arachis pintoï* was planted in December 2019.

Twice a year soil sampling was performed in the surface layer (0-20 cm), the first $t_{3-1}$ corresponded at 3 months after the tree planting and fertilization application, then $t_{11-1}$ was made just before the second input of fertilizer or compost. On the second year, same sampling campaign was followed, i.e., $t_{3-2}$ and $t_{11-2}$. One soil sampling represents one composite sample of 12 samplings, i.e., one per tree, for each modality and each block. The sampling was performed in the clockwise direction, shifting by 90°C at each campaign in order to consider the soil heterogeneity. The soil was sampled in the 0-20 cm horizon, and at 15 cm from the tree trunk, i.e., in the rhizosphere influenced by fertilizers.

### 1.2.2. Physical and chemical analyses

Soil and compost analyses were performed at the LAMA laboratory (ISO 9001, Laboratoire des Moyens Analytiques, US Imago IRD, Nouméa, New Caledonia). Soil samples were air-dried, sieved to 2 mm and grounded to 0.25 mm. Residual water was determined by drying samples at 105°C for 24 h. Total C and N were determined by catalyzed dry combustion-oxidation with a CHN SERCON INTEGRA 2® analyzer. Soil pH$_{H2O}$ and pH$_{KCl}$ of soil were determined following the NF ISO 10390 procedure with a solid:liquid ratio of 1:5. pH$_{H2O}$ of compost was determined following the same procedure. Assimilable N was measured by internal procedure of LAMA (ISO 14256-2; US IRD Imago, Nouméa). Total concentrations of major and trace elements P, K, Ca, Mg, Fe, Mn, Ni, Cr, Cu and Zn were determined by akali fusion (NF
ISO 14 869-2) and then analyzed by ICP-OES using a VARIAN® 730ES spectrometer. Pseudo-total concentrations were aqua regia digestion (NF EN 13 650) and then analyzed by ICP-OES or ICP-MS using a PERKIN ELMER® NexION 350x Inductively Coupled Plasma Mass Spectrometry. EDTA extractable fraction of Ni, Cr, Cu and Zn in soils and composts have been evaluated by the “BCR” method (Quevauviller, 1998). EDTA at 0.05M was retained with a ratio of 1:10 in order to avoid a possible lack of chelating agent. CaCl₂ extractable fraction was performed at 0.01 M with a ratio of 1:10, shaking 2 h (ISO 21268-2, 2019; Houba et al., 1990; Lebourg et al., 1996). Measurement of pH was performed after CaCl₂ extraction and was highly correlated to pH<sub>H2O</sub> measurement (R²=0.9984, p-value<0.001) (Figure SI 5-4). Thus, pH<sub>H2O</sub> was choose and described in the results hereafter.

From extractable EDTA and CaCl₂ concentrations, distribution coefficient of soil/solution (Kd: L kg⁻¹) of Cr, Ni, Cu and Zn were calculated according to the formula (Eq. 1):

$$Kd = \frac{C_{EDTA}}{C_{CaCl_2}} \quad (1)$$

Where C<sub>EDTA</sub> corresponded to extractable EDTA concentrations of trace metals (mg kg⁻¹) and C<sub>CaCl₂</sub> to extractable CaCl₂ concentrations of trace metals (L kg⁻¹). Kd allows to evaluate the partitioning of solid and solution phase.

Straw and cover crops were sampled in order to evaluate total concentrations of Cr, Ni, Cu and Zn input or accumulation by plants. Samples were oven-dried at 60°C during 48 h and ground at 0.25 mm. Total trace metals were measured after HNO₃ digestion following an internal procedure of LAMA (US IRD Imago, Nouméa) with a solid:liquid ratio of 1:10 attacked overnight, then hitting during 2 h at 100°C. 0.5 mL of H₂O₂ was added and tubes were a second time hit at 100°C during 2h. After cooling of the tubes and diluted with 10 mL of ultrapure water, tubes were centrifuged at 3 000 tours min⁻¹ during 5 min, and then analyzed by ICP-MS.

Quality controls were performed by calculating a z-score statistic indicator on the internal soil reference samples and certified reference material BCR® n°483 sewage amended soil (European Commission). All glassware used for the experiments was previously cleaned with HNO₃ (10%) overnight and rinsed with ultra-pure water. The reagent blanks were negligible and blank concentrations were systematically subtracted from sample concentrations. All the data presented was blank corrected.

### 1.2.3. Assessment of trace metal accumulation in soils

Different indexes can assess the degree of contamination in soils. The geo-accumulation index (Igeo), originally proposed by Müller (1979), is widely used to assess the potential risks of trace metals that derive from anthropogenic activities. The Igeo is calculated with the following equation (2):
$$Igeo=log2(\frac{C_n}{1.5\times B_n}) \qquad (2)$$

where Cn denotes the concentration of trace metal in the soil (mg kg⁻¹) and Bn represents the corresponding background value and was assessed on the soil without fertilization (mg kg⁻¹). A constant of 1.5 allows to analyze natural fluctuations and to detect very small anthropogenic influences. A positive Igeo indicates that there is a large trace metal contribution from anthropogenic activities. Seven classes of Geoaccumulation Index range as followed: uncontaminated (Igeo < 0), uncontaminated to moderately contaminated (0 < Igeo < 1), moderately contaminated (1 < Igeo < 2), moderately to heavily contaminated (2 < Igeo < 3), heavily contaminated (3 < Igeo < 4), heavily to extremely contaminated (4 < Igeo < 5), and extremely contaminated (Igeo > 5).

### 1.2.4. Data treatments

Statistical analyses used to study variation of extracted trace metals according to fertilization modality and soil management were interpreted by ANOVA and Newman-Keuls comparison (p-value < 0.05%) after testing the normality of residues and equality of variances by Shapiro and Levenne tests. In cases these conditions were not applicable, Kruskal-Wallis and Dunn tests were applied. To test the evolution of the CaCl₂ and EDTA concentrations of trace metals, and soil physical chemical parameters, both the fertilization and the soil management were tested with block factor considered as a randomized factor at each soil samplings. Principal components analysis (PCA) was used to visualize both effects of soil parameters and fertilization types in EDTA- and CaCl₂ concentrations of Ni, Cr, Cu and Zn. PCA was performed with FactoMineR and factoextra packages. Simple linear regression was calculated between CaCl₂- and EDTA-extractable concentration of trace metals. Multiple linear regressions were performed between CaCl₂ trace metals and other soil properties using MASS package. Indeed, soil parameters used as explicative variables are pH, C and total concentration of the given trace metal. Soil texture was not selected because it is unlikely that texture has been influenced by fertilization. Parameters such as P, N, K contents which are influenced by fertilization and partially correlated with both C or pH, were not selected. For log(Kd) models, only two parameters were selected, i.e., pH and log of C. Logarithms of variables were also preferred to untransformed variables. Indeed, pH is already considered as the log of a variable. Coefficients of distribution (Kd) were calculated as ratios of EDTA- on CaCl₂-concentrations of trace metals, expressed respectively in mg kg⁻¹ of soil and µg L⁻¹ of extracting solution, in order to evaluate the metal partitioning between the solid and the solution phases.
### I.3. Results

#### I.3.1. Amendment inputs and soil management

##### I.3.1.1. Mineral fertilizer and compost characteristics and comparison to the regulation threshold

###### Mineral fertilizer

The pH value of mineral fertilizers was acidic pH, i.e., 2.9 for NPK 0.32.16 applied at planting, but neutral, i.e., pH equal to 6.5 for NPK 15.5.20 applied from the second year at the soil surface (Table 5-2). For NPK 0.32.16, total concentrations of trace metals ranked as Ni (23 mg kg⁻¹) < Cu < (34 mg kg⁻¹) < Cr (40 mg kg⁻¹) < Zn (175 mg kg⁻¹). For NPK 15.5.20 concentrations were lower and trace metals ranked as same order than NPK 0.32.16, i.e., Ni (6 mg kg⁻¹) < Cr (16 mg kg⁻¹) < Cu < (18 mg kg⁻¹) < Zn (275 mg kg⁻¹).

Both mineral fertilizers, i.e., NPK 0.32.16 and NPK 15.5.20, applied in soils contained very low extractable CaCl₂ and EDTA concentrations, i.e., <0.02 µg L⁻¹ and <0.2 mg kg⁻¹ respectively for all trace metals (Table 5-4). Those CaCl₂, 1h-EDTA and 24h-EDTA concentrations of trace metals ranged in the following increase sequence: Cr < Cu < Ni < Zn. When expressed as percentage of total concentrations, trace metals ranged as same order and the percentages were still very low <0.1% for all trace metals. Mineral fertilizer NPK 0.32.16 applied at planting contained nevertheless more than 10-times higher trace metals extractable with CaCl₂ and more than twice 1h-EDTA concentrations compared to NPK 15.5.20 applied the second year.

###### Compost

Composts issued from a mixture of sewage sludges and green wastes had a slightly acidic pH, i.e., 5.9 ± 0.1, a high C, P and K concentrations, i.e., 212 ± 17 g kg⁻¹, 12110 ± 1549 mg kg⁻¹ and 9855 ± 617 mg kg⁻¹ respectively. Because of the presence of sewage sludges, composts were rich in P concentration. Ca and Mg showed the highest concentrations, i.e., 22437 ± 326 mg kg⁻¹ and 17007 ± 2852 mg kg⁻¹, respectively (Table 5-2). Physical-chemical quality of the compost was quite constant regarding the year's production of the three batches.

Total concentrations of trace metals ranked in increasing order as Cu (94 ± 15 mg kg⁻¹) < Zn (291 ± 61 mg kg⁻¹) < Ni (483 ± 51 mg kg⁻¹) < Cr (1307 ± 67 mg kg⁻¹). Pseudo-total concentrations showed globally the same range of concentrations and similar variation pattern, excepted for Cr. Indeed, concentrations measured after aqua regia extraction were half as much and more than 3-times less, respectively than concentrations measured after alkali fusion. As a consequence of these high differences, alkali fusion results were preferred in the following sections to express the total trace metal concentrations
contributed to the soil through the compost input. However, because French regulation (NFU 44-051) defines the threshold values based on aqua regia analyses (NF 13 650), we also used the concentrations of trace metals determined from aqua regia analyses for comparing our composts with French standards. Maximal thresholds for this type of compost were 60 mg kg⁻¹ for Ni, 120 mg kg⁻¹ for Cr, 300 mg kg⁻¹ for Cu and 600 mg kg⁻¹ for Zn. As expected, Ni and Cr exceeded by respectively 7- and 3-times maximum values authorized, while Cu and Zn concentrations in the composts were below the maximal defined thresholds. Considering alkali fusion, concentrations of Cr exceeded up to 10-times maximum values authorized by regulations.

Concentrations of CaCl₂, 1h-EDTA and 24h-EDTA of trace metals were described in **Table 5-4**. CaCl₂ concentrations increased in the following sequence: Cr (3.9 ± 0.1 µg.L⁻¹) < Cu (18.4 ± 0.4 µg.L⁻¹) < Ni (34.3 ± 6.8µg.L⁻¹) < Zn (252.8 ± 336.3µg.L⁻¹). When expressed as percentage of the total concentrations, trace metals ranked as Cr (0.003 ± 0.000%) < Ni (0.08 ± 0.03%) < Cu (0.23 ± 0.03%) < Zn (1.20 ± 1.63%). Trace metals extracted by both 1h- and 24h-EDTA (mg kg⁻¹) ranked as the same order Cr < Cu < Ni < Zn with respective 1h-EDTA mean values of 3.0 ± 1.0 mg kg⁻¹, 18.2 ± 1.3 mg kg⁻¹, 24.1 ± 3.9 mg kg⁻¹ and 156.2 ± 20.7 mg kg⁻¹. When expressed as percentage of total concentrations, trace metal ranking changed for Cr < Ni < Cu < Zn with respective 1h-EDTA mean values of 0.2 ±0.0%, 5.1 ± 0.8%, 19.7 ± 2.7%, 56.3 ± 19.2%. The amount of trace metals extracted with 24-EDTA are nearly 2-times higher for Ni, Cr, Cu, and nearly 1.3-times higher for Zn compared to 1h-EDTA extraction.

### 1.3.1.2. Soil management characteristics

Both straw mulch and *Arachis pintoï* cover crop characteristics are presented in **Table 5-5**. In straw, the concentrations of trace metals ranked in the following increasing order: Cu (3.69 ± 0.36 mg kg⁻¹) < Ni (4.87 ± 0.87 mg kg⁻¹) < Cr (6.05 ± 1.98 mg kg⁻¹) < Zn (36.73 ± 12.32 mg kg⁻¹). Mean concentrations of trace metals in *Arachis pintoï* were Cr (0.71 ± 0.09 mg kg⁻¹) < Ni (1.08 ± 0.32 mg kg⁻¹) < Cu (12.58 ± 3.04 mg kg⁻¹) < Zn (60.70 ± 18.09 mg kg⁻¹), with no difference highlighted regarding the fertilization modality. Straw mulch exhibited higher concentrations of Ni and Cr than cover crops, while the latter had higher concentrations of Cu and Zn than the straw.
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table 5-4:** Concentrations of Ni, Cr, Cu and Zn measured in mineral fertilizers and composts after extraction with CaCl₂ (µg L⁻¹) or with EDTA during 1h or 24h (mg kg⁻¹). Their respective % of the total metal concentration measured by alkali fusion were also presented. Numbers in brackets are the standard deviation (n=3)</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Year</th><th colspan="4">CaCl<sub>2</sub> (µg L<sup>-1</sup>)</th><th colspan="4">CaCl<sub>2</sub> (% of total trace metal)</th></tr><tr><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr></thead><tbody><tr><td>NPK 0.32.16</td><td>2019</td><td>0.0011</td><td>0.0002</td><td>0.0006</td><td>0.0202</td><td>0.046</td><td>0.002</td><td>0.018</td><td>0.115</td></tr><tr><td>NPK 15.5.20</td><td>2020</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>&lt;0.0001</td><td>0.003</td><td>&lt;0.0001</td><td>0.001</td><td>0.0002</td></tr><tr><td rowspan="3">Compost</td><td>2019</td><td>39.2</td><td>3.9</td><td>18.1</td><td>490.5</td><td>0.10</td><td>0.003</td><td>0.25</td><td>2.36</td></tr><tr><td>2020</td><td>29.5</td><td>3.8</td><td>18.7</td><td>15.0</td><td>0.06</td><td>0.003</td><td>0.21</td><td>0.05</td></tr><tr><td>Mean (sd)</td><td><b>34.3</b><br>(6.8)</td><td><b>3.9</b><br>(0.1)</td><td><b>18.4</b><br>(0.4)</td><td><b>252.8</b><br>(336.3)</td><td><b>0.08</b><br>(0.03)</td><td><b>0.003</b><br>(0.000)</td><td><b>0.23</b><br>(0.03)</td><td><b>1.20</b><br>(1.63)</td></tr><tr><td colspan="2"></td><th colspan="4">EDTA 1h (mg kg<sup>-1</sup>)</th><th colspan="4">EDTA 1h (% of total trace metal)</th></tr><tr><td>NPK 0.32.16</td><td>2019</td><td>0.0078</td><td>0.0018</td><td>0.0043</td><td>0.1398</td><td>0.033</td><td>0.005</td><td>0.012</td><td>0.080</td></tr><tr><td>NPK 15.5.20</td><td>2020</td><td>0.0008</td><td>0.0001</td><td>0.0051</td><td>0.1533</td><td>0.014</td><td>0.001</td><td>0.029</td><td>0.056</td></tr><tr><td rowspan="3">Compost</td><td>2019</td><td>22.7<br>(0.2)</td><td>2.9<br>(0.0)</td><td>17.2<br>(1.3)</td><td>171.7<br>(2.6)</td><td>5.5</td><td>0.23</td><td>22.2</td><td>77.0</td></tr><tr><td>2020</td><td>24.8<br>(5.3)</td><td>3.1<br>(0.0)</td><td>18.7<br>(1.4)</td><td>148.4<br>(22.2)</td><td>4.8</td><td>0.23</td><td>18.5</td><td>45.9</td></tr><tr><td>Mean (sd)</td><td><b>24.1</b><br>(3.9)</td><td><b>3.0</b><br>(1.0)</td><td><b>18.2</b><br>(1.3)</td><td><b>156.2</b><br>(20.7)</td><td><b>5.1</b><br>(0.8)</td><td><b>0.23</b><br>(0.00)</td><td><b>19.7</b><br>(2.7)</td><td><b>56.3</b><br>(19.2)</td></tr><tr><td colspan="2"></td><th colspan="4">EDTA 24h (mg kg<sup>-1</sup>)</th><th colspan="4">EDTA 24h (% of total trace metal)</th></tr><tr><td>NPK 0.32.16</td><td>2019</td><td>0.0084</td><td>0.0034</td><td>0.0046</td><td>0.1470</td><td>0.036</td><td>0.008</td><td>0.013</td><td>0.084</td></tr><tr><td>NPK 15.5.20</td><td>2020</td><td>0.0011</td><td>0.0001</td><td>0.0072</td><td>0.1933</td><td>0.020</td><td>0.001</td><td>0.040</td><td>0.070</td></tr><tr><td rowspan="3">Compost</td><td>2019</td><td>40.6<br>(0.9)</td><td>3.4<br>(0.2)</td><td>28.6<br>(1.5)</td><td>221.2<br>(14.2)</td><td>9.9</td><td>0.28</td><td>37.0</td><td>99.1</td></tr><tr><td>2020</td><td>43.9<br>(6.6)</td><td>5.8<br>(1.1)</td><td>35.5<br>(7.1)</td><td>212.4<br>(19.8)</td><td>8.6</td><td>0.43</td><td>34.8</td><td>65.6</td></tr><tr><td>Mean (sd)</td><td><b>42.8</b><br>(5.0)</td><td><b>5.0</b><br>(1.5)</td><td><b>33.2</b><br>(6.4)</td><td><b>215.3</b><br>(14.9)</td><td><b>9.0</b><br>(1.1)</td><td><b>0.38</b><br>(0.11)</td><td><b>35.5</b><br>(3.8)</td><td><b>76.8</b><br>(20.7)</td></tr></tbody></table>

<table><caption>**Table 5-5:** Total trace metal concentrations of Cr, Ni, Cu and Zn (mg kg⁻¹) measured in straw and in cover crops regarding the fertilization at the end of the 2-years. Brackets correspond to the standard deviation of the three blocks</caption><thead><tr><th></th><th>Fertilization</th><th>Cr<br>(mg kg<sup>-1</sup>)</th><th>Ni<br>(mg kg<sup>-1</sup>)</th><th>Cu<br>(mg kg<sup>-1</sup>)</th><th>Zn<br>(mg kg<sup>-1</sup>)</th></tr></thead><tbody><tr><td>Straw (P)</td><td></td><td>6.05 (1.98)</td><td>4.87 (0.87)</td><td>3.69 (0.36)</td><td>36.73 (12.32)</td></tr><tr><td rowspan="4">Cover crop (PC)</td><td>0</td><td>0.73 (0.10)</td><td>1.09 (0.48)</td><td>15.69 (3.55)</td><td>74.26 (33.43)</td></tr><tr><td>FM</td><td>0.62 (0.05)</td><td>1.21 (0.41)</td><td>9.62 (2.60)</td><td>55.53 (9.03)</td></tr><tr><td>D1</td><td>0.74 (0.12)</td><td>0.92 (0.29)</td><td>12.81 (0.50)</td><td>57.68 (13.03)</td></tr><tr><td>D2</td><td>0.75 (0.03)</td><td>1.10 (0.10)</td><td>12.20 (1.82)</td><td>55.32 (7.53)</td></tr><tr><td></td><td>Mean</td><td><b>0.71 (0.09)</b></td><td><b>1.08 (0.32)</b></td><td><b>12.58 (3.04)</b></td><td><b>60.70 (18.09)</b></td></tr></tbody></table>
I.3.2. Fertilization effect at the beginning of the experiment

At first soil sampling (t<sub>3-1</sub>), the fertilization had highly significant effect on different soil parameters (Table 5-6). Total and assimilable nitrogen, C, Ca, Cr, Ni and Cu total concentrations significantly increased with compost inputs, while C/N values significantly decreased. P concentrations were higher in FM soils. All CaCl<sub>2</sub> and 1h- and 24h-EDTA extractable concentrations of trace metals were significantly impacted by the fertilization with an increase from 0 to D2 compost modality. Only Ni-CaCl<sub>2</sub> and Zn-CaCl<sub>2</sub> values were higher in FM modality.

While C contents increased in average by 2-fold between 0 and D2 compost modality, total Cr and Ni
concentrations were multiplied by 4 and 5-times, respectively, between 0 and D2. EDTA extractable
concentrations, especially those of Ni and Cr greatly increased by 6.3 and 7.9- times respectively. CaCl2
extractable concentrations of Ni and Cr increased by 7.4 and 3.6-times in D2 modality compared to the
no-fertilization modality.
Chapitre 5

ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table 5-6:** Soils characteristics in the beginning of the field experiment t3-1 regarding fertilization (0 without fertilization, FM mineral fertilizer, D1 dose 1 of compost and D2 dose 2 of compost) impact and soil management (P straw and PC cover crop), asterisks correspond on different p-value: 0.05 - 0.01 *; 0.01 - 0.001
**; <0.001 ***. Numbers in bracket corresponded on standard deviation.</caption><thead><tr><th>Soil management</th><th>Fertilization</th><th>pH<sub>H2O</sub></th><th>pH<sub>KCl</sub></th><th>N total</th><th>Nas-similable</th><th>C total</th><th>C/N</th><th>Ca</th><th>Mg</th><th>Na</th><th>K</th><th>P</th><th>Fe</th><th>Mn</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Zn</th></tr><tr><th>Units</th><th></th><th></th><th></th><th></th><th>g kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>g kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.88<br>(0.49)</td><td>5.71<br>(0.73)</td><td>1.46 <b>ab</b><br>(0.04)</td><td>8.7 <b>ab</b><br>(3.6)</td><td>15.2 <b>ab</b><br>(0.8)</td><td>10.4 <b>ab</b><br>(0.4)</td><td>3 759 <b>a</b><br>(526)</td><td>5 168<br>(1284)</td><td>13 204<br>(1 607)</td><td>5 621<br>(1 229)</td><td>861 <b>a</b><br>(129)</td><td>53 680<br>(8 002)</td><td>2739<br>(124)</td><td>35.9 <b>a</b><br>(10.7)</td><td>10.5 <b>a</b><br>(1.5)</td><td>24.4 <b>ab</b><br>(5.4)</td><td>112 <b>a</b><br>(12)</td></tr><tr><td>Fm</td><td>6.62<br>(0.36)</td><td>5.73<br>(0.45)</td><td>1.36 <b>a</b><br>(0.08)</td><td>6.7 <b>ab</b><br>(2.7)</td><td>14.6 <b>a</b><br>(0.6)</td><td>10.7 <b>b</b><br>(0.2)</td><td>4 529 <b>ab</b><br>(403)</td><td>5 056<br>(463)</td><td>13 199<br>(946)</td><td>6 305<br>(1 101)</td><td>2 596 <b>b</b><br>(875)</td><td>49 321<br>(3 408)</td><td>2942<br>(157)</td><td>47.5 <b>ab</b><br>(12.8)</td><td>16.4 <b>a</b><br>(7.4)</td><td>25.9 <b>abc</b><br>(1.9)</td><td>131 <b>a</b><br>(15)</td></tr><tr><td>D1</td><td>6.91<br>(0.45)</td><td>5.91<br>(0.46)</td><td>1.48 <b>ab</b><br>(0.31)</td><td>5.0 <b>a</b><br>(1.0)</td><td>14.9 <b>ab</b><br>(3.7)</td><td>10.0 <b>ab</b><br>(0.4)</td><td>4 262 <b>ab</b><br>(274)</td><td>5 073<br>(1 164)</td><td>13 669<br>(710)</td><td>5 097<br>(654)</td><td>996 <b>a</b><br>(89)</td><td>51 486<br>(8 180)</td><td>2335<br>(393)</td><td>66.1 <b>bc</b><br>(13.9)</td><td>18.8 <b>a</b><br>(2.9)</td><td>26.0 <b>abc</b><br>(3.4)</td><td>108 <b>a</b><br>(5)</td></tr><tr><td>D2</td><td>7.23<br>(0.29)</td><td>6.38<br>(0.56)</td><td>2.59 <b>c</b><br>(0.13)</td><td>18.6 <b>b</b><br>(6.5)</td><td>25.2 <b>c</b><br>(2.0)</td><td>9.7 <b>a</b><br>(0.3)</td><td>5 423 <b>b</b><br>(510)</td><td>6 393<br>(2 343)</td><td>12 824<br>(1 201)</td><td>6 135<br>(848)</td><td>1 359 <b>a</b><br>(140)</td><td>49 410<br>(6 930)</td><td>2833<br>(318)</td><td>92.2 <b>cd</b><br>(13.9)</td><td>37.0 <b>b</b><br>(9.7)</td><td>30.7 <b>c</b><br>(3.3)</td><td>119 <b>a</b><br>(10)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>7.19<br>(0.19)</td><td>6.22<br>(0.20)</td><td>1.38 <b>a</b><br>(0.13)</td><td>7.6 <b>ab</b><br>(4.9)</td><td>14.1 <b>a</b><br>(1.2)</td><td>10.2 <b>ab</b><br>(0.1)</td><td>3 988 <b>a</b><br>(187)</td><td>5 313<br>(227)</td><td>12 875<br>(179)</td><td>6 059<br>(389)</td><td>817 <b>a</b><br>(121)</td><td>49 019<br>(4 684)</td><td>2821<br>(418)</td><td>32.4 <b>a</b><br>(5.0)</td><td>11.4 <b>a</b><br>(1.3)</td><td>24.8 <b>ab</b><br>(5.2)</td><td>146 <b>a</b><br>(30)</td></tr><tr><td>Fm</td><td>6.67<br>(0.52)</td><td>5.64<br>(0.77)</td><td>1.38 <b>a</b><br>(0.16)</td><td>7.6 <b>ab</b><br>(3.9)</td><td>14.9 <b>ab</b><br>(1.3)</td><td>10.8 <b>b</b><br>(0.6)</td><td>4 517 <b>ab</b><br>(833)</td><td>4 871<br>(946)</td><td>13 785<br>(1 050)</td><td>6 555<br>(174)</td><td>2 751 <b>b</b><br>(338)</td><td>49 909<br>(5 858)</td><td>2421<br>(598)</td><td>34.7 <b>a</b><br>(5.3)</td><td>10.4 <b>a</b><br>(0.9)</td><td>24.6 <b>ab</b><br>(2.4)</td><td>124 <b>a</b><br>(2)</td></tr><tr><td>D1</td><td>7.08<br>(0.64)</td><td>6.33<br>(0.47)</td><td>1.88 <b>b</b><br>(0.05)</td><td>8.6 <b>ab</b><br>(3.9)</td><td>19.6 <b>b</b><br>(0.7)</td><td>10.4 <b>ab</b><br>(0.2)</td><td>4 466 <b>ab</b><br>(1 020)</td><td>5 664<br>(1 315)</td><td>14 184<br>(1 408)</td><td>5 961<br>(270)</td><td>897 <b>a</b><br>(210)</td><td>53 282<br>(11 784)</td><td>3091<br>(1298)</td><td>55.2 <b>ab</b><br>(9.2)</td><td>16.4 <b>a</b><br>(2.1)</td><td>22.4 <b>a</b><br>(4.1)</td><td>123 <b>a</b><br>(33)</td></tr><tr><td>D2</td><td>6.72<br>(0.08)</td><td>5.84<br>(0.17)</td><td>2.91 <b>c</b><br>(0.11)</td><td>15.2 <b>ab</b><br>(10.2)</td><td>27.8 <b>c</b><br>(1.3)</td><td>9.6 <b>a</b><br>(0.2)</td><td>5 183 <b>b</b><br>(591)</td><td>5 626<br>(633)</td><td>13 189<br>(451)</td><td>5 226<br>(780)</td><td>1 466 <b>a</b><br>(127)</td><td>50 643<br>(6 582)</td><td>2747<br>(525)</td><td>116.8 <b>d</b><br>(3.6)</td><td>40.4 <b>b</b><br>(1.8)</td><td>28.1 <b>bc</b><br>(2.6)</td><td>137 <b>a</b><br>(17)</td></tr><tr><td colspan="2">Fertilization p-value</td><td></td><td></td><td></td><td>***</td><td>*</td><td>***</td><td>***</td><td>**</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
# Chapitre 5

## ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

### APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><thead><tr><th rowspan="3">Soil management</th><th rowspan="3">Fertilization</th><th colspan="6">CaCl<sub>2</sub></th><th colspan="6">1h-EDTA</th><th colspan="6">24h-EDTA</th></tr><tr><th rowspan="2">pH<sub>CaCl<sub>2</sub></sub></th><th colspan="5">µg L<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th></tr><tr><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.05<br>(0.56)</td><td>0.35 <b>ab</b><br>(0.30)</td><td>0.028 <b>a</b><br>(0.026)</td><td>2.23 <b>a</b><br>(0.75)</td><td>2.51 <b>a</b><br>(3.55)</td><td>0.59 <b>a</b><br>(0.25)</td><td>0.034 <b>a</b><br>(0.025)</td><td>6.03 <b>ab</b><br>(1.70)</td><td>7.27 <b>a</b><br>(2.58)</td><td>0.98 <b>a</b><br>(0.46)</td><td>0.11 <b>a</b><br>(0.03)</td><td>8.93 <b>ab</b><br>(2.05)</td><td>12.28 <b>a</b><br>(4.90)</td><td></td><td></td><td></td><td></td></tr><tr><td>Fm</td><td>6.19<br>(0.48)</td><td>2.43 <b>abc</b><br>(0.71)</td><td>0.000 <b>a</b><br>(0.000)</td><td>2.58 <b>a</b><br>(0.23)</td><td>9.50 <b>a</b><br>(5.71)</td><td>0.88 <b>a</b><br>(0.11)</td><td>0.052 <b>a</b><br>(0.022)</td><td>6.73 <b>ab</b><br>(1.14)</td><td>11.50 <b>abc</b><br>(1.65)</td><td>1.40 <b>a</b><br>(0.24)</td><td>0.22 <b>a</b><br>(0.09)</td><td>9.98 <b>ab</b><br>(1.33)</td><td>20.15 <b>abcd</b><br>(1.87)</td><td></td><td></td><td></td><td></td></tr><tr><td>D1</td><td>6.45<br>(0.44)</td><td>1.57 <b>abc</b><br>(1.03)</td><td>0.037 <b>a</b><br>(0.013)</td><td>3.96 <b>ab</b><br>(1.34)</td><td>8.06 <b>a</b><br>(8.76)</td><td>1.26 <b>ab</b><br>(0.26)</td><td>0.029 <b>a</b><br>(0.025)</td><td>7.22 <b>ab</b><br>(1.24)</td><td>9.53 <b>ab</b><br>(2.13)</td><td>2.21 <b>a</b><br>(0.39)</td><td>0.15 <b>a</b><br>(0.01)</td><td>11.66 <b>bc</b><br>(1.75)</td><td>16.26 <b>abc</b><br>(3.56)</td><td></td><td></td><td></td><td></td></tr><tr><td>D2</td><td>6.44<br>(0.85)</td><td>1.24 <b>abc</b><br>(0.39)</td><td>0.099 <b>b</b><br>(0.026)</td><td>4.86 <b>b</b><br>(0.85)</td><td>2.08 <b>a</b><br>(1.94)</td><td>3.60 <b>c</b><br>(1.94)</td><td>0.235 <b>b</b><br>(0.027)</td><td>9.10 <b>b</b><br>(0.78)</td><td>16.20 <b>cd</b><br>(0.21)</td><td>5.64 <b>b</b><br>(2.67)</td><td>0.65 <b>b</b><br>(0.30)</td><td>13.71 <b>c</b><br>(0.68)</td><td>23.57 <b>cd</b><br>(1.01)</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">PC</td><td>0</td><td>6.55<br>(0.25)</td><td>0.40 <b>a</b><br>(0.28)</td><td>0.018 <b>a</b><br>(0.017)</td><td>3.15 <b>ab</b><br>(0.88)</td><td>3.13 <b>a</b><br>(4.45)</td><td>0.49 <b>a</b><br>(0.04)</td><td>0.024 <b>a</b><br>(0.008)</td><td>7.10 <b>ab</b><br>(2.26)</td><td>7.16 <b>a</b><br>(0.71)</td><td>0.91 <b>a</b><br>(0.24)</td><td>0.10 <b>a</b><br>(0.01)</td><td>10.25 <b>abc</b><br>(1.79)</td><td>13.19 <b>a</b><br>(2.32)</td><td></td><td></td><td></td><td></td></tr><tr><td>Fm</td><td>5.78<br>(0.47)</td><td>3.54 <b>c</b><br>(1.26)</td><td>0.000 <b>a</b><br>(0.000)</td><td>2.98 <b>ab</b><br>(0.54)</td><td>13.52 <b>a</b><br>(9.26)</td><td>0.85 <b>a</b><br>(0.15)</td><td>0.043 <b>a</b><br>(0.022)</td><td>7.11 <b>ab</b><br>(1.43)</td><td>14.10 <b>bcd</b><br>(4.88)</td><td>1.17 <b>a</b><br>(0.19)</td><td>0.21 <b>a</b><br>(0.07)</td><td>9.60 <b>ab</b><br>(1.78)</td><td>21.97 <b>bcd</b><br>(5.90)</td><td></td><td></td><td></td><td></td></tr><tr><td>D1</td><td>6.73<br>(0.46)</td><td>0.72 <b>ab</b><br>(0.57)</td><td>0.014 <b>a</b><br>(0.011)</td><td>2.53 <b>a</b><br>(0.14)</td><td>2.39 <b>a</b><br>(2.18)</td><td>1.01 <b>a</b><br>(0.23)</td><td>0.028 <b>a</b><br>(0.014)</td><td>4.97 <b>a</b><br>(0.55)</td><td>9.04 <b>ab</b><br>(0.38)</td><td>1.71 <b>a</b><br>(0.46)</td><td>0.11 <b>a</b><br>(0.06)</td><td>7.51 <b>a</b><br>(1.52)</td><td>14.35 <b>ab</b><br>(0.55)</td><td></td><td></td><td></td><td></td></tr><tr><td>D2</td><td>6.42<br>(0.35)</td><td>2.69 <b>bc</b><br>(0.70)</td><td>0.102 <b>b</b><br>(0.030)</td><td>3.99 <b>ab</b><br>(0.60)</td><td>8.88 <b>a</b><br>(6.58)</td><td>3.17 <b>bc</b><br>(0.19)</td><td>0.181 <b>b</b><br>(0.023)</td><td>7.32 <b>ab</b><br>(0.56)</td><td>18.43 <b>d</b><br>(1.45)</td><td>5.51 <b>b</b><br>(0.59)</td><td>0.76 <b>b</b><br>(0.24)</td><td>11.81 <b>bc</b><br>(1.01)</td><td>27.66 <b>d</b><br>(2.28)</td><td></td><td></td><td></td><td></td></tr><tr><td colspan="2">Fertilization p-value</td><td>**</td><td>***</td><td>*</td><td></td><td></td><td>***</td><td>***</td><td>*</td><td>***</td><td>***</td><td>***</td><td>**</td><td>***</td><td></td><td></td><td></td><td></td></tr></tbody></table>
### I.3.3. Evolution of soil quality in response to agronomical practices in the two-years period

#### I.3.3.1. Physical and chemical parameters and total trace metal concentrations

##### Physical- and chemical characteristics evolution

Over the whole dataset, soil physical and chemical parameters were significantly impacted by fertilization (Table 5-8). Indeed, both pH<sub>H2O</sub> and pH<sub>KCl</sub> varied in the increasing sequence FM < 0 < D1 = D2 and significantly decreased in FM soils with time (Figure 5-1; Table SI 5-1; Table SI 5-2; Table SI 5-3). pH values tended to become higher in soils with cover crop in comparison to straw mulch, especially in 0, FM and D1 soils.

Concentrations of N, assimilable N, C, P, K, Mg and Ca significantly increased with the input of compost in soils and varied in the increasing sequence 0 < FM < D1 < D2, except for K and P concentrations which were the highest in FM soils. By contrast C/N ratio significantly decreased with fertilization according to the order FM > 0 = D1 > D2.

Na concentrations significantly varied with fertilization in the increasing sequence 0 = D2 < FM < D1, excepted for 0 which tended to increase with time. Ni, Cr and Cu concentrations significantly increased with compost input, with the highest concentrations in D2 soil. Cr and Ni total concentrations were well correlated to C total content, i.e., R² adjusted=0.7093 and R² adjusted = 0.709 respectively, and with P content, i.e., R² adjusted = 0.9196 and R² adjusted = 0.9261 respectively by excluding FM modality (Figure 5-2).

By contrast to fertilization, soil management had generally few impacts on physical-chemical parameters. Indeed, only pH<sub>H2O</sub>, assimilable N and Cu concentrations were significantly impacted on soil management (Table 5.8). pH<sub>H2O</sub> was more acidic in soils under straw than cover crop, excepted for D2 where comport had a buffer capacity on pH. Assimilable N tended to be higher in soils under straw than under cover crops for all fertilization modalities. In the same way, Cu concentrations were higher in soils under straw mulch, expected for 0 (Figure 5-1).
Chapitre 5

ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_77.png" /><figcaption>**Figure 5-1:** Evolution of soil physical and chemical parameters: pH<sub>H2O</sub>, N and C contents (g kg<sup>-1</sup>), concentrations (mg kg<sup>-1</sup>) of N assimilable, Ni, Cr, Cu and Zn over the two years period (t<sub>3-1</sub>, t<sub>11-1</sub>, t<sub>3-2</sub>, t<sub>11-2</sub>) according fertilization (0, FM, D1, D2) and soil management (P and PC). Y scale is different regarding each parameter.</figcaption></figure>
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_78.png" /><figcaption>**Figure 5-2:** Evolution of Ni and Cr total concentrations (mg kg⁻¹) regarding total C (g kg⁻¹) and P (mg kg⁻¹) concentrations over the 2-years. For P, FM modality was excluded for the linear regression model</figcaption></figure>

Total trace metal accumulation in soils

The Igeo are presented in **Table 5-7** for the three fertilization modalities FM, D1 and D2 measured after two years of experiment. Igeo for FM soils varied from -1.15 to -0.06 for Cr, Ni, Cu and Zn. Igeo for D1 soils varied from -0.97 to -0.06 for Cr, Cu and Zn, whereas for Ni Igeo was higher than 1, i.e., mean of 0.35. Igeo for D2 soils varied from -0.90 to -0.09 for Cu and Zn. In contrast for Cr and Ni, Igeo were higher than 1, i.e., mean of 1.64 and 1.91 respectively. For Ni, Igeo tended to be slightly higher for D2 soils under straw mulch (P: 2.07) in comparison to cover crops (PC: 1.75).

<table><caption>**Table 5-7:** Igeo was calculated regarding the mean of the soil management per fertilization modality at the sampling time t<sub>11-2</sub>. The background value used corresponded to the soil control without fertilization at t<sub>3-1</sub></caption><thead><tr><th>Fertilization</th><th>Soil management</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Zn</th></tr></thead><tbody><tr><td rowspan="3">FM</td><td></td><td>-0.32</td><td>-0.18</td><td>-0.58</td><td>-0.78</td></tr><tr><td>P</td><td>-0.25</td><td>-0.06</td><td>-0.51</td><td>-0.41</td></tr><tr><td>PC</td><td>-0.40</td><td>-0.30</td><td>-0.65</td><td>-1.15</td></tr><tr><td rowspan="3">D1</td><td></td><td>-0.07</td><td>0.35</td><td>-0.57</td><td>-0.83</td></tr><tr><td>P</td><td>-0.06</td><td>0.46</td><td>-0.44</td><td>-0.67</td></tr><tr><td>PC</td><td>-0.09</td><td>0.28</td><td>-0.70</td><td>-0.97</td></tr><tr><td rowspan="3">D2</td><td></td><td>1.64</td><td>1.91</td><td>-0.15</td><td>-0.67</td></tr><tr><td>P</td><td>1.67</td><td>2.07</td><td>-0.09</td><td>-0.42</td></tr><tr><td>PC</td><td>1.60</td><td>1.75</td><td>-0.21</td><td>-0.90</td></tr></tbody></table>
<table><caption>**Table 5-8:** Effect of fertilization and soil management regarding soil parameters over the two-years experiment. Statistical analyses resulting of a linear mixed model with bloc as an aleatory factor, with ns non significantly difference, and * corresponding to the degree of confidence <0.05 *, <0.01 **, <0.001 ***</caption><thead><tr><th>Variables</th><th>Fertilization</th><th>Soil management</th><th>Fertilization x<br>Soil management</th></tr></thead><tbody><tr><td>pH<sub>H2O</sub></td><td>***</td><td>*</td><td>*</td></tr><tr><td>pH<sub>KCl</sub></td><td>***</td><td>ns</td><td>**</td></tr><tr><td>N total</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Nassimilable</td><td>***</td><td>***</td><td>**</td></tr><tr><td>C total</td><td>***</td><td>ns</td><td>*</td></tr><tr><td>C/N</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Ca</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Mg</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Na</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>K</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>P</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Ni</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cr</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cu</td><td>***</td><td>***</td><td>ns</td></tr><tr><td>Zn</td><td>*</td><td>ns</td><td>**</td></tr><tr><td>Cr-EDTA24h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Ni-EDTA24h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cu-EDTA24h</td><td>***</td><td>**</td><td>***</td></tr><tr><td>Zn-EDTA24h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cr-EDTA1h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Ni-EDTA1h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cu-EDTA1h</td><td>***</td><td>***</td><td>***</td></tr><tr><td>Zn-EDTA1h</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cr-CaCl<sub>2</sub></td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Ni-CaCl<sub>2</sub></td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>Cu-CaCl<sub>2</sub></td><td>***</td><td>*</td><td>*</td></tr><tr><td>Zn-CaCl<sub>2</sub></td><td>***</td><td>ns</td><td>ns</td></tr></tbody></table>

### 1.3.3.2. EDTA concentrations of trace metals

Considering the whole dataset, EDTA extractable concentrations of trace metals increased over time and mean concentrations ranked as Cr (0.10 ± 0.14 mg kg⁻¹) < Ni (1.58 ± 1.45 mg kg⁻¹) < Cu (6.99 ± 1.60 mg kg⁻¹) < Zn (12.10 ± 5.64 mg kg⁻¹) for 1 h extraction. Similar pattern of variation was observed for 24 h extraction, but concentrations for all trace metals were higher after 24 h extraction, i.e., Cr (0.36 ± 0.13 mg kg⁻¹) < Ni (2.53 ± 1.23 mg kg⁻¹) < Cu (10.08 ± 8.95 mg kg⁻¹) < Zn (18.33 ± 16.24 mg kg⁻¹) (Table SI 5-1; Table SI 5-2; Table SI 5-3). 1 h-EDTA concentrations were significantly and linearly correlated to 24 h-EDTA concentrations (Figure 5-3). However, the proportion of 1 h- to 24 h-EDTA concentrations depended on the trace metal. Neither fertilization nor soil management had any effect on the slopes. Thus, 1 h-EDTA concentrations of trace metals were equal to 18.9 % of Cr-24 h-EDTA, 56.1 % of Ni-24 h-EDTA, 61.1 % of Cu-24 h-EDTA and 71.5 % of Zn-24 h-EDTA. EDTA extractable concentrations depended mainly on fertilization and D2 exhibited the highest extractable concentrations for all trace metals.
Regarding such correlations, tendencies described below for 1 h-EDTA concentrations were also valuable for 24 h-EDTA concentrations.

<figure><img src="image_79.png" /></figure>

<table><thead><tr><td>y</td><td>a</td><td>x</td><td>p-value</td><td>R<sup>2</sup>-adjusted</td></tr></thead><tbody><tr><td>Cr-1h-EDTA</td><td>0.189</td><td>Cr-24h-EDTA</td><td>***</td><td>0.936</td></tr><tr><td>Ni-1h-EDTA</td><td>0.561</td><td>Ni-24h-EDTA</td><td>***</td><td>0.991</td></tr><tr><td>Cu-1h-EDTA</td><td>0.611</td><td>Cu-24h-EDTA</td><td>***</td><td>0.991</td></tr><tr><td>Zn-1h-EDTA</td><td>0.715</td><td>Zn-24h-EDTA</td><td>***</td><td>0.993</td></tr></tbody></table>

**Figure 5-3:** Scatter plot of 1h-EDTA regarding 24h-EDTA extractable Cr (a), Ni (b), Cu (c) and Zn (d) grouped by the fertilization modalities. Table (e) gave the linear equation y=ax+b regarding x as 24h-EDTA extractable Ni, Cr, Cu and Zn with their corresponding p-value, R² adjusted and highlight a significative fertilization effect. * corresponding to degree of confidence <0.05 *, <0.01 **, <0.001 ***

The fertilization impacted on the EDTA extractable concentrations of Cr and Ni, especially for D1 and D2 modalities. Over the two years period, 1h-EDTA concentrations increased as 0 = FM =D1 << D2 (Figure 5-4). After two years, D2 soils had the significantly highest Ni- and Cr- 1h EDTA concentrations, i.e., respectively 5.44 ± 1.14 and 0.52 ±0.06 mg.kg⁻¹ against 0.60 ± 0.25 and 0.01 ± 0.01 mg.kg⁻¹ in soil control (Table SI 5-3). Excepted for D2, Cr- and Ni-EDTA extractable concentrations were quite stable during the 2-years for all modalities. For D2, both Cr- and Ni-EDTA concentrations significantly increased by respectively nearly 1.5- and 2-times from t₁₁⁻₁ to t₃⁻₂ while continuing to increase until t₁₁⁻₂.
No soil management effect was observed on Cr- and Ni-EDTA concentrations variations for all fertilization modalities.

Cu-EDTA concentrations were significantly higher in D2 modality, especially for straw mulch soil management in both years, i.e., 9.10 ± 0.78 mg.kg⁻¹ at t₃⁻₁ and 11.63 ± 0.92 mg.kg⁻¹ at t₁₁⁻₂ (Table SI 5-3). Soil management effect was observed with higher Cu-EDTA concentrations in soils under straw mulch. However, this difference was already observed at the first sampling time t₃⁻₁, when soil management was not set up. Thus, soil management effect could be more related to soil heterogeneity in the orchard.

Fertilization significantly affected Zn-EDTA concentrations which varied in the increasing sequence 0 = D1 < FM < D2. Moreover, Zn-EDTA concentrations for D2 soil significantly increased over time, while Zn-EDTA concentrations were quite stable for the other modalities of fertilization. No soil management effect was highlighted on Zn-EDTA concentrations.

<figure><img src="image_80.png" /><figcaption>**Figure 5-4:** Evolution of mobilizable EDTA concentrations (mg kg⁻¹) of Cr (a), Ni (b), Cu (c) and Zn (d) over the two years experiment t₃⁻₁, t₁₁⁻₁, t₃⁻₂ and t₁₁⁻₂ regarding fertilization modality, i.e., negative control without fertilization (0), positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input and regarding soil management, i.e., straw mulching (P) and crop cover (PC). The blue and orange lines correspond respectively to mean and median concentrations for the two years period and for all modalities combined. Y scale is different regarding each parameter.</figcaption></figure>

When expressed as the fraction of EDTA contents (% of the total concentrations), the ordered mean values changed according to Cr (0.12 ± 0.08%) < Ni (5.7 ± 1.7%) < Zn (11 ± 4%) < Cu (26 ± 4%) over the
2-years period and for all modalities combined (Figure 5-5). Fractions of extractable EDTA remained very low compared to their total contents, especially for Cr and Ni.

Considering the cropping modalities, the variations of extractable EDTA fractions (%) were less marked, for all trace metals studied than the extractable EDTA concentrations (mg kg⁻¹). For Cr, significantly higher %EDTA was found in D2 compared to the other modalities and %Cr-1h-ETDA increased with the second application of compost in soils, i.e., up to 0.25 ± 0.10% (D2) compared to 0.03 ± 0.01% (0) at t₁₁-₂ (Table SI 5-3). Extractable EDTA fractions of Ni and Zn showed a similar trend which was repeated for each sampling campaign in an increasing order 0 = D1 = FM < D2 for the 2-years period. Extractable EDTA fractions of Cu did not significatively vary over time. For all trace metals, soil management did not significantly impact extractable EDTA fractions (%) variation over time.

<figure><img src="image_81.png" /></figure>

**Figure 5-5:** Evolution of extractable EDTA concentrations (%) of Cr (a), Ni (b), Cu (c) and Zn (d) over the two years experiment t3-1, t11-1, t3-2 and t11-2 regarding fertilization modality, i.e., negative control without fertilization (0), positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input and regarding soil management, i.e., straw mulching (P) and crop cover (PC). The blue and orange lines correspond respectively to mean and median concentrations for the two years period and for all modalities combined. Y scale is different regarding each parameter.
### 1.3.3.3. CaCl₂ concentrations of trace metals

Considering the whole dataset, mean CaCl₂ concentrations of trace metals ranked as Cr (0.08 ± 0.12 µg L⁻¹) < Ni (3.33 ± 3.48 µg L⁻¹) = Cu (4.17 ± 1.83 µg L⁻¹) < Zn (28.69 ± 49.59 µg L⁻¹) (Figure 5-6).

When expressed as percentage of total concentrations, mean values of trace metals varied according to the same sequence, i.e., Cr (0.0010 ± 0.0008%) < Cu (0.16 ± 0.07%) = Ni (0.18 ± 0.23%) < Zn (0.33 ± 0.50%) (Figure 5-7). Both CaCl₂ concentrations and fractions of the total concentrations remained very low. All statistical differences for each sampling campaign can be found in the **Table 5-1; Table SI 5-1; Table SI 5-2; Table SI 5-3**. Cr-CaCl₂ concentrations were the highest for D2 soil, whatever the soil management, but they did not significantly vary between the other fertilization modalities. During the first year of sampling, Cr-CaCl₂ concentrations in FM modality were very low to no detectable. However, during the second year, concentrations increased and were on the same order of magnitude than concentrations measured in the D1 soil. Ni- and Zn-CaCl₂ concentrations tend to vary in the same way.

In average, they increase in the following sequence: 0<D1<2<FM (Figure 5-6). Ni-CaCl₂ concentrations are greatly higher, i.e., up to 10-times in FM soil compared to soil control for all sampling campaign. CaCl₂ concentrations of these two trace metals strongly increased during the second year of sampling in FM and D2 soils, particularly for Zn with straw mulch soil management (p-value < 0.01; Table SI 5-3).

Fertilization effect on Cu-CaCl₂ concentrations was less marked. However, during the second year, FM and D2 tended to have higher concentrations of Cu-CaCl₂. Moreover, over time and for all modalities, except PCO and PCD1, concentrations of Cu-CaCl₂ tended to increase. With 0 and D1 fertilization, Cu-CaCl₂ concentrations tended to increase with time. With 0 and D1 fertilization, Cu-CaCl₂ concentrations tended to be lower under cover crop management than under straw mulch management.
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_82.png" /></figure>

**Figure 5-6:** Evolution of CaCl₂ concentrations (µg L⁻¹) of Cr (a), Ni (b), Cu (c) and Zn (d) over the two years experiment t₃-1, t₁₁-1, t₃-2 and t₁₁-2 regarding fertilization modality, i.e., negative control without fertilization (0), positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input and regarding soil management, i.e., straw mulching (P) and crop cover (PC). The blue and orange lines correspond respectively to the mean and median concentrations for the two years period and for all modalities combined Y scale is different regarding each parameter.

<figure><img src="image_83.png" /></figure>

**Figure 5-7:** Evolution of CaCl₂ fractions of the total concentrations (%) of Cr (a), Ni (b), Cu (c) and Zn (d) over the two years experiment t₃-1, t₁₁-1, t₃-2 and t₁₁-2 regarding fertilization modality, i.e., negative control without fertilization (0), positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input and regarding soil management, i.e., straw mulching (P) and crop cover (PC). The blue and orange lines correspond respectively to the mean and median concentrations for the two years period and for all modalities combined. Y scale is different regarding each parameter.
### I.3.4. Relationship between CaCl₂ and EDTA concentrations of trace metals

Relationships between CaCl₂ and EDTA trace metal concentrations were assessed **Figure 5-8**. Cr- and Cu-CaCl₂ linearly varied with Cr-EDTA and Cu-EDTA, respectively. Slopes were equal to 0.8198 (R² adj.=0.8274, p-value<2.2e-16) and 0.5923 (R² adj. = 0.8833, p-value < 2.2e-16) for Cr and Cu, respectively. For Ni- and Zn-CaCl₂, the linear relationships between CaCl₂- and EDTA- concentrations were depending on the fertilization (**Figure 5-8**). However, R² adjusted of models, although significant, remained very low for Zn (R² adjusted < 0.5603).

<figure><img src="image_84.png" /></figure>

<table><thead><tr><th>Fertilization</th><th>y</th><th>a</th><th>x</th><th>Fertilization p-value</th><th>R<sup>2</sup>-adjusted</th></tr></thead><tbody><tr><td></td><td>Cr-CaCl<sub>2</sub></td><td>0.8198</td><td>Cr-1h-EDTA</td><td>***</td><td>0.8274</td></tr><tr><td></td><td>Cu-CaCl<sub>2</sub></td><td>0.5923</td><td>Cu-1h-EDTA</td><td>***</td><td>0.8833</td></tr><tr><td></td><td></td><td>1.5176</td><td></td><td>***</td><td>0.3983</td></tr><tr><td>0</td><td></td><td>1.1636</td><td></td><td>***</td><td>0.7410</td></tr><tr><td>FM</td><td rowspan="3">Ni-CaCl<sub>2</sub></td><td>7.6510</td><td rowspan="3">Ni-1h-EDTA</td><td>***</td><td>0.5953</td></tr><tr><td>D1</td><td>1.7898</td><td>***</td><td>0.7192</td></tr><tr><td>D2</td><td>1.21179</td><td>***</td><td>0.9120</td></tr><tr><td></td><td></td><td>2.1960</td><td></td><td>***</td><td>0.1928</td></tr><tr><td>0</td><td></td><td>0.7606</td><td></td><td>*</td><td>0.2219</td></tr><tr><td>FM</td><td rowspan="3">Zn-CaCl<sub>2</sub></td><td>6.346</td><td rowspan="3">Zn-1h-EDTA</td><td>***</td><td>0.3951</td></tr><tr><td>D1</td><td>1.6952</td><td>***</td><td>0.3977</td></tr><tr><td>D2</td><td>0.8130</td><td>***</td><td>0.5603</td></tr></tbody></table>

**Figure 5-8:** Scatter plot of CaCl₂ regarding 1h-EDTA extractable Ni (a), Cr (b), Cu (c) and Zn (d) grouped by the fertilization modalities. Table gave the linear equation y=ax regarding CaCl₂ and EDTA1h extractable Ni, Cr, Cu and Zn with their corresponding p-value, R²adjusted and highlight a significative fertilization effect when p-value <0.05 and R² close to 1. * corresponds to degree of confidence <0.05 *, <0.01 **, <0.001 ***
Considering the whole dataset, Kd of trace metals decreased over time and mean values ranked as Ni (847 ± 513 L kg⁻¹) < Cr (1010 ± 469 L kg⁻¹) < Zn (1601 ± 1369 L kg⁻¹) = Cu (1881 ± 556 L kg⁻¹) (Figure 5-9).

Cr-Kd showed a high heterogeneity of variation the first year and then values stabilized in the increasing order FM < 0 = D1 < D2. Ni- and Zn-Kd varied the most with fertilization modalities and values increasing as FM < D1 < 0 = D2. For Cu-Kd, variations were not impacted by fertilization, but values decreased the second year.

<figure><img src="image_85.png" /><figcaption>**Figure 5-9:** Evolution of extractable Kd (L kg⁻¹) of Cr (a), Ni (b), Cu (c) and Zn (d) over the two years experiment t3-1, t11-1, t3-2 and t11-2 regarding fertilization modality, i.e., negative control without fertilization (0), positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input and regarding soil management, i.e., straw mulching (P) and crop cover (PC). The blue and orange lines correspond respectively to mean and median concentrations for the two years period and for all modalities combined. Some Cr- and Zn- CaCl₂ concentrations are under quantification limits</figcaption></figure>

**I.3.5. Modelling relationship between soils variables and trace metal concentrations**

**I.3.5.1. Principal Component Analysis (PCA)**

Relationships between soils parameters the different trace metal pools were assessed using Principal Component Analysis (PCA) (Figure 5-10; Figure 5-11). Fertilization structured the distribution of EDTA and CaCl₂ extractable concentrations of Ni, Cr, Cu and Zn. The first component (Dimension 1, 36.2 % of the explained variance) was mainly explained by 1h- and 24h-EDTA extractable concentrations of Ni, Cr, and Cu and Zn, total concentrations of Cr and Ni, N and C contents. CaCl₂ extractable concentrations,
excepted for Cr, were not represented on Dimension 1 (Figure 5-10B). By contrast, the second component (Dimension 2, 16.4 % of the explained variance) was mainly determined by CaCl₂ extractable concentrations of Zn and Ni, Kd of Ni, Zn, Cr and Cu and pH<sub>H2O</sub> (Figure 5-11B). Total concentrations of Cr and Ni seemed to be well correlated to C and N total contents as well as the 1h-EDTA and 24h-EDTA extractable concentrations of Cr, Ni and Zn. The projection of individuals on the first two dimensions of the PCA (Figure 5-10A, C) indicated that compost inputs and more especially D2, engendered the release of EDTA extractable concentrations of Ni, Cr, Cu and Zn in the soils. By contrast, some other variables seemed to be correlated to CaCl₂ extractable concentrations, such as Kd partitioning and pH. CaCl₂ extractable concentrations of Ni and Zn were negatively correlated to pH<sub>H2O</sub> (R²adjusted>60% both for Ni and Zn; Figure SI 5-5). When individuals were projected to the 2nd and 3rd dimensions of the PCA (Figure 5-11A, C), FM modality engendered the release of CaCl₂ extractable concentrations of Ni and Zn. This observation was in the contrary of CaCl₂ extractable concentrations of Cr and Cu which were released with the compost input, more especially with D2.

### 1.3.5.2. Multiple Linear Regression equations

Following PCA, multilinear regression models (MLR) were made to explain CaCl₂ concentrations and Kd of trace metals from soil characteristics (Table 5-9).

<table><caption>**Table 5-9:** Calculation of the linear regression regarding CaCl₂ extractable concentrations of Ni, Cr, Cu and Zn and their Kd coefficient regarding the soil parameters of pH and C concentration (mg kg⁻¹). * corresponding to p-values with a degree of confidence <0.05 *, <0.01 **, <0.001 ***</caption><thead><tr><th></th><th>Equation (p-value)</th><th>R<sup>2</sup>adj</th><th>p-value</th></tr></thead><tbody><tr><td>log(Cr<sub>CaCl2</sub>)</td><td>0.47 + 0.76 log(Cr<sub>1h-EDTA</sub>) *** - 0.11 pH<sub>H2O</sub> *</td><td>0.7624</td><td>***</td></tr><tr><td>log(Ni<sub>CaCl2</sub>)</td><td>7.03 + 1.01 log(Ni<sub>1h-EDTA</sub>) *** - 0.80 pH<sub>H2O</sub> *** - 0.47 log(C.total) *</td><td>0.8106</td><td>***</td></tr><tr><td>log(Cu<sub>CaCl2</sub>)</td><td>-0.76 + 0.76 log(Cu<sub>1h-EDTA</sub>) *** + 0.21 log(Cu) *</td><td>0.4142</td><td>***</td></tr><tr><td>log(Zn<sub>CaCl2</sub>)</td><td>8.87 + 0.58 log(Zn<sub>1h-EDTA</sub>) *** - 1.25 pH<sub>H2O</sub> ***<br/>- 0.66 log(C total) **</td><td>0.6914</td><td>***</td></tr><tr><td>log(Kd<sub>Cr</sub>)</td><td>0.81 + 0.17 pH<sub>H2O</sub> ** + 0.34 log(C total) **</td><td>0.1719</td><td>***</td></tr><tr><td>log(Kd<sub>Ni</sub>)</td><td>-3.84 + 0.80 pH<sub>H2O</sub> *** + 0.41 log(C total) ***</td><td>0.8047</td><td>***</td></tr><tr><td>log(Kd<sub>Cu</sub>)</td><td>2.45 + 0.12 pH<sub>H2O</sub> **</td><td>0.07637</td><td>**</td></tr><tr><td>log(Kd<sub>Zn</sub>)</td><td>-6.85 + 1.28 pH<sub>H2O</sub> *** + 0.42 log(C total) *</td><td>0.6042</td><td>***</td></tr><tr><td></td><td>-5.64 + 1.28 pH<sub>H2O</sub> ***</td><td>0.5882</td><td>***</td></tr></tbody></table>
**Chromium:** log(Cr<sub>CaCl2</sub>) had a significantly positive influence on Cr-1hEDTA and negatively with pH. The Kd approach found a significantly positive influence of pH and C. However, the R² adjusted explaining the Kd variation was less than 20 %.

**Nickel:** log(Ni<sub>CaCl2</sub>) had a significantly positive influence of Ni-1h-EDTA and significantly negative with pH and C. The Kd approach is function of pH<sub>H2O</sub> and C, explaining 80 % of Kd variations.

**Copper:** log(Cu<sub>CaCl2</sub>) were significantly and positively influenced by extractable EDTA and total concentrations of Cu. However, this linear regression explained 41 % of Cu-CaCl<sub>2</sub>. Kd significantly and positively varied with pH<sub>H2O</sub>, but the R<sup>2</sup> adjusted was less than 10 %.

**Zinc:** equations found on log(Zn<sub>CaCl2</sub>) were interestingly based on a significantly positive influence of Zn-1h EDTA, and a significantly negative influence of pH<sub>H2O</sub> and C with a R<sup>2</sup> adjusted of 69 %. For Kd variations, the best model used pH and C variables with a R<sup>2</sup> adjusted of 60 % and another model without C explaining 59 % of the variables.
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_86.png" /><figcaption>**Figure 5-10:** PCA which explained more than 50% of dimension 1 and 2 of the different 35 variables (A), the contribution of the top 10 variables (B) and PCA with the individuals grouped by the modality of fertilizations (C).</figcaption></figure>
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_87.png" /><figcaption>**Figure 5-11:** PCA which explained less than 30% of dimension 2 and 3 of the different 35 variables (A), the contribution of the top 10 variables (B) and PCA with the individuals grouped by the modality of fertilizations (C).</figcaption></figure>
### I.4. Discussion

#### I.4.1. Quality of the compost input in the orchard

Physico-chemical characteristics of composts such as pH<sub>H2O</sub> (5.9 ± 0.1), total carbon (212 ± 17 g kg<sup>-1</sup>), C/N ratio (8.73 ± 0.91), phosphor concentration (12110 ± 1549 mg kg<sup>-1</sup>) improved the soil fertility in the *Washington Navel* orchard studied (**Table 5-2**). These parameters were in the same range than other composts of sewage sludge mixed with green waste (Obriot et al. 2016). C/N ratio around 8 means a fast mineralization rate favorable of soil micro-organism mineralization in soils (Mot et al. 2022). However, in our study, considering tropical climate and intense rainy season influenced by la Niña phenomenon, the mineralization of compost has been likely accelerated in comparison in neutral climate conditions (Rigby et al. 2016).

This compost had particularly high concentrations of Ni and Cr, i.e., 483 ± 51 mg.kg⁻¹ and 1307 ± 67 mg.kg⁻¹ (*Table 5-2*), never reported in the literature, and those trace metals are partly geogenic coming from soil particles derived from ultramafic substrates (Klein et al. 2023). The pseudo-total concentrations of trace metals, notably Cr, extracted with aqua regia were 3-times less than the concentrations extracted with alkali fusion. Thus, while maximal fluxes authorized by regulation on compost inputs (NFU 44-095) are based on concentration defined by aqua regia method, it is important to note that the “real” contamination of soil will be much higher. If Cr-bearing minerals are generally considered as resistant to weathering (Garnier et al. 2008, 2009), it is important to consider that such concentrations will greatly increase Cr stocks in soils.

#### I.4.2. Compost as a high source of trace metals

The highest total concentrations of all studied trace metals were found in soils of D2 modality. Indeed, Cr and Ni total concentrations significantly increased in a larger extend in soils by respectively almost 4-times between D2 and 0 after the two years experiments (**Figure 5-1**; *SI*; **Table 5-4**). Cu and Zn total concentrations increased as well but to a lesser extent, i.e. increase by 1.5 for Cu and 1.2 for Zn between D2 and 0. As indicated by the relationship between these two trace metals and the soil carbon content (**Figure 5-2**), compost represented a great source of contamination for amended soils. Thus, the Igeo value (> 2) indicated a contaminated D2 amended soils under straw by Ni, and moderately contaminated D2 amended soils by Ni under cover crop and by Cr for both soil management (Igeo between 0 and 1) (**Table 5-7**). Because trace metals are non-biodegradable, organic wastes with high concentrations lead to concentration or lixiviation of trace metal effects in soil (Achiba et al. 2010; Farrell et al. 2010; Santos et al. 2010). Thus, repeated inputs will lead to an increase in total concentrations of trace metals in soils, as previously shown for Ni in a Citrus orchard after seven years
of organic waste application in soils (Canet et al. 1997). The total concentration of trace metals in amended soils indicates the extent of the contamination and it can thus be considered as a reliable indicator for assessing the long term risk for the environment. However, it does not provide information on the forms of trace metals and on their potential mobility in the environment (Greenway and Song 2002; Amir et al. 2005), resulting in an inaccurate estimation of the short and medium term risks, as specified by Sahuquillo et al. (2003). In this goal, CaCl₂ and EDTA concentrations of trace metals could be more informative (Kim et al. 2015).

### I.4.3. Influence of fertilization on trace metal CaCl₂ and EDTA pools

As previously described for total concentrations of trace metals, D2 soils exhibited the higher concentrations of CaCl₂ and EDTA trace metals. Indeed, CaCl₂ and EDTA extractable concentrations of trace metals increased by almost 8-times for Ni and 15- and 9-times for respectively Cr-EDTA and -CaCl₂ concentrations, and by 2-times for Cu and 3-times for Zn with compost input at D2 compared to 0 (Table 5-1; Table S1 5-3). Such results indicated that if compost brought total trace metal concentrations, it was also a source of available CaCl₂ and EDTA pools. Different authors showed an increase in these pools after organic waste spreading. Laurent et al. (2020) described an increase in Cu-CaCl₂ and -EDTA concentrations after spreading of poultry litter or pig slurry composts because of Cu bound with soluble organic matter. Extractable Zn was also reported in studies with organic amended soils (Walter et al. 2002; Farrell et al. 2010; Santos et al. 2010; Doelsch et al. 2010; Cambier et al. 2019; Laurent et al. 2020). Although Ni and Cr are reported in the literature as less mobile, some studies showed that their mobility could be enhanced with urban waste compost or municipal sewage sludge composts applications depending on the soil and compost characteristics (Giusquiani et al. 1992; Pinamonti et al. 1999; Døelsch et al. 2006). Compost applied had the particularity to contain Ni and Cr coming from soils particles derived from ultramafic soils (Klein et al., 2023). Input of this compost on ultramafic soils in New-Caledonia has led to a massive remobilization of nickel and chromium in soils (Klein et al., 2023b). However, in soils with naturally low concentrations of these metals an increase of mobilizable EDTA pools from compost were also reported (Klein et al., 2023, in prep/Chapitre 4). Thus, Ni and Cr could be mobilizable over a longer term. Indeed, while trace metals tended to be stabilized during composting, the compost mineralization in-situ can lead to trace metal release (Klein et al., 2023; Usman et al. 2004; Clemente et al. 2006). Although mobilizable pools of trace metals increased, their concentrations in soil solution can be impacted by physical and chemical characteristics of soils.
### I.4.3.1. Effect of carbon content on Cr and Cu availability

In our study, soluble Cr-CaCl₂ can be directly predicted by extractable EDTA concentrations, i.e. 0.8198 x Cr-1h-EDTA (R²adjusted=0.8274, p-value<0.01) (Figure 5-8). Soil management did not impact extractable Cr-CaCl₂ concentrations. Indeed, Cr was mainly related to the compost input and correlated with C content (Figure 5-3). This suggest that the compost, by bringing mobilizable EDTA pool of Cr, ultimately will increase their concentration in soil solution. As shown by Klein et al., (2023), Cr came from the compost input and has a geogenic character. These authors showed a highest rapidly extractable EDTA pool of Cr at the end on composting process. One hypothesis was the link between labile organic matter degradation and Cr release in solution. Rodríguez-Espinosa et al. (2023) recently showed that raw organic waste without any composting treatment release the highest rate of soluble elements in soils. Thus, while the increase of soluble Cr was proportional to mobilizable pool, and thus, to the compost quantity spread, the magnitude of Cr-CaCl₂ released in soils could be depending on the degree of compost maturity. Nevertheless, Cr(VI) is generally the more soluble form at neutral and alkaline pH in soil, while Cr(III) could persist in solution at pH higher than 5.5 in the presence of organic ligands (Remoudaki et al. 2003), notably because organic colloids are known to be implied in Cr(III) solubilization (Pédrot et al. 2008; Löv et al. 2017). Moreover, because the toxicity of Cr is considered as depending on its speciation, further studies could be interested in Cr speciation following such compost inputs in the particular case of New Caledonia.

As for Cr, Cu-CaCl₂ was well correlated with extractable EDTA concentrations, i.e., 0.5923 x Cu-1h-EDTA (R²adjusted=0.8833, p-value<0.01) (Figure 5-8). Cambier et al., (2019) also reported a significant relationship between these two concentrations, i.e., Cu<sub>CaCl2</sub>=0.617 x Cu<sub>EDTA</sub> (mg kg<sup>-1</sup>)<sup>1.21</sup> (p-value < 0.01). Moreover, Kd values calculated here, were in the same order of magnitude than usually reported in other studies (McBride 1994; Cambier et al. 2019). Other authors found a small influence of pH upon the release of Cu in soils when compared to soil organic matter (Canet et al. 1997). In our study, total carbon content did not appear as a significant variable and was not selected in the equation (Table 5-8). However, other studies showed that the increase of Cu mobility after compost input was explained by the increase in Cu-dissolved organic matter complexes (Bravin et al. 2012; Tella et al. 2016; Laurent et al. 2020). Some authors reported that distribution of Cu in liquid and solid phases is mainly determined by the distribution of organic matter with a ratio Cu/OM similar in both phases, i.e., Kd=SOC/DOC (Degryse et al. 2009). Thus, total carbon content used in our equations could be not representative of the dissolved organic matter fraction and this could explain the absence of relation between total carbon content and Cu-CaCl₂ concentrations.
Interestingly, CaCl₂ and EDTA extractable concentrations of Cu concentrations tended to be higher in soils under the combination compost and straw inputs (Figure 5-4; Figure 5-6). Gondek et al. (2018) reported a same observation of a higher Cu soluble extracted in soil solution in sewage sludge amended soil and covered by maize straw input than under the compost amended soil alone. Cu is known to have a high affinity with organic matter (Kumpiene et al. 2008; Borggaard et al. 2019), therefore Cu mobility could increase because of Cu- humic or fulvic acids complexes formed (Hsu and Lo 2000). Moreover, straw decomposition could engender the formation of dissolved organic matter resulting to soluble organo-metallic complexes (Su et al. 2021). Although straw contained low Cu concentrations, i.e., below 10 mg kg⁻¹ (Table 5-5), straw input on soils could have impacted soil and evolution of trace metals by modifying soil properties and functioning of crop system. Indeed, some authors showed impact of straw mulch on pH (Wang et al. 2013), micro-organism activities and composition (Lu et al. 2015; Yu et al. 2020) or crop yield (Zhang et al. 2015).

#### I.4.3.2. Effect of pH and carbon content on Ni and Zn availability

Contrary to Cr- and Cu-CaCl₂, Ni and Zn- CaCl₂ cannot be interpreted or only predicted considering their EDTA concentrations. The monitoring of other variables, notably C content and pH were necessarily (Figure 5-8, Table 5-8). Indeed both coefficients of C content and pH were close for log(KdNi) and log(Kdzn), i.e., 0.41 and 0.42 respectively for C content and 0.80 and 1.28 respectively for pH. Both parameters are well known to influence CaCl₂ and EDTA extractable concentrations of trace metals regarding the type and the amendment frequency (Houot et al., 2009, Peltre et al., 2010, Cambier et al., 2019). Other authors found a high influence of pH on Ni-Kd and Ni-CaCl₂ (Degryse et al. 2009) and on Zn-Kd and Zn-CaCl₂ (Thiele and Leinweber, 2001; Canet et al., 1997) or of soil organic matter (Sauvé et al., 2000). Ni- and Zn-CaCl₂ seemed to have a similar behavior especially in response to FM amended soils. Indeed, the decrease in pH observed at FM modality, lead to a same increase of Zn-CaCl₂ and Ni-CaCl₂ extractable concentrations released in soils. Moreover, while compost inputs increased Ni- and Zn-EDTA pools, it also increased concentration of soil carbon, as well as pH, buffering subsequently the solubilization of Ni and Zn. However, it can be noticed that the decrease of pH in FM soils (Table SI 5-3) (5.5 in PFM compared to 6.5 in P0 at t₁₁-₂), lead to an increase in Ni and Zn solubilization (14.65 µg L⁻¹ and 247.04 µg L⁻¹ respectively in PFM compared to 1.16 µg L⁻¹ and 127.85 µg L⁻¹ respectively in P0 at t₁₁-₂) and consequently a decrease in Kd values. Other studies showed the link between soluble forms of Ni and Zn and deprotonation of the soil (Sanders and Adams 1987; Tella et al. 2016). Soil acidification in old orchard was reported as a main problematic of extractable CaCl₂ trace metal concentrations released in soils (Park and Cho 2011; Li et al. 2014). Indeed, in our study, considering the answer of Ni- and Zn- solubilization to soil characteristics over the two-year experiment, it seems that monitoring of
the soil pH and fertilization type is the only lever of action to avoid the solubilization of these trace
metals.

1.4.3.3. Soil management in order to regulate trace metal availability

In orchards, the soil management of plantation lines remains an agronomical challenge, especially in an agroecological point of view. Soil management showed only a significant effect on Cu behavior (Table 5-8). For both CaCl₂ and EDTA extractions, Cu was less extracted in soils under cover crop modality compared to straw. This difference could be due to soil heterogeneity. As a remind, soil management was set up in December 2019, so soil management effect could be observed only from the end of first year experiment. This could be explained also the little effect observed between these two soils management. Further investigations should thus be undertaken to evaluate the effect on extractable CaCl₂ and EDTA trace metals over the longer term.
### I.5. Conclusion

Valorization of rich Cr and Ni compost in *Washington Navel* orchard should be carefully monitored as compost inputs engender a soil contamination of Ni and Cr by increasing up to 4-times and of Cu by 2-times total concentrations in soils with D2 input after two years. Total concentrations of Zn did not vary. Moreover, for the four trace metals, extractable $CaCl_2$ and EDTA concentrations increased with compost applications. Ni- and Zn-$CaCl_2$ concentrations were the highest in FM modality. Extractable pools of trace metals could be thus monitored by the fertilization type as well as the amount and frequency of the inputs.

In contrast, soil management did not have any significant effect on the behavior of trace metals. Compost input had a higher impact on release of soluble trace metals in soils than soil management. Indeed, compost had a buffer capacity and was able to decrease the release of $CaCl_2$ concentrations of Ni and Zn in soils. However, an increase of the pH could be favorable to Cr solubilization, under hexavalent form, either as trivalent chromium linked with organic colloids. Further investigations should thus be undertaken to evaluate Cr speciation in amended soils. This two years study gives a first assessment of trace metal behavior which could be potentially bioavailable for plants at short term. Those results should be compared with real concentrations of trace metals transfer into the trees up to the fruit consumed in order to assess a sanitary risk. Moreover, the question arises as to how the behavior of these trace metal will change at long-term regarding fertilizer applied in the orchard and after its life cycle, especially regarding the high amounts of Ni and Cr brought by compost.
Chapitre 5

ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table SI 5-1:** Soil physical chemical parameters, total trace metal concentrations (mg kg⁻¹) and CaCl₂ (µg L⁻¹), EDTA-1h and 24h-extractable (mg kg⁻¹ and % of total metal) Ni, Cr, Cu and Zn at the beginning of the field experiment t₁₁-1 with letters corresponded on statistical differences and numbers in bracket on standard deviation. asterisks correspond on different p-value: 0.05 - 0.01 *; 0.01 – 0.001 **; <0.001 ***.</caption><thead><tr><th>t11-1</th><th></th><th>pH<sub>H2O</sub></th><th>pH<sub>KCl</sub></th><th>N total</th><th>Nas-similable</th><th>C total</th><th>C/N</th><th>Ca</th><th>Mg</th><th>Na</th><th>P</th><th>Fe</th><th>Mn</th><th>Al</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Zn</th></tr><tr><th>Units</th><th></th><th></th><th></th><th></th><th>g kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.76 a<br>(0.19)</td><td>5.54 a<br>(0.22)</td><td>1.46 a<br>(0.17)</td><td>13.67 ab<br>(2.78)</td><td>17.17 a<br>(1.48)</td><td>11.79 ab<br>(0.47)</td><td>3531 a<br>(386)</td><td>4541 a<br>(1116)</td><td>14 058 a<br>(878)</td><td>749 ab<br>(117)</td><td>41 985 a<br>(7745)</td><td>2115 a<br>(487)</td><td>65 960 a<br>(3313)</td><td>43 a<br>(3)</td><td>18 ab<br>(4)</td><td>23.0 a<br>(5.5)</td><td>96 a<br>(16)</td></tr><tr><td>Fm</td><td>7.04 a<br>(0.10)</td><td>6.03 a<br>(0.50)</td><td>1.30 a<br>(0.18)</td><td>12.74 ab<br>(2.58)</td><td>16.01 a<br>(0.85)</td><td>12.36 b<br>(0.37)</td><td>4104 a<br>(420)</td><td>4317 a<br>(664)</td><td>14 092 a<br>(676)</td><td>1758 cd<br>(177)</td><td>41 405 a<br>(3021)</td><td>2813 a<br>(229)</td><td>59 656 a<br>(2578)</td><td>37 a<br>(1)</td><td>16 a<br>(1)</td><td>26.6 a<br>(1.2)</td><td>103 a<br>(17)</td></tr><tr><td>D1</td><td>6.90 a<br>(0.27)</td><td>5.95 a<br>(0.56)</td><td>1.67 a<br>(0.32)</td><td>11.99 a<br>(6.54)</td><td>19.32 ab<br>(1.09)</td><td>11.58 ab<br>(0.71)</td><td>4024 a<br>(623)</td><td>4569 a<br>(954)</td><td>14 262 a<br>(769)</td><td>878 abc<br>(28)</td><td>43 582 a<br>(3867)</td><td>2161 a<br>(283)</td><td>63 905 a<br>(4056)</td><td>44 a<br>(7)</td><td>20 ab<br>(3)</td><td>28.3 a<br>(3.7)</td><td>101 a<br>(10)</td></tr><tr><td>D2</td><td>7.05 a<br>(0.57)</td><td>6.18 a<br>(0.63)</td><td>2.31 b<br>(0.47)</td><td>23.28 b<br>(3.00)</td><td>24.13 b<br>(2.62)</td><td>10.44 a<br>(0.26)</td><td>4586 a<br>(454)</td><td>4388 a<br>(332)</td><td>14 326 a<br>(1659)</td><td>1147 abc<br>(29)</td><td>36 397 a<br>(5939)</td><td>2318 a<br>(498)</td><td>59 141 a<br>(2612)</td><td>76 b<br>(16)</td><td>38 ab<br>(11)</td><td>26.1 a<br>(1.3)</td><td>97 a<br>(3)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>7.23 a<br>(0.17)</td><td>6.39 a<br>(0.32)</td><td>1.41 a<br>(0.40)</td><td>7.72 a<br>(0.72)</td><td>16.71 a<br>(2.34)</td><td>11.85 ab<br>(0.50)</td><td>3918 a<br>(232)</td><td>4435 a<br>(1276)</td><td>13 574 a<br>(930)</td><td>742 ab<br>(146)</td><td>40 656 a<br>(15001)</td><td>2443 a<br>(1039)</td><td>60 444 a<br>(4484)</td><td>39 a<br>(6)</td><td>17 ab<br>(3)</td><td>26.4 a<br>(7.7)</td><td>88 a<br>(17)</td></tr><tr><td>Fm</td><td>6.71 a<br>(0.53)</td><td>5.62 a<br>(0.56)</td><td>1.44 a<br>(0.28)</td><td>6.47 a<br>(1.80)</td><td>18.73 ab<br>(1.87)</td><td>13.09 b<br>(0.92)</td><td>4209 a<br>(461)</td><td>4222 a<br>(554)</td><td>14 182 a<br>(1229)</td><td>2108 d<br>(275)</td><td>38 754 a<br>(5678)</td><td>1806 a<br>(10)</td><td>60 787 a<br>(3419)</td><td>41 a<br>(7)</td><td>21 ab<br>(14)</td><td>23.4 a<br>(4.9)</td><td>92 a<br>(13)</td></tr><tr><td>D1</td><td>7.24 a<br>(0.49)</td><td>6.26 a<br>(0.58)</td><td>1.41 a<br>(0.74)</td><td>12.04 a<br>(6.67)</td><td>16.66 a<br>(4.61)</td><td>11.84 ab<br>(0.59)</td><td>4099 a<br>(705)</td><td>4551 a<br>(1002)</td><td>15 276 a<br>(1667)</td><td>678 a<br>(115)</td><td>38 127 a<br>(3995)</td><td>2191 a<br>(780)</td><td>61 840 a<br>(7777)</td><td>45 a<br>(10)</td><td>21 ab<br>(4)</td><td>21.8 a<br>(0.5)</td><td>96 a<br>(8)</td></tr><tr><td>D2</td><td>6.77 a<br>(0.14)</td><td>5.59 a<br>(0.36)</td><td>2.36 b<br>(0.25)</td><td>13.79 ab<br>(0.33)</td><td>24.53 b<br>(1.70)</td><td>10.40 a<br>(0.19)</td><td>4442 a<br>(404)</td><td>4699 a<br>(930)</td><td>13 959 a<br>(394)</td><td>1631 bcd<br>(881)</td><td>41 719 a<br>(7832)</td><td>2230 a<br>(403)</td><td>63 272 a<br>(3038)</td><td>77 b<br>(15)</td><td>39 b<br>(10)</td><td>24.1 a<br>(4.4)</td><td>116 a<br>(10)</td></tr><tr><td>Fertilization</td><td>ns</td><td>ns</td><td>***</td><td>**</td><td>***</td><td>***</td><td>ns</td><td>ns</td><td>ns</td><td>***</td><td>ns</td><td>ns</td><td>ns</td><td>***</td><td>**</td><td>ns</td><td>**</td><td>ns</td></tr><tr><td>Soil management</td><td>ns</td><td>ns</td><td>ns</td><td>**</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr><tr><td>Ferti x Soil management</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr></tbody></table>
# Chapitre 5

## ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

## APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><thead><tr><th colspan="2">t11-1</th><th colspan="5">CaCl<sub>2</sub></th><th colspan="5">1h-EDTA</th><th colspan="5">24h-EDTA</th></tr><tr><th>Soil management</th><th>Fertilization</th><th>pH<sub>CaCl2</sub></th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr><tr><th>Units</th><th></th><th colspan="5">µg L<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.16 a<br>(0.38)</td><td>0.71 a<br>(0.35)</td><td>0.000 a<br>(0.000)</td><td>2.07 a<br>(0.37)</td><td>16.55 a<br>(22.75)</td><td>0.66 a<br>(0.31)</td><td>0.01 a<br>(0.00)</td><td>6.46 a<br>(1.77)</td><td>8.30 ab<br>(3.86)</td><td>0.94 a<br>(0.38)</td><td>0.10 a<br>(0.02)</td><td>8.72 ab<br>(2.25)</td><td>12.34 ab<br>(4.71)</td></tr><tr><td>Fm</td><td>6.37 a<br>(0.47)</td><td>1.42 a<br>(0.68)</td><td>0.000 a<br>(0.000)</td><td>2.57 abc<br>(0.33)</td><td>6.35 a<br>(5.50)</td><td>0.79 a<br>(0.12)</td><td>0.04 a<br>(0.02)</td><td>6.92 ab<br>(0.23)</td><td>11.00 abc<br>(2.40)</td><td>1.10 a<br>(0.23)</td><td>0.14 a<br>(0.05)</td><td>8.77 ab<br>(1.52)</td><td>16.22 abc<br>(2.26)</td></tr><tr><td>D1</td><td>6.47 a<br>(0.21)</td><td>2.13 a<br>(1.33)</td><td>0.043 ab<br>(0.020)</td><td>3.81 bc<br>(1.03)</td><td>11.36 a<br>(10.89)</td><td>1.28 a<br>(0.36)</td><td>0.02 a<br>(0.01)</td><td>7.70 ab<br>(0.82)</td><td>9.76 abc<br>(2.70)</td><td>1.76 a<br>(0.43)</td><td>0.05 a<br>(0.03)</td><td>11.48 abc<br>(1.45)</td><td>15.10 abc<br>(3.67)</td></tr><tr><td>D2</td><td>6.62 a<br>(0.47)</td><td>2.11 a<br>(1.35)</td><td>0.090 ab<br>(0.032)</td><td>3.82 bc<br>(0.26)</td><td>7.33 a<br>(3.87)</td><td>2.88 b<br>(0.46)</td><td>0.20 b<br>(0.10)</td><td>9.52 b<br>(1.65)</td><td>14.43 bc<br>(2.41)</td><td>4.96 b<br>(0.47)</td><td>0.56 b<br>(0.24)</td><td>14.68 c<br>(1.31)</td><td>22.78 c<br>(3.42)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>6.75 a<br>(0.36)</td><td>0.30 a<br>(0.34)</td><td>0.062 ab<br>(0.065)</td><td>3.23 abc<br>(0.86)</td><td>2.28 a<br>(2.83)</td><td>0.50 a<br>(0.02)</td><td>0.02 a<br>(0.00)</td><td>6.62 ab<br>(1.54)</td><td>7.13 a<br>(0.99)</td><td>0.77 a<br>(0.06)</td><td>0.06 a<br>(0.01)</td><td>8.61 ab<br>(2.42)</td><td>10.99 a<br>(1.20)</td></tr><tr><td>Fm</td><td>6.07 a<br>(0.43)</td><td>2.49 a<br>(1.59)</td><td>0.000 a<br>(0.000)</td><td>2.60 abc<br>(0.50)</td><td>19.24 a<br>(18.48)</td><td>0.79 a<br>(0.17)</td><td>0.04 a<br>(0.03)</td><td>6.71 ab<br>(1.34)</td><td>13.38 abc<br>(4.50)</td><td>1.19 a<br>(0.26)</td><td>0.17 a<br>(0.03)</td><td>9.41 ab<br>(1.63)</td><td>20.77 bc<br>(5.94)</td></tr><tr><td>D1</td><td>6.78 a<br>(0.51)</td><td>1.14 a<br>(0.24)</td><td>0.023 ab<br>(0.012)</td><td>2.28 ab<br>(0.08)</td><td>4.08 a<br>(1.39)</td><td>0.91 a<br>(0.40)</td><td>0.02 a<br>(0.00)</td><td>5.14 ab<br>(1.35)</td><td>7.78 ab<br>(1.84)</td><td>1.33 a<br>(0.49)</td><td>0.04 a<br>(0.02)</td><td>7.27 a<br>(2.10)</td><td>12.32 ab<br>(2.56)</td></tr><tr><td>D2</td><td>6.35 a<br>(0.35)</td><td>3.17 a<br>(1.22)</td><td>0.110 b<br>(0.054)</td><td>4.12 c<br>(0.50)</td><td>12.01 a<br>(10.43)</td><td>2.91 b<br>(0.39)</td><td>0.11 ab<br>(0.02)</td><td>7.50 ab<br>(0.52)</td><td>15.36 c<br>(2.83)</td><td>4.59 b<br>(0.54)</td><td>0.53 b<br>(0.15)</td><td>12.37 bc<br>(1.03)</td><td>23.38 c<br>(3.62)</td></tr><tr><td>Units</td><td></td><td colspan="5">%</td><td colspan="5">%</td><td colspan="5">%</td></tr><tr><td rowspan="4">P</td><td>0</td><td>0.13 a<br>(0.16)</td><td>0.0002 a<br>(0.0003)</td><td>0.09 a<br>(0.01)</td><td>0.19 a<br>(0.27)</td><td>3.79 ab<br>(2.30)</td><td>0.03 a<br>(0.01)</td><td>28.57 a<br>(6.31)</td><td>8.76 ab<br>(4.45)</td><td>5.30 a<br>(2.30)</td><td>0.22 a<br>(0.01)</td><td>38.67 ab<br>(6.31)</td><td>12.97 a<br>(4.45)</td></tr><tr><td>Fm</td><td>0.09 a<br>(0.05)</td><td>0.0000 a<br>(0.0000)</td><td>0.10 a<br>(0.02)</td><td>0.07 a<br>(0.06)</td><td>5.02 ab<br>(0.67)</td><td>0.10 a<br>(0.05)</td><td>26.07 a<br>(1.69)</td><td>10.63 ab<br>(0.75)</td><td>6.96 ab<br>(0.67)</td><td>0.39 a<br>(0.05)</td><td>33.03 a<br>(1.69)</td><td>15.86 ab<br>(0.75)</td></tr><tr><td>D1</td><td>0.11 a<br>(0.08)</td><td>0.0011 a<br>(0.0007)</td><td>0.14 ab<br>(0.02)</td><td>0.12 a<br>(0.10)</td><td>6.46 ab<br>(2.42)</td><td>0.05 a<br>(0.02)</td><td>27.23 a<br>(0.64)</td><td>9.84 ab<br>(3.15)</td><td>8.87 abc<br>(2.42)</td><td>0.12 a<br>(0.02)</td><td>40.54 ab<br>(0.64)</td><td>15.22 ab<br>(3.15)</td></tr><tr><td>D2</td><td>0.05 a<br>(0.02)</td><td>0.0012 a<br>(0.0004)</td><td>0.15 ab<br>(0.02)</td><td>0.05 a<br>(0.06)</td><td>7.93 b<br>(1.81)</td><td>0.25 b<br>(0.10)</td><td>36.49 a<br>(6.58)</td><td>14.77 b<br>(1.99)</td><td>13.71 c<br>(1.81)</td><td>0.72 ab<br>(0.10)</td><td>56.29 b<br>(6.58)</td><td>23.32 b<br>(1.99)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>0.02 a<br>(0.02)</td><td>0.0018 a<br>(0.0020)</td><td>0.13 ab<br>(0.03)</td><td>0.02 a<br>(0.04)</td><td>3.00 a<br>(0.60)</td><td>0.04 a<br>(0.01)</td><td>25.41 a<br>(2.18)</td><td>8.14 a<br>(1.03)</td><td>4.68 a<br>(0.60)</td><td>0.17 a<br>(0.01)</td><td>32.74 a<br>(2.18)</td><td>12.58 a<br>(1.03)</td></tr><tr><td>Fm</td><td>0.18 a<br>(0.15)</td><td>0.0001 a<br>(0.0001)</td><td>0.12 ab<br>(0.04)</td><td>0.24 a<br>(0.26)</td><td>4.54 ab<br>(2.13)</td><td>0.09 a<br>(0.07)</td><td>29.38 a<br>(7.39)</td><td>14.28 ab<br>(3.17)</td><td>6.89 ab<br>(2.13)</td><td>0.41 a<br>(0.07)</td><td>40.80 ab<br>(7.39)</td><td>22.33 b<br>(3.17)</td></tr><tr><td>D1</td><td>0.04 a<br>(0.04)</td><td>0.0006 a<br>(0.0003)</td><td>0.11 a<br>(0.00)</td><td>0.03 a<br>(0.03)</td><td>4.32 ab<br>(1.53)</td><td>0.04 a<br>(0.00)</td><td>23.63 a<br>(6.54)</td><td>8.24 a<br>(2.56)</td><td>6.38 a<br>(1.53)</td><td>0.10 a<br>(0.00)</td><td>33.45 a<br>(6.54)</td><td>13.03 a<br>(2.56)</td></tr><tr><td>D2</td><td>0.08 a<br>(0.01)</td><td>0.0014 a<br>(0.0005)</td><td>0.18 b<br>(0.05)</td><td>0.11 a<br>(0.09)</td><td>7.75 b<br>(1.40)</td><td>0.14 ab<br>(0.01)</td><td>31.98 a<br>(7.34)</td><td>13.47 ab<br>(3.48)</td><td>12.20 bc<br>(1.40)</td><td>0.68 b<br>(0.01)</td><td>52.69 ab<br>(7.34)</td><td>20.46 ab<br>(3.48)</td></tr></tbody></table>
Chapitre 5

ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table SI 5-2:** Soil physical chemical parameters, total trace metal concentrations (mg kg⁻¹) and CaCl₂ (µg L⁻¹), EDTA-1h and 24h-extractable (mg kg⁻¹ and % of total metal) Ni, Cr, Cu and Zn at the beginning of the field experiment t₃-2 with letters corresponded on statistical differences and numbers in bracket on standard deviation. Asterisks correspond on different p-value: 0.05 - 0.01 *; 0.01 – 0.001 **; <0.001 ***.</caption><thead><tr><th>t3-2</th><th></th><th>pH<sub>H2O</sub></th><th>pH<sub>KCl</sub></th><th>N total</th><th>Nas-similable</th><th>C total</th><th>C/N</th><th>Ca</th><th>Mg</th><th>Na</th><th>P</th><th>Fe</th><th>Mn</th><th>Al</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Zn</th></tr><tr><th>Units</th><th></th><th></th><th></th><th>g kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>g kg<sup>-1</sup></th><th></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.88 <b>bc</b><br>(0.37)</td><td>5.81 <b>a</b><br>(0.43)</td><td>1.51 <b>ab</b><br>(0.18)</td><td>14.75 <b>ab</b><br>(6.06)</td><td>15.87 <b>ab</b><br>(1.75)</td><td>10.52 <b>bc</b><br>(0.10)</td><td>3391 <b>a</b><br>(240)</td><td>4873 <b>abc</b><br>(1346)</td><td>14 214 <b>a</b><br>(1582)</td><td>809 <b>a</b><br>(151)</td><td>46 872 <b>a</b><br>(11723)</td><td>2458 <b>a</b><br>(260)</td><td>63 085 <b>a</b><br>(1416)</td><td>40 <b>a</b><br>(10)</td><td>19 <b>a</b><br>(6)</td><td>33 <b>ab</b><br>(13)</td><td>100 <b>a</b><br>(22)</td></tr><tr><td>Fm</td><td>5.83 <b>a</b><br>(0.09)</td><td>5.24 <b>a</b><br>(0.27)</td><td>1.76 <b>ab</b><br>(0.14)</td><td>NA</td><td>15.85 <b>ab</b><br>(0.65)</td><td>9.03 <b>a</b><br>(0.89)</td><td>3714 <b>a</b><br>(416)</td><td>4464 <b>ab</b><br>(644)</td><td>14 991 <b>a</b><br>(298)</td><td>2492 <b>c</b><br>(732)</td><td>40 937 <b>a</b><br>(4217)</td><td>2650 <b>a</b><br>(287)</td><td>60 025 <b>a</b><br>(2757)</td><td>45 <b>a</b><br>(18)</td><td>23 <b>a</b><br>(8)</td><td>31 <b>ab</b><br>(2)</td><td>124 <b>a</b><br>(13)</td></tr><tr><td>D1</td><td>6.94 <b>bc</b><br>(0.24)</td><td>6.19 <b>a</b><br>(0.59)</td><td>1.90 <b>b</b><br>(0.08)</td><td>23.29 <b>b</b><br>(8.84)</td><td>20.38 <b>bc</b><br>(2.25)</td><td>10.69 <b>c</b><br>(0.93)</td><td>4086 <b>ab</b><br>(451)</td><td>4771 <b>abc</b><br>(854)</td><td>15 441 <b>a</b><br>(718)</td><td>889 <b>a</b><br>(34)</td><td>42 826 <b>a</b><br>(4976)</td><td>2240 <b>a</b><br>(169)</td><td>64 693 <b>a</b><br>(4011)</td><td>49 <b>a</b><br>(11)</td><td>24 <b>a</b><br>(6)</td><td>30 <b>ab</b><br>(4)</td><td>109 <b>a</b><br>(10)</td></tr><tr><td>D2</td><td>6.95 <b>bc</b><br>(0.60)</td><td>6.20 <b>a</b><br>(0.44)</td><td>2.70 <b>c</b><br>(0.09)</td><td>54.00 <b>c</b><br>(3.11)</td><td>24.81 <b>cd</b><br>(0.49)</td><td>9.18 <b>ab</b><br>(0.15)</td><td>4626 <b>ab</b><br>(393)</td><td>5508 <b>bc</b><br>(717)</td><td>14 061 <b>a</b><br>(1118)</td><td>1524 <b>ab</b><br>(105)</td><td>46 655 <b>a</b><br>(4703)</td><td>2646 <b>a</b><br>(237)</td><td>56 513 <b>a</b><br>(1791)</td><td>137 <b>b</b><br>(21)</td><td>51 <b>b</b><br>(7)</td><td>40 <b>b</b><br>(12)</td><td>121 <b>a</b><br>(8)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>7.32 <b>c</b><br>(0.03)</td><td>6.25 <b>a</b><br>(0.06)</td><td>1.33 <b>a</b><br>(0.07)</td><td>6.65 <b>a</b><br>(1.84)</td><td>13.66 <b>a</b><br>(0.71)</td><td>10.27 <b>abc</b><br>(0.07)</td><td>3589 <b>a</b><br>(219)</td><td>5066 <b>abc</b><br>(837)</td><td>14 106 <b>a</b><br>(741)</td><td>803 <b>a</b><br>(151)</td><td>48 740 <b>a</b><br>(3291)</td><td>2953 <b>a</b><br>(53)</td><td>59 872 <b>a</b><br>(3118)</td><td>31 <b>a</b><br>(2)</td><td>17 <b>a</b><br>(6)</td><td>27 <b>ab</b><br>(6)</td><td>112 <b>a</b><br>(16)</td></tr><tr><td>Fm</td><td>6.17 <b>ab</b><br>(0.43)</td><td>5.92<br>(0.52)</td><td>1.68 <b>ab</b><br>(0.12)</td><td>4.95 <b>a</b><br>(2.56)</td><td>18.16 <b>ab</b><br>(1.45)</td><td>10.85 <b>c</b><br>(0.85)</td><td>3594 <b>a</b><br>(631)</td><td>4107 <b>a</b><br>(480)</td><td>15 418 <b>a</b><br>(561)</td><td>1994 <b>bc</b><br>(45)</td><td>37 241 <b>a</b><br>(351)</td><td>1865 <b>a</b><br>(192)</td><td>63 444 <b>a</b><br>(2123)</td><td>28 <b>a</b><br>(4)</td><td>13 <b>a</b><br>(2)</td><td>27 <b>ab</b><br>(3)</td><td>102 <b>a</b><br>(11)</td></tr><tr><td>D1</td><td>7.38 <b>c</b><br>(0.43)</td><td>5.11<br>(0.52)</td><td>1.41 <b>a</b><br>(0.31)</td><td>5.05 <b>a</b><br>(1.49)</td><td>14.56 <b>a</b><br>(3.58)</td><td>10.30 <b>abc</b><br>(0.36)</td><td>3874 <b>ab</b><br>(727)</td><td>5316 <b>bc</b><br>(1106)</td><td>15 363 <b>a</b><br>(1199)</td><td>776 <b>a</b><br>(158)</td><td>48 784 <b>a</b><br>(6370) <b>a</b><br>(997)</td><td>2642 <b>a</b><br>(997)</td><td>60 660 <b>a</b><br>(7051)</td><td>53 <b>a</b><br>(3)</td><td>22 <b>a</b><br>(3)</td><td>24 <b>a</b><br>(3)</td><td>116 <b>a</b><br>(37)</td></tr><tr><td>D2</td><td>6.97 <b>bc</b><br>(0.19)</td><td>5.93<br>(0.28)</td><td>3.20 <b>d</b><br>(0.25)</td><td>15.68 <b>ab</b><br>(0.87)</td><td>29.21 <b>d</b><br>(2.13)</td><td>9.13 <b>ab</b><br>(0.06)</td><td>5143 <b>b</b><br>(61)</td><td>5735 <b>c</b><br>(1033)</td><td>14 294 <b>a</b><br>(965)</td><td>1778 <b>bc</b><br>(356)</td><td>48 800 <b>a</b><br>(5295)</td><td>2351 <b>a</b><br>(264)</td><td>60 481 <b>a</b><br>(4096)</td><td>142 <b>b</b><br>(33)</td><td>57 <b>b</b><br>(13)</td><td>32 <b>ab</b><br>(5)</td><td>133 <b>a</b><br>(17)</td></tr><tr><td>Fertilization</td><td>***</td><td>ns</td><td>***</td><td>***</td><td>***</td><td>**</td><td>***</td><td>***</td><td>ns</td><td>***</td><td>**</td><td>ns</td><td>ns</td><td>***</td><td>***</td><td>***</td><td>*</td><td>ns</td></tr><tr><td>Soil management</td><td>*</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>*</td><td>ns</td></tr><tr><td>Ferti x Soil management</td><td>ns</td><td>*</td><td>**</td><td>ns</td><td>**</td><td>**</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr></tbody></table>
# Chapitre 5

## ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

### APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><thead><tr><th rowspan="3">Units</th><th rowspan="3"></th><th colspan="5">CaCl<sub>2</sub></th><th colspan="3">1h-EDTA</th><th colspan="3">24h-EDTA</th></tr><tr><th rowspan="2">pH<sub>CaCl<sub>2</sub></sub></th><th rowspan="2">Ni</th><th rowspan="2">Cr</th><th rowspan="2">Cu</th><th rowspan="2">Zn</th><th rowspan="2">Ni</th><th rowspan="2">Cr</th><th rowspan="2">Cu</th><th rowspan="2">Zn</th><th rowspan="2">Ni</th><th rowspan="2">Cr</th><th rowspan="2">Cu</th><th rowspan="2">Zn</th></tr><tr><th colspan="5">µg L<sup>-1</sup></th><th colspan="3">mg kg<sup>-1</sup></th><th colspan="3">mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>6.36 <b>abc</b><br>(0.49)</td><td>0.66 <b>a</b><br>(0.20)</td><td>0.02 <b>a</b><br>(0.02)</td><td>3.78 <b>ab</b><br>(1.58)</td><td>2.17 <b>a</b><br>(0.18)</td><td>0.52 <b>a</b><br>(0.21)</td><td>0.02 <b>a</b><br>(0.00)</td><td>5.11 <b>a</b><br>(1.07)</td><td>6.78 <b>a</b><br>(2.66)</td><td>0.81 <b>a</b><br>(0.28)</td><td>0.07 <b>a</b><br>(0.01)</td><td>7.71 <b>a</b><br>(1.97)</td><td>11.37 <b>ab</b><br>(3.94)</td></tr><tr><td>Fm</td><td>5.51 <b>ab</b><br>(0.08)</td><td>8.80 <b>b</b><br>(1.81)</td><td>0.00 <b>a</b><br>(0.00)</td><td>3.36 <b>ab</b><br>(0.15)</td><td>90.58 <b>b</b><br>(22.75)</td><td>0.98 <b>a</b><br>(0.14)</td><td>0.04 <b>a</b><br>(0.01)</td><td>6.36 <b>ab</b><br>(0.27)</td><td>12.70 <b>a</b><br>(1.66)</td><td>1.14 <b>a</b><br>(0.17)</td><td>0.15 <b>a</b><br>(0.05)</td><td>7.80 <b>a</b><br>(0.36)</td><td>18.54 <b>b</b><br>(2.49)</td></tr><tr><td>D1</td><td>6.41 <b>abc</b><br>(0.33)</td><td>2.51 <b>ab</b><br>(1.47)</td><td>0.06 <b>a</b><br>(0.02)</td><td>5.18 <b>bc</b><br>(1.12)</td><td>12.49 <b>a</b><br>(12.84)</td><td>1.14 <b>a</b><br>(0.32)</td><td>0.06 <b>a</b><br>(0.01)</td><td>6.87 <b>ab</b><br>(0.98)</td><td>8.98 <b>a</b><br>(2.79)</td><td>1.37 <b>a</b><br>(0.36)</td><td>0.13 <b>a</b><br>(0.03)</td><td>7.63 <b>a</b><br>(1.05)</td><td>11.36 <b>ab</b><br>(3.26)</td></tr><tr><td>D2</td><td>6.53 <b>abc</b><br>(0.65)</td><td>4.42 <b>ab</b><br>(2.27)</td><td>0.26 <b>b</b><br>(0.05)</td><td>7.11 <b>c</b><br>(0.51)</td><td>12.82 <b>a</b><br>(17.52)</td><td>3.50 <b>b</b><br>(0.40)</td><td>0.36 <b>b</b><br>(0.07)</td><td>9.83 <b>c</b><br>(0.91)</td><td>19.57 <b>b</b><br>(1.56)</td><td>6.10 <b>b</b><br>(1.12)</td><td>1.10 <b>b</b><br>(0.29)</td><td>15.28 <b>b</b><br>(0.95)</td><td>29.79 <b>c</b><br>(1.35)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>6.70 <b>c</b><br>(0.02)</td><td>0.46 <b>a</b><br>(0.07)</td><td>0.03 <b>a</b><br>(0.01)</td><td>3.48 <b>ab</b><br>(0.81)</td><td>2.37 <b>a</b><br>(1.79)</td><td>0.47 <b>a</b><br>(0.02)</td><td>0.02 <b>a</b><br>(0.00)</td><td>6.27 <b>ab</b><br>(1.66)</td><td>6.47 <b>a</b><br>(0.34)</td><td>0.75 <b>a</b><br>(0.03)</td><td>0.06 <b>a</b><br>(0.01)</td><td>8.83 <b>a</b><br>(2.25)</td><td>10.67 <b>a</b><br>(0.12)</td></tr><tr><td>Fm</td><td>5.46 <b>a</b><br>(0.46)</td><td>8.33 <b>b</b><br>(4.75)</td><td>0.00 <b>a</b><br>(0.00)</td><td>3.32 <b>ab</b><br>(0.11)</td><td>78.28 <b>b</b><br>(45.65)</td><td>0.75 <b>a</b><br>(0.17)</td><td>0.03 <b>a</b><br>(0.01)</td><td>5.91 <b>ab</b><br>(1.40)</td><td>12.65 <b>a</b><br>(4.49)</td><td>1.03 <b>a</b><br>(0.18)</td><td>0.13 <b>a</b><br>(0.01)</td><td>8.48 <b>a</b><br>(1.25)</td><td>18.74 <b>b</b><br>(4.37)</td></tr><tr><td>D1</td><td>6.63 <b>bc</b><br>(0.48)</td><td>0.99 <b>a</b><br>(0.63)</td><td>0.05 <b>a</b><br>(0.02)</td><td>2.85 <b>a</b><br>(0.58)</td><td>5.42 <b>a</b><br>(0.57)</td><td>0.89 <b>a</b><br>(0.26)</td><td>0.05 <b>a</b><br>(0.02)</td><td>4.70 <b>a</b><br>(1.09)</td><td>7.85 <b>a</b><br>(1.06)</td><td>1.18 <b>a</b><br>(0.31)</td><td>0.11 <b>a</b><br>(0.05)</td><td>5.67 <b>a</b><br>(0.96)</td><td>11.07 <b>ab</b><br>(1.23)</td></tr><tr><td>D2</td><td>6.42 <b>abc</b><br>(0.21)</td><td>5.36 <b>ab</b><br>(1.04)</td><td>0.31 <b>b</b><br>(0.09)</td><td>6.77 <b>c</b><br>(0.48)</td><td>11.62 <b>a</b><br>(6.63)</td><td>4.32 <b>b</b><br>(0.61)</td><td>0.41 <b>b</b><br>(0.10)</td><td>8.53 <b>bc</b><br>(0.57)</td><td>24.24 <b>b</b><br>(2.11)</td><td>7.87 <b>b</b><br>(1.31)</td><td>1.64 <b>b</b><br>(0.61)</td><td>14.25 <b>b</b><br>(1.47)</td><td>36.57 <b>c</b><br>(3.33)</td></tr><tr><td rowspan="4">Units</td><td></td><td></td><td></td><td></td><td></td><td></td><td>%</td><td></td><td></td><td></td><td>%</td><td></td><td></td><td>%</td><td></td></tr><tr><td rowspan="4">P</td><td>0</td><td>0.16 <b>a</b><br>(0.23)</td><td>0.0006 <b>a</b><br>(0.0007)</td><td>0.13 <b>a</b><br>(0.05)</td><td>0.29 <b>ab</b><br>(0.47)</td><td>3.31 <b>a</b><br>(2.52)</td><td>0.04 <b>a</b><br>(0.02)</td><td>17.06 <b>a</b><br>(5.76)</td><td>7.42 <b>ab</b><br>(4.59)</td><td>5.08 <b>a</b><br>(3.45)</td><td>0.17 <b>a</b><br>(0.02)</td><td>25.69 <b>ab</b><br>(9.01)</td><td>12.24 <b>ab</b><br>(6.55)</td></tr><tr><td>Fm</td><td>0.42 <b>ab</b><br>(0.07)</td><td>0.0007 <b>a</b><br>(0.0004)</td><td>0.11 <b>a</b><br>(0.01)</td><td>0.75 <b>ab</b><br>(0.11)</td><td>4.58 <b>ab</b><br>(1.08)</td><td>0.09 <b>a</b><br>(0.05)</td><td>20.78 <b>a</b><br>(0.17)</td><td>10.35 <b>ab</b><br>(1.90)</td><td>5.38 <b>a</b><br>(1.37)</td><td>0.39 <b>a</b><br>(0.20)</td><td>25.47 <b>ab</b><br>(1.09)</td><td>15.12 <b>ab</b><br>(2.89)</td></tr><tr><td>D1</td><td>0.11 <b>a</b><br>(0.05)</td><td>0.0013 <b>ab</b><br>(0.0002)</td><td>0.18 <b>ab</b><br>(0.02)</td><td>0.13 <b>a</b><br>(0.14)</td><td>4.77 <b>ab</b><br>(1.11)</td><td>0.12 <b>a</b><br>(0.04)</td><td>22.69 <b>a</b><br>(0.90)</td><td>8.43 <b>ab</b><br>(3.30)</td><td>5.73 <b>a</b><br>(1.17)</td><td>0.26 <b>a</b><br>(0.00)</td><td>25.27 <b>ab</b><br>(2.00)</td><td>10.65 <b>a</b><br>(3.98)</td></tr><tr><td>D2</td><td>0.09 <b>a</b><br>(0.03)</td><td>0.0020 <b>bc</b><br>(0.0004)</td><td>0.19 <b>ab</b><br>(0.06)</td><td>0.11 <b>a</b><br>(0.14)</td><td>6.93 <b>bc</b><br>(0.27)</td><td>0.27 <b>b</b><br>(0.08)</td><td>26.09 <b>a</b><br>(8.94)</td><td>16.29 <b>cd</b><br>(2.47)</td><td>11.99 <b>bc</b><br>(0.71)</td><td>0.79 <b>bc</b><br>(0.13)</td><td>39.93 <b>bc</b><br>(10.74)</td><td>24.75 <b>c</b><br>(2.76)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>0.03 <b>a</b><br>(0.01)</td><td>0.0011 <b>ab</b><br>(0.0003)</td><td>0.13 <b>a</b><br>(0.01)</td><td>0.02 <b>a</b><br>(0.02)</td><td>3.09 <b>a</b><br>(1.22)</td><td>0.07 <b>a</b><br>(0.00)</td><td>22.85 <b>a</b><br>(1.26)</td><td>5.92 <b>a</b><br>(1.20)</td><td>4.97 <b>a</b><br>(2.05)</td><td>0.18 <b>a</b><br>(0.03)</td><td>32.25 <b>abc</b><br>(1.53)</td><td>9.72 <b>a</b><br>(1.59)</td></tr><tr><td>Fm</td><td>0.63 <b>b</b><br>(0.30)</td><td>0.0014 <b>ab</b><br>(0.0003)</td><td>0.13 <b>a</b><br>(0.02)</td><td>1.33 <b>b</b><br>(1.04)</td><td>5.87 <b>abc</b><br>(2.16)</td><td>0.10 <b>a</b><br>(0.04)</td><td>21.64 <b>a</b><br>(4.22)</td><td>12.22 <b>bc</b><br>(3.33)</td><td>8.10 <b>ab</b><br>(2.82)</td><td>0.46 <b>ab</b><br>(0.07)</td><td>31.00 <b>abc</b><br>(1.77)</td><td>18.24 <b>b</b><br>(2.84)</td></tr><tr><td>D1</td><td>0.04 <b>a</b><br>(0.03)</td><td>0.0009 <b>a</b><br>(0.0004)</td><td>0.12 <b>a</b><br>(0.04)</td><td>0.04 <b>a</b><br>(0.04)</td><td>3.97 <b>a</b><br>(0.95)</td><td>0.10 <b>a</b><br>(0.04)</td><td>19.70 <b>a</b><br>(5.69)</td><td>7.50 <b>ab</b><br>(3.51)</td><td>5.30 <b>a</b><br>(1.20)</td><td>0.21 <b>a</b><br>(0.09)</td><td>23.71 <b>a</b><br>(5.68)</td><td>10.52 <b>a</b><br>(4.67)</td></tr><tr><td>D2</td><td>0.10 <b>a</b><br>(0.00)</td><td>0.0024 <b>c</b><br>(0.0008)</td><td>0.22 <b>b</b><br>(0.03)</td><td>0.09 <b>a</b><br>(0.04)</td><td>7.71 <b>c</b><br>(0.83)</td><td>0.30 <b>b</b><br>(0.08)</td><td>27.16 <b>a</b><br>(2.54)</td><td>18.45 <b>d</b><br>(2.46)</td><td>13.98 <b>c</b><br>(1.34)</td><td>1.14 <b>c</b><br>(0.23)</td><td>45.30 <b>c</b><br>(4.48)</td><td>27.84 <b>c</b><br>(3.88)</td></tr></tbody></table>
# Chapitre 5
## ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC
### APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table SI 5-3:** Soil physical chemical parameters, total trace metal concentrations (mg kg⁻¹) and CaCl₂ (µg L⁻¹), EDTA-1h and 24h-extractable (mg kg⁻¹ and % of total metal) Ni, Cr, Cu and Zn at the beginning of the field experiment t₁₁-₂ with letters corresponded on statistical differences and numbers in bracket on standard deviation. Asterisks correspond on different p-value: 0.05 - 0.01 *; 0.01 – 0.001 **; <0.001 ***.</caption><thead><tr><th>t11-2</th><th></th><th>pH<sub>H2O</sub></th><th>pH<sub>KCl</sub></th><th>N total</th><th>Nas-similable</th><th>C total</th><th>C/N</th><th>Ca</th><th>Mg</th><th>Na</th><th>P</th><th>Fe</th><th>Mn</th><th>Al</th><th>Cr</th><th>Ni</th><th>Cu</th><th>Zn</th></tr><tr><th>Units</th><th></th><th></th><th></th><th>g kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th></th><th></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th><th>mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="5">P</td><td>0</td><td>6.48 <b>abc</b><br>(0.42)</td><td>5.30 <b>ab</b><br>(0.58)</td><td>1.38 <b>a</b><br>(0.08)</td><td>8.03 <b>ab</b><br>(2.67)</td><td>16.02 <b>a</b><br>(1.41)</td><td>11.62 <b>b</b><br>(0.38)</td><td>3250 <b>a</b><br>(444)</td><td>4964 <b>a</b><br>(1412)</td><td>14 436 <b>a</b><br>(1419)</td><td>878 <b>a</b><br>(129)</td><td>50 198 <b>a</b><br>(8011)</td><td>2559 <b>a</b><br>(316)</td><td>67 292 <b>a</b><br>(3206)</td><td>38 <b>a</b><br>(5)</td><td>15 <b>a</b><br>(7)</td><td>21 <b>a</b><br>(6)</td><td>104 <b>a</b><br>(19)</td></tr><tr><td>Fm</td><td>5.70 <b>a</b><br>(0.21)</td><td>4.43 <b>a</b><br>(0.10)</td><td>1.32 <b>a</b><br>(0.15)</td><td>8.96 <b>ab</b><br>(3.06)</td><td>15.33 <b>a</b><br>(1.73)</td><td>11.59 <b>b</b><br>(0.47)</td><td>2988 <b>a</b><br>(332)</td><td>4405 <b>a</b><br>(671)</td><td>14 914 <b>a</b><br>(516)</td><td>2097 <b>b</b><br>(186)</td><td>44 771 <b>b</b><br>(3743)</td><td>2817 <b>a</b><br>(30)</td><td>62 790 <b>a</b><br>(2326)</td><td>45 <b>a</b><br>(13)</td><td>15 <b>a</b><br>(3)</td><td>26 <b>ab</b><br>(3)</td><td>127 <b>a</b><br>(5)</td></tr><tr><td>D1</td><td>6.52 <b>abc</b><br>(0.37)</td><td>5.38 <b>ab</b><br>(0.33)</td><td>1.62 <b>a</b><br>(0.03)</td><td>9.27 <b>b</b><br>(3.29)</td><td>18.12 <b>a</b><br>(0.99)</td><td>11.22 <b>b</b><br>(0.76)</td><td>3680 <b>a</b><br>(466)</td><td>4835 <b>a</b><br>(853)</td><td>15 286 <b>a</b><br>(1115)</td><td>952 <b>a</b><br>(90)</td><td>47 523 <b>a</b><br>(6706)</td><td>2373 <b>a</b><br>(364)</td><td>66 710 <b>a</b><br>(3645)</td><td>52 <b>a</b><br>(10)</td><td>22 <b>a</b><br>(3)</td><td>27 <b>abc</b><br>(4)</td><td>106 <b>a</b><br>(9)</td></tr><tr><td>D2</td><td>6.70 <b>bc</b><br>(0.48)</td><td>5.88 <b>b</b><br>(0.61)</td><td>3.14 <b>b</b><br>(0.51)</td><td>37.58 <b>c</b><br>(9.31)</td><td>28.93 <b>b</b><br>(4.16)</td><td>9.24 <b>a</b><br>(0.24)</td><td>5002 <b>b</b><br>(356)</td><td>5843 <b>a</b><br>(700)</td><td>14 039 <b>a</b><br>(1706)</td><td>2017 <b>a</b><br>(324)</td><td>45 984 <b>b</b><br>(3702)</td><td>2578 <b>a</b><br>(391)</td><td>60 356 <b>a</b><br>(2461)</td><td>171 <b>b</b><br>(28)</td><td>66 <b>b</b><br>(18)</td><td>34 <b>c</b><br>(1)</td><td>126 <b>a</b><br>(28)</td></tr><tr><td rowspan="5">PC</td><td>0</td><td>7.02 <b>c</b><br>(0.07)</td><td>5.96 <b>b</b><br>(0.04)</td><td>1.30 <b>a</b><br>(0.03)</td><td>2.69 <b>ab</b><br>(0.85)</td><td>14.66 <b>a</b><br>(0.35)</td><td>11.25 <b>b</b><br>(0.22)</td><td>3455 <b>a</b><br>(271)</td><td>4712 <b>a</b><br>(860)</td><td>13 899 <b>a</b><br>(847)</td><td>783 <b>a</b><br>(118)</td><td>45 402 <b>a</b><br>(4443)</td><td>2630 <b>a</b><br>(240)</td><td>62 722 <b>a</b><br>(3332)</td><td>41 <b>a</b><br>(11)</td><td>15 <b>a</b><br>(2)</td><td>24 <b>a</b><br>(5)</td><td>114 <b>a</b><br>(8)</td></tr><tr><td>Fm</td><td>6.03 <b>ab</b><br>(0.25)</td><td>4.80 <b>ab</b><br>(0.40)</td><td>1.31 <b>a</b><br>(0.17)</td><td>1.74 <b>a</b><br>(0.72)</td><td>15.15 <b>a</b><br>(1.24)</td><td>11.62 <b>b</b><br>(1.00)</td><td>3439 <b>a</b><br>(368)</td><td>4398 <b>a</b><br>(768)</td><td>15 282 <b>a</b><br>(1113)</td><td>2169 <b>b</b><br>(192)</td><td>45 069 <b>b</b><br>(7019)</td><td>2115 <b>a</b><br>(507)</td><td>66 346 <b>a</b><br>(1794)</td><td>37 <b>a</b><br>(6)</td><td>14 <b>a</b><br>(2)</td><td>24 <b>a</b><br>(4)</td><td>98 <b>a</b><br>(26)</td></tr><tr><td>D1</td><td>7.01 <b>c</b><br>(0.41)</td><td>5.76 <b>b</b><br>(0.60)</td><td>1.30 <b>a</b><br>(0.23)</td><td>2.93 <b>ab</b><br>(0.94)</td><td>14.44 <b>a</b><br>(2.59)</td><td>11.15 <b>b</b><br>(0.24)</td><td>3798 <b>ab</b><br>(726)</td><td>5122 <b>a</b><br>(1181)</td><td>15 927 <b>a</b><br>(1442)</td><td>771 <b>a</b><br>(123)</td><td>47 216 <b>a</b><br>(5421)</td><td>2663 <b>a</b><br>(990)</td><td>65 672 <b>a</b><br>(6565)</td><td>46 <b>a</b><br>(4)</td><td>20 <b>a</b><br>(9)</td><td>23 <b>a</b><br>(3)</td><td>112 <b>a</b><br>(16)</td></tr><tr><td>D2</td><td>6.67 <b>bc</b><br>(0.07)</td><td>5.66 <b>b</b><br>(0.09)</td><td>3.00 <b>b</b><br>(0.05)</td><td>4.51 <b>ab</b><br>(0.92)</td><td>27.66 <b>b</b><br>(0.66)</td><td>9.22 <b>a</b><br>(0.12)</td><td>4940 <b>b</b><br>(167)</td><td>5755 <b>a</b><br>(1030)</td><td>14 435 <b>a</b><br>(531)</td><td>1738 <b>a</b><br>(278)</td><td>47 591 <b>a</b><br>(5931)</td><td>2235 <b>a</b><br>(370)</td><td>66 331 <b>a</b><br>(4551)</td><td>147 <b>b</b><br>(23)</td><td>57 <b>b</b><br>(11)</td><td>32 <b>bc</b><br>(6)</td><td>117 <b>a</b><br>(20)</td></tr><tr><td>Fertilization</td><td>***</td><td>***</td><td>***</td><td>***</td><td>***</td><td>***</td><td>***</td><td>*</td><td>ns</td><td>***</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>***</td><td>***</td><td>***</td><td>ns</td></tr><tr><td>Soil management</td><td>*</td><td>ns</td><td>ns</td><td>***</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr><tr><td>Ferti x Soil management</td><td>ns</td><td>ns</td><td>ns</td><td>***</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td><td>ns</td></tr></tbody></table>
Chapitre 5

ÉVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'ÉPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><thead><tr><th colspan="2">t11-2</th><th colspan="5">CaCl<sub>2</sub></th><th colspan="5">1h-EDTA</th><th colspan="5">24h-EDTA</th></tr><tr><th rowspan="2">Soil management</th><th rowspan="2">Fertilization</th><th rowspan="2">pH<sub>CaCl2</sub></th><th colspan="5">µg L<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th><th colspan="5">mg kg<sup>-1</sup></th></tr><tr><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr></thead><tbody><tr><td rowspan="4">P</td><td>0</td><td>5.85 <b>abc</b><br>(0.49)</td><td>1.16 <b>a</b><br>(0.25)</td><td>0.02 <b>a</b><br>(0.02)</td><td>4.30 <b>abc</b><br>(1.21)</td><td>127.85 <b>ab</b><br>(82.23)</td><td>0.60 <b>a</b><br>(0.25)</td><td>0.02 <b>a</b><br>(0.01)</td><td>5.96 <b>a</b><br>(1.02)</td><td>8.32 <b>a</b><br>(3.28)</td><td>0.88 <b>a</b><br>(0.28)</td><td>0.08 <b>a</b><br>(0.02)</td><td>8.22 <b>a</b><br>(1.26)</td><td>12.20 <b>a</b><br>(3.34)</td></tr><tr><td>Fm</td><td>5.02 <b>a</b><br>(0.12)</td><td>14.65 <b>c</b><br>(1.15)</td><td>0.00 <b>ab</b><br>(0.00)</td><td>8.82 <b>d</b><br>(3.44)</td><td>247.04 <b>c</b><br>(36.07)</td><td>0.87 <b>a</b><br>(0.11)</td><td>0.03 <b>a</b><br>(0.01)</td><td>6.81 <b>a</b><br>(0.05)</td><td>12.16 <b>a</b><br>(2.06)</td><td>1.14 <b>a</b><br>(0.08)</td><td>0.15 <b>a</b><br>(0.01)</td><td>8.97 <b>a</b><br>(1.35)</td><td>16.97 <b>a</b><br>(2.30)</td></tr><tr><td>D1</td><td>6.03 <b>abc</b><br>(0.41)</td><td>3.88 <b>ab</b><br>(2.53)</td><td>0.07 <b>ab</b><br>(0.01)</td><td>5.25 <b>abcd</b><br>(1.10)</td><td>50.85 <b>ab</b><br>(27.33)</td><td>1.12 <b>a</b><br>(0.21)</td><td>0.04 <b>a</b><br>(0.01)</td><td>6.66 <b>a</b><br>(0.70)</td><td>8.59 <b>a</b><br>(2.40)</td><td>1.62 <b>a</b><br>(0.32)</td><td>0.14 <b>a</b><br>(0.02)</td><td>8.59 <b>a</b><br>(1.01)</td><td>12.55 <b>a</b><br>(3.22)</td></tr><tr><td>D2</td><td>6.27 <b>bc</b><br>(0.61)</td><td>7.11 <b>abc</b><br>(4.36)</td><td>0.48 <b>c</b><br>(0.35)</td><td>8.26 <b>d</b><br>(2.45)</td><td>40.25 <b>a</b><br>(28.29)</td><td>5.44 <b>b</b><br>(1.14)</td><td>0.52 <b>b</b><br>(0.06)</td><td>11.63 <b>b</b><br>(0.92)</td><td>27.14 <b>b</b><br>(0.76)</td><td>9.37 <b>b</b><br>(2.47)</td><td>1.95 <b>b</b><br>(0.80)</td><td>17.79 <b>b</b><br>(0.43)</td><td>38.10 <b>b</b><br>(2.58)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>6.68 <b>c</b><br>(0.47)</td><td>0.60 <b>a</b><br>(0.22)</td><td>0.02 <b>a</b><br>(0.01)</td><td>3.40 <b>ab</b><br>(1.25)</td><td>9.60 <b>a</b><br>(7.31)</td><td>0.46 <b>a</b><br>(0.05)</td><td>0.02 <b>a</b><br>(0.00)</td><td>6.20 <b>a</b><br>(1.38)</td><td>7.07 <b>a</b><br>(0.27)</td><td>0.83 <b>a</b><br>(0.08)</td><td>0.06 <b>a</b><br>(0.01)</td><td>9.49 <b>a</b><br>(2.78)</td><td>12.10 <b>a</b><br>(0.13)</td></tr><tr><td>Fm</td><td>5.31 <b>ab</b><br>(0.34)</td><td>11.19 <b>bc</b><br>(3.94)</td><td>0.00 <b>ab</b><br>(0.00)</td><td>6.56 <b>bcd</b><br>(1.65)</td><td>164.11 <b>bc</b><br>(75.69)</td><td>0.75 <b>a</b><br>(0.16)</td><td>0.03 <b>a</b><br>(0.01)</td><td>6.67 <b>a</b><br>(1.59)</td><td>12.14 <b>a</b><br>(3.60)</td><td>1.08 <b>a</b><br>(0.20)</td><td>0.13 <b>a</b><br>(0.01)</td><td>8.78 <b>a</b><br>(0.98)</td><td>17.69 <b>a</b><br>(3.29)</td></tr><tr><td>D1</td><td>6.49 <b>bc</b><br>(0.47)</td><td>1.47 <b>a</b><br>(0.99)</td><td>0.04 <b>a</b><br>(0.02)</td><td>2.90 <b>a</b><br>(0.31)</td><td>13.69 <b>a</b><br>(13.38)</td><td>0.81 <b>a</b><br>(0.16)</td><td>0.04 <b>a</b><br>(0.01)</td><td>4.38 <b>a</b><br>(0.95)</td><td>6.76 <b>a</b><br>(1.06)</td><td>1.28 <b>a</b><br>(0.24)</td><td>0.12 <b>a</b><br>(0.04)</td><td>6.15 <b>a</b><br>(1.05)</td><td>11.43 <b>a</b><br>(0.99)</td></tr><tr><td>D2</td><td>6.27 <b>bc</b><br>(0.35)</td><td>7.25 <b>abc</b><br>(0.95)</td><td>0.42 <b>bc</b><br>(0.11)</td><td>7.37 <b>cd</b><br>(0.96)</td><td>28.08 <b>a</b><br>(9.36)</td><td>5.28 <b>b</b><br>(0.54)</td><td>0.41 <b>b</b><br>(0.01)</td><td>9.58 <b>b</b><br>(0.80)</td><td>25.49 <b>b</b><br>(1.24)</td><td>8.39 <b>b</b><br>(0.86)</td><td>1.50 <b>b</b><br>(0.54)</td><td>14.28 <b>b</b><br>(1.82)</td><td>34.17 <b>b</b><br>(1.77)</td></tr><tr><td rowspan="4">P</td><td>0</td><td>0.38 <b>abc</b><br>(0.55)</td><td>0.0006 <b>a</b><br>(0.0003)</td><td>0.35 <b>a</b><br>(0.23)</td><td>1.31 <b>bc</b><br>(0.87)</td><td>5.15 <b>ab</b><br>(4.27)</td><td>0.06 <b>a</b><br>(0.03)</td><td>29.00 <b>ab</b><br>(7.30)</td><td>8.62 <b>a</b><br>(5.01)</td><td>7.36 <b>a</b><br>(5.48)</td><td>0.20 <b>a</b><br>(0.05)</td><td>39.79 <b>abc</b><br>(8.53)</td><td>12.44 <b>a</b><br>(5.73)</td></tr><tr><td>Fm</td><td>0.99 <b>c</b><br>(0.19)</td><td>0.0021 <b>a</b><br>(0.0014)</td><td>0.92 <b>a</b><br>(0.95)</td><td>1.95 <b>c</b><br>(0.32)</td><td>5.95 <b>abc</b><br>(1.76)</td><td>0.08 <b>a</b><br>(0.03)</td><td>26.86 <b>ab</b><br>(3.21)</td><td>9.58 <b>a</b><br>(1.40)</td><td>7.73 <b>a</b><br>(1.45)</td><td>0.35 <b>a</b><br>(0.13)</td><td>35.18 <b>ab</b><br>(5.37)</td><td>13.36 <b>a</b><br>(1.29)</td></tr><tr><td>D1</td><td>0.19 <b>ab</b><br>(0.13)</td><td>0.0015 <b>a</b><br>(0.0004)</td><td>0.19 <b>a</b><br>(0.03)</td><td>0.49 <b>ab</b><br>(0.27)</td><td>5.33 <b>abc</b><br>(1.52)</td><td>0.09 <b>a</b><br>(0.03)</td><td>24.87 <b>ab</b><br>(1.05)</td><td>8.22 <b>a</b><br>(2.80)</td><td>7.66 <b>a</b><br>(2.03)</td><td>0.27 <b>a</b><br>(0.04)</td><td>32.08 <b>ab</b><br>(2.24)</td><td>12.02 <b>a</b><br>(4.02)</td></tr><tr><td>D2</td><td>0.10 <b>a</b><br>(0.04)</td><td>0.0027 <b>a</b><br>(0.0015)</td><td>0.24 <b>a</b><br>(0.08)</td><td>0.29 <b>ab</b><br>(0.18)</td><td>8.30 <b>bc</b><br>(0.69)</td><td>0.30 <b>b</b><br>(0.03)</td><td>33.93 <b>b</b><br>(2.83)</td><td>22.33 <b>b</b><br>(5.05)</td><td>14.16 <b>b</b><br>(0.90)</td><td>1.11 <b>a</b><br>(0.27)</td><td>51.93 <b>c</b><br>(2.35)</td><td>31.37 <b>b</b><br>(7.46)</td></tr><tr><td rowspan="4">PC</td><td>0</td><td>0.04 <b>a</b><br>(0.01)</td><td>0.0005 <b>a</b><br>(0.0004)</td><td>0.14 <b>a</b><br>(0.03)</td><td>0.08 <b>a</b><br>(0.06)</td><td>3.10 <b>a</b><br>(0.75)</td><td>0.05 <b>a</b><br>(0.02)</td><td>26.12 <b>ab</b><br>(2.36)</td><td>6.23 <b>a</b><br>(0.73)</td><td>5.60 <b>a</b><br>(1.17)</td><td>0.16 <b>b</b><br>(0.06)</td><td>39.68 <b>abc</b><br>(6.34)</td><td>10.65 <b>a</b><br>(0.83)</td></tr><tr><td>Fm</td><td>0.81 <b>bc</b><br>(0.28)</td><td>0.0013 <b>a</b><br>(0.0005)</td><td>0.27 <b>a</b><br>(0.04)</td><td>1.60 <b>c</b><br>(0.46)</td><td>5.42 <b>abc</b><br>(0.62)</td><td>0.09 <b>a</b><br>(0.04)</td><td>28.02 <b>ab</b><br>(3.25)</td><td>12.57 <b>a</b><br>(3.26)</td><td>7.91 <b>a</b><br>(1.89)</td><td>0.36 <b>a</b><br>(0.08)</td><td>37.38 <b>abc</b><br>(3.45)</td><td>18.84 <b>a</b><br>(6.35)</td></tr><tr><td>D1</td><td>0.08 <b>a</b><br>(0.08)</td><td>0.0009 <b>a</b><br>(0.0006)</td><td>0.13 <b>a</b><br>(0.03)</td><td>0.14 <b>a</b><br>(0.15)</td><td>4.40 <b>ab</b><br>(1.89)</td><td>0.08 <b>a</b><br>(0.02)</td><td>19.57 <b>a</b><br>(6.53)</td><td>6.24 <b>a</b><br>(1.93)</td><td>6.87 <b>a</b><br>(2.58)</td><td>0.27 <b>a</b><br>(0.11)</td><td>27.30 <b>a</b><br>(7.16)</td><td>10.48 <b>a</b><br>(2.54)</td></tr><tr><td>D2</td><td>0.13 <b>a</b><br>(0.02)</td><td>0.0028 <b>a</b><br>(0.0003)</td><td>0.23 <b>a</b><br>(0.04)</td><td>0.24 <b>ab</b><br>(0.04)</td><td>9.33 <b>c</b><br>(1.05)</td><td>0.28 <b>b</b><br>(0.02)</td><td>30.21 <b>ab</b><br>(3.67)</td><td>22.21 <b>b</b><br>(4.46)</td><td>14.83 <b>b</b><br>(1.64)</td><td>1.00 <b>b</b><br>(0.24)</td><td>44.84 <b>bc</b><br>(4.80)</td><td>29.66 <b>b</b><br>(5.19)</td></tr></tbody></table>
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_88.png" /><figcaption>**Figure SI 5-4:** Relation between soil pH<sub>H2O</sub> and pH<sub>CaCl2</sub> regarding fertilization</figcaption></figure>

<figure><img src="image_89.png" /><figcaption>**Figure SI 5-5:** Scatter plot of pH regarding logCaCl2-Ni (a) and -Zn (b) grouped by the fertilization. A linear regression line linked both relations</figcaption></figure>
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table SI 5-6:** Ratio of FM, D1, D2 modality on soil control (0) to evaluate the gain of elements regarding fertilization. Contents of C and total, extractable 1hEDTA and CaCl₂ of C, Ni, Cr, Cu and Zn are calculated with their mean, max, min values and standard deviation of the 3 blocs.</caption><thead><tr><th></th><th></th><th>Ratio</th><th>FM</th><th>D1</th><th>D2</th><th></th><th></th><th>Ratio</th><th>FM</th><th>D1</th><th>D2</th></tr></thead><tbody><tr><td rowspan="4">C</td><td></td><td>Mean</td><td>1.04</td><td>1.08</td><td>1.54</td><td rowspan="4">Cu</td><td>total</td><td>Mean</td><td>1.02</td><td>1.00</td><td>1.22</td></tr><tr><td></td><td>Max</td><td>1.15</td><td>1.17</td><td>1.74</td><td></td><td>Max</td><td>1.09</td><td>1.10</td><td>1.47</td></tr><tr><td></td><td>Min</td><td>0.99</td><td>1.03</td><td>1.35</td><td></td><td>Min</td><td>0.97</td><td>0.91</td><td>1.02</td></tr><tr><td></td><td>sd</td><td>0.07</td><td>0.07</td><td>0.16</td><td></td><td>sd</td><td>0.05</td><td>0.08</td><td>0.19</td></tr><tr><td rowspan="8">Ni</td><td rowspan="4">total</td><td>Mean</td><td>1.06</td><td>1.37</td><td>3.46</td><td rowspan="4">1HEDTA</td><td></td><td>Mean</td><td>1.07</td><td>0.96</td><td>1.48</td></tr><tr><td></td><td>Max</td><td>1.22</td><td>1.61</td><td>4.51</td><td></td><td>Max</td><td>1.11</td><td>1.02</td><td>1.74</td></tr><tr><td></td><td>Min</td><td>0.96</td><td>1.17</td><td>2.17</td><td></td><td>Min</td><td>1,04</td><td>0.91</td><td>1.25</td></tr><tr><td></td><td>sd</td><td>0.11</td><td>0.19</td><td>1.06</td><td></td><td>sd</td><td>0.03</td><td>0.05</td><td>0.24</td></tr><tr><td rowspan="4">1HEDTA</td><td>Mean</td><td>1.56</td><td>1.97</td><td>7.34</td><td rowspan="4">CaCl2</td><td></td><td>Mean</td><td>1.23</td><td>1.14</td><td>1.78</td></tr><tr><td></td><td>Max</td><td>1.75</td><td>2.10</td><td>10.15</td><td></td><td>Max</td><td>1.98</td><td>1.21</td><td>2.08</td></tr><tr><td></td><td>Min</td><td>1.36</td><td>1.83</td><td>5.00</td><td></td><td>Min</td><td>0.92</td><td>1.08</td><td>1.50</td></tr><tr><td></td><td>sd</td><td>0.16</td><td>0.13</td><td>2.23</td><td></td><td>sd</td><td>0.51</td><td>0.05</td><td>0.26</td></tr><tr><td rowspan="4">CaCl2</td><td>Mean</td><td>10.90</td><td>3.15</td><td>7.67</td><td rowspan="4">Zn</td><td>total</td><td>Mean</td><td>1.02</td><td>0.98</td><td>1.07</td></tr><tr><td></td><td>Max</td><td>15.76</td><td>3.26</td><td>9.00</td><td></td><td>Max</td><td>1.06</td><td>1.07</td><td>1.16</td></tr><tr><td></td><td>Min</td><td>4.19</td><td>3.02</td><td>5.66</td><td></td><td>Min</td><td>0.99</td><td>0.90</td><td>0.99</td></tr><tr><td></td><td>sd</td><td>5.81</td><td>0.11</td><td>1.54</td><td></td><td>sd</td><td>0.04</td><td>0.10</td><td>0.10</td></tr><tr><td rowspan="8">Cr</td><td rowspan="4">total</td><td>Mean</td><td>1.05</td><td>1.38</td><td>3.41</td><td rowspan="4">1HEDTA</td><td></td><td>Mean</td><td>1,71</td><td>1.17</td><td>2.76</td></tr><tr><td></td><td>Max</td><td>1.20</td><td>1.78</td><td>4.05</td><td></td><td>Max</td><td>1.91</td><td>1.29</td><td>3.42</td></tr><tr><td></td><td>Min</td><td>0.95</td><td>1.08</td><td>1.86</td><td></td><td>Min</td><td>1.58</td><td>1.00</td><td>1.93</td></tr><tr><td></td><td>sd</td><td>0.11</td><td>0.30</td><td>1.04</td><td></td><td>sd</td><td>0.16</td><td>0.13</td><td>0.72</td></tr><tr><td rowspan="4">1HEDTA</td><td>Mean</td><td>1.76</td><td>1.82</td><td>15.47</td><td rowspan="4">CaCl2</td><td></td><td>Mean</td><td>15.41</td><td>2.59</td><td>3.51</td></tr><tr><td></td><td>Max</td><td>2.12</td><td>2.93</td><td>23.93</td><td></td><td>Max</td><td>37.39</td><td>3.52</td><td>6.40</td></tr><tr><td></td><td>Min</td><td>1.63</td><td>0.99</td><td>7.22</td><td></td><td>Min</td><td>5.93</td><td>1.81</td><td>1.90</td></tr><tr><td></td><td>sd</td><td>0.24</td><td>0.86</td><td>7.93</td><td></td><td>sd</td><td>14.88</td><td>0.82</td><td>2.07</td></tr><tr><td rowspan="4">CaCl2</td><td>Mean</td><td>1.02</td><td>1.65</td><td>9.43</td><td rowspan="4"></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Max</td><td>2.90</td><td>2.57</td><td>20.05</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>Min</td><td>0.00</td><td>0.96</td><td>2.92</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>sd</td><td>1.35</td><td>0.75</td><td>7.79</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
## II. Prédiction des flux d'ETM apportées dans les sols au sein de la parcelle d'oranger

### II.1. Flux d'ETM liés à l'apport de compost

L'apport successif de compost riche en nickel et en chrome géogènes va engendrer des effets d'accumulation d'ETM dans les Fluvisols en raison des faibles concentrations naturelles dans ces sols du bassin versant de la Foa. Les flux entrants en ETM liés aux apports de compost peuvent être mis en relation aux concentrations dans les sols afin d'évaluer leur proportionnalité et ainsi prédire l'évolution potentielle de la contamination.

Les flux entrants par apport ont été calculés suivant la formule suivante (Laurent et al. 2020) (Eq.1) :

$$F_a = \frac{r.M}{dp.\rho} \qquad (1)$$

Avec $F_a$, le flux par apport (mg ETM.kg⁻¹ sol) ; $r$ la quantité appliquée de compost (kgMS m⁻²) ; $M$ la concentration en ETM dans le compost (mg.kg⁻¹) ; $dp$ la profondeur de sol influencée par l'apport de compost (m) ; $\rho$ la densité apparente (1000 kg.m⁻³).

Le flux cumulé ($F_c$) est calculé comme étant égal à la somme des différents apports sur une durée d'expérimentation donnée (n années).

Remarque : il est important de rappeler que l'apport de compost est réalisé au pied des arbres sur une surface équivalente à celle d'environ un mètre de diamètre et que les sols ne sont pas labourés. Ainsi, la profondeur d'influence correspond à 0,5 m en 1ère année et 0,2 m à partir de la 2ème année de culture. L'apport de compost correspond à 2,5 kg MS (dose 1) ou 10 kg MS (dose 2).

Les relations entre les flux d'ETM entrants et les concentrations en ETM dans les sols sont significativement linéaires pour le nickel et le chrome, avec des pentes proches de 0,70 ; ceci met en évidence des effets d'accumulation de ces deux ETM liés aux apports de compost (Figure 5-12). Pour le cuivre et le zinc, l'impact des apports de compost sur les flux entrants est beaucoup moins marqué, comme indiqué par les pentes plus faibles des relations linéaires (respectivement 0,49 et 0,53). Ces tendances sont imputables aux plus faibles concentrations en cuivre et en zinc dans le compost,
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

associées aux plus fortes concentrations en zinc notamment dans les sols en comparaison des flux entrants.

<figure><img src="image_90.png" /><figcaption>**Figure 5-12** : Concentrations totales en chrome et nickel (A) et en cuivre et zinc (B) dans les sols (mg.kg⁻¹) en fonction des flux cumulés d'ETM apportés par le compost sur 2 ans</figcaption></figure>

Les flux entrants d'ETM extractibles à l'EDTA (1h et 24h) ont également été confrontés aux concentrations de leurs homologues dans les sols (Figure 5-13). Pour l'ensemble des ETM étudiés, les relations entre les flux et les concentrations dans les sols étaient linéaires et très significatives. Cambier et al. (2019) ont également mis en évidence des relations significatives pour les différents ETM extraits à l'EDTA, excepté pour le nickel.

<figure><img src="image_91.png" /><figcaption>**Figure 5-13** : Concentrations extractibles en chrome (A), nickel (B), cuivre (C) et zinc (D) à l'EDTA 1h et 24h dans les sols (mg.kg⁻¹) en fonction des flux cumulés d'ETM extractibles EDTA apportés par le compost sur 2 ans</figcaption></figure>
Bien que ces relations soient significatives, il est apparu des différences entre les ETM :

Pour le cuivre comme pour le zinc, les pentes calculées étaient très proches aussi bien pour les relations calculées à partir des données EDTA 1h, qu'à partir des données EDTA 24h. Néanmoins, les valeurs des pentes étaient plus élevées pour le cuivre (environ 1,47) que pour le zinc (environ 0,65). Des tendances similaires ont été montrés par Cambier et al. (2019). Ces auteurs ont suggéré un rôle de la minéralisation du compost dans le sol après épandage pouvant conduire à des formes extractibles de cuivre à l'EDTA qui ne étaient pas initialement dans le compost. Ceci s'explique par les forts liens entre la matière organique et le cuivre (Amery et al. 2010; Manceau and Matynia 2010), et dans une moindre mesure du zinc (Antoniadis et Alloway 2002). Néanmoins, dans notre étude, la pente est semblable pour les extractions à 1 h et à 24 h, indiquant que la minéralisation du compost impacterait de manière proportionnelle les réservoirs mobilisables à court et long terme ; ce qui demeure questionnable.

Pour le nickel, les pentes estimées étaient légèrement plus élevées pour les relations calculées à partir des données EDTA 24 h (1,22), que celles issues des relations de l'EDTA 1 h (1,08). Ces résultats pourraient suggérer un impact du compost plus important sur le réservoir de nickel mobilisable à long terme après son épandage et suite à des apports répétés. Néanmoins, ils devront être confirmés lors de suivis pluriannuels, en raison de la faible différence mentionnée et des erreurs potentielles pouvant biaiser ces calculs.

Pour le chrome, les pentes calculées étaient nettement plus élevées pour les relations calculées à partir des données EDTA 24 h (2,28), que celles issues des relations de l'EDTA 1 h (0,85). Ces résultats suggèrent que les apports successifs sont susceptibles de modifier les réservoirs mobilisables à plus long terme. Dans le Chapitre 1, il a été démontré que le chrome était particulièrement présent dans la phase résiduelle du compost, notamment sous forme de chromite, et dans une moindre mesure dans la fraction réductible. Bien que considérée comme généralement faiblement altérable à court terme, la chromite pourrait constituer un réservoir important de chrome mobilisable une fois le compost épandu. En effet, certains auteurs ont mis en évidence un rôle de la dissolution de la chromite comme source de chrome dans les sols du Brésil (Garnier et al. 2009) et de Nouvelle-Calédonie (Traoré et al. 2008; Fandeur et al. 2009). Récemment, des auteurs ont mis en évidence des processus abiotiques et potentiellement biotiques de dissolution de la chromite dans les horizons oxydiques du profil latéritique de Goro (Nouvelle-Calédonie) (Wells et al. 2022). Si des tels processus doivent encore être explorés dans notre cas, les résultats suggèrent une mobilisation du chrome au cours du temps.
### II.2. Quelle contamination potentielle suite à des apports répétés ?

Les relations linéaires existantes entre les concentrations totales des ETM dans les sols et les flux entrants par le compost, permettent de prédire l'évolution des concentrations totales suite à des apports répétés de compost. La directive 2008/98/CE a mis en place des seuils maximums en ETM au-delà desquels les boues de station d'épuration issues du traitement des eaux usées ne peuvent être épandues sur les sols. Les seuils en nickel et en chrome de cette Directive ont été pris en référence afin de comparer l'évolution des concentrations totales en nickel et en chrome dans les sols suite à des apports répétés de compost (Tableau 5-10). Dans la section précédente, les concentrations en chrome et en nickel atteignaient respectivement 160 mg.kg⁻¹ et 70 mg.kg⁻¹ dans les sols de la modalité dose 2 après 2 ans. Ainsi, un dépassement des concentrations totales en chrome et en nickel selon la directive 2008/98/CE est atteint dès la deuxième année d'épandage, en lien avec les concentrations importantes en ces deux ETM dans le compost épandu (Cf- Igeo). Néanmoins, l'évolution des concentrations en chrome et en nickel a été appréhendée pour les deux modalités de compost, dose 1, dont les apports respectent les flux annuels en ces deux ETM et dose 2 représentant une dose d'apport « agronomique ». Les calculs sont basés sur un apport de 2,5 kg MS (dose 1) ou 10 kg MS (dose 2), de façon biennale, et considérant l'intégralité de la durée d'exploitation d'un tel verger, soit environ 25ans.

Ainsi, des flux entrants moyens de 20,8 mg Cr kg⁻¹ apport⁻¹ et de 7,61 mg Ni kg⁻¹ apport⁻¹ pour la dose 1, et de 83 mg Cr kg⁻¹ apport⁻¹ et 30 mg Ni kg⁻¹ apport⁻¹ pour la dose 2, sont considérés et additionnés à la concentration moyenne du fond pédo-géochimique naturel du sol témoin, soit 34,15 mg Cr kg⁻¹ et 10,9 mg Ni kg⁻¹. Il apparaît qu'en l'espace de 10 ans, les concentrations totales en chrome et en nickel, auront atteint les concentrations maximales définies par la Directive 2008/98/CE, pour la dose 1 (Figure 5-14). À la fin de la durée d'exploitation du verger, les concentrations totales en chrome et en nickel auront atteint 304 mg Cr kg⁻¹ et 110 mg Ni kg⁻¹, soit près de 10 fois les concentrations du fond pédo-géochimique naturel. Concernant la dose 2, les concentrations totales atteindront à la fin de la durée d'exploitation du verger, 1116 mg Cr kg⁻¹ et 407 mg Ni kg⁻¹, soit 35 fois en moyenne les concentrations du fond pédo-géochimique naturel.

Ces calculs demeurent néanmoins imparfaits à ce stade. En effet, ils ne considèrent pas les pertes par lixiviation ou ruissellement, ou encore l'absorption racinaire. Ils ne considèrent pas les entrées atmosphériques potentielles par dépôts secs ou humides, ni l'impact de l'apport de paille ou le rôle des plantes de couverture. Enfin, ils sont calculés en tenant compte d'une densité apparente moyenne de 1 g.cm⁻³ qui ne varierait pas au cours du temps dans les 20 premiers cm de sol. Malgré ces biais, ils permettent de mettre en évidence l'évolution potentielle de la contamination au regard des concentrations en nickel et en chrome contenues dans ce type de compost. Enfin, et comme indiqué
dans ce manuscrit, si les concentrations totales permettent d'évaluer l'intensité de la contamination, elles ne donnent pas d'indication sur la mobilité des ETM dans le système sol-eau-plante des agrosystèmes. Ces résultats préliminaires devront être affinés à l'avenir afin d'appréhender la mobilité environnementale de ces ETM, en lien notamment avec la minéralisation du compost après épandage.

<table><caption>**Tableau 5-10** : Concentrations en chrome, nickel, cuivre et zinc (mg kg⁻¹) mesurées dans le compost de l'étude correspondant aux valeurs moyennes de la Partie 1 mesurées par fusion alcaline.</caption><thead><tr><th></th><th>Compost de l'étude<br>(mg kg<sup>-1</sup>)</th><th>Valeurs limites dans les sols agricoles<br>(mg kg<sup>-1</sup>)*</th></tr></thead><tbody><tr><td>Cr</td><td>1307 ± 67</td><td>150</td></tr><tr><td>Ni</td><td>478 ± 59</td><td>50</td></tr><tr><td>Cu</td><td>94 ± 15</td><td>140</td></tr><tr><td>Zn</td><td>291 ± 61</td><td>300</td></tr></tbody></table>

*Directive 2008/98/CE

<figure><img src="image_92.png" /><figcaption>**Figure 5-14** : Evolution des concentrations en chrome (A) et en nickel (B) (mg kg⁻¹) dans les sols amendés par le compost</figcaption></figure>
### II.3. Conclusion

L'évolution des concentrations totales en nickel et en chrome, représentant les éléments problématiques, sont partiellement prédictibles en raison des effets de concentration mis en évidence.
Ainsi, même le plus petit apport de compost, augmentera inéluctablement les concentrations en chrome et en nickel lors d'épandage sur des sols dont le fond pédo-géochimique naturel serait faiblement concentré en ces éléments. Cependant, les concentrations totales ne permettent pas de prédire l'évolution des concentrations mobiles dans l'environnement. Ainsi, si les réservoirs mobilisables sont au moins partiellement définis par les apports de compost, nos résultats montrent qu'ils pourraient évoluer au cours du temps, notamment en lien avec la minéralisation du compost.
D'autre part, les mécanismes de mise en solution sont également régis par des paramètres biogéochimiques, comme le pH, qui peuvent également être impactés par l'apport de compost. Ainsi, bien que les réservoirs mobilisables tendent à augmenter, ce n'est pas nécessairement le cas des concentrations en solution. Il serait ainsi judicieux de confronter les données acquises durant cette thèse à celles issues de modèles permettant de simuler la distribution solide/liquide des ETM, tel que le modèle WHAM (Windermere Humic Aquaeous Model).
### III. Soil management of line plantation has a greater impact on trace metal transfer than fertilization in a Navel orchard (New Caledonia)

#### III.1. Introduction

Composting of organic waste is a promising method to transform solid waste into fertilizer rich in nutrients. Indeed, many waste are suitable for composting such as sewage sludge, green waste, straw or manure (Gonawala and Jardosh 2018; Sayara et al. 2020). Recycling of these organic waste could represent a substitute for mineral fertilizer and has been more recently present as a possible contribution to carbon fluxes and to soil preservation (Mohamad et al. 2016; Buerkert et al. 2023). Compost is notably known for provide available nutrients for plants, for increasing soil organic matter, and subsequently for improving soil structure, water infiltration or microbial activity; but depending on the raw organic waste quality, composts can also bring contaminants in soils such as trace metals (Singh and Agrawal 2008; Tucker et al. 2020). Trace metals are non-biodegradable elements and tend to concentrate in soils or substrates (Greenway and Song 2002; Farrell and Jones 2009; Zhan et al. 2022). Copper (Cu) and zinc (Zn) are commonly present in compost with sewage sludge (Lopes et al. 2011; Tella et al. 2013; Tella et al. 2016). Geogenic trace metals, i.e., Ni or Cr, less present in compost can also accumulated in the amended soils depending on organic waste applied and, on their concentration (Klein et al., 2023a; Tella, 2013).

Studies demonstrated that compost inputs engender a significant increase of extractable CaCl₂ and EDTA concentrations of Ni, Cr, Cu and Zn in soils (Cambier et al. 2019; Klein et al., 2023b). Extractable CaCl₂ and/or EDTA concentrations of trace metals in soils can be representative of the phyto-availability of trace metal concentrations measured within the plant (Lebourg et al. 1996; Sterckeman and Fismes 2005). These correlations between chemical extractions and actual measured concentrations in plant organs are highly dependent on the plant and trace metal considered as well as on soil physicochemical parameters (Pinamonti et al. 1997a; Tremel-Schaub and Feix 2005; Døelsch et al. 2006; Smith 2009; Legros et al. 2013). In parallel, studies have shown that high levels of bioavailable trace metals in agricultural soils are likely to result in trace metal transfer in the soil-plant system until food chains (Doelsch et al. 2010; Galal 2015; Gupta et al. 2019). Transport and accumulation of trace metals in the plant organs can have negative effects on crop productivity, soil microbial activity and they ultimately are a great concern to human health due to their biotoxicity. Thus, consumption of contaminated fruits or vegetables may also result in trace metal accumulation in the body and may cause acute or chronic toxicity risks for human health (Gupta et al. 2019). Sanitary control of agricultural production quality is very important. National and international standards allowed to respect the quality of food products
by controlling and authorizing minimum reference daily intake rate of trace metals in food (US Environmental Protection Agency, Anses, WHO).

A way to valorize compost presenting trace metals concentrations could make sense in arboriculture system. Indeed, orchard is known to generally low accumulate trace metals (Pinamonti et al. 1997b; Menti et al. 2006; Cheng et al. 2015; Roba et al. 2016; Brunetto et al. 2017; Gori et al. 2019). Agronomical practices applied on orchard such as cultivation of soils with leguminous crops and input of organic fertilizer can reduce the availability of trace metals and potential toxicity induced to fruit trees (Brunetto et al. 2017; Ferreira et al. 2018). Indeed, leguminous crops are known to their Cu phytoremediation capacity which could thus reduce Cu accumulation in fruit trees (Andreazza et al. 2011; Pinto et al. 2014). By contrast, straw input could decrease soil pH and increase dissolved organic matter, engendering an enhance of trace metal bioavailability by forming soluble organo-metallic complexes (Su et al. 2021). In parallel, compost is known to have a buffer capacity and reduced available forms of trace metals released in soils (Cambier et al. 2019; Laurent et al. 2020; Klein et al., 2023, Part I). However, with soil acidification, i.e., mineral fertilizer or straw inputs, soluble forms of Ni and Zn which are pH-dependent, could increase and be potentially available for plant uptake (Laurent et al. 2020; Klein et al., 2023b).

Thus, the hypothesis is that soil management of plantation lines could influence phytoavailability of trace metals brought by compost and thus the transfer of trace metal from soil to plants. To answer to this question, we first compared CaCl₂ and EDTA extractions performed on the soils to the trace metal concentrations measured in the leaves in order to study the predictive power of using chemical extractions to evaluate the phytoavailability of trace metals. Then, bioaccumulation factor of trace metals in leaves and translocation until the oranges were studied in orange trees of the orchard parcel in order to evaluate toxicity for human health to consume orange grown in the parcel amended with compost and regarding soil managements.
## III.2. Materiel and methods

### III.2.1. Study site and agronomical practices

The field experiment, a Navel orchard, is located in the IAC's agronomic research station in Pocquereux (21°43'895'S; 165°53'922'E; La Foa, New Caledonia), as described in *Part I Field experiment*, a same sampling campaign was applied with similar fertilization and soil management modalities. Soil sampling using in this study corresponding to sampling campaign of t<sub>3-1</sub> and t<sub>3-2</sub>.

Briefly, the experimental field is divided in 3 replication blocs with 8 modalities including 4 fertilization treatments: (1) soil negative control, without fertilization (0); (2) soil positive control, with a mineral fertilization (FM); (3) dose 1 of compost (D1); (4) dose 2 of compost (D2).

For the first year, the fertilizers were mixed in the planting hole. From the second year of cultivation, all fertilizer inputs, including composts, were applied on the surface without soil mixing because of surface-root trees. Inputs were divided into two parts along the cropping cycle, i.e., 65% in July/August for the flowering and fruit setting and 35% in December for the fruit growing (Table 5-11).

<table><caption>Table 5-11: Trace metal input in soils; *mixed in the planting hole** input divided in two parts (65% in July/August at flowering and fruit setting and 35% in December at fruit growing per tree)</caption><thead><tr><th>Crop cycle</th><th>Spreading</th><th>Mineral fertilizer</th><th>Dose 1 compost</th><th>Dose 2 compost</th></tr></thead><tbody><tr><td rowspan="2">Year 1:<br>2019-2020</td><td>Planting</td><td>0.32.16</td><td>3 kg raw matter</td><td>12 kg raw matter</td></tr><tr><td>hole*</td><td>2 kg</td><td>2.16 kg dry matter</td><td>8.63 kg DW</td></tr><tr><td rowspan="3">Year 2:<br>2020-2021</td><td rowspan="3">Surface**</td><td>15.5.20</td><td></td><td>12 kg raw matter</td></tr><tr><td>0.25 kg raw matter</td><td></td><td>6.52 kg DW</td></tr><tr><td>15.5.20</td><td></td><td>6 kg raw matter</td></tr><tr><td></td><td></td><td>0.15 kg</td><td></td><td>2.96 kg DW</td></tr></tbody></table>

Compost applied is a mixture of sewage sludge obtained from the wastewater treatment plant of Noumea (50%), and green waste from house-garden and communal parks maintenance of Mont-Dore city (50%), produced in the composting platform of Nakutakouin, New Caledonia (CDE pers. com., 2019). The dose 1 of compost input was calculated for respecting the annual and 10-years fluxes of nickel (Ni) and chromium (Cr) inputs defined by the French regulation (NFU 44-051). The dose 2 input was based on N, P, and K concentrations in composts and agronomical needs of the orchard but as a consequence, the quantity of Ni and Cr added largely exceed French regulations (Table 5-12).

Those fertilization treatments were coupled with two types of soil management, i.e., cover crop of legumes or straw mulching. The cover crop, *Arachis pintoi* were planted in December 2019. At the same time, 20 bales of straw of 250 kg each were applied on the row of the orchard in December 2019 and then 43 and 60 bales in June 2020 and March 2021, respectively.
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table 5-12:** Physico-chemical parameters of the mineral fertilizers NPK 0.32.16 and 15.5.20 and composts used in the study, total content dry weight (DW) measured by alkali fusion and aqua regal and comparison with the limit values of NFU 44-051 regulation. Numbers in brackets correspond to standard deviation (n=2)</caption><thead><tr><th></th><th></th><th>pH<sub>H20</sub></th><th>C</th><th>C/N</th><th>P</th><th>K</th><th>Ca</th><th>Mg</th><th>Fe</th><th>Mn</th><th>Al</th><th>Ni</th><th>Cr</th><th>Cu</th><th>Zn</th></tr><tr><th></th><th></th><th>-</th><th>g.kg<sup>-1</sup></th><th>-</th><th></th><th></th><th></th><th></th><th colspan="5">Alkali fusion (mg kg<sub>DW</sub><sup>-1</sup>)</th><th></th><th></th><th></th></tr></thead><tbody><tr><td rowspan="2">Mineral fertilizer</td><td>NPK 0.32.16</td><td>2.9</td><td></td><td></td><td>158 129</td><td>120 384</td><td>89 729</td><td>7 397</td><td>8 186</td><td>776</td><td>7 927</td><td>23</td><td>40</td><td>34</td><td>175</td></tr><tr><td>NPK 15.5.20</td><td>6.5</td><td></td><td></td><td>24 416</td><td>135 729</td><td>5 636</td><td>18 391</td><td>260</td><td>78</td><td>570</td><td>6</td><td>16</td><td>18</td><td>275</td></tr><tr><td rowspan="3">Compost</td><td>2019</td><td>5.9<br>(0.0)</td><td>218<br>(5)</td><td>9.79</td><td>10 322<br>(116)</td><td>10 495<br>(183)</td><td>22 535<br>(88)</td><td>13 742<br>(211)</td><td>36 080<br>(1 111)</td><td>789<br>(23)</td><td>29 968<br>(583)</td><td>410<br>(26)</td><td>1 231<br>(207)</td><td>77<br>(3)</td><td>223<br>(9)</td></tr><tr><td>2020</td><td>6.0<br>(0.0)</td><td>208<br>(23)</td><td>8.20</td><td>13 004<br>(30)</td><td>9 536<br>(385)</td><td>22 388<br>(444)</td><td>18 640<br>(526)</td><td>44 142<br>(2 716)</td><td>676<br>(67)</td><td>32 001<br>(2 421)</td><td>512<br>(10)</td><td>1 345<br>(17)</td><td>102<br>(5)</td><td>325<br>(21)</td></tr><tr><td>Mean<br>(sd)</td><td>5.9<br>(0.1)</td><td>212<br>(17)</td><td>8.73<br>(0.91)</td><td>12 110<br>(1549)</td><td>9 855<br>(617)</td><td>22 437<br>(326)</td><td>17 007<br>(2852)</td><td>41 454<br>(5 035)</td><td>714<br>(81)</td><td>31 324<br>(2 076)</td><td>483<br>(51)</td><td>1 307<br>(67)</td><td>94<br>(15)</td><td>291<br>(61)</td></tr><tr><td rowspan="3">Compost</td><td></td><td></td><td></td><td></td><td colspan="11">Aqua regia (mg kg<sub>DW</sub><sup>-1</sup>)</td></tr><tr><td>2019</td><td></td><td></td><td></td><td>8 029<br>(129)</td><td>7 187<br>(54)</td><td>16 962<br>(370)</td><td>5 005<br>(25)</td><td>19 770<br>(701)</td><td>533<br>(8)</td><td>15 540<br>(410)</td><td>416<br>(24)</td><td>329<br>(22)</td><td>96<br>(10)</td><td>302<br>(36)</td></tr><tr><td>2020</td><td></td><td></td><td></td><td>13 860<br>(349)</td><td>7 996<br>(483)</td><td>25 318<br>(336)</td><td>19 366<br>(626)</td><td>64 333<br>(6 122)</td><td>613<br>(61)</td><td>16 547<br>(1 505)</td><td>457<br>(16)</td><td>421<br>(21)</td><td>96<br>(6)</td><td>315<br>(12)</td></tr><tr><td></td><td>Mean<br>(sd)</td><td></td><td></td><td></td><td>11 916<br>(3 375)</td><td>7 726<br>(579)</td><td>22 533<br>(4 831)</td><td>14 579<br>(8 303)</td><td>49 479<br>(26 090)</td><td>586<br>(63)</td><td>16 212<br>(1 213)</td><td>443<br>(26)</td><td>391<br>(55)</td><td>96<br>(4)</td><td>310<br>(11)</td></tr><tr><td></td><td>NFU 44-051<br>regulation</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>60</td><td>120</td><td>300</td><td>600</td></tr></tbody></table>
### III.2.2. Sampling of orange trees organs: leaves and fruits

Leave and fruit samplings were realized during the two first cropping cycle, at the end of the warm season as preconized by Mademba-Sy et al. (2012). Fully expanded leaves were sampled once a year in April 2020 and 2021, i.e., respectively t<sub>8-1</sub> and t<sub>8-2</sub> in accordance with the maturity of the fruits. Leaves were sampled at the four cardinal points, on the upper third of the crown located at a sunny position. One tree out of two was sampled, a sample consisted thus of a composite sample of six trees for each modality in each block. Oranges were sampled only during the second year, i.e. April 2021 (t<sub>8-2</sub>), because only few modalities have produced fruits during the first year of sampling. For each bloc and modality, one orange by tree was kept representing an average for each modality. Orange production was heterogeneous for each tree, one orange per tree was kept as best as production allowed for all modalities. Both leaves and fruits sampled were kept at -20°C in the dark until physical and chemical analyses.

Leaves were washed with tap water and rinsed with ultrapure water. Fresh and dry mass of the leaves were measured before and after oven drying at 60°C for 72 h. Leaves were then finely ground for chemical analysis. Oranges, after being rinsed with tap water and ultrapure water, were cut into quarters, keeping one quarter out of two for analysis. Peel was separated from the pulp and seeds, if any, were removed. Pulp was freeze-dried and stored at -20°C to avoid rewetting due to hygroscopic characteristics of these samples, linked to the presence of sugar. Peels were dried in an oven at 60°C for 72 h.

### III.2.3. Physical and chemical analyses

For soil and compost analyzes, analyzes were performed at the LAMA laboratory (ISO 9001, Laboratoire des Moyens Analytiques, US Imago IRD, Nouméa, New Caledonia). Samples were air-dried, sieved to 2 mm and grounded to 0.25 mm. Residual water was determined by drying samples at 100°C for 24h. Total concentrations of major and trace elements P, K, Ca, Mg, Fe, Mn, Al, Ni, Cr, Cu and Zn were determined by akali fusion (NF ISO 14 869-2) and then analyzed by ICP-OES using a VARIAN® 730ES spectrometer. Pseudo-total concentrations were aqua regia digestion (NF EN 13 650) and then analyzed by ICP-OES or ICP-MS using a PERKIN ELMER® NexION 350x Inductively Coupled Plasma Mass Spectrometry. EDTA 0.05M extractable concentrations of Ni, Cr, Cu and Zn of soils and composts have been evaluated by the "BCR" method with 1:10 ratio and 1h shaking (Quevauviller, 1998). CaCl<sub>2</sub> 0.01M extractable concentrations with 1:10 ratio and 2h shaking (ISO 21268-2, 2019; Houba et al., 1990; Lebourg et al., 1996).
For leaves, concentrations of phosphorus (P), magnesium (Mg), potassium (K), calcium (Ca), nickel (Ni), chromium (Cr), copper (Cu) and zinc (Zn) were measured by double calcination of HCl/HF digestion according to an intern protocol of US49 of CIRAD Montpellier (Comité Inter Institut d'étude des techniques analytiques 1973; Bonvalet and Casassas 1986). Final solution was analyzed by ICP-MS (iCAPTM TQ, at GPTR AETE-ISO platform, OSU-OREME/Université de Montpellier). For fruits, concentrations of Ni, Cr, Cu and Zn were measured by HNO3/H2O2 digestion according to an intern protocol of LAMA (US IRD Imago, Nouméa). Final solution was analyzed by ICP-MS (PERKIN ELMER®).

### III.2.4. Bioaccumulation and transfer factors

Sanitary risk assessment was evaluated according to bioaccumulation factor (BCF) or translocation factor (TF) of trace metals. Bioaccumulation of trace metals into the plant was defined according to ratio of trace metal concentrations in plant organs on the concentration measured in the soils (Eq.1).

$$BCF = \frac{[TME]_{\text{Leaves}}}{[TME]_{\text{Soil}}} \qquad (1)$$

Where BCF, bioaccumulation factor; [TME]plant trace metal concentration (mg kg⁻¹) measured in leaves; [TME]soil trace metal concentration (mg kg⁻¹) measured in soils. Three BCF were considered in this study: BCFtotal represented bioaccumulation factor calculated according to the total concentration of trace metals in the soils, BCFEDTA according to the extractable EDTA concentration of trace metals in soils, BCFCaCl₂ according to the extractable CaCl₂ concentration of trace metals in soils.

Translocation factor of trace metals into the plant was calculated regarding the ratio of the trace metal concentration in the plant organs, i.e., concentration measured in the fruits on the leaves. (Eq. 2).

$$TF = \frac{[TME]_{\text{Fruits}}}{[TME]_{\text{Leaves}}} \qquad (2)$$

Where TF, translocation factor; [TME]Fruits means trace metal concentrations measured in peels and pulps (mg kg⁻¹); [TME]Leaves trace metal concentrations measured in leaves (mg kg⁻¹). A TF ratio below 1 means that trace metal concentrations were higher in fruits than in leaves and the inverse in the case of TF is higher than 1.

Human biotoxicity can be assessed by comparing the estimated daily ingestion dose (EDI) of Ni, Cr, Cu and Zn and the reference dose (RfD) that a person can ingest a substance over a lifetime without
adverse health effect (Saha and Zaman 2013). EDI depends thus of the daily orange consumption and the body weight of the consumer (Eq. 3).

$$EDI = \frac{C_m \times C_f \times I_R \times E_F \times E_D}{B_W \times A_T} \times 10^{-3} \quad (3)$$

Where Cm, trace metals concentration (mg kg⁻¹); Cf, conversion factor (0.15) in order to obtain dry mass of orange considering a humidity percentage of 85%; IR, daily ingestion rate corresponding to 1 orange per day with an average fresh weight of 200 g (Mademba-Sy et al. 2012); EF, exposition frequency estimated to 365 days per year; ED, exposition time, i.e., 70 years; BW, body weight of a person was considered to be 70 kg for this study; AT, average exposure time for non-carcinogens substances, i.e., 360 x 70 days.

Then, risk assessment was established by HQ corresponding to the estimated daily ingestion dose (EDI) on the reference dose (RfD in mg kg BW⁻¹ day⁻¹) (Ed. 4).

$$HQ = \frac{EDI}{RfD} \quad (4)$$

According to US EPA, RfD corresponded to 0.02 mg kg BW⁻¹ day⁻¹ for Ni; 0.0035 mg kg BW⁻¹ day⁻¹ for Cr; 0.04 mg kg BW⁻¹ day⁻¹ for Cu; 0.3 mg kg BW⁻¹ day⁻¹ for Zn.

### III.2.5. Control quality and statistical analysis

All glassware used for the experiments was previously rinsed with HNO₃ (10 %) overnight and rinsed with ultra-pure water. The reagent blanks were negligible and blank concentrations were systematically subtracted from sample concentrations. All the data presented are blank corrected. Quality of chemical analysis was ensured by reference samples of palm and strawberry plants to validate the chemical analyses performed on the plants.

Triplicates were realized and represented the 3 blocks of the parcel. For leaves, a mixed linear model analysis was performed and then analyzed using a three-factor ANOVA (time, fertilization, soil management) and including the block as a random factor. The data were log transformed to fit a normal distribution in order to allow statistical treatment. For oranges, statistical results were obtained using a linear mixed model followed by a two-factor ANOVA (fertilization and soil management). For all statistical treatments, the confidence interval was at 95 %. Statistical differences for each individual were highlighted using a pairwise (t-test). Correlation matrix was performed using the Pearson method to measure the linear relationship between two variables.
### III.3. Results

#### III.3.1. Trace metal concentrations in soils

Soil total and extractable EDTA and CaCl₂ concentrations of Cr, Ni, Cu and Zn can be found in **Figure 5-15**. Total concentrations of trace metals varied in the increasing sequence Cu (between 20 and 50 mg kg⁻¹) = Ni (between 10 and 70 mg kg⁻¹) < Cr (between 40 and 160 mg kg⁻¹) < Zn (between 80 and 160 mg kg⁻¹). Extractable EDTA and CaCl₂ concentrations followed the increasing sequence Cr (< 0.5 mg kg⁻¹ and < 0.4 µg L⁻¹, respectively) < Ni (< 6 mg kg⁻¹ and < 15 µg L⁻¹, respectively) < Cu (< 11 mg kg⁻¹ and < 8 µg L⁻¹, respectively) < Zn (< 30 mg kg⁻¹ and < 250 µg L⁻¹, respectively). Cr followed same pattern for all type of extraction with a fertilization effect, concentrations increased in modalities such as 0 < FM < D1 < D2. Similarly, Ni had a same increasing sequence with compost input, except extractable CaCl₂ where concentrations were the highest in FM modality (around 10 µg L⁻¹). For Cu, total concentrations did not vary with fertilization but were significantly higher in soils with straw. Extractable EDTA and CaCl₂ concentrations were as well the highest in straw modality, and especially in PD1. For Zn, although total concentrations did not vary, extractable EDTA concentrations were the highest in D2 modality (around 25 mg kg⁻¹) and in FM modality for extractable CaCl₂ concentrations (around 100 µg L⁻¹).

#### III.3.2. Trace metal concentrations in leaves

Over the two years study, concentrations of major and minor elements contained in the leaves varied on average for all modalities combined, in ascending order: Cr (0.18 ± 0.13 mg kg⁻¹) < Ni (0.62 ± 0.35 mg kg⁻¹) < Cu (2.48 ± 0.7 mg kg⁻¹) < Zn (16.96 ± 3.53 mg kg⁻¹) < Mn (28.41 ± 13.2 mg kg⁻¹) < Fe (75.75 ± 15.6 mg kg⁻¹) < P (2131.5 ± 585.3 mg kg⁻¹) < Mg (3061.88 ± 418.69 mg kg⁻¹) < K (17838.89 ± 2556.35 mg kg⁻¹) < Ca (22036.07 ± 2764.5 mg kg⁻¹) (**Table 5-13**). Significant correlations both positive and negative between the different elements were highlighted in **Figure 5-16**. Concentrations of Cr measured in leaves significantly decreased when P and Cu concentrations increase. Concentrations of Ni increased with those of Na, Mg and Zn. Concentrations of Cu increased in parallel with those of Mg and P. Finally, concentrations of Zn increased with those of Na, Mg and Fe.
# Chapitre 5

## EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

### APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_93.png" /><figcaption>**Figure 5-15** : Evolution of Cr, Ni, Cu and Zn concentrations of total and extractable EDTA (mg kg⁻¹) and CaCl₂ (µg L⁻¹) in soils in two sampling campaigns (t₃-1 and t₃-2) for the different fertilization modalities, i.e., control without fertilization O, positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input, and soil management modalities, i.e., straw mulch (P) and cover crop (PC).</figcaption></figure>
# Chapitre 5
## EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC
### APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<table><caption>**Table 5-13:** Mean concentrations (mg kg⁻¹) of calcium (Ca), potassium (K), magnesium, (Mg), phosphorus (P), sodium (Na), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), nickel (Ni) and chromium (Cr) measured in Navel leaves in two sampling campaigns (t8-1 and t8-2) for the different fertilization modalities, i.e., control without fertilization 0, positive control with mineral fertilization (FM), dose 1 (D1) and dose 2 (D2) of compost input, and soil management modalities, i.e., straw mulch (P) and cover crop (PC). Numbers in bracket represent standard deviation (n=3).</caption><thead><tr><th></th><th></th><th>Ca<br>mg kg<sup>-1</sup></th><th>K<br>mg kg<sup>-1</sup></th><th>Mg<br>mg kg<sup>-1</sup></th><th>P<br>mg kg<sup>-1</sup></th><th>Na<br>mg kg<sup>-1</sup></th><th>Fe<br>mg kg<sup>-1</sup></th><th>Mn<br>mg kg<sup>-1</sup></th><th>Zn<br>mg kg<sup>-1</sup></th><th>Cu<br>mg kg<sup>-1</sup></th><th>Ni<br>mg kg<sup>-1</sup></th><th>Cr<br>mg kg<sup>-1</sup></th></tr></thead><tbody><tr><td rowspan="6">t8-1</td><td rowspan="2">P</td><td>0</td><td>25 403 <b>bc</b><br>(2762)</td><td>19 056 <b>de</b><br>(1086)</td><td>3 194 <b>abc</b><br>(225)</td><td>1 651 <b>a</b><br>(72)</td><td>198 <b>a</b><br>(64)</td><td>79.6 <b>abcde</b><br>(6.5)</td><td>39.4 <b>abc</b><br>(14.7)</td><td>18.6 <b>abc</b><br>(3.3)</td><td>2.34 <b>abcd</b><br>(0.32)</td><td>0.674 <b>a</b><br>(0.304)</td><td>0.213 <b>a</b><br>(0.021)</td></tr><tr><td>FM</td><td>20 380 <b>ab</b><br>(2096)</td><td>21 686 <b>ef</b><br>(887)</td><td>3 487 <b>bc</b><br>(524)</td><td>2 362 <b>abc</b><br>(382)</td><td>302 <b>a</b><br>(160)</td><td>75.1 <b>abcd</b><br>(7.3)</td><td>30.3 <b>abc</b><br>(2.6)</td><td>20.4 <b>bc</b><br>(1.8)</td><td>2.67 <b>abcd</b><br>(0.32)</td><td>1.34 <b>a</b><br>(0.884)</td><td>0.157 <b>a</b><br>(0.013)</td></tr><tr><td rowspan="2">PC</td><td>D1</td><td>21 366 <b>abc</b><br>(3043)</td><td>17 164 <b>cd</b><br>(785)</td><td>3 112 <b>abc</b><br>(199)</td><td>1 637 <b>a</b><br>(89)</td><td>261 <b>a</b><br>(110)</td><td>77.6 <b>abcde</b><br>(2.8)</td><td>21.5 <b>abc</b><br>(6.2)</td><td>21.0 <b>c</b><br>(4.4)</td><td>2.15 <b>abcd</b><br>(0.10)</td><td>0.662 <b>a</b><br>(0.321)</td><td>0.373 <b>a</b><br>(0.191)</td></tr><tr><td>D2</td><td>21 348 <b>abc</b><br>(764)</td><td>18 901 <b>de</b><br>(2225)</td><td>3 175 <b>abc</b><br>(219)</td><td>1 750 <b>a</b><br>(106)</td><td>210 <b>a</b><br>(73)</td><td>76.7 <b>abcd</b><br>(2.4)</td><td>19.0 <b>ab</b><br>(3.2)</td><td>18.8 <b>abc</b><br>(1.7)</td><td>2.03 <b>ab</b><br>(0.31)</td><td>0.342 <b>a</b><br>(0.057)</td><td>0.187 <b>a</b><br>(0.065)</td></tr><tr><td rowspan="6">t8-2</td><td rowspan="2">P</td><td>0</td><td>22 731 <b>abc</b><br>(1 722)</td><td>18 183 <b>cd</b><br>(473)</td><td>3 069 <b>abc</b><br>(197)</td><td>2 057 <b>abc</b><br>(216)</td><td>244 <b>a</b><br>(31)</td><td>95.9 <b>de</b><br>(13.1)</td><td>26.4 <b>abc</b><br>(3.0)</td><td>16.6 <b>abc</b><br>(1.4)</td><td>2.82 <b>bcd</b><br>(0.26)</td><td>0.469 <b>a</b><br>(0.107)</td><td>0.174 <b>a</b><br>(0.055)</td></tr><tr><td>FM</td><td>18 418 <b>a</b><br>(1 167)</td><td>23 736 <b>f</b><br>(1133)</td><td>3 333 <b>abc</b><br>(347)</td><td>2 870 <b>bc</b><br>(183)</td><td>257 <b>a</b><br>(48)</td><td>86.5 <b>bcde</b><br>(7.4)</td><td>41.2 <b>abc</b><br>(21.3)</td><td>19.1 <b>abc</b><br>(2.0)</td><td>3.46 <b>d</b><br>(0.56)</td><td>0.867 <b>a</b><br>(0.301)</td><td>0.228 <b>a</b><br>(0.115)</td></tr><tr><td rowspan="2">PC</td><td>D1</td><td>22 574 <b>abc</b><br>(857)</td><td>19 170 <b>de</b><br>(519)</td><td>3 632 <b>c</b><br>(783)</td><td>2 384 <b>abc</b><br>(969)</td><td>298 <b>a</b><br>(175)</td><td>108 <b>e</b><br>(3.1)</td><td>23.8 <b>abc</b><br>(5.6)</td><td>19.8 <b>bc</b><br>(2.6)</td><td>3.19 <b>bcd</b><br>(0.57)</td><td>1.12 <b>a</b><br>(0.927)</td><td>0.189 <b>a</b><br>(0.024)</td></tr><tr><td>D2</td><td>18 661 <b>a</b><br>(887)</td><td>17 894 <b>cd</b><br>(384)</td><td>3 159 <b>abc</b><br>(184)</td><td>1 904 <b>ab</b><br>(138)</td><td>192 <b>a</b><br>(35)</td><td>90.4 <b>cde</b><br>(23.0)</td><td>24.1 <b>abc</b><br>(2.7)</td><td>19.2 <b>abc</b><br>(3.0)</td><td>2.33 <b>abcd</b><br>(0.53)</td><td>0.638 <b>a</b><br>(0.246)</td><td>0.396 <b>a</b><br>(0.111)</td></tr><tr><td rowspan="6">t8-2</td><td rowspan="2">P</td><td>0</td><td>23 173 <b>abc</b><br>(2 962)</td><td>15 799 <b>abc</b><br>(1 087)</td><td>2 806 <b>abc</b><br>(86)</td><td>1 615 <b>a</b><br>(154)</td><td>156 <b>a</b><br>(2)</td><td>61.0 <b>a</b><br>(9.0)</td><td>42.3 <b>abc</b><br>(26.0)</td><td>14.4 <b>abc</b><br>(1.6)</td><td>2.07 <b>abc</b><br>(0.38)</td><td>0.584 <b>a</b><br>(0.273)</td><td>0.127 <b>a</b><br>(0.123)</td></tr><tr><td>FM</td><td>22 438 <b>abc</b><br>(2 038)</td><td>17 945 <b>cd</b><br>(329)</td><td>2 526 <b>a</b><br>(223)</td><td>1 658 <b>a</b><br>(124)</td><td>161 <b>a</b><br>(32)</td><td>62.3 <b>ab</b><br>(4.4)</td><td>47.5 <b>c</b><br>(1.8)</td><td>13.1 <b>ab</b><br>(0.6)</td><td>1.66 <b>a</b><br>(0.05)</td><td>0.365 <b>a</b><br>(0.073)</td><td>0.357 <b>a</b><br>(0.566)</td></tr><tr><td rowspan="2">PC</td><td>D1</td><td>22 187 <b>abc</b><br>(1 848)</td><td>14 385 <b>ab</b><br>(1 249)</td><td>2 833 <b>abc</b><br>(175)</td><td>1 750 <b>a</b><br>(142)</td><td>148 <b>a</b><br>(21)</td><td>58.7 <b>a</b><br>(7.8)</td><td>24.2 <b>abc</b><br>(12.0)</td><td>13.7 <b>abc</b><br>(2.0)</td><td>2.10 <b>abc</b><br>(0.13)</td><td>0.556 <b>a</b><br>(0.296)</td><td>0.115 <b>a</b><br>(0.056)</td></tr><tr><td>D2</td><td>20 082 <b>ab</b><br>(857)</td><td>17 309 <b>cd</b><br>(600)</td><td>2 614 <b>ab</b><br>(462)</td><td>1 861 <b>ab</b><br>(161)</td><td>133 <b>a</b><br>(46)</td><td>57.5 <b>a</b><br>(4.7)</td><td>19.4 <b>ab</b><br>(5.0)</td><td>12.6 <b>a</b><br>(2.7)</td><td>1.96 <b>ab</b><br>(0.378)</td><td>0.332 <b>a</b><br>(0.164)</td><td>0.230 <b>a</b><br>(0.168)</td></tr><tr><td rowspan="6">t8-2</td><td rowspan="2">P</td><td>0</td><td>27 020 <b>c</b><br>(974)</td><td>16 872 <b>cd</b><br>(637)</td><td>2 815 <b>abc</b><br>(231)</td><td>2 846 <b>bc</b><br>(458)</td><td>203 <b>a</b><br>(52)</td><td>73.7 <b>abcd</b><br>(8.4)</td><td>23.2 <b>abc</b><br>(6.32)</td><td>15.3 <b>abc</b><br>(3.6)</td><td>2.85 <b>bcd</b><br>(0.99)</td><td>0.441 <b>a</b><br>(0.174)</td><td>0.144 <b>a</b><br>(0.095)</td></tr><tr><td>FM</td><td>21 445 <b>abc</b><br>(3 277)</td><td>17 197 <b>cd</b><br>(442)</td><td>3 107 <b>abc</b><br>(40.1)</td><td>2 088 <b>abc</b><br>(423)</td><td>214 <b>a</b><br>(24)</td><td>74.9 <b>abcd</b><br>(4.1)</td><td>39.5 <b>bc</b><br>(9.7)</td><td>16.2 <b>abc</b><br>(2.7)</td><td>2.13 <b>abc</b><br>(0.51)</td><td>0.697 <b>a</b><br>(0.028)</td><td>0.044 <b>a</b><br>(0.019)</td></tr><tr><td rowspan="2">PC</td><td>D1</td><td>23 626 <b>abc</b><br>(2 189)</td><td>16 579 <b>bcd</b><br>(1145)</td><td>3 165 <b>abc</b><br>(689)</td><td>3 157 <b>c</b><br>(751)</td><td>198 <b>a</b><br>(47)</td><td>66.7 <b>abc</b><br>(4.3)</td><td>16.8 <b>ab</b><br>(1.1)</td><td>14.2 <b>abc</b><br>(0.7)</td><td>3.43 <b>cd</b><br>(1.15)</td><td>0.707 <b>a</b><br>(0.164)</td><td>0.061 <b>a</b><br>(0.008)</td></tr><tr><td>D2</td><td>21 726 <b>abc</b><br>(2 874)</td><td>13 546 <b>a</b><br>(746)</td><td>2 965 <b>abc</b><br>(32)</td><td>2 515 <b>abc</b><br>(403)</td><td>179 <b>a</b><br>(34)</td><td>67.5 <b>abc</b><br>(10.0)</td><td>16.0 <b>a</b><br>(2.5)</td><td>18.4 <b>abc</b><br>(4.8)</td><td>2.51 <b>abcd</b><br>(0.37)</td><td>0.649 <b>a</b><br>(0.263)</td><td>0.040 <b>a</b><br>(0.023)</td></tr></tbody></table>
<figure><img src="image_94.png" /><figcaption>**Figure 5-16:** Correlation matrix of concentrations (mg kg⁻¹) of calcium (Ca), potassium (K), magnesium, (Mg), phosphorus (P), sodium (Na), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), nickel (Ni) and chromium (Cr) measured in Navel leaves in two sampling campaigns (t₈₋₁ and t₈₋₂). Color and gradient indicate respectively the nature and the intensity of the correlation. Crosses correspond to a non-significant correlation at p-value=0.05.</figcaption></figure>

### III.3.3. Influence of agricultural practices on trace metal concentrations in leaves

A small fertilization effect was highlighted on trace metal concentrations measured in leaves (Table 5.4). Only concentrations of Ca, P and Mn in leaves were impacted by the fertilization. Indeed, Ca concentrations significantly increased in compost D2 modality compared to control soils 0, i.e., from 18 661 ± 887 mg kg⁻¹ for P0 to 25 403 ± 2 562 mg kg⁻¹ for PCD2 at t₈₋₁ (Table 5-13). By contrast, P and Mn concentrations in leaves tended to decrease in the following order: FM > 0 > D1 > D2. Concentration of P in leaves ranged from 2 870 ± 183 mg kg⁻¹ in PCFM trees to 1 750 ± 106 mg kg⁻¹ in PD2 trees at t₈₋₁ and for Mn from 47.5 ± 1.8 mg kg⁻¹ in PFM trees to 16.0 ± 2.5 mg kg⁻¹ in PCD2 trees at t₈₋₂.

Considering the overall dataset, soil management had a highly significant effect on the leaf concentrations of P, Fe and Cu. Indeed, these concentrations were clearly higher in the leaves of trees cultivated with cover crops compared to trees cultivated with straw mulch, whatever the fertilization modality.
<table><caption>**Table 5-14:** Statistic effect of time, fertilization and soil management factors on the concentrations of major and minor elements in Navel leaves. Results came from a mixed linear model with bloc factor as a random factor. Asterisks correspond to p-value ranged <0.05-0.01 *, 0.01-0.001**and <0.001***</caption><thead><tr><th></th><th>Fertilization</th><th>Soil management</th><th>Time</th></tr></thead><tbody><tr><td>log(Ca)</td><td>***</td><td>ns</td><td>*</td></tr><tr><td>log(P)</td><td>ns</td><td>***</td><td>ns</td></tr><tr><td>log(K)</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>log(Na)</td><td>ns</td><td>*</td><td>***</td></tr><tr><td>log(Mg)</td><td>ns</td><td>*</td><td>***</td></tr><tr><td>log(Mn)</td><td>***</td><td>ns</td><td>ns</td></tr><tr><td>log(Fe)</td><td>ns</td><td>***</td><td>***</td></tr><tr><td>log(Zn)</td><td>ns</td><td>ns</td><td>***</td></tr><tr><td>log(Cu)</td><td>.</td><td>***</td><td>**</td></tr><tr><td>log(Ni)</td><td>*</td><td>ns</td><td>*</td></tr><tr><td>log(Cr)</td><td>ns</td><td>ns</td><td>***</td></tr></tbody></table>

Concentrations of elements measured in leaves tended also to vary between two-sampling times, as suggested by the time effect (Table 5-14). Leaf concentrations of Mg, Fe, Zn and Cr tended to be lower in the second year of sampling, whereas the concentration of Na strongly increased.

Nevertheless, leaf concentrations of elements highly varied according to a same fertilization or soil management modality. Thus, the evolution of Cr, Cu, Ni and Zn leaf concentrations was as described below.

**Leaf Cr concentrations** highly significantly decreased with time and especially in fertilized modalities. For example, leaf concentrations of Cr for PCD2 trees were divided by close to 10 between t<sub>8-1</sub> and t<sub>8-2</sub> (Table 5-13; Figure 5-17A). For no fertilized trees (P0 and PC0), leaf concentrations of Cr were lower than in D1 and D2 trees at t<sub>8-2</sub> when they were cultivated with cover crops in comparison with straw mulch.

**Leaf Ni concentrations** did not significantly vary regarding fertilization modalities (Table 5-14; Figure 5-17B). Indeed, leaf concentrations of Ni did not vary in no fertilized trees (P0 and PC0). Nevertheless, Ni concentrations measured in trees within the fertilized modalities, and particularly with the input of compost (D1 and D2) tended to be higher in the leaves of trees grown with cover crops (PC) compared to straw application (P). This was particularly notable and significant for D2 fertilization modality and at t<sub>8-2</sub> for FM.

**Leaf Cu concentrations** were significantly higher for trees cultivated with cover crops, whatever the fertilization modality, i.e., up to 1.6 times higher in PCD1 compared to PD1 at t<sub>8-2</sub> (Table 5-13; Figure 5-17B).
**5-17C)**. Concentrations of Cu did not vary much with time, excepted for FM fertilized trees for which the leaf concentrations significantly decreased between t<sub>8-1</sub> and t<sub>8-2</sub> for both soil management.

Leaf Zn concentrations did not vary with fertilization nor soil management modalities. However, Zn concentrations significantly decreased over time for all fertilization and soil management modalities (Table 5-13; Figure 5-17D). In the second year, concentrations of Zn in leaves tended to be higher in leaves from trees cultivated with cover crop, especially for FM and D2 modalities, as observed for Ni.

Leaf Zn concentrations did not vary with fertilization nor soil management modalities. However, Zn concentrations significantly decreased over time for all fertilization and soil management modalities (Table 5-13; Figure 5-17D). In the second year, concentrations of Zn in leaves tended to be higher in leaves from trees cultivated with cover crop, especially for FM and D2 modalities, as observed for Ni.

<figure><img src="image_95.png" /><figcaption>**Figure 5-17:** Evolution of Cr (A), Ni (B), Cu (C) and Zn(D) (mg kg<sup>-1</sup>) concentrations measured in Navel leaves over the two years period (t<sub>8-1</sub> and t<sub>8-2</sub>) according to fertilization (0, FM, D1 and D2) and soil management (P and PC). Y scales were different for each trace metal, i.e., until 1 mg kg<sup>-1</sup> for Cr, 2 mg kg<sup>-1</sup> for Ni, 5 mg kg<sup>-1</sup> for Cu and 30 mg kg<sup>-1</sup> for Zn.</figcaption></figure>
### III.3.4. Relationship between trace metal concentrations in leaves and extractable CaCl₂, EDTA and total concentrations in soils

Leaf concentrations of Cr, Ni and Zn were not significantly correlated with extractable CaCl₂, EDTA and total trace metal concentrations in soils (Table 5-15). Only Cu had a significantly but negatively linear regression between concentrations measured in leaves and extractable CaCl₂ and 1h-EDTA concentrations measured in soils (Figure 5-18; Table 5-15). However, and although significative, the explained variance was below 10%, suggesting a low quality of the model.

<figure><img src="image_96.png" /><figcaption>**Figure 5-18:** Log of trace metal concentrations in leaves Cr-Leaves (A), Ni-Leaves (B), Cu-Leaves (C) and Zn-Leaves (D) (mg kg⁻¹) according to their extractable CaCl₂ concentrations (µg L⁻¹) in soils</figcaption></figure>
<table><caption>**Table 5-15:** Linear regression between leave concentrations of Cr, Ni, Cu and Zn according to their extractable CaCl₂, EDTA and total concentrations measured in soils for all fertilization and soil management modalities combined. ns corresponded to not statistically fit with the linear regression model (p-value > 0.05) and R²a corresponded to adjusted R²</caption><thead><tr><th></th><th>log(ETM<sub>CaCl2</sub>)</th><th>log(ETM<sub>EDTA1h</sub>)</th><th>log(ETM<sub>EDTA24h</sub>)</th><th>log(ETM<sub>total</sub>)</th></tr></thead><tbody><tr><td>log(Cr<sub>Leaves</sub>)</td><td>-0.56 + 0.26 Cr<sub>CaCl2</sub><br>ns; R<sup>2</sup>a=0.04</td><td>-0.68 + 0.14 Cr<sub>EDTA1h</sub><br>ns; R<sup>2</sup>a=0.01</td><td>-0.74 + 0.18 Cr<sub>EDTA24h</sub><br>ns; R<sup>2</sup>a=0.02</td><td>-1.56 + 0.40 Cr<sub>total</sub><br>ns; R<sup>2</sup>a=0.04</td></tr><tr><td>log(Ni<sub>Leaves</sub>)</td><td>-0.28 + 0.05 Ni<sub>CaCl2</sub><br>ns; R<sup>2</sup>a=-0.001</td><td>-0.26 - 0.08 Ni<sub>EDTA1h</sub><br>ns; R<sup>2</sup>a=-0.01</td><td>-0.24 - 0.06 Ni<sub>EDTA24h</sub><br>ns; R<sup>2</sup>a=-0.01</td><td>-0.06 - 0.15 Ni<sub>total</sub><br>ns; R<sup>2</sup>a=0.01</td></tr><tr><td>log(Cu<sub>Leaves</sub>)</td><td>0.53 - 0.26 Cu<sub>CaCl2</sub><br>p-value=0.006;<br>R<sup>2</sup>a=0.13</td><td>0.61 - 0.28 Cu<sub>EDTA1h</sub><br>p-value=0.045;<br>R<sup>2</sup>a=0.06</td><td>0.59 - 0.22 Cu<sub>EDTA24h</sub><br>ns; R<sup>2</sup>a=0.04</td><td>0.81 - 0.30 Cu<sub>total</sub><br>ns; R<sup>2</sup>a=0.04</td></tr><tr><td>log(Zn<sub>Leaves</sub>)</td><td>1.22 + 0.002 Zn<sub>CaCl2</sub><br>ns; R<sup>2</sup>a=-0.02</td><td>1.14 + 0.07 Zn<sub>EDTA1h</sub><br>ns; R<sup>2</sup>a=0.013</td><td>1.08 + 0.12 Zn<sub>EDTA24h</sub><br>ns; R<sup>2</sup>a=0.04</td><td>0.73 + 0.23 Zn<sub>total</sub><br>ns; R<sup>2</sup>a=0.02</td></tr></tbody></table>

### III.3.5. Bioaccumulation factor and transfer of trace metal in the soil-tree system

#### III.3.5.1. Bioaccumulation factor of trace metals from soil to leaves

Considering the overall dataset, bioaccumulation factor (BCF) calculated on total trace metal concentrations ranged regarding trace metal considered in the increasing order Cr < Ni = Cu < Zn, with BCF<sub>total</sub> below 1 for all trace metals (Figure 5-19). For BCF calculated regarding extractable CaCl₂ and EDTA trace metal concentrations, trace metals range in the increasing order Cu < Ni < Zn < Cr with a BCF higher than 10 for Cr and Zn. A highly significative fertilization effect impacted the variation of BCF which tended to decrease with the input of fertilization and thus, especially with compost D2 modality (Table 5-16, Figure 5-19). Significative soil management and time effects observed depend on the trace metal considered and are detailed below.
Chapitre 5
EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC
APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

<figure><img src="image_97.png" /></figure>

**Figure 5-19:** Evolution of bioaccumulation factor (BCF) from total, EDTA and CaCl₂ concentrations of Cr, Ni, Cu and Zn to leaves regarding fertilization (0, FM, D1 and D2), soil management (P and PC) between t₈-₁ and t₈-₂. Y scale was different for each BCF.

**Table 5-16:** Statistic effect of time, fertilization and soil management of Cr, Ni, Cu and Zn bioaccumulation factors (BCF) by considering concentrations measured in leaves and extractable CaCl₂ (BCF<sub>CaCl2</sub>), EDTA (BCF<sub>EDTA</sub>) and total (BCF<sub>total</sub>) concentrations in soils. Results are issues from a mixed linear regression model with the bloc as a random factor.

<table><thead><tr><th></th><th>Fertilization</th><th>Soil management</th><th>Time</th></tr></thead><tbody><tr><td>log(Cr-BCF<sub>total</sub>)</td><td>**</td><td>ns</td><td>*</td></tr><tr><td>log(Ni-BCF<sub>total</sub>)</td><td>***</td><td>**</td><td>***</td></tr><tr><td>log(Cu-BCF<sub>total</sub>)</td><td>***</td><td>***</td><td>***</td></tr><tr><td>log(Zn-BCF<sub>total</sub>)</td><td>ns</td><td>ns</td><td>**</td></tr><tr><td>log(Cr-BCF<sub>EDTA1h</sub>)</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>log(Ni-BCF<sub>EDTA1h</sub>)</td><td>***</td><td>*</td><td>ns</td></tr><tr><td>log(Cu-BCF<sub>EDTA1h</sub>)</td><td>***</td><td>***</td><td>.</td></tr><tr><td>log(Zn-BCF<sub>EDTA1h</sub>)</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>log(Cr-BCF<sub>CaCl2</sub>)</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>log(Ni-BCF<sub>CaCl2</sub>)</td><td>***</td><td>ns</td><td>***</td></tr><tr><td>log(Cu-BCF<sub>CaCl2</sub>)</td><td>***</td><td>***</td><td>***</td></tr><tr><td>log(Zn-BCF<sub>CaCl2</sub>)</td><td>***</td><td>ns</td><td>***</td></tr></tbody></table>
**Cr-BCF** had a similar pattern between BCF calculated by considering extractable CaCl₂, EDTA and total soil concentrations. Cr-BCF was significantly lowest for compost D2. Furthermore, BCF decreased significantly in the second year regardless of the fertilization applied, mineral fertilization or compost, with no variation for the control. Soil management did not imply a significant effect on the evolution of the BCF.

**Ni-BCF** had a relatively similar pattern between BCF calculated with extractable CaCl₂, EDTA and total soil concentrations. A highly significant effect of fertilization was observed, with the lowest BCF for compost D2 modality. Although there was no difference in the control, a significant effect of soil management showed a higher BCF for trees planted with cover crops and especially for D1, D2 and at t₈₁ for FM fertilization modalities. Moreover, BCF decreased significantly in the second year, especially for BCFtotal and BCFCaCl₂, whatever the fertilization and soil management modalities.

**Cu-BCF** showed once again a similar variation between BCF calculated with extractable CaCl₂, EDTA and total soil concentrations. BCF decreased very significantly with fertilization according to the order D1>FM=0>D2 for cover crop and 0=FM>D1>D2 for straw. For all modalities, trees planted with cover crops exhibited a significantly higher BCF than those with straw. Moreover, BCFCaCl₂ decreased significantly in the second year.

**Zn-BCF** showed different pattern of variations depending on the BCF calculated. Indeed, BCFtotal did not vary significantly with fertilization nor soil management. Only a significant effect of the time factor was observed with a significant decrease of BCFtotal in the second year, particularly for trees planted with straw, except for the control and PD1. In contrast, BCFEDTA and BCFCaCl₂ varied significantly with fertilization, in the increasing order D2<FM=D1<0 for BCFEDTA and FM=D1=D2<0 for BCFCaCl₂. Both decreased significantly in the second year, except for the control. Although no significant effect of soil management was observed, BCFCaCl₂ tended to be lower for trees planted with straw for compost D1 modality.

### III.3.5.2. Concentrations and translocation factors of trace metals into the fruits

Fruits harvested in the second year had low trace metal concentrations, i.e., <15 mg kg⁻¹ and which varied according to the following increasing sequence Cr < Ni < Cu < Zn. Concentrations of Cr in pulp were usually under the detection limit of ICP-MS measurement and remained similar in peel regardless of the fertilization and soil management modalities (Figure 5-20). There was no significant effect of fertilization or soil management modalities on trace metal concentrations contained in peels and pulps.
Only Cu had higher concentrations in pulp at PD1 compared to PFM. For Ni, pulp concentrations were higher in oranges from the cover crop modalities for FM and D2 compared to straw, as described for leaves (Figure 5-18). For Zn, a trend was observed with higher concentrations measured in peels and pulps in oranges from trees grown with straw mulch with FM and D1 fertilization.

<figure><img src="image_98.png" /><figcaption>**Figure 5-20:** Concentrations of Cr, Ni, Cu and Zn contained in peels and pulps regarding fertilization (0, FM, D1, D2) soil management (P and PC) modalities at t8-2. Concentration of Cr in pulps was under limit of quantification. Y scale was different for each trace metals and orange part.</figcaption></figure>

TF varied according to the following increasing sequence Ni < Zn < Cu < Cr (Figure 5-21). Cr-TF was higher than 1 for trees grown with cover crops with D1 and D2 fertilization, meaning that Cr concentrations were higher in leaves than in fruits.

Both Ni- and Zn-TF ratios were below 1 for all modalities, meaning a higher Ni and Zn concentration in fruits than in leaves.

For Cu, TF was higher than 1 for trees with straw, while they tended to be lower than 1 for trees with cover crops. Thus, trees cultivated with straw accumulated preferably Cu in fruits compared to trees cultivated with cover crops where Cu concentration was higher in leaves.

There was no significant effect of fertilization. However, the soil management significantly impacted TF variation of trace metals. TF of Cr tended to be higher for trees cultivated with cover crops, only for compost modalities, i.e., D1 and D2. TF of Ni and Zn tended to be higher for trees cultivated with straw
mulch in comparison of trees cultivated with cover crops. This effect was particularly marked for fertilized modalities, i.e., FM, D1 and D2 fertilization. As explained previously, TF of Cu was clearly impacted by the soil management whatever the fertilization.

<figure><img src="image_99.png" /><figcaption>**Figure 5-21:** Translocation factor (TF) of Cr (A), Ni (B), Cu (C) and Zn (D) according concentrations of trace metals in fruits on those respectively in leaves regarding fertilization (0, FM, D1 and D2) and soil management (P and PC) at t<sub>8-2</sub>. Y scale was different regarding trace metal considered. Blue line indicated a TF equal to 1</figcaption></figure>

### III.3.5.3. Biotoxicity assessment for human risk

Mean, maximum and minimum estimated daily intake (EDI) of Ni, Cu, Zn contained in a 200 g orange for a 70 kg person were presented in **Table 5-17**. EDI of Cr was not presented because Cr concentrations were below detection limit.

<table><caption>**Table 5-17:** Estimated daily intake (EDI mg kg bw<sup>-1</sup>day<sup>-1</sup>) in Ni, Cu and Zn in an orange of 200 g considering 85% of humidity and for a person of 70 kg, according to fertilization (0, FM, D1 et D2) and soil management (P et PC) modalities with the reference dose (RfD mg kg bw<sup>-1</sup> day<sup>-1</sup>) for each trace metal issue to US EPA.</caption><thead><tr><th colspan="3">mg kg bw<sup>-1</sup> day<sup>-1</sup></th><th colspan="3">mg kg bw<sup>-1</sup> day<sup>-1</sup></th></tr><tr><th></th><th></th><th></th><th>Cu</th><th>Ni</th><th>Zn</th></tr></thead><tbody><tr><td rowspan="3">P</td><td>0</td><td>Mean</td><td>0.0010</td><td>0.0001</td><td>0.0023</td></tr><tr><td></td><td>Max</td><td>0.0012</td><td>0.0001</td><td>0.0029</td></tr><tr><td></td><td>Min</td><td>0.0008</td><td>0.0000</td><td>0.0017</td></tr><tr><td rowspan="3">FM</td><td></td><td>Mean</td><td>0.0008</td><td>0.0000</td><td>0.0026</td></tr><tr><td></td><td>Max</td><td>0.0010</td><td>0.0001</td><td>0.0027</td></tr><tr><td></td><td>Min</td><td>0.0007</td><td>0.0000</td><td>0.0025</td></tr><tr><td rowspan="3">D1</td><td></td><td>Mean</td><td>0.0014</td><td>0.0001</td><td>0.0028</td></tr><tr><td></td><td>Max</td><td>0.0015</td><td>0.0001</td><td>0.0029</td></tr><tr><td></td><td>Min</td><td>0.0011</td><td>0.0000</td><td>0.0027</td></tr><tr><td rowspan="3">D2</td><td></td><td>Mean</td><td>0.0011</td><td>0.0001</td><td>0.0028</td></tr><tr><td></td><td>Max</td><td>0.0012</td><td>0.0001</td><td>0.0032</td></tr><tr><td></td><td>Min</td><td>0.0009</td><td>0.0000</td><td>0.0024</td></tr><tr><td>RfD</td><td></td><td></td><td>0.0400</td><td>0.0200</td><td>0.3000</td></tr></tbody></table>
EDI for each trace metal was very low regardless the fertilization and soil management modalities and varied according to the following increasing sequence Ni < Cu < Zn (Table 5-17). For Ni, the maximum EDI calculated remained at 0.0001 mg kg bw⁻¹ day⁻¹, for Cu at 0.016 mg kg bw⁻¹ day⁻¹ in PCD1 and for Zn at 0.0032 mg kg bw⁻¹ day⁻¹ in PD2. All of these EDI were well below the reference dose (RfD), i.e., 0.02 mg kg bw⁻¹ day⁻¹ for Ni, 0.04 mg kg bw⁻¹ day⁻¹ for Cu and 0.3 mg kg bw⁻¹ day⁻¹ for Zn.

### III.4. Discussion

#### III.4.1. Trace metal concentrations in organ trees and estimation by chemical extraction in soils

##### III.4.1.1. Trace metal concentrations in leaves and fruits

Over all modalities, trace metal concentrations measured in leaves and fruits were relatively low, i.e., Cr (<0.5 mg kg⁻¹) < Ni (<1.0 mg kg⁻¹) < Cu (<5.0 mg kg⁻¹) < Zn (<25 mg kg⁻¹) (Figure 5-18; Figure 5-20) and were below other studies conducted on orange or citrus orchards (Menti et al. 2006; Galal 2015). Canet et al. (1997) evaluated the bioavailability of trace metals in soils cultivated with citrus following inputs of organic waste and reported same order of magnitude of Cr concentrations measured in leaves (0.1-0.2 mg kg⁻¹) and slightly higher in pulp (0.1-0.2 mg kg⁻¹). For the other trace metals, concentrations were reported in same order of magnitude (10-14 mg kg⁻¹ and 4.1-5.0 mg kg⁻¹) for Cu (34-46 mg kg⁻¹ et 2.3-3.1 mg kg⁻¹) for Zn and (0.9-2.6 mg kg⁻¹ et 0.1-0.6 mg kg⁻¹) for Ni in respectively leaves and pulp. Concentrations measured followed same decreasing sequence: leaf>peel>pulp than other studies on the accumulation of Pb, Cd, Cr, As and Hg in Navel trees in China (Cheng et al. 2015).

##### III.4.1.2. Trace metal concentrations in Navel trees compared to trace metal chemically extracted in soils

Concentrations of Cr, Ni, Cu and Zn measured in leaves were not correlated to those measured in soils, whatever the extraction considered, i.e., CaCl₂ nor EDTA (Figure 5-15). This absence of relation suggested that CaCl₂ and EDTA extractions did not reflect phytoavailability of these trace metals. If organic chelating agents, such as EDTA which is known to over-represent the elements that are really available to plants, saline solutions such as CaCl₂ is usually considered as representative of elements bioavailable to plants. Thus, different authors have demonstrated the interest of CaCl₂ extraction to evaluate bioavailability of different elements and under different pedoclimatic contexts (Lebourg et al. 1996). Thus, close relationships between leaf concentrations and extractable CaCl₂ concentrations in soils have already been demonstrated for rice (Zhang et al. 2010), for fern plants such as *Medicago polymorpha* and *Poa annua* (Ciadamidaro et al. 2017), for Chinese cabbage (Wang et al. 2004), for Cd,
Ni and Zn in lettuce, spinach and corn (Novozamsky et al. 1993) and for Ni, Cu, Pb and Zn in *Phaseous vulgaris* (Meers et al. 2007). Nevertheless, in a tropical context, other authors have shown a lack of correlation between extractable CaCl₂ concentrations of trace metals in soils in leaf concentrations of sugarcane (Collin and Doelsch 2010). If the different chemical methods aim to mimic biological processes, they often do not represent phyto-availability especially under in-situ conditions in various agro-climatic conditions(Gupta and Aten 1993; Sterckeman and Fismes 2005). Indeed, correlations between plants and reagent depend on the plant species, the interaction with other trace metals as well as the physico-chemical parameters of the soil, i.e., pH, redox potential, organic matter content, soil texture and temperature, presence of microorganisms (Gupta et al. 2019).

### III.4.2. Impact on agronomic practices on trace metal concentrations measured in leaves and fruits of the orchard

#### III.4.2.1. Impact of fertilization on trace metal uptake in Navel orchard

Fertilization and more especially compost input significantly increased total concentrations of trace metals, as well as extractable CaCl₂ and ETDA concentrations in soils (Figure 5-15). However, leaf and fruit concentrations of Cr, Ni, Cu and Zn were not impacted by the fertilization the two first years of the crop cycle (Figure 5-17; Table 5-14). Only an increase of Ni concentrations in leaves could be observed for trees cultivated with FM. Indeed, this mineral fertilizer is enriched with micro-nutriments easily extractible and thus available for plants. Ni-CaCl₂ concentrations were the highest in FM soils (up to 10 µg L⁻¹; Figure 5-15). However, when comparing D2 with 0 soils, compost input significantly increased extractable EDTA and CaCl₂ concentrations in soils of Cr and Ni by around 4-times, of Cu and Zn by around 2-times, except for Zn-CaCl₂. Although BCFtotal calculated suggested no accumulation of trace metals in leaves of the Navel orchard (BCFtotal < 1) (Figure 5-19), BCF showed a significant effect on fertilization (Table 5-16) with a significant decrease in trees with compost input, especially D2 for all trace metals (Figure 5-19).

As input of organic mulch modify microbiologic and rhizosphere activity (Forge et al. 2003), a possible explanation could be due to a stabilization of trace metals in root cell walls or mycorrhizal fungi in the tree root systems. Moreover straw could as well maintain a certain level of humidity which lead to stabilize trace metals in the rhizosphere (Kahle 1993). Moreover, compost input brought elements in soil solution, and thus ionic competition could occurred in the transfer of trace metal in soil-plant system with an increase of ionic strength and a decrease in trace metals adsorption (Abu Al-Rub et al. 2003; Zhang 2011).
In parallel, compost input suggested any phytotoxicity to the *Navel* orchard, which is confirmed by measurements of tree growth and orange production yield (*Figure SI 5-7*). Indeed, the combination of mulch and compost resulted in a significant gain in orange production (*Figure SI 5-8*). These results are in agreement with other studies which showed that both compost and straw were reported in the literature for their capacity to improve soil structure and soil organic matter and thus, agricultural production and plant growth (Kumari et al. 2020).

Translocation factors (TF) of trace metals into the plant were below 1 for Ni and Zn for all modalities. This suggested a preferably storage in leaves as reported by Cheng et al., (2015). For Cr, TF was below 1 only for trees cultivated with straw and compost input. For Cu, TF was below 1 only for trees cultivated with leguminous crops. As compost input or soil management modified soil properties, physical and chemical parameters could be involved in the storage location of trace metals in leaves or fruits. Other studies reported that trace metal transfer in edible part of the plant depends on soil properties such as pH, soil organic matter or CEC which affect the valence of soil trace metals and their adsorption capacity of the plant (Khan et al. 2015; Liu et al. 2021).

### III.4.2.2. Impact of soil management on trace metal uptake in Navel orchard

By contrast to the fertilization modality, soil management showed a significative effect of trace metal concentrations in leaves (*Table 5-13*; *Table 5-14*; *Figure 5-17*). No significative effect was observed on trace metal concentrations measured in fruits. Other studies reported a major bioaccumulation of trace metals in leaves (Cheng et al. 2015; Khan et al. 2015). This could also explain the differences observed of trace metal concentrations measured in leaves compared to no differences for fruits.

The mechanisms of root uptake by plants are species specific and usually depending on the elements considered. Cr is a non-essential element for plants, and physiological mechanisms implied in this uptake remain uncertain (Ertani et al. 2017). The toxicity of chromium depends on its speciation, which influences its uptake, transport and accumulation in the plant. Uptake of Cr(III) seems to be a passive mechanism, whereas Cr(VI) uptake would be an active mechanism via sulfate or phosphate transporters, due to a similar structure of chromate ions with the two previous ones (De Oliviera et al., 2014; 2016; Hahid et al. 2017). Thus, after input of mineral P, some authors highlighted a decrease in Cr(VI) toxicity on the *Arabidopsis thaliana* model (Lopèz-Bucio et al., 2014). Although we are not certain about Cr speciation in solution, the significant decreasing relationship between phosphorus and foliar Cr concentrations (*Figure 5-16*) could suggest that such ionic competition for Cr uptake is taking place in the orchard. On the other hand, a significant effect of soil management could be demonstrated on foliar P and Cr concentrations (*Table 5-13*; *Table 5-14*). Thus, and independently of fertilization, trees
planted with cover crops had higher foliar P concentrations and lower Cr concentrations than trees cultivated with straw. Cover crop planted was a leguminous, *Arachis pintoï*, known for its ability to fix atmospheric nitrogen through a bacterial symbiosis, the rhizobia (Khetmalas and Bal 2005). Co-cropping with leguminous also implies an increase in P uptake by the companion plant and a better P use efficiency (Sharma and Gupta 2002; Xue et al. 2016; Tang et al. 2021). This would be explained by a root production of phosphatase and phytase or carboxylate enzymes that would increase phosphorus solubilization (Inal et al. 2007). Thus, although Cr speciation in solution should be identified, assimilation of Cr(VI) by orange trees could decrease indirectly by *Arachis pintoï* whose presence favors the solubilization of P being more competitive for root adsorption. Such mechanisms could explain the results obtained concerning the higher P concentrations in leaves of orange trees cultivated with *Arachis pintoï*, and the significant decreasing relationship between foliar P and Cr concentrations.

However, soil management impacts the most variation of Cu concentrations in leaves. Indeed, leaf Cu concentrations were significantly the highest in trees grown with cover crop compared those with straw (Figure 5-18). Although *Arachis pintoï* is well documented in the literature for its Cu phytoremediation capacity (Andreazza et al. 2011; Pinto et al. 2014), another mechanism could explain this increase of leaf Cu concentrations trees cultivated with cover crop. Indeed similarly, leaf Fe concentrations (Table 5-13) and in a less marked measure for Ni and Zn at both FM and compost D2 modality the second year (Figure 5-18), were higher in trees cultivated with cover crop than straw. Uptake of these trace metals in leaves could be attributed to root interactions which modify rhizosphere environment and microbiological activity. Rhizobial and non-rhizobial bacteria of leguminous are known to have multiple plant growth promoting effect (PGP) (Tapia-Garcia et al., 2020). Among them, the production of organic acids and siderophores are known to be able to increase trace metal availability (Sessitsch et al. 2013; Alves et al. 2022; Etesami 2022). Indeed, siderophores are metal chelating agents produced by microorganisms particularly under Fe-limiting conditions (Schwyn and Neilands 1987). Their role and mechanism are well described in the literature for Fe solubilization and they are able to increase availability of other trace metals such as Ni, Cu and Zn (Broadley et al. 2007; Bellenger et al. 2008; Chen et al. 2014). Moreover, Cesco et al. (2006) showed an increase of Fe uptake as well by Citrus in relation with the production of siderophores by graminaceous species. Thus, siderophores could be present in *Navel* orchard from our study with the co-crop *Arachis pintoï*.
### III.4.3. Human risk linked to the use of a compost Ni and Cr rich in a Navel orchard

Regarding sanitary risk for human health, according to the US Environmental Protection Agency (EPA), when comparing the estimated daily intake (EDI) of trace metals contained in orange for a 70 kg person, EDI is well below the reference dose (RfD) for all orange harvested (Table 5-17). Thus, there is any risk for human health of consuming oranges produced in the Navel orchard regardless the fertilization or soil management modalities.
### III.5. Conclusions

Compost inputs in orchard could be a judicious way for decreasing mineral fertilizer needs, especially when coupled to adequate soil managements. In New Caledonia, composts exhibit especially high concentrations of Ni (up to 400 mg kg⁻¹) and Cr (up to 1 200 mg kg⁻¹), and soil inputs subsequently increase their total and mobilizable concentration, as well as their concentration in soil solution. Moreover, no is known about the fate of trace metal from compost in orchard when these inputs are coupled with different soil management. Here, we studied, the impact of soil management, i.e., straw or legume cover crops (*Arachis pintoi*) with different fertilization, notably compost inputs, on the soil-orange tree trace metal transfer. For all cropping modalities, the concentrations measured both in leaves and fruits, did not correlate with the concentrations of trace metal measured in soils as total, mobilizable from EDTA extraction, and in solution from CaCl₂ extraction, suggesting that all these methods did not reflect the phytoavailability of trace metal in the orange tree. Surprisingly, and even considering an important impact on fertilization, especially compost input on trace metal concentrations, it did not impact their concentration in leaves and fruits. However, for all trace metals, BCF tended to decrease with the fertilization, especially the compost inputs. On contrary, soil management highly impacted the trace metal uptake in *Navel* orchard, i.e., both the concentrations in leaves and the BCF. Concentrations of Ni, Cu and Zn were almost 2-times higher in leaves from trees cultivated with cover crop than straw. Rhizobia bacteria producing siderophores, could be implied. Cr uptake decreased by half in leaves of trees cultivated with cover crop compared to straw, notably under compost modality from the second year. By increasing the P solubilization, leguminous could decrease Cr absorption through ionic competition effects. Whatever the soil and fertilization management considered here, the fruits exhibited similar and low trace metal concentrations (<10 mg.kg⁻¹ for all trace metals). Regarding growth and yield of the orchard and fruit concentration, our results suggest no phytotoxicity of the compost applied for the orchard, neither of the fruit consumption by humans whatever the soil management considered. These results, obtained in a short term in comparison to the life cycle of the orchard, will have to be deepened by a pluri-annual follow-up. Especially the impacts of repeated inputs on the fate of trace metal, in link with the soil management of line plantations, should be assessed both in soil and for soil-orange tree transfer.
Chapitre 5

EVOLUTION DE LA MOBILITE DU NICKEL, CHROME, CUIVRE ET ZINC

APRES L'EPANDAGE D'UN COMPOST RICHE EN NICKEL ET EN CHROME EN AGRUMICULTURE

III.6. Supplementary information

<figure><img src="image_100.png" /></figure>

**Figure SI 5-7:** Evolution of basal circumference (cm) of trees according to fertilization (0, FM, D1, D2) and soil management (P and PC) over the two years period

<figure><img src="image_101.png" /></figure>

**Figure SI 5-8:** Orange yield production (kg ha⁻¹) regarding fertilization modalities (0, FM, D1 and D2) and soil management (P and PC) over the two years