No abstract

An on-farm trial was carried out at KARI (Tigoni) and in Nyandarua County in central Kenyan highlands to determine the yields of some common potato cultivars following storage in a diffuse light store (DLS) for eight months. The trial was carried out for two consecutive seasons i.e. March-July 2012 (first season) and October 2012 to February 2013 (second season). Eight potato cultivars commonly grown in Kenya and of different maturity periods were used. In Nyandarua, the experiment was carried out in three farmers' fields while the KARI Tigoni station was meant for comparison. In each site, the experiment was a split-plot with potato cultivars as main-plot factor and storage as sub-plot factor. There were three replications in each site. Planting of tubers after storage in DLS gave significantly (P≤0.05) more yields than planting freshly harvested tubers. This difference was observed both on the farmers' fields and at KARI Tigoni research station.

An on-farm storage trial was conducted at six sites in Nyandarua County using seed tubers of eight officially recognized Kenyan potato varieties and one commonly grown farmers' variety called Cangi. The seeds were stored under diffuse light store (DLS) conditions in low-cost structures owned by the growers to test the feasibility of prolonged seed storage under on-farm conditions. Three farmers' groups and three individual farmers were used in this study. In general, DLS wooden structures with iron sheet roof or mud-walled with iron sheet roofs were used for storage.Most of the varieties stored satisfactorily for up to 8 months. Kenya Mpya and Kenya Mavuno had higher overall acceptability than Sherekea, Asante, Desiree, Kenya Karibu, Tigoni and Dutch Robjin. Kenya Mpya, Sherekea and Kenya Mavuno had the least shrinkage following 8 months of storage. The unofficial cultivar Cangi which is the most popular in Nyandarua had poor storability but could be planted 2 to 3 months following harvest. Results indicated that DLS could be used by ware potato growers for prolonged seed storage the following season. This way the growers could be assured of good potato harvests due to the use of well sprouted tubers. This is critical in case of seasons with low or less than average rainfall as experienced in recent years.

The potato subsector in Kenya has an unexploited potential which, if properly harnessed, can make significant contributions to Kenya's development aspirations - particularly those related to food and nutrition security, and economic development - as articulated in the country's two main policy documents: Kenya Vision 2030 and the Agriculture Sector Development Strategy (ASDS) 2010-2020. Despite the investments made in the potato subsector in the last several years, its growth has been unsatisfactory. The subsector is currently characterized by: (i) low commercialization; (ii) low average yields; (iii) poor competitiveness; (iv) high wastage; and (v) low value addition with limited processing and limited agribusiness activities. There are very few contractual arrangements between producers and end users of potatoes (e.g. processors, fast food restaurants or supermarkets). In order to transform the potato subsector from subsistence to a vibrant, commercially oriented subsector, a new roadmap - one which leverages available resources to deliver economic growth and opportunity, improved food security and nutrition, and environmental sustainability is required. This chapter presents a roadmap that provides a guide on the core investment areas necessary to revitalize the potato subsector. The roadmap is anchored on three investment areas, namely: (i) the seed potato value chain; (ii) the ware potato value chain; and (iii) the processed potato value chain. The targets of the roadmap are to increase yields by at least 20% in the next 10 years to achieve three overarching objectives, namely: (i) a 15% increase in farm incomes; (ii) improved food security; and (iii) more business opportunities for at least 10% of potato-growing households. These growth targets will be achieved through implementation of several flagship projects in each of the priority value chains focusing on several areas including value chain financing, improvement of markets, formulation of favourable policies, adoption of improved farming technologies (e.g. irrigated potato farming) and promotion of value addition.

A study on contract farming among 137 randomly selected potato farmers in the Bomet and Molo districts was done to evaluate its impact on potato production and productivity using cross-sectional data. Descriptive and inferential statistics on farmers' socio-economic, institutional and geographical aspects were used. Stochastic frontier model analysis was used to evaluate farmers' attributes that affect their production efficiency under contract farming. Contract farming enhanced potato productivity and incomes while also becoming an incentive for farmers to supply a niche market and it increased their demand for farm inputs. Due to the lack of a sound organized market for potatoes, there was inefficiency in potato production which caused a decline in inputs demanded. To overcome these problems farmers formed an organized production and marketing system under a contractual arrangement with the buyers. This led to increased demand for quality inputs and enhanced access to credit. In response to the challenges in contract farming, a tri-partied system of farmers, service providers and processors was constituted for arbitration. Contract farming in the districts has shown that farmers could produce sufficient quantities of high quality potatoes that fetch premium price if they are organized to do so. However, rules on contracts have to be agreed on and followed by all participating players. Contract farming involved extra costs but the accrued benefits were higher due to improved productivity, efficiency and the premium price paid under the contract. There was also a reduction in processing losses due to delivery of quality tubers (losses due to rotting, browning and peeling were reduced by 0.78%, 0.3% and 0.75%, respectively) compared with the pre-project period. Attributes of respondents such as being the head of the household, highest level of training received, large family size and contract farming participation significantly enhanced production efficiency while credit access and age of respondent had significant negative effects on production efficiency.