Soil quality and soil fertility status in major soil groups at the Tombel area, South-West Cameroon (2024)

3.1. Data collection and analyses

Based on a previous study by (Nguemezi, 2019), a field campaign using hand auger and hand dug bore holes was carried out in this study area to collect topsoil samples from different soil groups based on parent rocks and landscape position. Ninety-nine composite soil samples were randomly collected on the A surface horizon (topsoil) of different soil groups for physicochemical analyses. Undisturbed soil samples were also collected for bulk density. Of the one ninety-nine soil samples collected, seven are collected on dystric vitric Andosols (melanic) > 500 m asl, twenty-four on dystric vitric Andosols (melanic) < 500 m asl, ten on umbric Andosols (fragic), sixteen on umbric pisoplinthic Plinthosols (haplic dystric), eleven on fragic Umbrisols (arenic), five on dystric fragic Cambisols (humic), nine on rhodic Acrisols (cutanic humic), four on leptic fragic Umbrisols, and thirteen on mollic Ferralsols (eutric humic). Using an Edelman auger, under each soil group, the composite samples were collected at a depth of 0–25 cm. These soil samples were air-dried before grinding and sieving and then used for routine laboratory analysis. Physical analyses included bulk density (BD), and particle size distribution. The bulk density (BD) was obtained using the method of Koppeki cylinder (Blake, 1982). Particles size was determined by the hydrometer method (Day, 1965; Boverwijk, 1967). Chemical analyses included: organic carbon (OC), total nitrogen (N), available P, exchangeable cations (Ca, Mg, K, Na); cations exchange capacity (CEC), exchangeable Al and acidity (pH). Soil organic carbon was determined by chromic acid digestion and spectrophotometric analysis (Heanes, 1984). The total N was determined from a wet acid digest (Buondonno etal., 1995) and N analysed by colorimetric analysis using a UV-VIS spectrophotometer (Anderson and Ingram, 1993). The available P was extracted using the Bray II procedure and the resulting extract was analyzed using the molybdate blue procedure described by (Murphy and Riley, 1962). The cation exchange capacity (CEC) was obtained at pH 7 using ammonium acetate method. Exchangeable cations (Ca, Mg, K and Na) were extracted by ammonium acetate at pH7 and analyzed by flame atomic absorption spectrophotometry using the AAS (Mehlich, 1984). Soil acidity (pH) was determined in a 1:2.5 soil suspension with deionized water.

3.2. Computation of soil fertility parameters

Most soil fertility studies have been carried out in relation with major agronomic crops where fertilizer applications led to increased crop production (Dabin, 1961; Waller etal., 1975). This is evaluated on the basis of physicochemical properties and computed soil fertility parameters. The physicochemical properties commonly used are: OM, N, C/N, available P, Ca, Mg, K, Na, exchangeable Al, S (exchangeable sum of bases), CEC, textural class (TC) and bulk density (BD). These soil properties are used to calculate soil fertility parameters such as: sum of exchangeable cations (S); Forestier index (IF), soils aggregate stability index (ISS), soil sealing index (IB), and Kamprath index (m). S is obtained by summing up exchangeable cations which are: Ca. Mg. K and Na.

Soil aggregate stability index (ISS) relating soil resistance to external disruption forces was assessed using the following Pieri's formula Eq. (1) (Pieri, 1992):

with OC. the soil organic carbon; L. the silt fraction; and A. the clay fraction. An ISS>9% indicates stable structure, 7% < ISS≤9% indicates low risk of structural degradation, 5% < ISS≤7% indicates high risk of degradation, and ISS≤5% indicates structurally degraded soil.

Soil sealing index (IB) related to the risk of soils erosion and compaction was estimated using Remy formula Eq. (2) (Remy and Marin-Laflèche, 1974):

with C equal to 0.2 x (Ph–7); Lf. the fine silt; Lg. the coarse silt; A. the clay; and OM. the soil organic matter content. An IB < 1.4, indicates soils without risk of thrust and without risk of erosion; 1.4 < IB ≤ 1.6, indicates soils with a low risk of erosion; 1.6 < IB ≤ 1.8, indicates soils with a medium risk of erosion; IB ≥ 1.8 indicates soils with high risk of erosion.

Forestier index (IF) was assessed using the following formula Eq. (3) (Forestier, 1960):

with S. the sum of exchangeable cations; A. the clay fraction; and Lf. the fine silt fraction. An IF < 1.5, indicates soils with low nutrient reserves, and an IF > 1.5 indicates soils with good nutrient reserves.

Aluminium toxicity is defined by the Kamprath index Eq. (4) (Kamprath, 1970), for determining the degrees of toxicity of exchangeable aluminium. It is the ratio

Al³⁺ = exchangeable aluminium in meq:100g of soil, and S = sum of exchangeable bases in meq:100g of soil. If m < 20%, indicates soils with aluminium toxicity; 20 < m (%) < 50, indicates soils with high aluminium toxicity; and m > 50 %, indicates soils with very high aluminium toxicity.

In addition to the other soil fertility parameters, the sum of exchangeable bases (S), and the cation exchangeable capacity (CEC) were grouped into classes, allowing these results to be appreciated. When S < 2meq/100g, it indicates very low values; 2 < S (meq/100g) < 5, indicates low values; 5 < S (meq/100g), it indicates average values; 10 < S (meq/100g) < 15, it indicates high values; S > 15 meq/100g, it indicates very high values (Beernaert and Bitondo, 1992). When the CEC <5 meq/100g, indicates very low values; 5 < CEC (meq/100g) < 10, indicates low values; 10 < CEC (meq/100g) < 25, indicates average values; 25 < CEC (meq/100g) < 40, indicates high values; and CEC >40 meq/100g, indicates very high values (Beernaert and Bitondo, 1992).

3.3. Analyzing soil fertility parameter equilibriums

Some balances have been established between the physicochemical soil properties such as textural class, pH and nutrient concentrations, reported on binary and ternary diagrams according to models used by FAO-ISRIC, 2014, Forestier (1960), Dabin (1961) and Martin (1979). The textural diagram of FAO shows different textural classes of soils in relation to their agronomic interest. The triangular diagram of Dabin (1961) indicates the poles of relative richness in a given cation in the equilibrium of the cationic balance (Ca/Mg/K). Soil pH is a measure of the concentration of free H⁺ protons in the soil solution. It is a very important parameter that directly influences the chemical reactions in the soil and the availability of nutrients in form that can be assimilated by plants. Soil pH, a reflection of the physicochemical conditions of the soil solution, has a direct effect on the bioavailability of nutrients through solubilization and insolubilization phenomena specific to each element (Merelle, 1998). K and Mg, and Ca and Mg, in the absorbing complex exhibit antagonisms or synergies. The binary diagram of Dabin (1961) makes it possible to highlight these antagonisms or synergies between the Ca, Mg and K cations in the soil. These cations play plastic and physiological roles in soils (Merelle, 1998). Soil pH is closely related to the sum of bases present in the soil (Meyim-Dayombo, 2000). Indeed, pH being a measure of the H⁺ concentration in the soil, the more H⁺ there is, the less it can have cations such as Ca²⁺; Mg²⁺; K⁺; and Na⁺ in soil. So, the more acidic the soil, the less it contains bases. Soil pH reflects the state of saturation in bases of the absorbing complex.

3.4. Computation of soil quality index (SQI)

Calculating soil quality consists in combining the physicochemical and biological properties of the soil that are easily changeable in response to variations in soil conditions (Blake, 1982; Brejda etal., 2000). The different steps to calculate the SQI have described in the works of Ngo-Mbogba etal. (2015). With reference to previous work in in Southern Cameroon and elsewhere, ten indicators were selected for this study (Ngo-Mbogba etal., 2015). They are: OM, pH water, CEC, Ca, Mg, K, C/N ratio, available P, exchangeable Al and N. This dataset of indicators focused more on soil chemical parameters because some authors (Yemefack etal., 2006; Ngo-Mbogba, 2009) reported their utmost important influence and manifestation on crops growth characteristics.

Each indicator was normalized by Ngo-Mbogba etal. (2015), and the SQI parameter was calculated by the method described by Eq. (5) (Andrews etal., 2002).

W is the normalized indicator; X is the indicator score; SQI is the soil quality index; i is a soil property and n, the number of soil properties.

3.5. Statistical analysis

Descriptive statistics were calculated on 25 variables because some soil properties are less dynamic than other. Nine variables cited in section 3.4, showing significant variation were then selected for further analyses. One-way ANOVA was performed to assess the influence of different soil groups on soil chemical properties (OM, Bray P, Ca, Mg, K, Al). The separation of means between the different soil groups was made using the Tukey's test. The most appropriate soil quality indicators have been selected by applying the principal component analysis. Excel 2013 and R (R, 2012) were used to perform these analyses.

4.1. Summary statistics

The statistics of the 25 soil variables obtained on the different soil groups are summarized in Table1. Most of them show a positive skewness varying between 0.19 and 5.68; meaning that the mean is usually greater than the median, which is also greater than the mode; except for sands, silts, sealing index (IB), and base saturation (S: CEC) showing negative skewness varying between -0.04 and -1.23. Those variables with skewness less than -1 or greater than 1, are skewed meaning that the right tail of the distribution is longer than the left for positive skewness and the reverse for negative skewness. The kurtosis is also highly variable, with some values greater than 1 or less than -1. This departure of the skewness and the kurtosis for zero means that most of these variables have a slight abnormal distribution. Fortunately, ANOVA is not a very sensitive to moderate deviations from normal, because simulations studies, shown that the rate of false positives is not very affected by this violation of the normality assumption (Lix etal., 1996).

Except for Al, pH and C/N with of coefficient of variation (CV%) around 15%, all other variables have high to very high CV, meaning that there is a high variability of soil parameters and SQ (soil quality) within soil groups in Tombel area. Computed indices such as IB (from Particle size, OM, pH) and IF (Particle size and Exchangeable bases), derived from the combination of several parameters showed the highest rate CV, following by exchangeable bases and their derived ratios. These CV seem to be controlled by a multiplying effect from various input parameters.

4.2. Variability of soils properties and soils fertility parameters across soils groups

From summary statistics of the 25 variables from 8 soil groups, 12 variables identified as the most variable (OM, N, C/N, CEC, Sand, Clay, Silt, ISS, m, IF, (Ca + Mg)/K) and BD), were used for ANOVA and mean separations (Tukey's HSD). The results presented in Table2 show a great variability of significantly differences from one soil to another.

The organic matter content showed a significant difference between dystric vitric Andosols (melanic) above 500m high and other soil groups, namely umbric Andosols (fragic), mollic Ferralsols (eutric humic), umbric pisoplinthic Plinthosols (haplic dystric), fragic Umbrisols (arenic) and rhodic Acrisols (cutanic humic). This significant difference between dystric vitric Andosols (melanic) above 500m high and other soil groups can be explained by the double protection between the latter and free aluminum, as reported in many Andosols (Tématio, 2005). On the other hand, the slight difference between dystric vitric Andosols (melanic) at different altitude may be due to altitude effect (Tsozué etal., 2019) or to human activities more pronounced in lower altitude. CEC also shows a significant difference between several soil groups. Soils with higher CEC have an important nutrients reserve (high IF). This important nutrients reserve and high CEC are associated with high levels of OM in these soils (Omoko, 1996; Yerima Bernard and Van Ranst, 2005).

The structural stability index (ISS), sand and clay showed a significant difference between several soil groups. The good structural stability of dystric vitric Andosols (melanic) above 500m high is assigned to high levels of OM and the clay fraction which favour the aggregation of soil particles (Lal, 1994). The combination of clays and humic compounds in the clay-humic complex results in the formation of aggregates, basic elements of soil structure in the upper horizons. These colloidal lumps contribute to the formation of an airy structure by allowing moreover a better retention of water in soils.

4.3. Variability of fertility parameters equilibriums across soils types

The FAO Textural Diagram based on the Tombel soils data (Figure2a) defines two soil texture groups: clayey textured soils and balanced textured soils. Soils with clayey texture are dystric vitric Andosols (melanic) below 500 m high, umbric Andosols (fragic), umbric pisoplinthic Plinthosols (haplic dystric) and mollic Ferralsols (eutric humic). Balanced textured soils include dystric vitric Andosols (melanic) above 500 m high, fragic Umbrisols (arenic), dystric fragic Cambisols (humic) and rhodic Acrisols (cutanic humic).

The triangular diagram of Dabin (1961), adapted to the Tombel soils (Figure2b), indicates that all the soils are close to the optimal equilibrium, except the umbric Andosols (fragic), showing K deficient. In reference to acidity, the Dabin (1961) diagram has defined three classes of soil fertility (Figure2c): poor fertility soils, average fertility soils and good fertility soils. Soils showing poor fertility have a pH between 4.75 and 5.1. These include umbric pisoplinthic Plinthosols (haplic dystric), dystric vitric Andosols (melanic) below 500 m high, umbric Andosols (fragic), dystric fragic Cambisols (humic) and mollic Ferralsols (eutric humic). They show no N deficiency, except for umbric Andosols (fragic). Soils showing average fertility have a pH between 5.1 and 5.5, with no N deficiency, except for fragic Umbrisols (arenic). They include fragic Umbrisols (arenic), rhodic Acrisols (cutanic humic) and leptic fragic Umbrisols. Soil showing good fertility is dystric vitric Andosols (melanic) above 500m high with have a pH greater than 5.5.

According to Martin's binary fertility plot (1979), all the soil groups are above the Mg and Ca deficiency thresholds (Mg = 0.3 meq:100g) and Ca (Ca = 1 meq:100g) (Figure2f). This diagram groups the soils of Tombel plain into two broad classes: soils balanced in Ca and Mg (1 < Ca:Mg < 5) and soils deficient in Mg relative to Ca (Ca:Mg > 5). The class of balanced soils in Ca and Mg includes umbric Andosols (fragic), umbric pisoplinthic Plinthosols (haplic dystric), leptic fragic Umbrisols, dystric fragic Cambisols (humic), rhodic Acrisols (cutanic humic) and mollic Ferralsols (eutric humic). Deficient soils in Mg are dystric vitric Andosols (melanic) and fragic Umbrisols (arenic).

The balance between the saturation rate (S: CEC) and acidity (pH) makes it possible to highlight the impact of pH on the evolution of exchangeable bases in the soil. The related diagram (Figure2d) groups the Tombel plain soils into two broad classes: soils with a low base saturation (S: CEC ≤20%) and soils with a medium base saturation (20 < S: CEC (%) <50). The class of soils with low base saturation rate includes only mollic Ferralsols (eutric humic). The soil class with average saturation level includes all the other soils groups.

4.4. Soil quality index of different soils groups

4.5. Soils fertility status

The statistical analysis of the physicochemical properties, the fertility parameters and the soils quality index as well as the balances between these parameters made it possible to evaluate the current state of fertility of the identified soil groups in the Tombel plain; by grouping them into fertility classes according to (Quemada and Cabrera, 1995) modified, which according to the limitations in question and their degree of intensity, defined the following classes (Table3):

• ➢

  Class I: soil characteristics are not present or present only weak limitations;

• ➢

  Class II: soil characteristics do not have more than 3 moderate limitations possibly associated with low limitations;

• ➢

  Class III: soil characteristics have more than 3 moderate limitations possibly associated with a single severe limitation;

• ➢

  Class IV: soil characteristics have more than one severe limitation.

Table4 shows four groups of soils in Tombel area according to their fertility level.

This is:

• ❖

  Class I grouping soils with a very good fertility level. These correspond to dystric vitric Andosols (melanic) (ANdvm) above 500 m high; with low limitations in available P.

• ❖

  Class II groups soils with good fertility level. These are dystric vitric Andosols (melanic) (ANdvm) below 500 m high and leptic fragic Umbrisols (UMlf). The ANdvm below 500 m high has low limitations in available P, K and S. The UMlf has moderate limitations in available P and soil acidity (pHw).

• ❖

  Class III includes soils with average fertility level. They are dystric fragic Cambisols (humic) (CMdfh), rhodic Acrisols (cutanic humic) (ACrch), fragic Umbrisols (arenic) and mollic Ferralsols (eutric humic) (FRmeh). The CMdfh have moderate limitations in available P and K, and in some extend in S; they also have a severe limitation in pHw. The ACrch have moderate limitations in available P, K and CEC. They present a severe limitation in S content. The UMfa have low limitations in K and S, and severe limitations in available P and Soil Quality Index (IQS). The FRmeh have moderate limitations in available P and bases saturation; and severe limitations in pHw and CEC. Bringing a calcium amendment makes it possible to promote the availability P and Mg, for the plant; to promote the installation of roots. Maintenance liming which consists of making a contribution every 3–4 years to maintain a sufficient pHw. It will be necessary to estimate the quantities according to the exports realized on the parcel (ex: mowing) and the acidifying action of the mineral fertilizers if they are brought regularly.

• ❖

  Class IV includes poor fertility soils. These are umbric Andosols (fragic) (ANuf) and umbric pisoplinthic Plinthosols (haplic dystric) (PLuphd). Both soils have low limitations in available P and K; and severe limitations in Sealing Index (IB) and soil aggregate stability index (ISS). This class of soils with poor fertility require several years of tillage for the restoration of its properties. To restore these properties, in addition to recommendations for the improvement of soils with medium fertility, several solutions are proposed. Farmers must practice the fallow system after cultivation to maintain soil fertility; to alternate the types of cultures; and promulgate new soil nutrient supply mechanisms from inputs (composts, chemical fertilizers, mineral fertilizers ...). Improve the physical fertility of soils, by: adding soil cover by plant residues, and vegetation cover, which leads to a decrease in the volume and runoff but also maintains the porosity on the surface; stimulate soil biological activity, consists of multiplying earthworms, improving soil life and improving of deep drainage; and the increase of the level of humus on the surface leads to the increase of the structural stability and the decrease of the erosive risk. Rectification liming, which consists of bringing a significant quantity over several consecutive years to correct a low pHw. The inputs are made in small quantities at a time to raise the pH slowly so the mineral elements may become blocked.

The very good fertility soils represent 66km² (3.79%). The good fertility soils cover an area of 506km² (29.04%). An average fertility soils cover an area of 787km² (46.49%). And the poor fertility soils represent 375km²; (21.46%) (Figure4).

Analysis of the fertility status of each soil group shows that soils with good and very good fertility status are characterized by high to very high Soil Quality Index (SQI). This can be explained by the significant nutrient reserves (IF > 1.5) and the high levels of organic matter (OM> 4.2%). Soils with average fertility status are characterized by a mean Soil Quality Index (SQI); this translates their low wealth into nutrients. On the other hand, soils with poor fertility status are characterized by the low and average SQI. The poor fertility status of these soils is related to physical parameters that have severe limits (IB and ISS), because the soil quality index rather express the chemical richness of soils in nutrients (chemical properties of soils).

Author contribution statement

C. Nguemezi, P. Tematio, M. Yemefack, D. Tsozue, T.B.F. Silatsa; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Competing interest statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

• Al-Zubaid I.A., Yanni S., Bashour I. 2008. Potassium Status in Some Lebanese Soils. [Google Scholar]
• Anderson J.M., Ingram J.S.I. second ed. CAB InternationalThe Cambrian News; 1993. Tropical Soil Biology and Fertility: a Handbook of Methods. s.L. [Google Scholar]
• Andrews S.S., Karlen D.L., Mitchell J.P. Acomparison of soil quality indexing methods for vegetable production systems in Northern California. Agric. Ecosyst. Environ. 2002;(90):25–45. [Google Scholar]
• Beernaert F., Bitondo D. Cameroun; 1992. Sample and Pratical Methods to Evaluate Analytical Data of Soil Profiles. s.n. [Google Scholar]
• Blake G.R. America Society of Agronomy and Crop Science Society of America; 1982. Bulk Density, Soils Analysis. [Google Scholar]
• Boverwijk A. Particle size analysis of soils by means of the hydrometer method. Sediment. Geol. 1967;(1):403–406. [Google Scholar]
• Brejda J.J., Moorman T.B., Karlen D.L., Dao T.H. Identification of regional soil quality factors and indicators: I. Central and southern high plains. Soil Sci. Soc. Am. J. 2000:2115–2124. (64) [Google Scholar]
• Buondonno A., Rashad A.A., Coppola E. Buondonno, Comparing tests for soil fertility. 11. The hydrogen peroxide/sulfuric acid treatment as an alternative to the copper/selenium catalyzed digestion process for routine determination of soil nitrogen-Kjeldahl. Commun. Soil Sci. Plant Anal. 1995;(26):1607–1619. [Google Scholar]
• Dabin B. Association française d'Etude du Sol (AFES); 1961. Les Facteurs de Fertilité des Sols des Régions Tropicales en Cultures irriguée. Bull, s.L. [Google Scholar]
• Day P.R. Particle fractionation and particle size nanlysis. In: Black C.A., editor. Methods of Soil Analysis, Part I. Agronomy n°9. Am. Soc. s.l.; Madison, WI: 1965. [Google Scholar]
• Demirağ Turan İ., Dengiz O., Özkan B. Spatial assessment and mapping of SOIL QUALITY INDEX for desertification in the semi-arid terrestrial ecosystem using MCDM in interval type-2 fuzzy environment. Comput. Electron. Agric. 2019 [Google Scholar]
• Dengiz O. Archives of Agronomy and Soil Science; 2019. SOIL QUALITY INDEX for Paddy fields Based on Standard Scoring Functions and Weight Allocation Method. [Google Scholar]
• Doran J.W., Parkin T. Defining and assessing soil quality. In: Doran J.W., editor. Defining Soil Quality for a Sustainable Environment. SSSA Special Publication n35. SSSA and ASA. 1994. pp. 3–21. Madison, Volume WI. [Google Scholar]
• Dumanski J., Pieri C. Vol. 81. Agriculture. Ecosystems & Environment; 2000. Land Quality Indicators: Research Plan; pp. 93–102. [Google Scholar]
• FAO-ISRIC . Vol. 106. World Soil Ressources Reports; 2014. (World Reference for Soil Resources 2014, First Update 2015). [Google Scholar]
• Forestier J. Fertilité des sols des caféières en RCA. Agron. Trop. XIV. 1960:306–348. (3) [Google Scholar]
• Foth H.D., Ellis B.G. 1997. Soil Fertility. [Google Scholar]
• Heanes D.L. Determination of organic C in soils by an improved chromic acid digestion and spectrophotometric procedure. Commun. Soil Sci. Plant Anal. 1984;1191–1213(15) [Google Scholar]
• Kamprath E.J. Exchangeable aluminium as a criterion for limiting leached mineral soils. Soils Soc. Am. Proc. 1970;(24):252–254. [Google Scholar]
• Lal R. 1994. Methods and Guidelines for Assessing Sustainability Use of Soil and Water Resources in the Tropics. s.l.: s.n. [Google Scholar]
• Lix L.M., Keselman J.C., Keselman H.J. Consequences of assumption violations revisited: a quantitative review of alternatives to the one-way analysis of variance F test. Rev. Educ. Res. 1996;(66):579–619. [Google Scholar]
• Marschner H. Academic Press; London. UK: 2008. Mineral Nutrition of Higher Plants. s.l. [Google Scholar]
• Martin D. Fertilité chimique des sols d’une ferme du Congo. Cah. ORSTOM. Sér. Pédol. 1979;47–64 (XVII (1)) [Google Scholar]
• Martin D., Sieffermann G. Le département du Mungo (Ouest Cameroun). Etude des sols et leur utilisation. Cah. ORSTOM. sér. Pédol. 1966;IX(1):27–49. s.l.: [Google Scholar]
• Mehlich M. Mehlich 3 soil test extractant: a modofocation of the Melhlich 2 extractant. Commun. Soil Sci. Plant Anal. 1984;1409–1416(15) [Google Scholar]
• Merelle . Edition GEMAS éd. Nantes; 1998. L'anbalyse de terre aujourd'hui. s.n. [Google Scholar]
• Meyim-Dayombo S.L. 2000. Effet de diverses jachères sur l’évolution de la fertilité d’un sol ferrallitique des environs de Yaoundé (Cameroun). Application à l’évaluation des terres pour les principales cultures pratiquées dans la région : Arachide, banane-plantain, mais, manioc. s.l.: s.n. [Google Scholar]
• MINADER . Meme Divisional Delegate; 2013. Annual Report for the Ministry of Agriculture and Rural Development, South West Region. s.l.: s.n. [Google Scholar]
• Mulumba L.N., Lal R. Mulching effects on selected soil physical properties. Soil Tillage Res. 2008;98:106–111. [Google Scholar]
• Murphy J., Riley J.P. Amodified single solution method for determination of phosphate in natural waters. Anal. Chim. Acta. 1962;31–36(27) [Google Scholar]
• Ngo-Mbogba M. 2009. Influence du type de végétation sur la qualité des sols dans le bassin versant de Nsimi-Zoétélé dans le plateau Sud camerounais forestier. s.l.: s.n. [Google Scholar]
• Ngo-Mbogba M., Yemefack M., Nyeck B. Assessing soil quality under different land cover types within shifting agriculture in south Cameroon. Soil Tillage Res. 2015;150:124–131. [Google Scholar]
• Nguemezi C. 2019. Les sols de la plaine de Tombel (Sud-Ouest, Cameroun): Classification, cartographie, evaluation de la fertilité et séquestration du carbone. s.l.: s.n. [Google Scholar]
• Nkouathio D.G., Menard J.J., Wandji P., Bardintzeff J.M. The Tombel graben (West Cameroon): a recent monogenetic volcanic field of the Cameroon Line. J.Afr. Earth Sci. 2002;35:285–300. (2002) [Google Scholar]
• Nkouathio D.G., Wandji P., Bardintzeff J.M., Kagou Dongmo A. Pyroclastic rocks as natural fertilizers in Cameroon. S06d-pt-148. IAVCEI General Assembly. Pucon. Chile., Volume November. 2004:14–19. [Google Scholar]
• Nurullah A. Assessment of production service capacity by soil quality evaluations. Fresenius Environ. Bull. 2019:7030–7041. 28(10/2019) [Google Scholar]
• Nyeck B., Bilong P., Eno Belinga S.M. 1999. Caractérisation des équilibres cationiques dans les sols et évaluation des terres de la région forestière humide du Sud Cameroun. Site de Zoétélé., s.l.: Collect. 2/1999. GEOCAM 2 : Press. [Google Scholar]
• Omoko M. 1996. Éléments de pédologie appliquée. s.l.: s.n. [Google Scholar]
• Parnes R. 2013. Soil Fertility. A Guide to Organic and Inorganic Soil Amendments. s.l.: s.n. [Google Scholar]
• Pieri C.J.M.G. 1992. Fertility of Soils: A Future for Farming in the West African Savannah. s.l.: s.n. [Google Scholar]
• Quemada M., Cabrera M.L. CERES-N model predictions of nitrogen mineralised from cover crop residues. SSSA (Soil Sci. Soc. Am.) J. 1995;1059–1065(59) [Google Scholar]
• Remy J.C., Marin-Laflèche A. L’analyse de terre : réalisation d’un programme d’interprétation automatique. Ann. Agron. 1974:607–632. 1974(25(4)) [Google Scholar]
• R . Vol. 3. The R Foundation for Statistical Computing; Vienna. Austria: 2012. http://www.R-project.org/ (Roasted Marshmallows”). URL. [Google Scholar]
• Silatsa T.B.F., Yemefack M. 2017. Digital Soil Mapping Strategies for Regional Land Use Planning in the North and South-West Regions of Cameroun. Yaounde, Cameroon: s.n. [Google Scholar]
• Tématio P. 2005. Etude cartographique et pétrologique des sols à caractères ferrallitiques et andosoliques dans les Monts Bambouto (Ouest Cameroun) : Influence de la lithologie et des facteurs du milieu sur la nature et la distribution des sols en région de montagne tropi. s.l.: s.n. [Google Scholar]
• Tematio P., Nyama A.B., Kengni L. Influence de la mise en culture sur la fertilité des sols en région forestière tropicale humide du Sud Cameroun. Buletin de la Société Vaudoise des Sciences Naturelles. 2001;87 [Google Scholar]
• Tematio P., Tsafack E.I., Kengni L. Effects of tillage. fallow and burning on selected properties and fertility status of Andosols in the Mounts Bambouto. West Cameroon. Agric. Sci. 2011;2:334–340. [Google Scholar]
• Temgoua E., Djoukouo J., Likeng J., Tematio P. Structural stability of andisols and andic Ferralsols from mount bambouto. West Cameroon highlands. Cameroon J. Exp. Biol. 2014;10:26–34. (01) [Google Scholar]
• Tsozué D., Nghonda J., Tematio P., Djakba Basga S. Changes in soil properties and soil organic carbon stocks along an elevation gradient at Mount Bambouto, Central Africa. Catena. 2019;175:251–262. [Google Scholar]
• Tsozué D., Tematio P., Azinwi Tamfuh P. Relationship between soil characteristics and fertility. Implications in two typical dystrandept soils of the Cameroon western highland. J.Soil Sci. 2016;11(2):36–48. [Google Scholar]
• Velayutham M., Bhattacharyya T. Soil resource management. Natural resource management for agricultural production in India. In: Yadav J.S.P., Singh G.B., editors. International Conference on Managing Natural Resources for Sustainable Agricultu. 2000. r, s.l. [Google Scholar]
• Waller S.S., Britton C.M., Dodd J.D. Soils fertility and production parameters of andropogon scopariers tillers. J.Manag. 1975;26(6) [Google Scholar]
• Yemefack M., Jetten V.G., Rossiter D.G. Developing a minimum data set for characterizing soil dynamics in shifting cultivation systems. Soil Till. Res. 2006;84–98(86) [Google Scholar]
• Yerima Bernard P.K., Van Ranst . Trafford Publishing; 2005. Introduction to Soil Science : Soils of the Tropics; p. 397p. s.l.:E. Doc. [Google Scholar]