The spatial effects of the household's food insecurity levels in Ethiopia: by ordinal geo-additive model.

Background: Food insecurity and vulnerability in Ethiopia are historical problems due to natural- and human-made disasters, which affect a wide range of areas at a higher magnitude with adverse effects on the overall health of households. In Ethiopia, the problem is wider with higher magnitude. Moreover, this geographical distribution of this challenge remains unexplored regarding the effects of cultures and shocks, despite previous case studies suggesting the effects of shocks and other factors. Hence, this study aims to assess the geographic distribution of corrected-food insecurity levels (FCSL) across zones and explore the comprehensive effects of diverse factors on each level of a household's food insecurity. Method: This study analyzes three-term household-based panel data for years 2012, 2014, and 2016 with a total sample size of 11505 covering the all regional states of the country. An extended additive model, with empirical Bayes estimation by modeling both structured spatial effects using Markov random field or tensor product and unstructured effects using Gaussian, was adopted to assess the spatial distribution of FCSL across zones and to further explore the comprehensive effect of geographic, environmental, and socioeconomic factors on the locally adjusted measure. Result: Despite a chronological decline, a substantial portion of Ethiopian households remains food insecure (25%) and vulnerable (27.08%). The Markov random field (MRF) model is the best fit based on GVC, revealing that 90.04% of the total variation is explained by the spatial effects. Most of the northern and south-western areas and south-east and north-west areas are hot spot zones of food insecurity and vulnerability in the country. Moreover, factors such as education, urbanization, having a job, fertilizer usage in cropping, sanitation, and farming livestock and crops have a significant influence on reducing a household's probability of being at higher food insecurity levels (insecurity and vulnerability), whereas shocks occurrence and small land size ownership have worsened it. Conclusion: Chronically food insecure zones showed a strong cluster in the northern and south-western areas of the country, even though higher levels of household food insecurity in Ethiopia have shown a declining trend over the years. Therefore, in these areas, interventions addressing spatial structure factors, particularly urbanization, education, early marriage control, and job creation, along with controlling conflict and drought effect by food aid and selected coping strategies, and performing integrated farming by conserving land and the environment of zones can help to reduce a household's probability of being at higher food insecurity levels.

Household food insecurity levels in Ethiopia: quantile regression approach.

Introduction: Numerous natural and man-made factors have afflicted Ethiopia, and millions of people have experienced food insecurity. The current cut-points of the WFP food consumption score (FCS) have limitations in measuring the food insecurity level of different feeding patterns due to the diversified culture of the society. The aim of this study is to adapt the WFP food security score cut-points corrected for the different feeding cultures of the society using effect-driven quantile clustering. Method: The 2012, 2014, and 2016 Ethiopian socio-economic household-based panel data set with a sample size of 3,835 households and 42 variables were used. Longitudinal quantile regression with fixed individual-specific location-shift intercept of the free distribution covariance structure was adopted to identify major indicators that can cluster and level quantiles of the FCS. Result: Household food insecurity is reduced through time across the quintiles of food security score distribution, mainly in the upper quantiles. The leveling based on effect-driven quantile clustering brings 35.5 and 49 as the FCS cut-points corrected for cultural diversity. This corrected FCS brings wider interval for food insecure households with the same interval range for vulnerable households, where the WFP FCS cut-points under estimate it by 7 score. Education level, employment, fertilizer usage, farming type, agricultural package, infrastructure-related factors, and environmental factors are found to be the significant contributing factors to food security. On the other hand, the age of the head of the household, dependency ratio, shock, and no irrigation in households make significant contributions to food insecurity. Moreover, households living in rural areas and farming crops on small lands are comparatively vulnerable and food insecure. Conclusion: Measuring food insecurity in Ethiopia using the WFP FCS cut-off points underestimates households' food insecurity levels. Since the WFP FCS cut-points have universality and comparability limitations, there is a need for a universally accepted local threshold, corrected for local factors those resulted in different consumption patterns in the standardization of food security score. Accordingly, the quantile regression approach adjusts the WFP-FCS cut points by adjusting for local situations. Applying WFP cut-points will wrongly assign households on each level, so the proportion of households will be inflated for the security level and underestimated for the insecure level, and the influence of factors can also be wrongly recommended the food security score for the levels. The quantile clustering approach showed that cropping on a small land size would not bring about food security in Ethiopia. This favors the Ethiopian government initiative called integrated farming "ኩታ ገጠም እርሻ" which Ethiopia needs to develop and implement a system that fits and responds to this technology and infrastructure.

Field stitching approach for the wave optical modeling of black silicon structures.

The interest in black silicon structures as an anti-reflective interface at the front side of silicon solar cells increased strongly with the rise of diamond wire sawing. The application of optical modeling in order to predict optimal structure parameters could be highly valuable. However, due to the random nature of the structure as well as dimensions in the range of the wavelengths of interest, optical modeling is still a challenge. Within this work, the stitching method of rigorously calculated fields is extended and applied to a black silicon structure. A Fourier transform is used to determine the angular intensity distribution in the far field. In combination with the OPTOS formalism, this allows modeling of silicon substrates with black silicon front side and shows a reasonably good agreement with optical measurement results. Implementing the investigated structure into a solar cell configuration reveals not only a low reflectance but also a very good light trapping performance close to that of a Lambertian scatterer.

Nutritive Value of Grasses in Semi-arid Rangelands of Ethiopia: Local Experience Based Herbage Preference Evaluation versus Laboratory Analysis.

We examined the nutritive value of common grass species in the semi-arid rangelands of Borana in southern Ethiopia using local experience based herbage preference (LEBHP) perception and laboratory techniques. Local pastoralists in the study area were asked to identify common grass species and rank them according to the species' preferences and palatability to cattle. The pastoralists listed a total of 15 common grass species which were then sampled during the main rain and cold dry seasons and analyzed for crude protein (CP), Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF) and ash content to verify pastoralists' claim regarding the quality of individual species. The relative feed value (RFV) and dry matter digestibility (DMD) were also calculated using NDF and ADF contents. Spearman's rank correlation was used to examine possible relationships between laboratory results and pastoralists' experience on grass quality. Cenchrus ciliaris, Chrysopogon aucheri, Digitaria milanjiana, Eragrostis papposa and Panicum maximum were the top five species based on LEBHP perception. There were indications of inconsistency in terms of LEBHP perception among the different pastoral communities. The chemical composition of all grass species showed significant (p<0.05) variation between sites, seasons and species. The results showed that the CP values for the Borana rangelands were in the range of 8.7% in the main rain season to 5.1% for the cold dry season. The fiber constituents were relatively low in the main rain season compared to the cold dry season. Overall, Digitaria milanjiana had the highest CP (16.5%) content, while the least was recorded with Heteropogon contortus (10.8) and Aristida adoensis (9.8%) during the main rain season. It seems that the spatial variability of landscapes within the wider geographical regions, soil properties and texture, and land-use patterns probably contributed to site differences in species quality. Generally, the RFV of individual grass species was significantly (p<0.05) varied between and within sites. The ranking of species by pastoralists according to their preferences by cattle was highly correlated with the chemical composition of laboratory results of individual grass species with 'r' values for CP (0.94), ash (0.95), NDF (-0.98), ADF (-0.93) and ADL (-0.93). We suggest the complimentary use of LEBHP and laboratory techniques in evaluating the nutritive quality of rangeland forage species for sustainable animal production.