The literature contains scarcely any reliable figures on the macro-economic importance of post-harvest losses or of measures to reduce such losses. For the African countries this is due to the lack of reliable production statistics, incomplete knowledge of the extent of losses and inadequate understanding of the post-harvest systems involved. Because of the erratic occurrence of the LGB, the losses caused by it are hard to estimate and can only be stated in approximate terms for a whole country. There is a lack of data on the external costs borne by society for the promotion and application of plant protection measures. These externalities include costs in the health sector caused by improper handling of pesticides, and also opportunity costs caused by loss of labour. Costs arising from campaigns for the proper use of pesticides or special costs for sensitizing the rural population are usually not included in cost-benefit calculations.
Henckes (1992) only briefly touched upon the macro-economic aspects of his integrated stored product protection proposal. For treatment of the quantity of some 1.6 million tons of maize stored annually in small farm stores in Tanzania, he calculated an insecticide requirement of 1 778 t worth 12.5 million DM. Through "dividing the harvest" this could be reduced by 50%, thus saving expenditures of about 6 million DM. However, according to Mallya & Nyakunga (1996) only 140 t of stored product protection insecticides are distributed annually, so that savings of less than 500 000 DM appear more realistic.
The project progress review report by Krause & Mück (1996) cited in section 6 above contains a macro-economic analysis for the southern parts of Benin, Ghana and Togo. Here the authors based their calculation on the assumptions given in Box 6 and on the FAO production statistics for 1994. On this basis, they determined an annual loss potential caused by the LGB of 40 000 t maize worth about 12 mil-lion DM. In this example, Tn provided a reduction in losses of 28 000 t with a value of 8.4 million DM. The use of additional cost-effective integrated post-harvest management techniques was shown by this calculation to provide further savings of 1.8 million DM (or 6 000 t maize).
The British National Resource Institute (NRI) of the Overseas Development Agency (ODA) has also addressed the loss situation and questions of cost-effectiveness in connection with its projects for the biological control of the LGB in Kenya and Ghana. The visual loss estimation method developed by NRI staff offered a considerable simplification of field work (Compton et al., 1996). While methods such as the counting and weighing methods mentioned in section 5 involve a considerable workload in evaluation, the method of Compton et al. (1996) permits more rapid work without being less accurate.
The method is based on rating maize samples in six damage classes. The rating is carried out using reference pictures. The individual damage classes are assigned specific dry matter losses determined using the counting and weighing method. After separating the maize into the six damage classes, it is presented to market women and traders. These then say what they would be willing to pay for maize in each class.
Wright et al. (1993) reported cassava chip losses caused by the LGB in the central region of Togo figuring 9.7% after 3 months and 19.5% after 7 months. This corresponds to 4% of total cassava production at the national level.
Magrath (no year) carried out a model calculation, estimating the economic impacts of the LGB in Ghana between 1995 and 2000. Box 8 summarizes the main findings.
Box 8: Model calculation of the macro-economic impact of the LGB in Ghana Magrath (no year) studied storage losses caused by the LGB in 1995 in the Volta
· Value loss with severe LGB infestation: 10-30%
The monetary losses to the national economy in maize stored at farm level was · Value losses depend upon the occurrence of the LGB.
The calculation, which was carried out separately for each region, delivered the · In the absence of further control measures, value losses will rise from 18 million DM in 1997 to 25 million DM in the year 2000.
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When the costs of control are deducted, the model calculation shows that net savings of 9 million DM remain. The costs of the extension programme need to be further deducted from these savings - however, Magrath (no year) reports no figures for these.
A comprehensive appraisal of the macro-economic impacts of post-harvest measures must also take further beneficial effects into consideration. We note the following effects:
· Improvement of food security and food quality
· Creation of employment opportunities and income in rural areas
· Stabilization of agricultural prices
· Reduction of the rural exodus to urban centres
· Promotion of self-help capacities
· Development of national human resources
· Increased export potential and promotion of South-South trade
· Reduction of trade deficits and of foreign exchange expenditures
· Conservation of natural resources.