Profit efficiency among Kenyan smallholders milk producers: A case study of Meru-South district, Kenya

Production inefficiency is usually analyzed by economical efficiency, which is composed of two components-technical and allocative efficiencies. This study provided a direct measure of production efficiency of the smallholder milk producers in Kenya using a stochastic profit frontier and inefficiency model. The primary data were collected, using IMPACT (intergrated modeling platform for mixed animal crops systems) structured questionnaire and includes four conventional inputs and socio-economic factors affecting production. The result showed that profit efficiencies of the sampled farmers varied widely between 26% and 73% with a mean of 60% suggesting that an estimated 40% of the profit is lost due to a combination of both technical and allocative inefficiencies in the smallholder dairy milk production. This study further observed that level of education, experience, and the size of the farm influenced profit efficiency positively while profit efficiency decreased with age. This implies that profit inefficiency among smallholder dairy milk producers can be reduced significantly with improvement in the level of education of sampled farmer

Effect of fruit-to-leaf area ratio on fruit quality and vegetative growth of 'bing' sweet cherry trees at optimal leaf area index

Fruit yield and quality determine grower income from commercial sweet cherry orchards. The objective of this study was to determine the effect of Fruit Number to Leaf Area Ratio (FNLAR, fruit m-2 LA) on Mean Fruit Weight (MFW), firmness (F), soluble solids content (SSC), titratable acidity (TA) and SSC:TA ratio of `Bing¿ sweet cherries trees of near-optimal leaf area index (LAI). The effect of FNLAR on Mean Shoot Growth (MSG) and trunk cross-sectional area increment (TCSAI) also was analysed to determine possible competition between reproductive and vegetative growth. Regression analysis was used with FNLAR as the independent variable. While SSC:TA, MSG and TCSAI were not significantly correlated to FNLAR (P>0.05), MFW, TA and SSC decreased linearly with increasing FNLAR (

Fruit dry weight and quality of 'bing' sweet cherries grown without source limitations

Understanding the seasonal pattern of potential fruit growth is important for identification and timing of possible management operations, and quantification of this pattern is an important prerequisite to serve as input for crop growth models. `Bing¿ sweet cherry trees were heavily thinned at 63 degree-days (DD) (=8 days) after full bloom so weight and quality of the remaining fruit could be monitored under conditions of limiting and non-limiting carbohydrate supply. The effect of fruit thinning on mean shoot growth and trunk cross-sectional area also was analysed to detect possible translocation from reproductive to vegetative growth. Mean Fruit Dry Weight (MFDW) of tagged fruit was estimated weekly, based on fruit diameter, to identify the moment of the onset of competition between fruit within trees. At harvest, Fruit Number to Leaf Area Ratio (FNLAR, fruits m-2 LA) was 52% lower in heavily-thinned trees than in non-thinned trees. Yield per tree was higher (

Relationship between fruit weight and the fruit-to-leaf area ratio, at the spur and whole-tree level, for three sweet cherry varieties

Fruit weight is the main quality parameter of sweet cherries and leaf area/fruit is the most important characteristic influencing fruit weight. The objective of this study was to determine the relationship between Mean Fruit Weight (MFW) and the Fruit Number to Leaf Area Ratio (FNLAR) for `Bing¿, `Van¿ and `Lapins¿, grown under tatura-trellis and vase training systems, at both the spur and whole-tree level. The research was performed through regression analysis with FNLAR as the independent variable and MFW as the dependent variable. There were no significant interactions between training system and cultivar for the effect of FNLAR on MFW at either the spur or whole-tree level. Also, there were no significant differences between training systems. The R2 for the relationships per cultivar were higher at the whole-tree level than at the spur level. At both levels, `Lapins¿ had the highest fruit weight potential and `Van¿ the lowest. At the spur level, the slopes of the regression were similar for the different cultivars, but at the whole-tree level, `Van¿ was less sensitive. The better fit at the whole-tree level suggests that fruits of a spur are supplied not only by the leaves on that spur, but also from other less fruit-loaded spurs, from non-fruiting shoots and from reserve

NNLO QCD corrections to event shape variables in electron positron annihilation

Precision studies of QCD at electron-positron colliders are based on measurements of event shapes and jet rates. To match the high experimental accuracy, theoretical predictions to next-to-next-to-leading order (NNLO) in QCD are needed for a reliable interpretation of the data. We report the first calculation of NNLO corrections O(alpha_s^3) to three-jet production and related event shapes, and discuss their phenomenological impact.Comment: Contributed to 2007 Europhysics Conference on High Energy Physics, Manchester, England 19-25 July 200

Exploring the variability among smallholder farms in the banana-based farming systems in Bukoba district, Northwest Tanzania

A study was conducted in the high and low rainfall zones in the banana-based farming system in Bukoba district, Tanzania, to explore the variability among household characteristics and farm productivity. Approaches used included a participatory rural appraisal, rapid system characterization, surveys and detailed farm monitoring in two villages, one from each zone in 2005 through 2006. Based on a wealth-ranking, four household resource groups with decreasing wealth were identified: Resource group 1 > Resource group 2 > Resource group 3 > Resource group 4, distinguished by domestic assets, livestock ownership and labour relations. Through principal component analysis using additional variables defined by research team, three Functional Resource Groups from among the four Resource groups at each rainfall zone were identified distinguished by: soil fertility management, food security and farm and off-farm income as important indicators of variability. Further detailed monitoring over 14 months (from March, 2006 through May, 2007) in at least three households from each functional resource group showed that N, P and K balances among land use types and farms were driven by levels of organic inputs used and were also related to wealth and dependence on off-farm activities. However, all households were net food buyers, implying food insecurity. In addition, off-farm activities and off-farm income were important livelihood survival strategie