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INTRODUCTION
The inadequate management of the soils applied for many years due to the use of models with high inputs and an agricultural exploitation beyond their possibilities, have led to their deterioration. This is one of the most pressing difficulties in the context of the global food crisis. In this regard, Febles et al. (2018), refer that between five and seven million ha of fertile soil are lost, with 70% being affected by degradation, specifying it for the Red Ferralitic soils of the Mayabeque province, where 44.86% of them are currently very few productive.
In this sense, since 2012 it has been proposed that the protection of soils constitutes a problem of national security and sustainability (Cánepa et al., 2012), for which strategies must be established with technological procedures and a surveillance system for them. . This corresponds to the guidelines established in 2017, in the FAO 2030 agenda for the sustainable development of peoples, an aspect that is actively promoted in the year 2015 to 2024, considered as the international decade of soil. Despite these conditions, the monitoring of the impact of the operations carried out is not generalized, since the conventional protocols used are not always feasible to be applied in a systematic way, due to the high cost and laboriousness of some techniques, equipment and instruments required in the quantitative analysis of soil quality.
The circular or radial paper chromatography technique, whose method was introduced for the analysis of the health of soils by Pheiffer in 1933, has now been taken up for these purposes in countries such as the United States, Canada, Germany and spread throughout America. Latinos mainly in Mexico, Colombia and Brazil. The work carried out by Restrepo and Pinheiro have played a fundamental role, taking it to producers in rural areas due to its accessibility at the field level, as it does not require expensive analytical equipment and allows obtaining integrated information on physical and chemical properties. , biological and biochemical of soils Restrepo and Pinheiro (2015).
Despite this, the scientific literature for these purposes has not yet been generalized and the integration of radial cormatography in conventional soil quality monitoring protocols has not been established, which could make it a viable alternative to establish the systematic monitoring of their status during handling. The extension of this technique depends on having standard chromas of the materials to be studied and its greater effectiveness with the models that allow making predictions to be able to conduct the quantitative analysis of the soils for its more extensive study in the different scenarios. Aspect that despite the advantages of this technique may limit its establishment in conventional protocols for monitoring the state of soils, especially Cuban and Red Ferralitics, where there are no references in this regard.
In accordance with these antecedents, the present work was carried out with the objective of evaluating the viability of radial chromatography as a complementary analytical method for the systemic study of Red Ferralitic soils with different managements. For these purposes, it is necessary to obtain standard chroma for these soils supported by mathematical models that associate the qualitative information provided by chromas with conventional quantitative variables used in soil monitoring, which would allow the generalization of this technique in diagnosis integrator and preliminary of the state of the same.
MATERIALS AND METHODS
Characterization of the soils under study
Representative soils of the area were taken from the Mayabeque province. They were characterized by their morphological description, according to the latest version of the Cuban soil classification Hernández et al. (2015), as hydrated Red Ferralitic soils (FRh), which are correlated with the European databases of the World Reference Base (2008) and the North American Soil Taxonomy classification of soils (Soil Survey Staff, 2010) cited by Arteaga et al. (2018).
Three soils with different management were used: one with low anthropic activity (conserved) and two with high anthropic activity (with different degrees of degradation and management), according to the categories of degradation due to anthropic action established by Hernández et al. (2014). The management history and the location of the soils are reflected in Table 1, according to references provided by Reyes et al. (2014).
TABLE 1 Management history and location of the hydrated Red Ferralitic soils studied
| FRh soils | Management history | Location |
|---|---|---|
| FRh (M) | Fruit trees for more than 40 years without human intervention | San José de las Lajas |
| FRh (C) | Sugarcane cultivation for more than 40 years | San Nicolás de Bari |
| FRh (P) | FRh (P) Potato cultivation for more than 10 years (previously sugarcane) | San Nicolás de Bari |
The working procedure followed for the development of the research (analytical and chromatographic analysis), consisted of four fundamental parts: (I) Soil sampling: five samples were collected at each site at five points, at a depth of 0-20 cm, after being identified and separated, they were prepared by being dried in the shade and sieved. To obtain representative samples, they were quartered and homogenized; later the mass (g) was determined. (II) The quantitative characterization carried out in triplicate to the studied indicators, summarized in table 2 (the selection of the quality indicators for soil monitoring was based on those referred to in the specialized literature and the established norms, which are integrated in a methodology to evaluate the quality of Red Ferralitic soils, referred by Arteaga et al. (2016). (III) The qualitative characterization of the soils from the obtaining and interpretation of the chromas of each one and of the humic fractions of These, following the methodology used for chromatography on circular filter paper by Restrepo and Pinheiro (2015), consisting of nine main steps, reflected in Table 3. (IV) Establishment of partial multiple regression relationships between analytical studies and the qualitative.
TABLE 2 Indicators evaluated in the quantitative analyzes of soils
| Indicators | Method | Reference |
|---|---|---|
| pH at 25 ° C (pH meter PHSJ-3F) | Potentiometric (DDSJ-308A conductivity meter). |
|
| Electrical conductivity (EC), Total dissolved solids (TDS),% salinity | ||
| Basal respiration (RB) | CO2 evolution respiration method | ISO 16072 (2002) |
| Microbial biomass (MB-C) | Fumigation-extraction |
Vance |
|
Metabolic coefficient (qCO2) Determination of humic acids (AH) and fulvic acids (AF) (Relationship between AH/AF and AH/COS) |
Relationship between RB / MBC Wet oxidation (5 mL of soil extract with 10 mL of 1 mol / L K2Cr2O7 and 20 mL of concentrated H2SO4) Walker-Black, 1934. Colorimetric (RayLeigh UV 2601) (spectrophotometer at 600 nm |
|
TABLE 3 Methodology used for chromatography on circular filter paper
| Steps | Description (Restrepo y Pinheiro, 2015) |
|---|---|
| For the preparation of the watman filter paper n0.1, the center of it was drilled with a 2 mm diameter punch, then two holes are made with the tip of a needle, the first to mark the distance from the center to the path of the silver nitrate (AgNO3), the second for the final run. To obtain the wicks, the paper is squared so that there are squares of 2 cm2, which are rolled up to form them. | |
| Impregnation or sensitization of the filter paper using AgNO3 at 0.5%, the same operation is carried out until the solution reaches the second mark, the paper is removed and it is allowed to dry horizontally on a blotting paper, immediately they are placed inside a box dark. | |
| Preparation of the sample of 5 g of soil with 50 ml of 1% sodium hydroxide (NaOH) to dissolve, subsequently it is stirred circularly until achieving 49 turns and it is left to rest for at least six hours. | |
| Sample extraction for analysis: 50 mL of a freshly made 1% NaOH solution are added to 5 g of soil contained in an erlenmeyer flask. They are stirred for 15 minutes, then left to rest for an hour and the stirring operation is repeated until completely resting. | |
| Impregnation of the filter paper with the soil solution: let it run up to 6 cm. | |
| Identification of the chromatograms | |
| Drying or developing the chromatograms: once the paper is dry it is exposed indirectly to sunlight. | |
| Preservation of chromatograms when immersed in liquid paraffin (previously heated) to avoid deterioration of the development. | |
| Description and interpretation of the chromatograms: it was carried out based on the identification of the areas that compose it, taking into account the number, size or width and shape present in the image; in addition to the regularity or not of the shape, the harmony and integration of the areas, the presence of revealed colors, the formation of rings, clouds, spots, halos, forms of the terminations (edges) of the radiation obtained (Figure 1). |
This last aspect was valued with the cost analysis involved in the qualitative technique of chromatography on circular filter paper compared with the quantitative analyzes, taking the prices of available quantitative analyzes for the latter.
To determine the width of the chroma areas and the separation between the radiations, the caliper was used (Figure 1).
A cost study was carried out based on the expenditure from the qualitative analysis with radial chromatography compared to that produced in the quantitative analyzes performed, taking the prices of available quantitative analyzes for the latter (OMA, 2019).
The elaboration of the graphs and tables were carried out with the Microsoft Excel 2010 software of the Windows 10 Operating System. The results of the quantitative analysis were statistically processed with the Statgraphics Package XVII, using simple ANOVA and the Tukey multiple comparison test (p ˂0 , 05). In addition, in the chroma studies, the multiple regression association method and the coefficients of determination were used to descriptively establish the significance of the models; as well as the partial tests of significance of the independent variables.
In the study of the model, the dependent variables are: pH, electrical conductivity, total dissolved solids, salinity, basal respiration, microbial biomass, total organic carbon, relationship between HA / AF and HA / COS; and the independent variables: width of the chroma zones and the separation of the radiations in the same for each study soil. Two models were established for soils: (I) pattern (p) taken from mango. (II) agrogenic (a) of potato and sugarcane. For the latter they presented a coefficient of determination higher than that obtained in the models for potato and cane soils separately.
RESULTS AND DISCUSSION
Quantitative evaluations of physicochemical and biological properties of soils
The values of the physical-chemical properties are reflected in Table 4, these are indicative of a soil with very low anthropic activity for the FRh (M), while the values of the other two soils, FRh (C) and FRh ( P), suggest according to their management history that they have been under intensive cultivation for a long time and reflect a tendency to high anthropic activity.
TABLE 4 Physico-chemical properties of Red Ferralitic soils hydrated with FRh potato (P), FRh cane (C) and FRh mango (M)
| Soils | pH (H2O) | CE (mScm -1) | STD (g.L-1) | Salinity (%) |
|---|---|---|---|---|
| 6,30a | 12,24a | 7,34a | 0,71a | |
| 8,12b | 13,22b | 7,53a | 0,73a | |
| 8,15b | 13,24b | 7,54a | 0,73a | |
| 0.066 | 0.028 | 0.025 | 0.04 |
Different letters differ significantly from each other, Tukey p<0.05%
The pH value in the soil FRh (M) is close to the range of neutrality and for soils with high anthropic activity they reflect a basic character. The increases in pH values due to anthropic action are referred to irrigation water and the climatic change that has occurred that brings with it a recalcification of the soil horizons (Hernández et al., 2014). As a consequence, there is a tendency to increase the properties of electrical conductivity (CE) and total dissolved solids (TDS), without finding significant differences (p ˂0.05) between their salinity, when comparing these agrogenic soils with the most preserved mango.
These values are within the range established for preserved and degraded Red Ferralitic soils according to (Hernández et al., 2014) and those referred by Reyes et al. (2014) in the quantitative study of the properties of these hydrated Red Ferralitic soils.
Table 5 shows the characterization of the organic matter of the evaluated soils, the highest value of total carbon (total C) was recorded in the soil with low anthropic activity of mango FRh (M), in relation to those subjected to cultivation intensive potato and cane. Among the latter, significant differences were found (p <0.05), the value of the FRh (C) being more than doubled in relation to that found in the soil FR (P); where it can be seen that there has been a significant reduction in carbon retention, which suggests a greater anthropic activity with potato cultivation. These results correspond to what was expressed by (Hernández et al., 2014), regarding the loss of carbon content in soils with great anthropic activity and with those obtained for these soils by Reyes et al. (2014).
TABLE 5 Properties of the organic matter of the evaluated soils
| Soils | Ctotal (g∙C∙kg-1) | C/N | COS (g∙C∙kg-1) | C (AH/AF) | C (AH/COS) |
|---|---|---|---|---|---|
| FRh (M) | 74,37a | 7,34 a | 24,54 a | 1,22 a | 0,55 a |
| FRh (C) | 68,50 b | 6,76 b | 9,48 b | 0,91 b | 0,48 b |
| FRh (P) | 24,52 c | 2,42 c | 3,43 c | 0,17 c | 0,15 c |
| Es | 5,971 | 0,589 | 2,375 | 0,117 | 0,046 |
Different letters differ significantly from each other, Tukey p< 0.05%
Regarding soluble organic carbon (SOC), higher values are also observed with significant differences between the FRh (M) management with respect to the rest of the agrogenic soils, suggesting losses of carbon reserves. Which can be found between 30% and 75%, as indicated by (Hernández et al., 2014) for FR soils as a result of intensive agricultural exploitation. These authors state that in Cuba SOC losses in Ferralitic soils have been high in the surface horizons (0-20 cm), due to intensive use with crops with few roots such as sugarcane and potatoes.
Regarding the AH / AF and AH COS ratio shown in Table 5, it is observed that the soil FRh (M) presented the highest values, differing significantly from FRh (C) and FRh (P), the decrease in the latter. These indices suggest the decrease in the quality of the organic matter present in the soil mango> cane> potato (Santos & Camargo, 2008). Similar patterns show the values of the C / N ratio, indicating a loss in stability in these soils, fundamentally for the soil with potato.
The biological properties evaluated in the soils (Table 6) confirm the previous results, the basal respiration evaluated in these soils differ significantly between mango and sugarcane and potato; the microbial biomass marks more the differences between these soils, even between the agrogenic ones, where a marked loss of the present microbial biomass is observed.
TABLE 6 Biological properties of the evaluated soils
| Soils | CR (mgCO2.kg1∙h-1) | BM (mg∙kg-1) | qCO2(h-1) |
|---|---|---|---|
| FRh (M) | 186,38 a | 35,55 a | 0,0052 c |
| FRh (C) | 160,34 b | 6,56 b | 0,0244 b |
| FRh (P) | 174,42 b | 2,81 b | 0,0620 a |
| Es | 4,899 | 3,961 | 0,006 |
Different letters differ significantly from each other, Tukey p< 0.05%.
Even more significant, the differences between soils are presented in the metabolic coefficient, it tends to be higher in soils FRh (C) and FRh (P) with respect to FRh (M), indicating a tendency to increase carbon expenditure in the respiration per unit of microbial biomass for the most degraded, due to a higher activity product of the mineralization process, which suggests a microbial stress as a consequence of soil management (Santiago et al., 2018), being referred to as a sensitive indicator to the changes produced during intensive cultivation, being very useful to estimate the early edaphic quality of a soil (Arteaga et al., 2018).
Qualitative characterization of the soils under study
When observing the representative images of each FRh soil under different management (Figure 2), it is possible to appreciate the marked differences between them, mainly between the soil with low anthropic activity, FRh (M), with those with high anthropic activity: FRh (C ) and FRh (P), and even between the latter with each other.
FIGURE 2 Chroma images for all the replicas made of the hydrated Red Ferralitic soils with different handling in the order of mango FR (M) - cane FR (C) - potato FR (P) and their humic fractions.
The analysis of the chroma images can be synthesized in the following elements:
(I) The chroma for the mango soil (Figure 3), is interpreted as having a good, non-compacted structure, valued in the central Z. (ZC) with a creamy color that fades to be integrated into the next area and the rest with each other (ZC, ZM, ZP, ZE); the intermediate zone (ZM) is seen with a light brown collation combined with the following zone of organic or protein matter (ZP), which indicates the mineral diversity associated with organic matter with a good presence and available for plants and integrated Due to the microbiological activity, it is manifested with golden colorations. The radiations and undulations in the enzymatic Z. reveal a good enzymatic and protein activity, according to what was proposed as desired for soils that have not undergone drastic changes in their composition (Restrepo and Pinheiro, 2015), which corresponds to the history of management of this soil with more than 40 years without anthropic intervention with the presence of fruit trees in addition to the results of the physicochemical and biological properties previously analyzed (Tables 4, 5 and 6).
(II) In the chroma for sugarcane and potato soils (Figure 3), they suggest that they have been treated with high doses of fertilizers and mechanization, the ZC are wider and white in color that is integrated into the next zone of homogeneously, which indicates the lack of structure and the effect of the use of a large amount of chemicals in the soil, mainly, although there may have also been application of manure; inputs that have been applied in high doses established in the fertilization package for potato production in Cuba (Minag-Cuba, 2016).
FIGURE 3 Analysis of the central and internal zones in the chromatographic images of the FRh soils of mango (M), cane (C), potato (P).
The mineral zone (ZM), in the cane soil begins to be defined and less integrated with a darker coloration that intensifies in the potato soil, as well as its broader amplitude (even less integrated), with smooth, defined terminations and not formed (Figure 3). In the chromas of these soils, a mineral zone that is blocked is interpreted, evidencing the null interaction with the organic matter zone, indicating the absence of transformation of the minerals (Restrepo and Pinheiro, 2015).
The zone of organic or protein matter (ZP) that represents organic matter (Figure 3), reveals the balance that exists between the mineralization and humification processes, shows the ideal presence in the mangal, however, for the soil of cane results in a slightly dark coloration, which suggests the existence of a slow decomposition process, where mineralization begins to prevail. The total C contents and the humified C / SOC ratio support this information obtained, such as where soil degradation corresponds to carbon losses because mineralization prevails over humification, which decreases according to Santiago et al. (2018), in the mango-cane-potato sense.
(III) The analysis of the quality of the soil organic matter, from the chromas made to the humified fractions (humic acids AH and fulvic acids AF), is clearly reflected in the chroma images (Figure 4), it corresponds with the values obtained in the relation of the C of the HA and the COS, evidenced by the higher values for the mango, where said chroma reflects a greater stability in the humified fractions. In the case of agrogenic soils, it is shown to be more blocked, fundamentally for potatoes, reflected with the dark brown halo present in the potato chroma.
(IV) The ZE enzymatic zone (Figure 3 and 4), shows the humification processes and the presence of nutrients assimilated by the plants in the mangal, the shape of the toothed terminations and the shadows between them show the high availability of these and the very dark brown color also indicates humification processes. For sugarcane and potato soils, it lacks shape with the absence of terminations, which suggests slow humification processes, which may be scarce, surpassed by the mineralization process, which shows limited biological activity.
FIGURE 4 Chromatographic images of the humic (HA) and fulvic (AF) fractions of the FRh soils of mango (M), cane (C), potato (P).
(V) This can be complemented by analyzing the radiographic contrast shown in Figure 4, with respect to the mangal floor. In this, the radial formation starts from the center towards the external zones (Figure 3 and 4), it is shown branched in the form of pens; This reveals the diversity of nutrients and active microbiology present in the soil for mango, the lumpy textures are a symptom of organic aggregates and abundant flocculation, which is desirable for a soil of adequate quality (Medina et al., 2018). However, the cane and potato chromatograms do not present a radial formation, like the mangal, which shows the lack of total equilibrium in these soils due to their management. The characteristics of the cane and potato chromatograms correspond to soils destroyed by highly soluble fertilizers of synthetic origin, according to Restrepo and Pinheiro (2015) and this is indicated by the quantitative analysis carried out on these soils, shown in tables 4, 5 and 6.
The evaluation of the physical-chemical and biological properties in the hydrated Red Ferralitic soils showed notable differences between the management received, conservation and high anthropic activity, where between these two sugarcane (C) and potato (P) soils differences are observed. significant among them, being more significant the degradation for the potato soil that was clearly evidenced in modifications reflected in the images of the chromas, indicating the selectivity, specificity of this method to evaluate in a previous and integrated way the state of the soils at level of organic matter, minerals and their microbiology, providing integrative information.
Models to predict quantitative variables of the state of agricultural soils
The most significant models from the descriptive point of view were selected, from the determination coefficients R2, in them the most significant variables in each model obtained from the partial analysis of the independent variables stand out, being generally the zones central (ZC), enzymatic (ZE) and organic or protein matter (ZP) which contribute the most to the variables dependent on the quantitative indicators analyzed.
| REGRESSION MODELS (Sig: 0.0000 ***) (Est: 95%) | |||||
|---|---|---|---|---|---|
|
p: standard soil (FRh Mango) a: Agrogenic soils (FRh cane and potato) Ind. Quantitative: STD: total dissolved solids, C: carbon, HA: humic acids, AF: fulvic acids. COS: soil organic carbon. OM: organic matter. CE: electrical conductivity. TOC: total organic carbon. BM: microbial biomass. Basal soil respiration (CR). Metabolic coefficient (qCO2). Ind. Qualitative: WIDTH OF THE CHROME AREA AND SEPARATION BETWEEN THE RADIATIONS | |||||
| Zona(Z) | Central (ZC) | Mineral (ZM) | Materia Orgánica o Proteica (ZP) | Enzimática (ZE) | Separación entre las radiaciones (SRa) |
| Combinación de las Z. mineral proteica (ZM + ZP) | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase of the Central Z., Mineral Z. with the MO or protein Z., Enzymatic Z. and in the separation of the Radiations, the pH value increases by 0.5081, 0.0561, 0.034927, 0.0936, 0.2733 units. in H2O respectively. For each unit of increase of the Z. Central, Z. Mineral, Z. MO or protein, Z. Enzymatic and in the separation of Radiations increases by 0.1944, 0.0799, 0.0216, 0, 1144, 0 .0522 units the pH value in H2O respectively. | |||||
|
Models: Yp ( Ya ( rediction: For each unit of increase of the Central Z., Mineral Z. with the MO or protein Z., Enzymatic Z. and in the separation of the Radiations, the value of the CE increases by 0.2227, 0.0878, 0.0532, 0.1852 units respectively. For each unit of increase of the Z. Central, Z. Mineral, the Z. MO or protein, Z. Enzymatic and in the separation of the Radiations increases in 1998, 0.2168, 0.8796, 0.1213, 0.2222 units the value of the CE respectively. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in the Central Z. the TOC value increases by 2.7193 U and in the mineral Z. with protein, and between radiations it decreases by 2.2012 and 0.8968 units respectively. For each unit of increase of the Central Z., Mineral Z. with the Z. MO or protein, Z. Enzymatic and with the separation of the Radiations increases by 0.0048, 0.0022, 0, 0.0014, 0, 0021, 0.0010 units the TOC value respectively. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in the Central Z. the value of the C / N ratio increases by 2.1392 U and in the mineral Z. with Protein and between radiations they decrease by 2.5522 and 1.4837 units respectively. For each unit of increase of the Z. Central, Z. Mineral, Z. MO or protein and Z. Enzymatic decreases by 0.0523, 0.0134, 0, 0.0214, 0.0433 units the COT value respectively and increases by 0.0131 u with the separation of the Radiations. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in the Z. Central, Z. Enzymatic and in the separation of radiation, the value of Humic Acids increases by 5.9295, 1.0222 and 1.4960 units respectively and in the mineral Z. with protein decreases by 1.01196 U . For each unit of increase in the Z. Central, Z. mineral, Z. protein, Z. Enzymatic and in the separation of radiation, the value increases by 3.8897, 2.3456, 0.0213, 0.5454 units. of Humic Acids respectively. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase of the Z. Central, Z. Protein, Z. Enzymatic and the separation between the Radiations increases in 7.3643, 0.2438, 1.1708, 0.3729 units the value of AH + AF and in the Z. mineral decreases in 2.9801 units respectively. For each unit of increase in the Z. Central, Z. Proteic, Z. Enzymatic and the separation between the Radiations increases by 5.8900, 0.5673, 0. 5667, 0.2138 units the value of AH + AF and in the mineral Z. decreases by 4.5432 units respectively | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in the Z. Central, Z. Mineral, Z. Enzymatic and in the separation of radiation, the microbial biomass increases by 32.2203, 5.8494 and 4.5610 U respectively and in the Z. Mineral decreases 8.6344 U. For each unit of increase of the Z. Central, Z. Enzymatic and in the separation of the radiations increases in 23.4335, 6.8901, 4.9980, 3.1278 U the microbial biomass respectively. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in Mineral Z. and Enzymatic Z. the value of basal respiration decreases by 12.6022 and 4.8595 U, respectively, for each unit of increase in the separation between Radiations, CR increases by 14.2398 U. For each unit of increase in Mineral Z. and Enzymatic Z. the value of basal respiration decreases by 69.7890 and 10.3456 U, respectively, for each unit of increase between Radiations, CR increases by 12.8907 U. | |||||
|
Models: Yp ( Ya ( Prediction: For each unit of increase in Mineral Z. and radiation separation, the Metabolic Coefficient increases by 0.0293 and 0.0028 U respectively, for each unit of increase in Central Z. and Enzymatic Z. decreases 0.0172 and 0.0018 U. For each unit of increase in Mineral Z. and radiation separation, the Metabolic Coefficient increases by 1.1225 and 1.1213 U, respectively, for each unit of increase in Central Z. and Enzymatic Z. 1.2390 decreases. and 1.8790 U. | |||||
With the proposed regression models it is possible to predict from the dependent variable chromas such as pH, total organic C content, C / N ratio, CE, humified soil fractions through the indicators: AH, AH + AF and soil biological activity such as microbial biomass and metabolic coefficient, which will support the interpretation of the results and introduce this method in the systemic analysis for soil quality monitoring.
With the application of radial chromatography, standard chromatograms were obtained with the respective multiple regression models that may be useful in future studies of hydrated Red Ferralitic soils with different managements to predict the essential physical-chemical and biological properties to be evaluated and thus suggest the procedure to follow to carry it out analytically. This can make systemic monitoring of them more viable due to the decrease in the complexity of the methodology followed for its realization with time savings and in the economy of the process.
This last aspect was evaluated through the cost analysis involved in the qualitative technique of chromatography on circular filter paper compared to quantitative analyzes. The economic valuation was made from the average cost of five replicates of chromatographic analysis on circular filter paper is $ 23.40 USD, with which the analysis of 13 variables can be performed ($ 1.98 per variable). In contrast, quantitative analyzes are quoted in a range of $ 95.00, cost $ 7.31 / variable. This demonstrates the feasibility of the method not only because of its simplicity, which allows it to be applied in studies "in situ" in production systems, but also because of the low economic costs involved with its use.
From these results a work protocol is derived for the systemic monitoring of soils with different management during their exploitation by introducing radial chromatography to it, which would contribute to maintaining the sustainability of this important natural resource during its use.
CONCLUSIONS
Radial chromatography turned out to be a fast, functional, integrative and economical method that allows it to be adapted to the existing conditions in situ to predict indicators that lead to complement the quantitative study of Red Ferralitic soils with different managements, making systemic monitoring more viable for diagnose its quality in making adequate agricultural decisions; which would lead to establish an autonomous management of soil knowledge during its management, contributing to its sustainability.
