Clay minerals constitute an important component of the soil system and knowledge of their role in soil fertility is imperative for sustainable soil management and productivity. The aim of this work is to overview the influence of clay minerals on some major soil fertility attributes. The rationale for carrying out this work is that most soil fertility studies rarely incorporate soil mineralogy. Clay minerals, through their physical and chemical properties, affect soil fertility by controlling nutrient supplies and availability, through the sequestration and stabilization of soil organic matter, by controlling soil physical properties through microaggregate formation, by influencing soil acidity and controlling soil microbial population and activity. The main processes involved in these relationships are dissolution-precipitation and adsorption-desorption processes, alongside mechanisms involving the formation of short-range-ordered phases. Although the determination of soil mineralogical properties is very costly and time-consuming, information about a soil's mineralogy is imperative for a holistic understanding and proper management of soil fertility. Therefore, the development of rapid, low-cost, reliable and efficient techniques of soil mineralogical analysis, directly applicable to soil fertility investigations, constitutes a major challenge. Also, future research should investigate the relationships between clay minerals and soil nitrogen vis-à-vis sequestration and stabilization. Lastly, clay minerals should be considered in studies dealing with soil quality assessment, especially in the choice of soil quality indicators.

No abstract

No abstract

No abstract

Potential N (SN) and P (SP) supplies, N and P utilization efficiencies and fertilizer recovery rates for the northern Guinea Savanna (NGS) agroecological zone of Nigeria were derived from data collected on farmers' fields, and used as input in the QUantitative Evaluation of the Fertility of Tropical Soils (QUEFTS) model. The potential N supply ranged from 7 to 56 kg N ha -1 , with a mean of 25 kg N ha -1 , while SP ranged from 2 to 12 kg P ha -1 with a mean of 5 kg P ha -1 . Both SN (CV = 42%) and SP (CV = 57%) were highly variable between farmers' fields. Deriving potential nutrient supply from 'a' values gives lower estimates. The empirical equation in QUEFTS that estimates SN (SN ¼ 1:7 Â OC Â ðpH À 3Þ) sufficiently predicted the SN of soils in the NGS (RMSE = 8.0 kg N ha -1 index of agreement (IOA) = 0.81). The SP equation (SP ¼ 0:35 Â ð1 À 0:5 Â ðpH À 6Þ 2 Þ Â OC þ 0:5Â OlsenP) predicted moderately potential P supply (RMSE = 6.80 kg P ha -1 , IOA = 0.54). When N or P is maximally accumulated in the plant (i.e., least efficiently utilized), the utilization efficiency was 21 kg grain kg -1 N taken up and 97 kg grain kg -1 P taken up. When these nutrients were maximally diluted in the plant (i.e., most efficiently utilized), the utilization efficiency was 70 kg grain kg -1 N taken up and 600 kg grain kg -1 P taken up. The range in N recovery fraction (NRF) of N fertilizer applied was from 0.30 to 0.57, with a mean of 0.39, while the P recovery fraction (PRF) ranged from 0.10 to 0.66 with a mean of 0.24. Although SP was moderately predicted, when QUEFTS model input parameters were adjusted for the NGS, the model sufficiently (IOA = 0.83, RMSE = 607 kg DM ha -1 ) estimated maize grain yield in the NGS of Nigeria. The original QUEFTS model however, gave better predictions of maize grain yield as reflected by the lower RMSE (IOA = 0.84, RMSE = 549 kg DM ha -1 ). Consequently, QUEFTS is a simple and efficient tool for making yield predictions in the NGS of northern Nigeria.