Figure 1.
Brazilian banana curls production and study sites in Ribeira River Valley, São Paulo state. Adapted from Almeida and Zanlorenssi (2018) and https://www.ovaledoribeira.com.br/2012/01/mapa-do-vale-do-ribeira-pelo-google.html.
Table 1.
Studied site characterisation at the Eldorado, Registro and Sete Barras counties.
| City | Eldorado | Registro | Sete-Barras | ||||
|---|---|---|---|---|---|---|---|
| System | Forest | Banana | Forest | Banana | Forest | Banana | |
| Age of system | 30 | 50 | 35 | 15 | 45 | 40 | |
| Latitude | 24°29′57″S | 24°23′34″S | 24°26′29″S | ||||
| Longitude | 48°02′48″O | 47°49′36″O | 47°53′22″O | ||||
| Climate Köppen* | Am | Af | Af | ||||
| Mean annual temperature (°C) | 23.9–24.3 (lowest 13°C) in July, and highest (34.2°C) in February | ||||||
| Mean annual rainfall (mm) | 1500–1600 | ||||||
| Soil texture | Clay Loam | Clay | Clay Loam | ||||
| Liming | 30 days before planting, based on raising BS to 70% and Mg content to 8 mmol · dm −3 | ||||||
| Fertilization | Potassium | 200 a 450 kg of K2O · ha−1 at formation stage and 100–750 kg of K2O · ha−1 at production stage | |||||
| Nitrogeneous | 200 kg of mineral N at formation stage and 160–400 kg N mineral · ha−1 · year−1 | ||||||
| Phosphate | 40–120 kg of P2O5 · ha−1 with annual repetitions according to soil analysis | ||||||
| Organic | Application in the pit (10–15 L of cattle manure) or chicken manure (3–5 L · pit−1) | ||||||
Table 2.
Execution process of the SQIs and SMAF.
| SQI | Selection of indicators | Interpretation | Integration | Reference |
|---|---|---|---|---|
| SQI-1 | TDS | Non-Linear | Weighted | Cherubin et al. (2016a) |
| SQI-2 | Additive | |||
| SQI-3 | Linear | Weighted | Andrews et al. (2002) | |
| SQI-4 | Additive | |||
| SQI-5 | MDS | Non-Linear | Weighted | Cherubin et al. (2016a) adapted |
| SQI-6 | Additive | |||
| SMAF | Weighted | Andrews et al. (2004) |
Table 3.
Soil indicators associated with soil functions and database.
| Soil function | Indicator | Unit | Dataset | ||
|---|---|---|---|---|---|
| Chemical | |||||
| f(i) Storage, availability and cycling of nutrients | P | mg · dm−3 | TDS | MDS | |
| K | mg · dm−3 | TDS | MDS | ||
| Ca | mmolc · dm−3 | TDS | - | ||
| Mg | mmolc · dm−3 | TDS | - | ||
| S | mmolc · dm−3 | TDS | - | ||
| B | mg · dm−3 | TDS | - | ||
| Cu | mg · dm−3 | TDS | - | ||
| Mn | mg · dm−3 | TDS | - | ||
| Fe | mg · dm−3 | TDS | - | ||
| Zn | mg · dm−3 | TDS | - | ||
| pH | - | TDS | MDS | ||
| H + Al | mmolc_ · dm−3 | TDS | - | ||
| BS | % | TDS | - | ||
| CEC | mmolc_ · dm−3 | TDS | - | ||
| Physical | |||||
| f(ii) Soil–water dynamic and soil aeration | BD | kg · m−3 | TDS | MDS | |
| f(iv) Sustain plant growth | |||||
| TP | m−3 · m−3 | TDS | - | ||
| f(ii) Soil–water dynamic and soil aeration | MaP | m−3 · m−3 | TDS | - | |
| MiP | m−3 · m−3 | TDS | - | ||
| SWSC | - | TDS | - | ||
| f(iv) Sustain plant growth | WFPS | - | TDS | MDS | |
| SAC | - | TDS | - | ||
| f(ii) Soil–water dynamic and soil aeration | Kfs | cm · h−1 | TDS | - | |
| f(v) Ability to resist degradation | |||||
| f(iv) Sustain plant growth | ASI | % | TDS | MDS | |
| f(v) Ability to resist degradation | |||||
| f(v) Ability to resist degradation | MWD | Mm | TDS | - | |
| SSI | % | TDS | - | ||
| Biological | |||||
| f(iii) Sustain biological activity | Mdens | Indiv · m −2 | TDS | - | |
| EWorm | Indiv · mC2 | TDS | - | ||
| Mrich | - | TDS | - | ||
| Mdiver | - | TDS | - | ||
| f(i, ii, iii, iv) | SOC | g · kg−1 | TDS | MDS | |
1 ASI, aggregate stability index; B, boron; BD, bulk density; BS, base saturation; Ca, calcium; CEC, electrical conductivity; Cu, copper; EWorm, oligochaetes; Fe, iron; H + Al, hydrogen + aluminium; K, potassium; Kfs, saturated hydraulic conductivity; Mdens-Density, Mrich, macrofauna richness; MDiver, Shannon’s diversity-index; MDS, minimum dataset.; Mg, magnesium; MiP, microporosity; Mn, manganese; MWD, weighted average diameter; P, phosphorus; pH, ionic hydrogen potential; S, sulphur; SAC, soil aeration capacity; SOC, soil organic carbon; SSI, structural quality index; SWSC, soil water storage capacity MaP, macroporosity; TDS, total dataset; TP, total porosity; WFPS, water filled pore space; Zn, zinc.
Table 4.
Mean values of the indicators of chemical, physical and biological sectors, to characterise each land use.
| Chemical | Forest | Banana | SD | Physical | Forest | Banana | SD | Biological | Forest | Banana | SD |
|---|---|---|---|---|---|---|---|---|---|---|---|
| BS% | 81 | 92 | 9.74 | Ksat (cm · h−1) | 39.82 | 3.34 | 25.79 | Mdiver | 1.5 | 1.4 | 0.09 |
| pH CaCl2 | 5.5 | 6.5 | 0.70 | WMD (mm) | 3.20 | 4.20 | 0.71 | ||||
| H + Al (mmolc · dm−3) | 18 | 13 | 5.82 | SSI (%) | 71.88 | 52.07 | 14.01 | Mrich | 2.0 | 1.8 | 0.17 |
| CEC (mmolc · dm−3) | 111 | 171 | 38.49 | ASI (%) | 11.76 | 14.67 | 2.06 | ||||
| Fe (mg · dm−3) | 81 | 72 | 32.92 | TP (m3 · nr−3) | 0.50 | 0.58 | 0.05 | Abundance (indv · m−2) | 28.1 | 32.7 | 0.28 |
| Cu (mg · dm−3) | 3 | 4 | 1.55 | SAC | 0.36 | 0.16 | 0.15 | ||||
| Zn (mg · dm−3) | 9 | 13 | 5.91 | MiP (m3 · m−3) | 0.32 | 0.48 | 0.11 | Eworm (indv · m−2) | 0.8 | 0.6 | 0.12 |
| Mn (mg · dm−3) | 50 | 26 | 17.49 | WFPS | 0.64 | 0.84 | 0.14 | ||||
| B (mg · dm−3) | 0.18 | 0.27 | 0.10 | SWSC | 0.63 | 0.84 | 0.15 | SOC (g · kg−1) | 24.75 | 30.81 | 6.93 |
| Mg (mmolc · dm−3) | 22 | 45 | 14.86 | BD (Mg · m−3) | 1.25 | 1.27 | 0.02 | ||||
| Ca (mmolc · dm−3) | 68 | 106 | 27.16 | ||||||||
| K (mmolc · dm−3) | 2 | 6 | 4.10 | MaP (m3 · m−3) | 0.18 | 0.09 | 0.06 | ||||
| P (mg · dm−3) | 16 | 125 | 65.88 | ||||||||
| S (mg · dm−3) | 12 | 12 | 2.35 |
1 SD is the standard deviation of all indicators. ASI, aggregate stability index; B, boron; BD, bulk density; BS, bases saturation; Ca, calcium; CEC, electrical conductivity; Cu, copper; EWorm, oligochaetes; Fe, iron; H + Al, hydrogen + aluminium; K, potassium; Ksat, saturated hydraulic conductivity; MaP, macroporosity; Mdiver, Shannon’s diversity-index; Mg, magnesium; MiP, microporosity; Mn, manganese; Mrich, Margallef’s wealth-index; P, phosphorus; pH, ionic hydrogen potential; S, sulphur; SAC, soil aeration capacity; SD, standard deviation; SOC, soil organic carbon; SSI, structural quality index; SWSC, soil water storage capacity; TP, 33; WFPS, water filled pore space; WMD, weighted mean diameter; Zn, zinc.
Figure 2.
Mean values of the Forest and Banana systems for SQIs, considering the TDS, non-linearly interpreted, with integration weighted and additive, respectively, for SQI-1 (A) and SQI-2 (B) and contribution of soil functions in each one. Contribution of the soil indicators§ in the respective score functions (C) non-linear. ns: non-significant; *non-significant interaction; simple effects evaluated; **significant interaction; means followed by the same uppercase letter between functions and lowercase between systems do not differ by Tukey’s test (p < 0.05); i–availability and nutrient cycling; ii–availability of water and soil aeration; iii–support to biological activity; iv-sustaining plant growth; v–ability to resist degradation. ASI, aggregate stability index; BD, bulk density; BS, base saturation; CEC, electrical conductivity; SOC, soil organic carbon; SQIs, soil quality indexes, SSI, structural quality index; SWSC, soil water storage capacity; TDS, total dataset; TP, total porosity; WFPS, water filled pore space; WMD, weighted mean diameter. §Abbreviations are the same as in Table 3.
Figure 3.
Mean values of the Forest and Banana systems for SQIs, considering the TDS, linearly interpreted, with integration weighted and additive, respectively, for SQI-3 (A) and SQI-4 (B) and contribution of soil functions in each one. Contribution of the soil indicators§ in the respective score functions (C) linear. ns: non-significant; *non-significant interaction; simple effects evaluated; **significant interaction; means followed by the same uppercase letter between functions and lowercase between systems do not differ by Tukey’s test (p < 0.05); i–availability and nutrient cycling; ii–availability of water and soil aeration; iii–support to biological activity; iv-sustaining plant growth; v-ability to resist degradation. ASI, aggregate stability index; BD, bulk density; BS, base saturation; CEC, electrical conductivity; SAC, soil aeration capacity; SOC, soil organic carbon; SQIs, soil quality indexes, SSI, structural quality index; SWSC, soil water storage capacity; TDS, total dataset; TP, total porosity; WFPS, water filled pore space; WMD, weighted mean diameter.
§The full description of the indicators can be found in Table 3.
Figure 4.
Mean values of the Forest and Banana systems for SQIs, considering the MDS, non-linearly interpreted, with integration weighted, additive and additive, respectively, for SQI-5 (A) and SQI-6 (B) and SMAF (C) and contribution of soil sectors in each one. Contribution of the soil indicators§ in the respective score sector (D). ns: non-significant; *non-significant interaction; simple effects evaluated; **significant interaction; means followed by the same uppercase letter between functions and lowercase between systems do not differ by Tukey’s test (p < 0.05). BD, bulk density; MDS, minimum dataset; SOC, soil organic carbon; SMAF, Soil management assessment framework; SQIs, soil quality indexes; WFPS, water filled pore space; WMD, weighted mean diameter.
§The full description of the indicators can be found in Table 3.
Table 5.
Statistical parameters of the SQIs and SMAF for evaluating land use systems Forest and Banana.
| SQI | Mean | CV (%) | RMSE | Std. Error Mean | Confidence intervals | F test |
|---|---|---|---|---|---|---|
| SQI-1 | 0.73 c | 5.47 | 0.039 | 0.0150 | 0.126 | 0.40 ns |
| SQI-2 | 0.77 bc | 2.80 | 0.022 | 0.0079 | 0.069 | 0.00 ns |
| SQI-3 | 0.40 e | 9.44 | 0.037 | 0.0134 | 0.118 | 0.00 ns |
| SQI-4 | 0.55 d | 7.06 | 0.039 | 0.0172 | 0.126 | 1.80 ns |
| SQI-5 | 0.84 ab | 6.73 | 0.057 | 0.0263 | 0.182 | 2.46 ns |
| SQI-6 | 0.84 ab | 6.68 | 0.056 | 0.0261 | 0.180 | 2.48 ns |
| SMAF | 0.87 a | 1.92 | 0.017 | 0.0068 | 0.053 | 1.10 ns |
1 Means followed by the same letter in the columns do not differ by Tukey test (p < 0.05) between SQIs. ns: non-significant by F test (p < 0.05) between land use systems.
CV, coefficient of variation; RMSE, root mean square error; SMAF, soil management assessment framework; SQIs, soil quality indexes.