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This study was aimed to evaluate nutritional and antinutritional contents of complementary foods from locally available and affordable raw materials (maize, pea, and anchote) grown in Western Ethiopia. The six formulated complementary diets analyzed for their proximate, mineral, and antinutritional continents were compared with Codex standards. The mineral ratios and molar ratios of the formulated diets were also evaluated and compared with each standard values. Six formulations were generated by d‐optimal mixture design. The formulated ingredient ranges 45%–61% maize, 23%–31% pea, and 14%–28% anchote. Design‐Expert® 6 (Stat‐Ease) was used to constrain the three components. The formulated diets ranged from 14.92% to 20.99%, 5.95% to 9.94%, 2.75% to 3.41%, and 59.10% to 66.22% of protein, fat, fiber, and utilizable carbohydrate, respectively. Mineral contents (mg/100 g) of the formulated diet ranged from 225.45 to 261.32, 11.48 to 12.61, 2.73 to 3.00, 357.92 to 391.13, 298.55 to 332.63, 252.00 to 278.01, and 44.26 to 51.56 for calcium, iron, zinc, phosphorous, potassium, sodium and magnesium, respectively. The proximate and mineral contents of the formulated diet 5 meet the Codex standards, except the fat contents of the complementary food standards. The molar ratios of the formulated diets in this study were below standard reference and which show the high mineral bioavailability in all the formulated diets. The results of the study revealed that the formulated diets contain very low antinutritional factors and high mineral bioavailability. The paper's findings show that the complementary food formulated from maize, pea, and anchote flours particularly diet 5 may be suitable to alleviate protein energy malnutrition and it can be used as a substitute for the expensive commercial complementary food. [ABSTRACT FROM AUTHOR]

This paper provides recommendations on how large-scale household surveys should be conducted to generate the data needed to train models for satellite-based crop type mapping in smallholder farming systems. The analysis focuses on maize cultivation in Malawi and Ethiopia, and leverages rich, georeferenced plot-level data from national household surveys that were conducted in 2018–20 and integrated with Sentinel-2 satellite imagery and complementary geospatial data. To identify the approach to survey data collection that yields optimal data for training remote sensing models, 26,250 in silico experiments are simulated within a machine learning framework. The best model is then applied to map seasonal maize cultivation from 2016 to 2019 at 10-m resolution in both countries. The analysis reveals that smallholder plots with maize cultivation can be identified with up to 75% accuracy. Collecting full plot boundaries or complete plot corner points provides the best quality of information for model training. Classification performance peaks with slightly less than 60% of the training data. Seemingly little erosion in accuracy under less preferable approaches to georeferencing plots results in the total area under maize cultivation being overestimated by 0.16–0.47 million hectares (8–24%) in Malawi. [ABSTRACT FROM AUTHOR]

In Ethiopia, intercropping of medicinal and aromatic plants, like spearmint, with cereals is not well known and undertaken as a common practice. Intercropping spearmint (Sm) with major produced cereal crops such as maize (Mz) can give a chance for farmers to diversify their incomes. Therefore, the field experiment was conducted at Wondo Genet, Rift Valley of Ethiopia under rain-fed conditions during the 2020 cropping season to investigate the effect of spearmint population density and spatial arrangements on the productivity of the maize-spearmint intercropping. The experiment was laid out in a factorial arrangement based on a randomized complete block design with three replications. Treatments were made from a factorial combination of spearmint population density (100, 75, 50, and 25%), and spatial arrangements (1Mz:1Sm, and 1Mz:2Sm) ratio. Data on phenological, growth and yield-related crop parameters were collected following their respective standard methods and procedures and further subjected to analysis of variance (ANOVA) using SAS version 9.4. Whenever the ANOVA result showed a significant difference among treatments for a parameter mean separation was further done using the least significant difference (LSD). The analysis of variance showed that the main effect, their interaction, and cropping system didn’t significant effect (P>0.05) on phenological, vegetative growth, and yield-related parameters of the main crop, maize. On the other hand, the spatial arrangement by population density interaction significantly affected the total fresh above ground-biomass, and leaf yield, and essential oil yield of spearmint where the maximum (22.70-ton, 12.72-ton, and 0.047-ton ha-1 ) in their respective order were recorded at 100% spearmint population density with a double row arrangement respectively. The sole spearmint was superior to other intercropped treatments in each of the two)harvesting cycles for above-ground biomass, leaf, and essential oil yield. The LER values indicated that intercropping maize with a 100% spearmint population at the double row arrangement gave a 63% intercropping advantage with a monetary advantage index (MAI) of 71108 ETB followed by a 75% spearmint population at the same density with 58% advantage and MAI of 65275 ETB. Therefore, intercropping of 75% spearmint population density at double row arrangement with maize could be recommended for the study area. [ABSTRACT FROM AUTHOR]

Agriculture is a risky business that is subject to endogenous risks. Endogenous risks caused by input utilization, input affordability and input availability may prove detrimental to the production potential of farmers. The study was aimed at examining the risk perception, risk aversion and risk management strategies of maize producers in Awi zone, which is found in the northwest part of Ethiopia. The study involved 343 respondents who produced maize under risk. Descriptive statistics, a seven-point Likert scale, the observed economic behaviour method, factor analysis and a seemingly unrelated regression model were used to process the data. The results showed that farmers have different perceptions of the endogenous risk associated with input availability and input affordability which has a different probability of occurrence and severity of damage. The observed economic behaviour method showed that farmers in the area also have different risk aversion behaviours: about 7.29% of the respondents in the study area have high risk aversion attitudes, while about 30.61% have medium risk aversion attitudes and 62.10% of them have low risk aversion attitudes. The seemingly unrelated regression model output showed that farmers' economic, social, demographic and institutional factors, as well as their risk behaviour, determine the risk management strategies that they employ. Maize farmers in the area applied human risk management strategies, production risk management strategies, diversification, financial risk management strategies and marketing risk management strategies to tackle the endogenous risks in the area. It was deduced that maize farmers have a risk averse behaviour even if their risk aversion levels differ based on the scope of the management strategies that they employ to combat risk. Following the finding of the study, a holistic approach to risk management that encompasses all actors, such as farmers, researchers, extension services and financial institutions should be involved to make the appropriate interventions. [ABSTRACT FROM AUTHOR]

In this article, we demonstrated the dynamic impact of a bumper harvest and drought shocks on the maize market and on the trade regime in Ethiopia. Regional market integration of Ethiopia's white maize market with the South Sudan and Kenyan maize markets was also examined using cointegration analysis. Despite the renewed conflict in South Sudan, Addis Ababa maize market is cointegrated with Juba's maize market. The simulation analysis indicated that a 20% increase in maize yield could reduce the maize price by 81%. This implies a decrease in the maize price level of 70% (110 USD/t) below the export parity price. This makes maize exports profitable and shifts the trade regime from autarky to an export parity regime. On the other hand, the effect of a drought could increase maize prices by 61% in the short run (within the year). At the current market price, the domestic maize price is wandering between the border prices and it is unprofitable to export maize. Therefore, lifting the export ban, even during normal harvest seasons, would not do any harm to the domestic maize price. [ABSTRACT FROM AUTHOR]

Declining soil fertility was the major factor for lower productivity of maize and to combat these problems, commercial fertilizers have been applied. However, rising costs of inorganic fertilizers may not encourage the smallholder farmers. Therefore, in sourcing for an alternative that reduces the cost of production while increasing the productivity, integrated soil fertility management has been recommended. Several research attempts have been made to optimize the integrated uses of organic and inorganic fertilizers at different locations. An experiment conducted in Bako concluded use of 12 t ha−1 of FYM with 28/12 NP2O5 kg ha−1 saved up to 75% cost of commercial fertilizer. A trial at Wolaita recommended combined use of compost (5 t ha−1) with 50 kg urea and 100 kg DAP ha−1. Another field experiment conducted in Western Oromiya, application of 150/50 kg ha−1 of the Urea and DAP with 4 t FYM ha−1 was recommended for sustainable production of maize. An experiment conducted at Wujiraba concluded better yield and quality obtained with the application of 120 kg N and 15 kg S ha−1 with 10 t ha−1of compost. Another trial conducted on an acidic nitosol of Southwestern Ethiopia concluded application of 50% recommended NP and 50% compost gave the highest grain yield. A field experiment at Wolaita also indicated, using compost at 5 t ha−1 fortified with urea is better. Another work done at Ebantu showed that combination of vermicompost at 2.5 t ha−1 and mineral P fertilizer (20 kg ha−1) with lime (4 t ha−1) was optimum. [ABSTRACT FROM AUTHOR]

High-resolution and consistent grid-based climate data are important for model-based agricultural planning and farm risk assessment. However, the application of models at the regional scale is constrained by the lack of required high-quality weather data, which may be retrieved from different sources. This can potentially introduce large uncertainties into the crop simulation results. Therefore, in this study, we examined the impacts of grid-based time series of weather variables assembled from the same data source (Approach 1, consistent dataset) and from different sources (Approach 2, combined dataset) on regional scale crop yield simulations in Ghana, Ethiopia and Nigeria. There was less variability in the simulated yield under Approach 1, ranging to 58.2%, 45.6% and 8.2% in Ethiopia, Nigeria and Ghana, respectively, compared to those simulated using datasets retrieved under Approach 2. The two sources of climate data evaluated here were capable of producing both good and poor estimates of average maize yields ranging from lowest RMSE = 0.31 Mg/ha in Nigeria to highest RMSE = 0.78 Mg/ha under Approach 1 in Ghana, whereas, under Approach 2, the RMSE ranged from the lowest value of 0.51 Mg/ha in Nigeria to the highest of 0.72 Mg/ha in Ethiopia under Approach 2. The obtained results suggest that Approach 1 introduces less uncertainty to the yield estimates in large-scale regional simulations, and physical consistency between meteorological input variables is a relevant factor to consider for crop yield simulations under rain-fed conditions. [ABSTRACT FROM AUTHOR]

The productivity of maize in Ethiopia has remained lower than the world average because of several biotic and abiotic factors. Stemborers and poor soil fertility are among the main factors that contribute to this poor maize productivity. A novel cropping strategy, such as the use of push-pull technology, is one of the methods known to solve both challenges at once. A push-pull technology targeting the management of maize stemborers was implemented in the Hawassa district of Ethiopia with the ultimate goal of increased food security among smallholder farmers. This study evaluated farmers' perception of push-pull technology based on their experiences and observations of the demonstration plots that were established on-farm in Dore Bafano, Jara Gelelcha and Lebu Koremo village of the Hawasa district in 2016 and 2017. This study examined farmers' perception of the importance of push-pull technology in controlling stemborers and improving soil fertility and access to livestock feed. In both cropping seasons, except for Jara Gelelcha, the maize grain yields were significantly higher in the climate-adapted push-pull plots compared to the maize monocrop plots. The majority (89%) of push-pull technology-practising farmers rated the technology better than their maize production methods on attributes such as access to new livestock feed and the control of stemborer damage. As a result, approximately 96% of the interviewed farmers were interested in adopting the technology starting in the upcoming crop season. Awareness through training and effective dissemination strategies should be strengthened among stakeholders and policymakers for the sustainable use and scaling-up of push-pull technology. [ABSTRACT FROM AUTHOR]