Search

Soil fertility management has been a great challenge to smallholder farmers in the Northern Tanzania, especially in the Maasai landscape. Therefore understanding the nutrient status become important to forecast productivity, promote sustainability, and propose an appropriate technique for crop productivity sustainability. The study examines soil fertility status of the Maasai landscape. Systematic approach known as the Land Degradation Surveillance Framework (LDSF) were used to identify soil sampling points. A total of 604 soil samples from two soil depth (0 – 30 and 30 – 50 cm) were collected for physiochemical properties analysis using Mid-infrared (MIR) spectroscopy. The chosen level for determining statistical significance, was set at P = 0.05. Results showed a significant differences (P < 0.01) for particle size distribution, SOC, EC, CEC, TN, pH, N, P, K, Ca, S, Mg, Mn and Zn across the landscape zones. It was observed that soil parameters such as pH (6.62 – 7.44), CEC (27.59 – 32.82 meq/100 g), and EC (90.12 - 121.93 µS/cm) were in the adequate and acceptable range while SOC (0.89 – 1.89 %) was observed to be in low amount. Other nutrients such as N (0.09 – 0.14 %), P (9.46 – 14.87 mg/kg), and K (175.91 - 293.5 mg/kg) were in inadequate amounts except for the S (12.9 – 15.43 mg/kg) which was in optimum, Ca (3117.5 - 4155.31 mg/kg) ranged between low to optimum, and Mg (556.95 - 603.26 mg/kg) was in excessive amounts. However, Mn (114.13 mg/kg – 128.95 mg/kg) was in excess. This study found that, there is a significance difference on soil fertility status across the landscape. Major soil nutrient fertility constraints found were N, P, Ca, and K for some soils. The study recommends that interventions to address the issue of soil fertility in the northeast Maasai landscape should consider the altitude issue due to variations in soil health and nutrient content.

Climate-smart agriculture (CSA) is agriculture that increases productivity, improves resilience, and mitigates climate change. Smallholder adoption of farming technology is necessary to speed the transition to CSA. Here, we assessed the determinants of adoption of five technologies that can help achieve some of the CSA outcomes in smallholder farms in Tanzania. They included crop and livestock diversity, irrigation, application of chemical fertilizers, and agroforestry. Using data collected from 821 farming households, a multivariate probit model was employed to evaluate the determinants of adoption, allowing for examination of synergies and trade-offs between the technologies. Application of chemical fertilizers was fairly well adopted (34% of farmers), while irrigation was least adopted (26%). Some technologies, including crop diversity and irrigation as well as application of chemical fertilizer and agro-forestry, complemented each other. Trade-offs were observed between livestock diversity and irrigation. Female control of farm resources, farm location, and household resources were major determinants of adoption. We, therefore, recommend strategies that seeks to enhance building household resource as pathway for improved adoption of new technologies.