Assessment of soil health indicators for sustainable production of maize in smallholder farming systems in the highlands of Cameroon Bertin Takoutsing a, ⁎, John Weber b , Ermias Aynekulu c , Jose Antonio Rodríguez Martín d , Keith Shepherd c , Andrew Sila c , Zacharie Tchoundjeu a , Lucien Diby e a World Agroforestry Centre (ICRAF), West and Central Africa, BP 16317 Yaoundé, Cameroon b World Agroforestry Centre, West and Central Africa, Sahel Node, BP E 5115 Bamako, Mali c World Agroforestry Centre (ICRAF), P.O. Box 30677-00100 GPO, Nairobi, Kenya d Dept. Environment, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (I.N.I.A.), Ctra. de A Coruña 7.5, 28040 Madrid, Spain e World Agroforestry Centre (ICRAF), Avenue Jean-Mermoz, 28 BP 2823 Abidjan, Côte d'ivoire abstract article info Article history: Received 5 November 2015 Received in revised form 25 April 2016 Accepted 29 April 2016 Available online xxxx Agricultural intensification has been recognized as one of the solutions to increase food production to feed the ever-increasing population in sub-Saharan Africa. This can partly be achieved if quantitative and up-to-date in- formation on soil health indicators are not available. This study used the land health surveillance framework, which combines ground-sampling schemes based on sentinel site and infrared spectroscopy to select a minimum dataset of soil health indicators to identify key land constraints for maize production and target potential inter- ventions. We found high variability in soil properties in the study area which was mainly due to inherent soil con- ditions and land management practices. The most variable soil properties (CV N 0.38) were nitrogen (N), electric conductivity (ECd), exchangeable bases (ExBas), boron (B), calcium (Ca), potassium (K), magnesium (Mg), man- ganese (Mn) and phosphorus (P). Moderate variability (0.2 b CV b 0.38) was observed for carbon (C), silt and sand, while properties with least variability (CV b 0.2) were pH and aluminium (Al). The effects of land-use and soil depth were significant (p b 0.05) for most of the soil properties. Principal component analysis (PCA) identified soil nutrient availability, metal concentration and texture as the three main factors that explain most of the variability observed. Significant interactions were observed between soil properties confirming the need for a minimum dataset of indicators. ExBas, B, pH, Mn, ECd, P and clay content formed the minimum dataset of soil health indicators for the study area. The results also showed that the soils of the study site are marginally suit- able for the production of maize (Zea mays L.). Low limitations with respect to exchangeable bases (Ca, Mg, K and Na) and severe limitations with respect to B (b 0.15 mg kg -1 ), pH (b 6.20), P (b 6.5 mg kg -1 soil) and clay content (N 63%) were detected. However, potential for improvement exists through integrated soil management practices that include the use of organic and inorganic fertilizers, minimum soil tillage, and inclusion of legumes in crop rotations that could improve soil physical and chemical properties. © 2015 Elsevier B.V. All rights reserved. Keywords: Principal component analysis (PCA) Infrared spectroscopy (IR) Land health surveillance Sentinel site Soil quality Soil security 1. Introduction Increasing agricultural production to feed the ever-increasing popu- lation is most challenging in Sub-Saharan Africa (SSA) because of soil degradation, most often linked to unsustainable agricultural practices (Verhulst et al., 2011; Turmel et al., 2015). The discrepancy between crop yield and population growth raises doubt about how millions of smallholder farmers will feed themselves, and how the current produc- tion system can generate enough to feed the non-agricultural popula- tion. This is particularly the case as the amount of additional arable land that can be brought into cultivation continues to decline (Ricker- Gilbert et al., 2014). Intensification to increase agricultural productivity is seen as one of the solutions and entails enhancing the capacity of soil to augment yields per hectare, increase cropping intensity per unit of land, and change land use from low value crops to those that receive higher market prices. This cannot be achieved if quantitative and up- to-date information are not available to assess changes in soil quality (Pattison et al., 2008), and the effects of these changes on soil capacity to support plant growth and provide ecosystem services (Firbank et al., 2013; Smith et al., 2013). In an agricultural context, high soil qual- ity means a highly productive soil with low levels of degradation and high capacity to withstand extreme weather events and reduce nutrient loss (Karlen et al., 2013). Changes in soil quality can be assessed by measuring appropriate in- dicators and comparing them with desired values (critical limits or threshold level), at different time intervals, for a specific use in a Geoderma 276 (2016) 64–73 ⁎ Corresponding author at: World Agroforestry Centre, P.O. Box 16317, Yaoundé, Cameroon. E-mail address: b.takoutsing@cgiar.org (B. Takoutsing). http://dx.doi.org/10.1016/j.geoderma.2016.04.027 0016-7061/© 2015 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Geoderma journal homepage: www.elsevier.com/locate/geoderma