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Addis Ababa, Ethiopia

Luedeling E.,International Center for Research in Agroforestry | Luedeling E.,University of Bonn | Smethurst P.J.,CSIRO | Baudron F.,CIMMYT Ethiopia | And 9 more authors.
Agricultural Systems

Agroforestry has attracted considerable attention in recent years because of its potential to reduce poverty, improve food security, reduce land degradation and mitigate climate change. However, progress in promoting agroforestry is held back because decision-makers lack reliable tools to accurately predict yields from tree-crop mixtures. Amongst the key challenges faced in developing such tools are the complexity of agroforestry, including interactions between various system components, and the large spatial domains and timescales over which trees and crops interact. A model that is flexible enough to simulate any agroforestry system globally should be able to address competition and complementarity above and below ground between trees and crops for light, water and nutrients. Most agroforestry practices produce multiple products including food, fiber and fuel, as well as income, shade and other ecosystem services, all of which need to be simulated for a comprehensive understanding of the overall system to emerge. Several agroforestry models and model families have been developed, including SCUAF, HyPAR, Hi-SAFE/Yield-SAFE and WaNuLCAS, but as of 2015 their use has remained limited for reasons including insufficient flexibility, restricted ability to simulate interactions, extensive parameterization needs or lack of model maintenance. An efficient approach to improving the flexibility and durability of agroforestry models is to integrate them into a well-established modular crop modeling framework like APSIM. This framework currently focuses on field-scale crops and pastures, but has the capability to reuse or interoperate with existing models including tree, livestock and landscape models, it uses parameters that are intuitive and relatively easy to measure, and it allows scenario analysis that can include farm-scale economics. Various types of agroforestry systems are currently being promoted in many contexts, and the impacts of these innovations are often unclear. Rapid progress in reliable modeling of tree and crop performance for such systems is needed to ensure that agroforestry fulfills its potential to contribute to reducing poverty, improving food security and fostering sustainability. © 2015 The Authors. Source

Wegary D.,CIMMYT Ethiopia | Vivek B.S.,Indian International Crops Research Institute for the Semi Arid Tropics | Labuschagne M.T.,University of the Free State
Crop Science

Growing maize (Zea mays L.) hybrids tolerant to drought and low-nitrogen (N) stress would significantly reduce yield losses occurring in Africa. This study evaluated the performance of quality protein maize (QPM) F1 hybrids, and general (GCA) and specific combining ability (SCA) of QPM inbred lines for grain yield and other agronomic traits under stress and nonstress environments. A diallel cross of 15 QPM inbred lines was evaluated under drought and low-N stresses and optimal conditions in a total of 17 environments in Eastern and Southern Africa. Significant variations were observed among the hybrids for all measured traits. TZMI703 × (6207QB/6207QA), GQL5 × (6207QB/6207QA), and CML511 × (6207QB/6207QA) were identified as the best single crosses across environments. The GCA and SCA mean squares were significant for all measured traits, indicating that additive and nonadditive genetic effects were important in this set of genotypes under all test environments. The GCA effects were more important under drought stress, and SCA effects were more important under low-N and optimal conditions for grain yield. There was preponderance of GCA effects for most agronomic traits tested in all environmental conditions. Inbred lines CML159SR, GQL5, CML159, and CML312SRQ exhibited favorable GCA effects for grain yield under stress and optimal conditions, indicating that the genetic systems controlling a given trait under different conditions are at least partially similar. Cross combinations with favorable SCA effects for grain yield and other traits were also identified. Generally, this study provided evidence that good performance can be achieved under stress and nonstress conditions in QPM germplasm. © Crop Science Society of America. Source

Wegary D.,CIMMYT Ethiopia | Vivek B.,Indian International Crops Research Institute for the Semi Arid Tropics | Labuschagne M.,University of the Free State

Genetic distance analysis among quality protein maize (QPM) inbred lines and the correlation of genetic distance with heterosis would help to design breeding strategy and predict hybrid performance. This study was carried out to determine the amount of genetic diversity among QPM inbred lines using SSR markers and morphological distances; to classify the inbred lines according to their relationships; and to estimate the correlations of SSR markers and morphological distances with hybrid performance, heterosis and specific combining ability (SCA). One-hundred and five hybrids generated by diallel crossing of 15 QPM inbred lines were evaluated with the 15 parents for 17 morphological traits at Harare, Zimbabwe and Bako, Ethiopia and also examined for DNA polymorphism using 40 SSR markers. SSR markers and morphological methods of genetic distance estimates showed moderately high genetic distance among the inbred lines studied. Cluster analysis based on the two distance measures grouped the 15 parental lines differently. The SSR marker-based genetic distance was positively and highly significantly correlated with grain yield (r = 0.37), and negatively and highly significantly with days to anthesis (r = -0.40) and days to silking (r = -0.42). These relationships suggest that high grain yield and earliness of QPM hybrids can be predicted from SSR marker determined distances of the parents, although the correlation values were not very high. The correlations of SSR marker distance with heterosis were too low to be of predictive value except for the case of plant height. Morphological distances were of less importance in predicting hybrid performance and SCA effects of hybrids. © 2012 Springer Science+Business Media B.V. Source

Nepir G.,Ambo University | Wegary D.,CIMMYT Ethiopia | Zeleke H.,Alemaya University

Quality protein maize (QPM) cultivars contain higher levels of lysine and tryptophan as compared to non-QPM counterparts, and can minimize the risk of protein malnutrition among communities increasingly dependent on maize as their food staple. This study was undertaken to assess the performances of QPM hybrids, and estimate heterosis and combining ability effects of highland QPM inbred lines for grain yield, agronomic and protein quality traits. Hybrids of 20 inbred lines and two testers, and the parental lines were evaluated across three locations in Ethiopia. Significant variations were observed among the parents and the hybrids for almost all measured traits that allows the selection of preferred inbred lines and hybrids. Several hybrids showed desirable heterosis for most studied traits. Mean squares attributable to general (GCA) and specific (SCA) combining ability effects were significant for most traits. However, the contributions of GCA sum of squares to the variation among the hybrids were larger than SCA sum of squares, suggesting that the traits were conditioned mainly by additive gene effects. Inbred lines L12, L17, L19, and L20 had desirable GCA effects for grain yield, whereas L12 and L13 were the best general combiners for protein quality traits. Hybrids L17 x 142-1eQ and L20 x 142-1-eQ showed most desirable perse performances and SCA effects for grain yield. Based on grain yield SCA effects, most inbred lines used in the study were grouped into distinctive heterotic patterns. This study indicated the possibility of developing highland QPM germplasm with acceptable grain yield, agronomic and protein quality traits. © 2015, Consiglio per la Ricercame la sperimentazione in Agrcoltura. All rights reserved. Source

Baudron F.,CIMMYT Ethiopia | Giller K.E.,Wageningen University | Giller K.E.,World Conservation Monitoring Center
Biological Conservation

Global demand for agricultural products is expected to double in the next decades, putting tremendous pressure on agriculture to produce more. The bulk of this increase will come from developing countries, which host most biodiversity-rich areas of the planet. Whilst most biodiversity is found in production landscapes shared with people, where agriculture represents an increasing threat, international conservation organisations continue to focus on the maintenance and expansion of the network of protected areas. When conservation organisations partner with agricultural programmes, they promote low input, extensive agriculture. Combined with the focus on protected areas, this may exacerbate rather than mitigate conflicts between biodiversity conservation and agricultural production. Two models have been proposed to increase agricultural production whilst minimising the negative consequences for biodiversity: 'land sparing' and 'land sharing'. Although often polarized in debates, both are realistic solutions, depending on the local circumstances. We propose a number of criteria that could guide the choice towards one or the other. We conclude that general principles to be considered in both land sparing and land sharing are: managing spillover effects, maintaining resilience and ecosystem services, accounting for landscape structure, reducing losses and wastes, improving access to agricultural products in developing countries and changing consumption patterns in developed countries, and developing supportive markets and policies. © 2013 Elsevier Ltd. Source

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