Optimizing a Cyanobacterial Bio-Fertilizer Manufacturing System for Village-Level Production in Ethiopia.

Fertilizer use in Ethiopia is low, and crop yields and malnutrition rates reflect this low usage rate.  Urea is too expensive for most farmers, and compost supplies are inadequate.  A locally-produced bio-fertilizer produced by harnessing cyanobacteria could help bridge this gap.  The objective of these experiments was to optimize a cyanobacterial bio-fertilizer production system and, specifically, to identify the most productive cyanobacterial culture, water source, plastic liner type, and aeration schedule to optimize bio-fertilizer production on a village-level.  Factorial combinations of four cyanobacteria strains cultured from Ethiopian soils and three water sources (Hawassa groundwater, Lake Hawassa, and Wesha River water) were laid out in a complete randomized design with three replications in a laboratory study.  The river water provided the highest cyanobacterial growth rates for each of the strains.  Cyanobacteria strain E3 (Anabaena sp.) consistently had the highest optical density, growth rate, heterocyst frequency, and total N concentration.  Therefore, strain E3 and river water were selected for the next experiment to optimize parameters for mass production of cyanobacterial bio-fertilizer.  A factorial combination of two pond lining materials (transparent and black plastic sheeting) and two aeration schedules (30 min on followed by 30 min off and 60 min on followed by 60 min off) were laid out in a randomized complete block design with three replications in 1 x 2  x 0.2 m ponds (~400 L each). The transparent plastic lined pond with 60 min on/off aeration performed significantly better than other combinations with higher biomass, optical density and growth rate.  However, there was no significant different in total N fixed under the two aeration schedules.  In conclusion, the E3 strain grown in Wesha river water in transparent plastic lined ponds fixed the most N.  Additional research is needed to optimize aeration schedules and approaches.