Author(s)

Neil-Yohan Musadji^1,2*, Rolf Gaël Mabicka Obame³, Michel Mbina Mounguengui⁴, Jean Aubin Ondo⁵, Lydie-Stella Koutika⁶, Eric Ravire⁷, Claude Geffroy²

¹Laboratoire De Chimie, Des Milieux et Des Matériaux Inorganiques, Laboratoire D’Analyse Des Sols et Environnement, Département Des Sciences Fondamentales De L’Ingénieur, Institut National D’Agronomie et De Biotechnologies, Université Des Sciences et Techniques De Masuku, Franceville, Gabon.
²Institut De Chimie Des Milieux et Matériaux De Poitiers (IC2MP), Université De Poitiers, Poitiers, France.
³Laboratoire De Chimie, Des Milieux et Des Matériaux Inorganiques, Laboratoire D’Analyse Des Sols et Environnement, Département De Phytotechnologie, Institut National D’Agronomie et De Biotechnologies, Université Des Sciences et Techniques De Masuku, Franceville, Gabon.
⁴Département De Géologie, Faculté Des Sciences, Université Des Sciences et Techniques De Masuku, Franceville, Gabon.
⁵Laboratoire Pluridisciplinaire Des Sciences, Ecole Normale Supérieure, Libreville, Gabon.
⁶Centre De Recherche Sur La Productivité et La Durabilité Des Plantations Industrielles, Pointe Noire, Republic of Congo.
⁷Sucaf Gabon Somdiaa, Franceville, Gabon.

Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivariate soil quality indice (SQI) models, such as additive quality index (AQI), weighted quality indexes (WQI_add and WQI_com) and Nemoro quality index (NQI), applied to two approaches of indicator selection: total data set (TDS) and minimum data set (MDS). Physical and chemical soil indicators were extracted from the ORSTOM’s reports resulting from a sampling campaign in different provinces of Gabon. The TDS approach shows soil quality status according to eleven soil indicators extracted from the analysis of 1,059 samples from arable soil layer (0 - 30 cm depth). The results indicated that 87% of all provinces presented a very low soil quality (Q5) whatever the model. Among soil indicators, exchangeable K⁺ and Mg²⁺, bulk density and C/N ratio were retained in MDS, using principal component analysis (PCA). In the MDS approach, 50 to 63% of provinces had low soil quality grades with AQI, WQI_add and NQI, whereas the total was observed with WQI_com. Only 25% of provinces had medium soil quality grades with AQI and NQI models, while 12.5% (NQI) and 25% (AQI) presented high quality grades. Robust statistical analyses confirmed the accuracy and validation (0.80 < r < 0.91; P ≤ 0.016) of AQI, WQI_add and NQI into the TDS and MDS approaches. The same sensitivity index value (1.53) was obtained with AQI and WQI_add. However, WQI_add was chosen as the best SQI model, according to its high linear regression value (R² = 0.82) between TDS and MDS. This study has important implications in decision-making on monitoring, evaluation and sustainable management of Gabonese soils in a pedoclimatic context unfavorable to plant growth.

Gabon, Ferralitic Soil, Soil Indicators, Standard Score Function, Soil Quality Indices, Sustainable Soil, Soil Management

Musadji, N. , Obame, R. , Mounguengui, M. , Ondo, J. , Koutika, L. , Ravire, E. and Geffroy, C. (2024) Multivariate Approach to Characterizing Soil Quality of Gabonese’s Ferralitic Soils. Open Journal of Soil Science, 14, 237-268. doi: 10.4236/ojss.2024.144014.