PRA training for Swaziland NPPO, 9th to 12th December, 2013 in Mbabane, Swaziland.

The Centre Of Phytosanitary Excellence (COPE) in conjunction with FANRPAN together with Harmonized Seed Security Project (HaSSP) organized a three day training workshop on Pest Risk Analysis at Mbabane, Swaziland on the 9th to 12th December 2013.This PRA course was attended by 18 trainees from various institutions and stakeholders in Agriculture, Swaziland through theory classes and practical hands-on training on PRA. The trainees together with the guidance of the trainers from COPE/KEPHIS and DARSS (Swaziland NPPO) developed pest list of maize

The three day intensive PRA course involved 18 participants from various institutions and stakeholders in Agriculture which include: Swaziland National Plant Protection Organization, DARSS, Ministry of Agriculture, NAMBOARD, Cotton Board, SQCS and SDEMANE Farming of Swaziland. The participants were taken through theory classes, practical hands-on training on PRA; and a final exam was taken on completion of the approved units. The trainers were from KEPHIS- COPE (Asenath Koech) and the Swaziland NPPO (Bheki Nzima).
The course context covered principles of PRA, sources of PRA information, Tools for PRA and stages in PRA. As part of the practical training participants were introduced to the computer skills and PRA software. In addition participants were required to develop a Pest List for Maize. The initial working pest list was obtained from the CPC software and the internet for major pest attacking Zea mays L. The PRA focused on Risks associated with trade in seed or grain of Maize between The Kingdom of Swaziland and the Republic of South Africa, as proposed by the participants. After conducting training for 3 days, trainees were evaluated on what they had learnt though administration of a written examination. This was to test their level of understanding in the various topics covered. The trainees scored in the exam an average score of 67.78%. The trainees gave the course a score of 96.6% for the combined parameters of good, very good and excellent.