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This paper describes an experimental auction conducted among maize traders and farmers in Western Kenya to measure adoption for two low-cost technologies that can measure grain moisture content. Willingness-to-pay auctions (WTP) were combined with a risk preference lottery, allowing an opportunity to study the impact of risk preferences on technology adoption. The specifics of this technology also allows us to identify the impact of risk aversion on willingness to pay for a technology when production uncertainty is not part of the equation. We also randomized two variations of the BDM method for collecting WTP data allowing for a mechanism by which to study the impact of the method on valuation data. We find some evidence that risk aversion increased willingness to pay. Another result with implications in implementation of field experiments in the developing world is that farmers were sensitive to the method in which the auction was presented but traders were not. Acknowledgement

In this paper we present farmer evaluation of a dominant male sterile gene – Ms44 – for maize varieties in Kenya. More than 1000 farmers, 58% women, evaluated the varieties in 8 sites. Our results show that farmers have a wide range of criteria they use in evaluating maize varieties. These criteria do include tassel formation and pollen shed, for which they score Ms44 varieties lower than their conventional counterparts in the mid-season evaluation. This clearly shows farmers can distinguish the male sterility trait at midseason. They still preferred the Ms44 varieties over the others during the mid-season evaluation, because of higher scores on other criteria, inlcuding yield. At the end-season evaluation, tassel formation in Ms44 varieties does not receive a lower score, indicating the trait is no longer observable at harvest. On the methods, asking farmers about different criteria does affect their evaluation, so this type of studies needs to be carefully designed, as demonstrated here. Farmers tend to state many criteria as importance, while not making much distinction between them. Regression overall evaluation over evaluations of different individual criteria, however, shows a more nuanced story. Again, including different criteria affect the weight of the other criteria. Acknowledgement : We appreciate the support of the IMAs project in funding this research

Climate change is a threat to food security in Africa. Maize is the most important staple crop in Kenya, but production per capita has decreased in recent decades. Climate smart agriculture technologies become more important, but it is important to evaluate them with farmers to learn about their needs. Therefore, we conducted participatory evaluations of five miaze varieties both on-farm and on-station. We found that farmers’ perception of varieties are complex, with yield, drought tolerance, and early maturing valued the most. Men value characteristics related to size higher than women (cob size, stalk thickness). On average, men give higher scores than women, and women score more nuanced. On-station, DH02 was liked the best, and Tego the least. On-farm, DH02 was liked the least, while Duma43 was liked the most. Further, onfarm, DH02 was liked less in the wet year than in the dry year. Farmers’ scores did not reflect yield data well, indicating their complex perceptions of varieties. Further, farmers in Makueni could increase their annual income by 51.500 KSh by adopting the improved maize varieties from this study. Maize companies could benefit from an increase in sales, with a potential demand in Makueni of 3.500 metric tons per season.

The International Centre of Insect Physiology and Ecology (icipe), undertook a biological control (BC) programme for control of stemborers from 1993 to 2008, to reduce cereal yield losses due to stemborer attack in East and Southern Africa. The programme released four biological control agents the larval parasitoids Cotesia flavipes and Cotesia sesamiae, the egg parasitoid Telenomus isis and the pupal parasitoid Xanthopimpla stemmator to control the economically important stemborer pests Busseola fusca, Chilo partellus and Sesamia calamistis. Two of the natural enemies that were released got established and spread to many localities in the region. This study adopted the economic surplus model based on production, market and GIS data to evaluate the economic benefits and cost-effectiveness of the programme in three countries Kenya, Mozambique and Zambia. Findings show that the biological control intervention has contributed to an aggregate monetary surplus of US$ 1.4 billion to the economies of the three countries with 84% from maize production and the remaining 16% from sorghum production. The net present value over the twenty years period was estimated at US$ 272 million for both crops and ranged from US$ 142 million for Kenya to US$ 39 million for Zambia. The attractive internal rate of return (IRR) of 67% compared to the considered discount rate of 10%, as well as the estimated benefit-cost ratio (BCR) of 33:1, illustrate the efficiency of investment in the BC research and intervention. The estimated number of people lifted out of poverty through the BC-programme was on average 57,400 persons (consumers and producers) per year in Kenya, 44,120 persons in Mozambique, and 36,170 persons in Zambia, representing an annual average reduction of poor populations, respectively of 0.35, 0.25 and 0.20% in each of the three countries. These findings underscore the need for increased investment in BC research to sustain cereal production and improve poor living conditions.

Optimizing Sample Surveys in Farming Systems Research. The collection of agricultural data, essential for Farming Systems Research, is expensive and the quality of the estimated statistics directly linked to the available budget. This paper shows how to calculate estimator precision of sample surveys from a small number of basic parameters, and how to compare it to a cost function for an optimal resource allocation. Basic parameters are calculated for key variables of the data base of the Farming System Research Team of Sikasso, Mali, and the estimator precision is derived for a number of options. It is shown that this precision can only be very modest with a minimal mean square error of 5 % to 10 %, for the typical small sample size (12 villages, each with 8 farms). Increasing the number of villages diminishes this error, but the effect of an increasing number of farms per village decrease quickly above six to eight farms per village. This type of surveys should therefore not be used for agricultural statistics. They do produce indicators of limited precision, but independend and readily accessible. They are better suited to analyze relationships between variables, to link causes wich constraints and reasons with technology adoption, and to follow major changes in the system's evolution.

On-farm trials in South Mali, combined with a survey of farmer s' criteria, both men's and women's, show that the properties of the new corn varieties do not correspond well to their selection criteria. A better understanding of farmers' objectives is therefore essential in selecting new varieties.