Background: Potato is one of the major staple crops in the Eastern and Central Africa sub-region. Its importance continues to rise due to increased urbanization and demand for potato is projected. This increase will definitely come with its share of challenges that need to be addressed. This study was aimed to measure the level of technical efficiency, yield loss due to inefficiency and identify the factors that influence the efficiency levels of potato producers' in Chilga District. Primary data were collected from 150 farmers selected using multistage sampling procedure and analyzed using descriptive statistics, a parametric stochastic frontier production function models. Results:The results of the study indicated that the minimum, maximum and average yields of potato production in the sample households were 1000, 36,000 and 13,108 kg/ha, respectively. The stochastic frontier and Cobb-Douglas functional form with a one-step approach was employed to analyze efficiency and factors affecting efficiency in potato production. The mean technical efficiency (TE) was found to be 46%, and about 17,782.43 kg of potato output per hectare was lost due to inefficiency factors implying there is a room for improvement in technical efficiency by 54% with the present technology. The Stochastic Production Frontier (SPF) result revealed that DAP at 5% and Oxen, MDE and seed at 1% probability level significantly influencing potato production. The socio-economic variables that exercised important role for variations in technical efficiency positively were age and improved seed and nevertheless distance to market was found to increase inefficiency significantly among farm household.Conclusions: There is considerable difference in the efficiency level among plots. Hence if inputs are used to their maximum potential, there will be considerable gain from improvement in technical efficiency. The estimated SPF model together with the inefficiency parameters shows that age and improved seed variety were influenced by inefficiency negatively whereas distance to market increased the level of technical inefficiency.

Background: Forest stand density in tropical rainforests is crucial functional and structural variable of forest ecosystems in which above ground biomass can be derived. Currently, there is a growing demand for airborne and terrestrial LIDAR in measuring forest trees parameters for accurate assessment of forest biomass/carbon stock to meet the requirements of UN-REDD + program. Although several studies have been conducted on above ground biomass/ carbon stock in tropical rainforest using forest inventory parameters derived from airborne and terrestrial LIDAR, no research was conducted on how the estimation of above ground biomass/carbon stock using airborne and terrestrial LIDAR derived parameters is affected by forest stand density in a tropical rainforest. Therefore, this study aims to analyze and investigate the strength of the relationship between forest stand density and its above ground biomass estimated using airborne and terrestrial LIDAR derived trees parameters. Purposive sampling approach was adopted for the selection of the unit of analysis. Results are based on data collected from 32 sample plots measured and scanned in the field. Airborne LIDAR was used to derive upper canopy trees height, while terrestrial LIDAR was used to derive the height of lower canopy trees and DBH of all lower and upper canopy trees. The DBH measured in the field was used to compute forest stand density and to validate the DBH manually extracted from TLS point cloud data. The DBH manually derived from TLS point cloud data was used to estimate AGB of the sampled plots for both upper and lower canopy trees.Results: Descriptive statistics, linear regression and correlation analysis were used to answer the research questions of this study. Out of 1033 trees measured and scanned in the field, 855 trees (82.7%) were extracted from TLS point cloud data and 178 trees (17.3%) were missed due to occlusion. The Pearson correlation coefficient (r) between a total number of trees measured and scanned in the field and the total number of trees extracted from TLS point cloud data was 0.95. R 2 of 0.89 was found to explain the relationship between number of missed trees per plot against a number of trees measured in the field per plot. The strength of the effect of forest stand density on AGB is explained by R 2 which is 0.91. Conclusions:Based on the findings, forest stand density have significant effect on above ground biomass at 1% significance level. Since there is a strong relationship between forest stand density and AGB and the measurement of forest stand density from the ground is fast, forest stand density could be recommended as a proxy to estimate above ground biomass. © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creat iveco mmons .org/licen ses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative ...

No abstract

No abstract

Agricultural commercialization is a process of transformation from subsistence farming system to market oriented production system. Promoting smallholder farmers to produce beyond their consumption and enabling them to be profit oriented should be given priority in order to foster the economic growth in developing countries where agriculture is the pillar of the economy and smallholder farmers are the largest section of the country like Ethiopia. However, due to a number of reasons smallholder farmers’ level of commercialization is very low and insignificant. There are only few studies conducted about agricultural commercialization in Ethiopia but the studies are not focused to specific crop. Therefore, the aim of this study was to analyse the factors that determine market participation and degree of commercialization by smallholder maize producers in North Western Ethiopia. Data were collected from 385 smallholder maize producers in three districts where maize is produced potentially through multistage sampling method. Interview schedule, focus group discussion and key informant interview were used to collect the required primary data. In order to achieve the study objectives, Tobit model was employed to analyse both market participation and intensity of commercialization. From the analysis education level, livestock holding, frequency of extension contact, training, off/non-farm income activity, quantity of maize and lagged price were found to have significant effect on market participation whereas intensity of commercialization was significantly influenced by education level, livestock holding, training, frequency of extension contact, off/non-farm activity, quantity of maize produced and lagged price. Finally based on the findings, smallholder maize producers should be supported regularly by extension agents in order to increase their practical skills which results enhancement of their market participation and intensity of commercialization.