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Agriculture in West Africa is constrained by several yield-limiting factors, such as poor soil fertility, erratic rainfall distributions and low input systems. Projected changes in climate, thus, pose a threat since crop production is mainly rain-fed. The impact of climate change and its variation on the productivity of cereals in smallholder settings under future production systems in Navrongo, Ghana and Nioro du Rip, Senegal was assessed in this study. Data on management practices obtained from household surveys and projected agricultural development pathways (through stakeholder engagements), soil data, weather data (historical: 1980–2009 and five General Circulation Models; mid-century time slice 2040–2069 for two Representative Concentration Pathways; 4.5 and 8.5) were used for the impact assessment, employing a crop simulation model. Ensemble maize yield changes under the sustainable agricultural development pathway (SDP) were −13 and −16%, while under the unsustainable development pathway (USDP), yield changes were −19 and −20% in Navrongo and Nioro du Rip, respectively. The impact on sorghum and millet were lower than that on maize. Variations in climate change impact among smallholders were high with relative standard deviations (RSD) of between 14% and 60% across the cereals with variability being higher under the USDP, except for millet. Agricultural production systems with higher intensification but with less emphasis on soil conservation (USDP) will be more negatively impacted by climate change compared to relatively sustainable ones (SDP).
Dilys MacCarthy; Myriam Adam; Bright Freduah; Benedicta Fosu-Mensah; Peter Ampim; Mouhamed Ly; Pierre Traore; Samuel Adiku. Climate Change Impact and Variability on Cereal Productivity among Smallholder Farmers under Future Production Systems in West Africa. Sustainability 2021, 13, 5191 .
AMA StyleDilys MacCarthy, Myriam Adam, Bright Freduah, Benedicta Fosu-Mensah, Peter Ampim, Mouhamed Ly, Pierre Traore, Samuel Adiku. Climate Change Impact and Variability on Cereal Productivity among Smallholder Farmers under Future Production Systems in West Africa. Sustainability. 2021; 13 (9):5191.
Chicago/Turabian StyleDilys MacCarthy; Myriam Adam; Bright Freduah; Benedicta Fosu-Mensah; Peter Ampim; Mouhamed Ly; Pierre Traore; Samuel Adiku. 2021. "Climate Change Impact and Variability on Cereal Productivity among Smallholder Farmers under Future Production Systems in West Africa." Sustainability 13, no. 9: 5191.
Plant traits of interest for sorghum breeders to develop dual-purpose varieties are stem diameter, flag leaf size, crop cycle, and number of grains per panicle. To develop dual-purpose varieties, breeders need to improve traits linked both to grain and biomass production. To identify these traits, we studied the phenotypic plasticity of eighteen traits and the performance of ten contrasting sorghum genotypes, used in West Africa. Trials were carried out in a randomized complete blocks design with four replicates from 2013 to 2016 in Bambey, Sinthiou Malem and Nioro du Rip in Senegal. The results revealed three plant types. The first type, “biomass production”, contained genotypes IS15401 and SK5912, and was linked to cycle duration, leaf area, and plant height. The second type, “grain production”, grouped the caudatum race sorghum 621B, F2-20 and Soumba, and was associated with the number of grains per panicle and the width of the flag leaf. The third group, “dual-purpose”, corresponding to the genotypes Fadda, Nieleni and Pablo, combined some favourable traits for grain and biomass: stem diameter, internode length, number of green leaves and number of grains per panicle. The study showed that high and stable grain yields were associated with stability in flag leaf size, phenology and number of grains per panicle, and a high and stable biomass yield was associated with stability in stem diameter. Those stable plant traits might be of interest for sorghum breeders selecting to develop dual-purpose varieties.
Malick Ndiaye; Bertrand Muller; Komla Kyky Ganyo; Aliou Guissé; Ndiaga Cissé; Myriam Adam. Phenotypic plasticity of plant traits contributing to grain and biomass yield of dual-purpose sorghum. Planta 2021, 253, 1 -14.
AMA StyleMalick Ndiaye, Bertrand Muller, Komla Kyky Ganyo, Aliou Guissé, Ndiaga Cissé, Myriam Adam. Phenotypic plasticity of plant traits contributing to grain and biomass yield of dual-purpose sorghum. Planta. 2021; 253 (4):1-14.
Chicago/Turabian StyleMalick Ndiaye; Bertrand Muller; Komla Kyky Ganyo; Aliou Guissé; Ndiaga Cissé; Myriam Adam. 2021. "Phenotypic plasticity of plant traits contributing to grain and biomass yield of dual-purpose sorghum." Planta 253, no. 4: 1-14.
The productivity of smallholder farming systems is held back by poor soil fertility, low input levels and erratic rainfall distribution in the sorghum-based cropping systems of the Sudano-Sahelian zone of West Africa. We assessed the sensitivity of current agricultural practices to climate change and to improved management practices: (i) increased fertilizer application combined with increased plant populations and (ii) use of improved sorghum varieties. We applied the Decision Support Systems for Agro-Technological Transfer (DSSAT) Cropping Systems Model, and the Agricultural Production Systems sIMulator (APSIM), for a multiple-farm assessment (i.e. diverse types of management and soils) in Koutiala (Mali) and Navrongo (Ghana), which are representative sites for West African sorghum production systems. Baseline climate data from observed weather (1980–2009) and future climates from five Global Circulation Models (GCMs: 2040–2069) in two Representative Concentration Pathways (RCP 4.5 and 8.5) were used as inputs for crop models. In Navrongo, under current management, sorghum yields either decreased or increased compared to the baseline, depending on the crop models and the GCMs; changes in management options induced a yield increase of up to 256%. The addition of genetic improvement resulted in further yield increases (24%). In Koutiala, sorghum yield changes for future climates ranged from −38 to +8% assuming current management. Shifting to an improved cultivar had a marginal effect on grain yields, while increased fertilizer rates resulted in grain yield increases ranging of 20% and 153% for DSSAT and APSIM, respectively, assuming the current climate. We conclude that in the Sudano-Sahelian zone of West Africa sorghum, as it is cultivated today, appears moderately vulnerable to climate change, while doubling fertilizer inputs with an adjusted planting density, in the current climate, would more than double yields. However, by exploring farm diversity we established that, under certain conditions, the effect of the future climate might be as important as the effect of management changes in the current climate, hinting at the importance of locally-relevant management practices.
Myriam Adam; Dilys Sefakor MacCarthy; Pierre C. Sibiry Traoré; Andree Nenkam; Bright Salah Freduah; Mouhamed Ly; Samuel G.K. Adiku. Which is more important to sorghum production systems in the Sudano-Sahelian zone of West Africa: Climate change or improved management practices? Agricultural Systems 2020, 185, 102920 .
AMA StyleMyriam Adam, Dilys Sefakor MacCarthy, Pierre C. Sibiry Traoré, Andree Nenkam, Bright Salah Freduah, Mouhamed Ly, Samuel G.K. Adiku. Which is more important to sorghum production systems in the Sudano-Sahelian zone of West Africa: Climate change or improved management practices? Agricultural Systems. 2020; 185 ():102920.
Chicago/Turabian StyleMyriam Adam; Dilys Sefakor MacCarthy; Pierre C. Sibiry Traoré; Andree Nenkam; Bright Salah Freduah; Mouhamed Ly; Samuel G.K. Adiku. 2020. "Which is more important to sorghum production systems in the Sudano-Sahelian zone of West Africa: Climate change or improved management practices?" Agricultural Systems 185, no. : 102920.
Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multi‐model assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N ha‐1) for five environments in SSA, including cool sub‐humid Ethiopia, cool semi‐arid Rwanda, hot sub‐humid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from two‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average rRMSE of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter‐comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low‐input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.
Gatien N. Falconnier; Marc Corbeels; Kenneth J. Boote; François Affholder; Myriam Adam; Dilys S. MacCarthy; Alex C. Ruane; Claas Nendel; Anthony M. Whitbread; Éric Justes; Lajpat R. Ahuja; Folorunso M. Akinseye; Isaac N. Alou; Kokou A. Amouzou; Saseendran S. Anapalli; Christian Baron; Bruno Basso; Frédéric Baudron; Patrick Bertuzzi; Andrew J. Challinor; Yi Chen; Delphine Deryng; Maha Elsayed; Babacar Faye; Thomas Gaiser; Marcelo Galdos; Sebastian Gayler; Edward Gerardeaux; Michel Giner; Brian Grant; Gerrit Hoogenboom; Esther S. Ibrahim; Bahareh Kamali; Kurt Christian Kersebaum; Soo‐Hyung Kim; M Van Der Laan; Louise Leroux; Jon I. Lizaso; Bernardo Maestrini; Elizabeth A. Meier; Fasil Mequanint; Alain Ndoli; Cheryl H. Porter; Eckart Priesack; Dominique Ripoche; Tesfaye S. Sida; Upendra Singh; Ward N. Smith; Amit Srivastava; Sumit Sinha; Fulu Tao; Peter J. Thorburn; Dennis Timlin; Bouba Traore; Tracy Twine; Heidi Webber. Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa. Global Change Biology 2020, 26, 5942 -5964.
AMA StyleGatien N. Falconnier, Marc Corbeels, Kenneth J. Boote, François Affholder, Myriam Adam, Dilys S. MacCarthy, Alex C. Ruane, Claas Nendel, Anthony M. Whitbread, Éric Justes, Lajpat R. Ahuja, Folorunso M. Akinseye, Isaac N. Alou, Kokou A. Amouzou, Saseendran S. Anapalli, Christian Baron, Bruno Basso, Frédéric Baudron, Patrick Bertuzzi, Andrew J. Challinor, Yi Chen, Delphine Deryng, Maha Elsayed, Babacar Faye, Thomas Gaiser, Marcelo Galdos, Sebastian Gayler, Edward Gerardeaux, Michel Giner, Brian Grant, Gerrit Hoogenboom, Esther S. Ibrahim, Bahareh Kamali, Kurt Christian Kersebaum, Soo‐Hyung Kim, M Van Der Laan, Louise Leroux, Jon I. Lizaso, Bernardo Maestrini, Elizabeth A. Meier, Fasil Mequanint, Alain Ndoli, Cheryl H. Porter, Eckart Priesack, Dominique Ripoche, Tesfaye S. Sida, Upendra Singh, Ward N. Smith, Amit Srivastava, Sumit Sinha, Fulu Tao, Peter J. Thorburn, Dennis Timlin, Bouba Traore, Tracy Twine, Heidi Webber. Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa. Global Change Biology. 2020; 26 (10):5942-5964.
Chicago/Turabian StyleGatien N. Falconnier; Marc Corbeels; Kenneth J. Boote; François Affholder; Myriam Adam; Dilys S. MacCarthy; Alex C. Ruane; Claas Nendel; Anthony M. Whitbread; Éric Justes; Lajpat R. Ahuja; Folorunso M. Akinseye; Isaac N. Alou; Kokou A. Amouzou; Saseendran S. Anapalli; Christian Baron; Bruno Basso; Frédéric Baudron; Patrick Bertuzzi; Andrew J. Challinor; Yi Chen; Delphine Deryng; Maha Elsayed; Babacar Faye; Thomas Gaiser; Marcelo Galdos; Sebastian Gayler; Edward Gerardeaux; Michel Giner; Brian Grant; Gerrit Hoogenboom; Esther S. Ibrahim; Bahareh Kamali; Kurt Christian Kersebaum; Soo‐Hyung Kim; M Van Der Laan; Louise Leroux; Jon I. Lizaso; Bernardo Maestrini; Elizabeth A. Meier; Fasil Mequanint; Alain Ndoli; Cheryl H. Porter; Eckart Priesack; Dominique Ripoche; Tesfaye S. Sida; Upendra Singh; Ward N. Smith; Amit Srivastava; Sumit Sinha; Fulu Tao; Peter J. Thorburn; Dennis Timlin; Bouba Traore; Tracy Twine; Heidi Webber. 2020. "Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa." Global Change Biology 26, no. 10: 5942-5964.
Myriam Adam; Burkina Faso Cirad; K. J. Boote; G. N. Falconnier; C. H. Porter; E. Eyshi; H. Webber; France Cirad. Modeling the effects of climate change on agriculture: a focus on cropping systems. Managing soil health for sustainable agriculture Volume 1 2020, 1 .
AMA StyleMyriam Adam, Burkina Faso Cirad, K. J. Boote, G. N. Falconnier, C. H. Porter, E. Eyshi, H. Webber, France Cirad. Modeling the effects of climate change on agriculture: a focus on cropping systems. Managing soil health for sustainable agriculture Volume 1. 2020; ():1.
Chicago/Turabian StyleMyriam Adam; Burkina Faso Cirad; K. J. Boote; G. N. Falconnier; C. H. Porter; E. Eyshi; H. Webber; France Cirad. 2020. "Modeling the effects of climate change on agriculture: a focus on cropping systems." Managing soil health for sustainable agriculture Volume 1 , no. : 1.
Introducing sorghum (Sorghum bicolor L. Moench) genotypes into new environments is necessary for expanding the production of food and fuel, but these efforts are complicated by significant genotype × environment interactions that can reduce their effectiveness. This study set out to thoroughly analyze genotype × environment interactions and assess trade-offs between the agronomic performance and the stability of grain and biomass yields of ten contrasting genotypes under Sudano-Sahelian conditions. Experiments were carried out in a randomized complete block design with four replicates. They were conducted from 2013 to 2016 in Bambey, Sinthiou Malem and Nioro du Rip in Senegal. The joint analysis of variance revealed a highly significant effect (p < 0.0001) of genotypes (G), environments (E) and G × E interaction. Most genotypes showed specific adaptations. The best grain yields were obtained by the Nieleni and Fadda hybrids, while the improved varieties IS15401 and SK5912 were best for biomass production. An Additive Main effect and Multiplicative Interaction (AMMI) analysis showed that good grain yields were associated with environments having good soil fertility and good rainfall, while biomass yields were more influenced by the sowing date and rainfall. Similarly, we were able to confirm for our 10 sorghum genotypes that yield stability was generally associated with low performance, except for the Nieleni and Fadda hybrids, which performed well for grain and biomass production regardless of the environment. The Senegalese control genotype, 621B, showed particular susceptibility to growing conditions (soil), but remained very productive (more than 3 tons per hectare) under good agro-pedological conditions. These results lead us to recommend the Fadda and Nieleni hybrids for the entire study region, while 621B can also be recommended, but only for highly specific environments with good soils.
Malick Ndiaye; Myriam Adam; Komla Kyky Ganyo; Aliou Guissé; Ndiaga Cissé; Bertrand Muller. Genotype-Environment Interaction: Trade-Offs between the Agronomic Performance and Stability of Dual-Purpose Sorghum (Sorghum bicolor L. Moench) Genotypes in Senegal. Agronomy 2019, 9, 867 .
AMA StyleMalick Ndiaye, Myriam Adam, Komla Kyky Ganyo, Aliou Guissé, Ndiaga Cissé, Bertrand Muller. Genotype-Environment Interaction: Trade-Offs between the Agronomic Performance and Stability of Dual-Purpose Sorghum (Sorghum bicolor L. Moench) Genotypes in Senegal. Agronomy. 2019; 9 (12):867.
Chicago/Turabian StyleMalick Ndiaye; Myriam Adam; Komla Kyky Ganyo; Aliou Guissé; Ndiaga Cissé; Bertrand Muller. 2019. "Genotype-Environment Interaction: Trade-Offs between the Agronomic Performance and Stability of Dual-Purpose Sorghum (Sorghum bicolor L. Moench) Genotypes in Senegal." Agronomy 9, no. 12: 867.
Soil nutrient deficiency and rainfall variability impair the production of sorghum (Sorghum bicolor (L). Moench) in Sudano-Sahelian zone. The aim is to study the environmental factors that can determine the effect of fertilizer application on sorghum grain yield and to formulate tailored fertilization strategies according to sorghum varieties (hybrid and open pollinated improved varieties) and environmental context. Field experiments were conducted during the 2015 and 2016 growing seasons in Nioro du Rip and in Sinthiou Malème (Senegal). In a randomized complete block design arranged in a split-plot with four replications, three factors were tested: sorghum genotype (G: Fadda, Faourou, Soumalemba and Soumba with different cycle lengths), environment (E: irrigation and rainfed, different soil types and fertility levels), and fertilization management (M: five different combinations of application dose and application time) including T1 = no fertilizer applied; T2 (recommended practice, 100%) = 150 kg/ha of NPK (15-15-15) at emergence + 50 Kg/ha of urea (46%) at tillering + 50 kg/ha of urea at stem extension; T3 = 50% T2; T4 (100% delay) = 150 kg/ha of NPK +50 kg/ha of urea at stem extension +50 kg/ha of urea at heading ; T5 = 50% T4. Results showed that: (i) in most environments, stressed plants under late application treatments (T4 and T5) recovered biomass once the fertilizer was applied (ii); grain yield with T5 was higher than with T4 under well-watered conditions (sufficient and well distributed rainfall and eventual complementary irrigations) ; (iii) Fadda, a hybrid, responded differently to fertilization than the other varieties only for biomass production, (iv) late fertilizer application treatment (T4) gave higher grain yield than the recommended practice (T2) in the environment with low yield potential, and (v) long cycle duration genotypes benefited better from late fertilization compared to short cycle duration genotypes. This study showed that under Sudano-Sahelian conditions late fertilization of sorghum can be beneficial to grain yield if the rainy season has a slow start, depending on sorghum genotypes (i.e., cycle length), and on the initial N content of the soil.
Komla Kyky Ganyo; Bertrand Muller; Malick Ndiaye; Espoir Koudjo Gaglo; Aliou Guissé; Myriam Adam. Defining Fertilization Strategies for Sorghum (Sorghum bicolor (L.) Moench) Production Under Sudano-Sahelian Conditions: Options for Late Basal Fertilizer Application. Agronomy 2019, 9, 697 .
AMA StyleKomla Kyky Ganyo, Bertrand Muller, Malick Ndiaye, Espoir Koudjo Gaglo, Aliou Guissé, Myriam Adam. Defining Fertilization Strategies for Sorghum (Sorghum bicolor (L.) Moench) Production Under Sudano-Sahelian Conditions: Options for Late Basal Fertilizer Application. Agronomy. 2019; 9 (11):697.
Chicago/Turabian StyleKomla Kyky Ganyo; Bertrand Muller; Malick Ndiaye; Espoir Koudjo Gaglo; Aliou Guissé; Myriam Adam. 2019. "Defining Fertilization Strategies for Sorghum (Sorghum bicolor (L.) Moench) Production Under Sudano-Sahelian Conditions: Options for Late Basal Fertilizer Application." Agronomy 9, no. 11: 697.
Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems.
Bright S. Freduah; Dilys S. MacCarthy; Myriam Adam; Mouhamed Ly; Alex C. Ruane; Eric C. Timpong-Jones; Pierre S. Traore; Kenneth J. Boote; Cheryl Porter; Samuel G. K. Adiku. Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices. Agronomy 2019, 9, 639 .
AMA StyleBright S. Freduah, Dilys S. MacCarthy, Myriam Adam, Mouhamed Ly, Alex C. Ruane, Eric C. Timpong-Jones, Pierre S. Traore, Kenneth J. Boote, Cheryl Porter, Samuel G. K. Adiku. Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices. Agronomy. 2019; 9 (10):639.
Chicago/Turabian StyleBright S. Freduah; Dilys S. MacCarthy; Myriam Adam; Mouhamed Ly; Alex C. Ruane; Eric C. Timpong-Jones; Pierre S. Traore; Kenneth J. Boote; Cheryl Porter; Samuel G. K. Adiku. 2019. "Sensitivity of Maize Yield in Smallholder Systems to Climate Scenarios in Semi-Arid Regions of West Africa: Accounting for Variability in Farm Management Practices." Agronomy 9, no. 10: 639.
Rainfall uncertainty and nutrient deficiency affect sorghum production in Sahel. This study aimed at (i) determining the responses (varieties*water*nitrogen) of various West-African sorghum (Sorghum bicolor L. Moench) varieties to the application of fertilizer (NPK and urea) at selected growing stages according to water regime (irrigated or not, different rainfall patterns) and (ii) simulating them to define alternative fertilization strategies. This chapter proposes alternative fertilization strategies in line with rainfall patterns. Split plot experiments with four replications were carried out in two locations (Senegal), with four improved sorghum varieties (Fadda, IS15401, Soumba and 621B). Treatments were T1, no fertilizer; T2 = 150 kg/ha of NPK (15-15-15) at emergence +50 kg/ha of urea (46%) at tillering +50 Kg/ha of urea at stem extension; T3 = half rate of T2 applied at the same stages; T4 = 150 kg/ha of NPK + 50 kg/ha of urea at stem extension +50 kg/ha of urea at heading, and T5 = half rate of T4 applied at the same stages. Plant height, leaf number, grain yield, and biomass were significantly affected by the timing and rate of fertilizers. Grain yield were affected by water*nitrogen and nitrogen*variety interactions. It varied from 2111 to 261 kg/ha at “Nioro du Rip” and from 1670 to 267 kg/ha at “Sinthiou Malème.” CERES-Sorghum model overestimated late fertilizer grain yields. To achieve acceptable grain yield, fertilizers application should be managed regarding weather.
Komla Kyky Ganyo; Bertrand Muller; Aliou Guissé; Myriam Adam. Fertilization Strategies Based on Climate Information to Enhance Food Security Through Improved Dryland Cereals Production. Handbook of Climate Change Resilience 2019, 917 -934.
AMA StyleKomla Kyky Ganyo, Bertrand Muller, Aliou Guissé, Myriam Adam. Fertilization Strategies Based on Climate Information to Enhance Food Security Through Improved Dryland Cereals Production. Handbook of Climate Change Resilience. 2019; ():917-934.
Chicago/Turabian StyleKomla Kyky Ganyo; Bertrand Muller; Aliou Guissé; Myriam Adam. 2019. "Fertilization Strategies Based on Climate Information to Enhance Food Security Through Improved Dryland Cereals Production." Handbook of Climate Change Resilience , no. : 917-934.
Objectif: L’objectif est d’étudier les réponses de variétés de sorgho à des apports contrastés de NPK et urée qui pourraient être dictés par les informations météorologiques.Méthodologie et résultats: Des essais en split plot avec quatre répétitions ont été conduits à Nioro du Rip et Sinthiou Malème (Sénégal) sur sols sableux en conditions pluviales. Quatre variétés (Fadda, Faourou, Soumalemba et Soumba) ont été soumises à cinq modalités de fertilisation : T1 = pas d’engrais ; T2 = 150kg/ha de NPK (15-15-15) à la levée + 50 kg/ha d’urée (46%) au tallage + 50 kg/ha d’urée à la montaison (recommandation au Sénégal pour le sorgho) ; T3 = moitié dose de T2 appliquée aux mêmes stades ; T4 = 150 kg/ha de NPK + 50 kg/ha d’urée à la montaison + 50 kg/ha d’urée à l’épiaison (T2 décalé) et T5 = moitié dose T4 apportée aux mêmes stades. La fertilisation tardive a permis aux plantes stressées, de recouvrir la croissance telle si les apports étaient faits tôt dans la saison. Les rendements ont varié suivant les localités. L’apport décalé de la dose recommandée (T4) a été plus bénéfique que la moitié dose décalée (T5). Lesvariétés ont montré des réponses différentes les unes des autres, avec Soumalemba qui a mieux réagi aux apports tardifs.Conclusion et application des résultats: Il ressort de cette étude que la fertilisation tardive a été bénéfique aussi bien pour le grain que la biomasse. Elle reste une alternative à la gestion de fertilisation telle que recommandée ou pratiquée par les paysans en cas de début de saison de pluie non favorable surtout dans des pays agropastoraux comme le Sénégal. Les structures d’appui technique aux paysans devront intégrer les prévisions ou observations pluviométriques dans les recommandations de fertilisation afin d’optimiser l’efficience des engrais et la productivité du sorgho.Mots clés: NPK-urée, optimisation, variabilité pluviométrique, sorgho, SénégalEnglish Title: Optimizing NPK and urea based on weather forecast to increase sorghum production in Sudano-Sahelian zones in SenegalEnglish AbstractObjective: Rainfall variability and soil nutrients deficiency accentuated by climate change affects sorghum production in Senegal. This work aims to study the responses of sorghum (Sorghum bicolor L. Moench) to contrasting application of NPK and urea that could be based on weather forecasts.Methodology and results: A split-plot experiment with four replications was carried out at “Nioro du Rip” and “Sinthiou Malème” (Senegal) on sandy soils in rainfed conditions. Four sorghum varieties (Fadda, Faourou, Soumalemba et Soumba) were submitted to five fertilizer treatments defined as T1 = no fertilizer; T2 = 150 kg/ha of NPK (15-15-15) at emergence + 50 kg/ha of urea (46%) at tillering + 50 Kg/ha of urea at stem extension (recommended practice in Senegal for sorghum); T3 = half rate of T2 applied at the same stages; T4 = 150 kg/ha of NPK + 50 kg/ha of urea at stem extension + 50 kg/ha of urea at heading (delay T2) and T5 = half rate of T4 applied at the same stages. Late fertilization allowed plants stressed to recover growth as if fertilizer is applied early in-season. Yield varied according to locations. The application of full dose late inseason (T4) was more beneficial to late application of half rate (T5). Varieties responded differently to fertilization with Soumalemba wich responded better to late application.Conclusion and application of results: It appears from this study that late fertilization has been beneficial for both grain and biomass. It remains an alternative to fertilization management as recommended or practiced by farmers in the event of an unfavorable rain season, especially in agro-pastoral countries like Senegal. Technical support structures for farmers should integrate rainfall forecasts or observations into fertilization recommendations in order to optimize fertilizer efficiency and sorghum productivity.Keywords: NPK-urea, optimizing, rainfall variability, sorghum, Senegal
Komla Kyky Ganyo; Bertrand Muller; Espoir Koudjo Gaglo; Aliou Guissé; Ndiaga Cissé; Myriam Adam. Optimisation du NPK et urée basée sur les informations climatiques pour accroitre la production du sorgho en zones soudano-sahéliennes du Sénégal. Journal of Applied Biosciences 2019, 131, 13293 .
AMA StyleKomla Kyky Ganyo, Bertrand Muller, Espoir Koudjo Gaglo, Aliou Guissé, Ndiaga Cissé, Myriam Adam. Optimisation du NPK et urée basée sur les informations climatiques pour accroitre la production du sorgho en zones soudano-sahéliennes du Sénégal. Journal of Applied Biosciences. 2019; 131 (1):13293.
Chicago/Turabian StyleKomla Kyky Ganyo; Bertrand Muller; Espoir Koudjo Gaglo; Aliou Guissé; Ndiaga Cissé; Myriam Adam. 2019. "Optimisation du NPK et urée basée sur les informations climatiques pour accroitre la production du sorgho en zones soudano-sahéliennes du Sénégal." Journal of Applied Biosciences 131, no. 1: 13293.
Myriam Adam; K.A. Dzotsi; G. Hoogenboom; Pierre C. Sibiry Traore; C.H. Porter; H.F.W. Rattunde; B. Nebie; W.L. Leiser; E. Weltzien; J.W. Jones. Modelling varietal differences in response to phosphorus in West African sorghum. European Journal of Agronomy 2018, 100, 35 -43.
AMA StyleMyriam Adam, K.A. Dzotsi, G. Hoogenboom, Pierre C. Sibiry Traore, C.H. Porter, H.F.W. Rattunde, B. Nebie, W.L. Leiser, E. Weltzien, J.W. Jones. Modelling varietal differences in response to phosphorus in West African sorghum. European Journal of Agronomy. 2018; 100 ():35-43.
Chicago/Turabian StyleMyriam Adam; K.A. Dzotsi; G. Hoogenboom; Pierre C. Sibiry Traore; C.H. Porter; H.F.W. Rattunde; B. Nebie; W.L. Leiser; E. Weltzien; J.W. Jones. 2018. "Modelling varietal differences in response to phosphorus in West African sorghum." European Journal of Agronomy 100, no. : 35-43.
Objectif: L’introduction de nouveaux génotypes de sorghos adaptés à divers environnements est confrontée à la présence d’interaction génotype x environnements significative qui en réduise l’efficacité. La présente étude, conduite sur six environnements - combinaisons site-date de semis-année -, analyse l’interaction génotypeenvironnement et l’adaptabilité et stabilité du rendement grain et biomasse paille de 10 génotypes de sorgho (Sorghum bicolor (L.) Moench).Méthodologie et résultats: L’essai a été conduit selon un dispositif en Blocs Complets Randomisés avec quatre répétitions. L'Anova combinée pour les rendements grains et biomasse paille a révélé une valeur hautement significative (P<0,01) pour les génotypes, les environnements et leurs interactions. L'interaction significative a montré que les génotypes réagissent différemment dans les différents environnements. Les rendements moyens des génotypes ont varié de 1854 Kg.ha-1 (Nieleni) à 547 Kg.ha-1(SK5912) pour le grain ; et de 12103 Kg.ha-1 (IS15401) à 4647 Kg.ha-1 (CSM63E) pour la biomasse paille. Pour les environnements, les rendements ont varié de 1714 Kg.ha-1 (S13D1) à 530 Kg.ha-1(B13D2) pour le grain ; et de 9642 Kg.ha-1 (B13D2) à 5742 Kg.ha-1 (S13D2) pour la biomasse paille. L’analyse AMMI a montré que de bons rendements grains été associés avec des environnements à bonnes fertilité de sol et une bonne pluviométrie, alors que les rendements biomasse paille été plus influencés par la date de semis et la pluviométrie. De même, nous avons pu confirmer pour nos 10 génotypes de sorghos que la stabilité des rendements est en général associée avec de faibles performances, à l’exception du génotype Nieleni qui a de bonnes performances en grain et biomasse paille indépendamment de l’environnement. Conclusion et applications des résultats: Les environnements ont provoqués des réponses différentes des génotypes et la plupart de ces génotypes ont montré une spécificité environnementale. Cette étude trouve son application en sélection variétale et en agronomie. Elle pourrait non seulement aider les programmes de sélection dans le choix des stratégies de sélection pour l’amélioration des rendements en exploitant positivement l’interaction sur les sites à haut potentiel de rendement (S13D1 et S13D2) et l’adaptation générale aux sites au potentiel relativement plus faible (B13D1 et B13D2) mais aussi d’élargir la zone de culture du sorgho au Sénégal qui se fait sur sol argileux. En effet, les dix génotypes étudiés offrent aux producteurs une large gamme de choix variétal en fonction des conditions de cultures (sol et gestion) surtout Nieleni pour assurer leur production en grain et paille dans nos systèmes de production mixtes agriculture-élevage, où la double production est une option privilégiée.Mots clés: Sorgho, Rendement, interaction génotype-environnement, stabilité,...
Malick Ndiaye; Myriam Adam; Bertrand Muller; Aliou Guisse; Ndiaga Cisse. Performances agronomiques et stabilité phénotypique de génotypes de Sorgho (Sorghum bicolor (L.) Moench) au Sénégal: une étude des interactions génotypes-environnement. Journal of Applied Biosciences 2018, 125, 12617 .
AMA StyleMalick Ndiaye, Myriam Adam, Bertrand Muller, Aliou Guisse, Ndiaga Cisse. Performances agronomiques et stabilité phénotypique de génotypes de Sorgho (Sorghum bicolor (L.) Moench) au Sénégal: une étude des interactions génotypes-environnement. Journal of Applied Biosciences. 2018; 125 (1):12617.
Chicago/Turabian StyleMalick Ndiaye; Myriam Adam; Bertrand Muller; Aliou Guisse; Ndiaga Cisse. 2018. "Performances agronomiques et stabilité phénotypique de génotypes de Sorgho (Sorghum bicolor (L.) Moench) au Sénégal: une étude des interactions génotypes-environnement." Journal of Applied Biosciences 125, no. 1: 12617.
To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.
Babacar Faye; Heidi Webber; Jesse B Naab; Dilys S MacCarthy; Myriam Adam; Frank Ewert; John P A Lamers; Carl-Friedrich Schleussner; Alex Ruane; Ursula Gessner; Gerrit Hoogenboom; Ken Boote; Vakhtang Shelia; Fahad Saeed; Dominik Wisser; Sofia Hadir; Patrick Laux; Thomas Gaiser. Impacts of 1.5 versus 2.0 °C on cereal yields in the West African Sudan Savanna. Environmental Research Letters 2018, 13, 034014 .
AMA StyleBabacar Faye, Heidi Webber, Jesse B Naab, Dilys S MacCarthy, Myriam Adam, Frank Ewert, John P A Lamers, Carl-Friedrich Schleussner, Alex Ruane, Ursula Gessner, Gerrit Hoogenboom, Ken Boote, Vakhtang Shelia, Fahad Saeed, Dominik Wisser, Sofia Hadir, Patrick Laux, Thomas Gaiser. Impacts of 1.5 versus 2.0 °C on cereal yields in the West African Sudan Savanna. Environmental Research Letters. 2018; 13 (3):034014.
Chicago/Turabian StyleBabacar Faye; Heidi Webber; Jesse B Naab; Dilys S MacCarthy; Myriam Adam; Frank Ewert; John P A Lamers; Carl-Friedrich Schleussner; Alex Ruane; Ursula Gessner; Gerrit Hoogenboom; Ken Boote; Vakhtang Shelia; Fahad Saeed; Dominik Wisser; Sofia Hadir; Patrick Laux; Thomas Gaiser. 2018. "Impacts of 1.5 versus 2.0 °C on cereal yields in the West African Sudan Savanna." Environmental Research Letters 13, no. 3: 034014.
Farm systems were re-designed together with farmers during three years (2013–2015) in Southern Mali with the aim to improve income without compromising food self-sufficiency. A cyclical learning model with three steps was used: Step 1 was the co-design of a set of crop/livestock technical options, Step 2 the on-farm testing and appraisal of these options and Step 3 a participatory ex-ante analysis of re-designed farm systems incorporating the tested options. Two iterations of the cycle were performed, in order to incorporate farmers’ point of view and researchers’ learning. We worked together with 132 farmers representing four farm types: High Resource Endowed with Large Herd (HRE-LH); High Resource Endowed (HRE); Medium Resource Endowed (MRE) and Low Resource Endowed (LRE) farms. In the first cycle of 2012–2014 farmers re-designed their farms and the reconfigurations were assessed ex ante using the average yields and gross margins obtained in the 2013 on-farm trials. HRE-LH farmers experienced a disappointing decrease in food self-sufficiency and MRE farmers were disappointed by the marginal improvement in gross margin. In a second cycle in 2014–2015, farmer insights gathered during field days and statistical analysis of trial results allowed a better understanding of the variability of option performance and the link with farm context: niches were identified within the farms (soil type/previous crop combinations) where options performed better. The farm systems were re-designed using this niche-specific information on yield and gross margin, which solved the concerns voiced by farmers during the first cycle. Without compromising food self-sufficiency, maize/cowpea intercropping in the right niche combined with stall feeding increased HRE-LH and HRE farm gross margin by 20–26% respectively (i.e. 690 and 545 US$ year−1) with respect to the current farm system. Replacement of sorghum by soyabean (or cowpea) increased MRE and LRE farm gross margin by 29 and 9% respectively (i.e. 545 and 32 US$ year−1). Farmers highlighted the saliency of the niches and the re-designed farm system, and indicated that the extra income could be re-invested in the farm. Our study demonstrates the feasibility and the usefulness of a cyclical and adaptive combination of participatory approaches, on-farm trials and ex-ante analysis to foster learning by farmers and researchers, allowing an agile reorientation of project actions and the generation of innovative farm systems that improve farm income without compromising food self-sufficiency. The re-designed farm systems based on simple, reproducible guidelines such as farm type, previous crop and soil type can be scaled-out by extension workers and guide priority setting in (agricultural) policies and institutional development
Gatien N. Falconnier; Katrien Descheemaeker; Thomas A. Van Mourik; Myriam Adam; Bougouna Sogoba; Ken E. Giller. Co-learning cycles to support the design of innovative farm systems in southern Mali. European Journal of Agronomy 2017, 89, 61 -74.
AMA StyleGatien N. Falconnier, Katrien Descheemaeker, Thomas A. Van Mourik, Myriam Adam, Bougouna Sogoba, Ken E. Giller. Co-learning cycles to support the design of innovative farm systems in southern Mali. European Journal of Agronomy. 2017; 89 ():61-74.
Chicago/Turabian StyleGatien N. Falconnier; Katrien Descheemaeker; Thomas A. Van Mourik; Myriam Adam; Bougouna Sogoba; Ken E. Giller. 2017. "Co-learning cycles to support the design of innovative farm systems in southern Mali." European Journal of Agronomy 89, no. : 61-74.
Better defining niches for the photoperiod sensitive sorghum (Sorghum bicolor L. Moench) varieties of West Africa into the local cropping system might help to improve the resilience of food production in the region. In particular, crop models are key tools to assess the growth and development of such varieties against climate and soil variability. In this study, we compared the performance of three process-based crop models (APSIM, DSSAT and Samara) for prediction of diverse sorghum germplasm having widely varying photoperiod sensitivity (PPS) using detailed growth and development observations from field trials conducted in West Africa semi-arid region. Our results confirmed the capability of each selected model to reproduce growth and development for varieties of diverse sensitivities to photoperiod. Simulated phenology and morphology organs during calibration and validation were within the closet range of measured values with the evaluation of model error statistics (RMSE and R2). With the exception of highly sensitive variety (IS15401), APSIM and Samara estimates indicate the lowest value of RMSE (<7days) against the observed values for phenology events (flowering and maturity) compared to DSSAT model. Across the varieties, there was over-estimation for simulated leaf area index (LAI) while total leaf number (TLN) fitted well with the observed values. Samara estimates were found to be the closet with the lowest RMSE values (<3 leaves for TLN and <1.0 m2/m2 for LAI) followed by DSSAT and APSIM respectively. Prediction of grain yield and biomass was less accurate for both calibration and validation. The predictions using APSIM were found to be closest to the observed followed by DSSAT and Samara models respectively. Based on detailed field observations, this study showed that crop models captured well the phenology and leaf development of the photoperiod sensitive (PPS) varieties of West Africa, but failed to estimate accurately partitioning of assimilates during grain filling. APSIM and SAMARA as more mechanistic crop models, have a higher sensitivity of the adjustment of key parameters, notably the specific leaf area for APSIM in low PPS varieties, while SAMARA shows a higher response to parameters changes for high PPS varieties.
F.M Akinseye; Myriam Adam; S.O Agele; Munir Hoffmann; Pierre C. Sibiry Traore; A.M. Whitbread. Assessing crop model improvements through comparison of sorghum ( sorghum bicolor L. moench) simulation models: A case study of West African varieties. Field Crops Research 2016, 201, 19 -31.
AMA StyleF.M Akinseye, Myriam Adam, S.O Agele, Munir Hoffmann, Pierre C. Sibiry Traore, A.M. Whitbread. Assessing crop model improvements through comparison of sorghum ( sorghum bicolor L. moench) simulation models: A case study of West African varieties. Field Crops Research. 2016; 201 ():19-31.
Chicago/Turabian StyleF.M Akinseye; Myriam Adam; S.O Agele; Munir Hoffmann; Pierre C. Sibiry Traore; A.M. Whitbread. 2016. "Assessing crop model improvements through comparison of sorghum ( sorghum bicolor L. moench) simulation models: A case study of West African varieties." Field Crops Research 201, no. : 19-31.
For most biophysical domains, differences in model structures are seldom quantified. Here, we used a taxonomy-based approach to characterise thirteen rice models. Classification keys and binary attributes for each key were identified, and models were categorised into five clusters using a binary similarity measure and the unweighted pair-group method with arithmetic mean. Principal component analysis was performed on model outputs at four sites. Results indicated that (i) differences in structure often resulted in similar predictions and (ii) similar structures can lead to large differences in model outputs. User subjectivity during calibration may have hidden expected relationships between model structure and behaviour. This explanation, if confirmed, highlights the need for shared protocols to reduce the degrees of freedom during calibration, and to limit, in turn, the risk that user subjectivity influences model performance. A taxonomy-based approach was used to classify AgMIP rice simulation models.Different model structures often resulted in similar outputs.Similar structures often led to large differences in outputs.User subjectivity likely hides relationships between model structure and behaviour.Shared protocols are still needed to limit the risks during calibration.
Roberto Confalonieri; Simone Bregaglio; Myriam Adam; Françoise Ruget; Tao Li; Toshihiro Hasegawa; Xinyou Yin; Yan Zhu; Kenneth Boote; Samuel Buis; Tamon Fumoto; Donald Gaydon; Tanguy Lafarge; Manuel Marcaida; Hiroshi Nakagawa; Alex C. Ruane; Balwinder Singh; Upendra Singh; Liang Tang; Fulu Tao; Job Fugice; Hiroe Yoshida; Zhao Zhang; Lloyd T. Wilson; Jeff Baker; Yubin Yang; Yuji Masutomi; Daniel Wallach; Marco Acutis; Bas Bouman. A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation. Environmental Modelling & Software 2016, 85, 332 -341.
AMA StyleRoberto Confalonieri, Simone Bregaglio, Myriam Adam, Françoise Ruget, Tao Li, Toshihiro Hasegawa, Xinyou Yin, Yan Zhu, Kenneth Boote, Samuel Buis, Tamon Fumoto, Donald Gaydon, Tanguy Lafarge, Manuel Marcaida, Hiroshi Nakagawa, Alex C. Ruane, Balwinder Singh, Upendra Singh, Liang Tang, Fulu Tao, Job Fugice, Hiroe Yoshida, Zhao Zhang, Lloyd T. Wilson, Jeff Baker, Yubin Yang, Yuji Masutomi, Daniel Wallach, Marco Acutis, Bas Bouman. A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation. Environmental Modelling & Software. 2016; 85 ():332-341.
Chicago/Turabian StyleRoberto Confalonieri; Simone Bregaglio; Myriam Adam; Françoise Ruget; Tao Li; Toshihiro Hasegawa; Xinyou Yin; Yan Zhu; Kenneth Boote; Samuel Buis; Tamon Fumoto; Donald Gaydon; Tanguy Lafarge; Manuel Marcaida; Hiroshi Nakagawa; Alex C. Ruane; Balwinder Singh; Upendra Singh; Liang Tang; Fulu Tao; Job Fugice; Hiroe Yoshida; Zhao Zhang; Lloyd T. Wilson; Jeff Baker; Yubin Yang; Yuji Masutomi; Daniel Wallach; Marco Acutis; Bas Bouman. 2016. "A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation." Environmental Modelling & Software 85, no. : 332-341.
Climate change is expected to impact global food supply and food security by affecting growing conditions for agricultural production. Process-based dynamic growth models are important tools to estimate crop yields based on minimum inputs of climate, soil, crop management, and crop cultivar parameters. Using region-specific cultivar parameters is critical when applying crop models at a global scale because cultivars vary in response to climate conditions, soils, and crop management. In this study, parameters were developed for modern cultivars representing all 17 CIMMYT wheat Mega Environments (MEs) using field experimental data and genetic cultivar relationships for the CROPSIM-CERES model in DSSAT v 4.5 (Decision-Support System for Agrotechnology Transfer). Cultivar performance was tested with independent CIMMYT breeding trial field experiments across several locations. Then crop simulations were carried out at 0.5 × 0.5 ° pixels for global wheat-growing areas, using cultivars representing MEs, soil information, region-specific crop management, and initial soil conditions. Aggregated simulated wheat yields and production were compared to reported country yields and production from Food and Agriculture Organization (FAO) statistics, resulting in a Root Mean Square Error (RMSE) of 1.3 t/ha for yield and 2.2 M t/country for country production. Some of the simulated errors are relatively large at country level because of uncertainties in pixel information for climate, soil, and crop management input and partly because of crop model uncertainties. In addition, FAO yield statistics have uncertainties because of incomplete farm reports or poor estimates. Nevertheless, this new cultivar-specific, partially-validated global baseline simulation enables new studies on issues of food security, agricultural technology, and breeding advancement impacts combined with climate change at a global scale.
S. Gbegbelegbe; D. Cammarano; S. Asseng; R. Robertson; U. Chung; M. Adam; O. Abdalla; T. Payne; M. Reynolds; K. Sonder; B. Shiferaw; G. Nelson. Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars. Field Crops Research 2016, 202, 122 -135.
AMA StyleS. Gbegbelegbe, D. Cammarano, S. Asseng, R. Robertson, U. Chung, M. Adam, O. Abdalla, T. Payne, M. Reynolds, K. Sonder, B. Shiferaw, G. Nelson. Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars. Field Crops Research. 2016; 202 ():122-135.
Chicago/Turabian StyleS. Gbegbelegbe; D. Cammarano; S. Asseng; R. Robertson; U. Chung; M. Adam; O. Abdalla; T. Payne; M. Reynolds; K. Sonder; B. Shiferaw; G. Nelson. 2016. "Baseline simulation for global wheat production with CIMMYT mega-environment specific cultivars." Field Crops Research 202, no. : 122-135.
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without re-running the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 °C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].
D. Makowski; S. Asseng; F. Ewert; S. Bassu; J.L. Durand; T. Li; P. Martre; Myriam Adam; P.K. Aggarwal; C. Angulo; Christian Baron; B. Basso; P. Bertuzzi; C. Biernath; H. Boogaard; K.J. Boote; B. Bouman; S. Bregaglio; N. Brisson; S. Buis; Davide Cammarano; A.J. Challinor; R. Confalonieri; Sjaak Conijn; M. Corbeels; D. Deryng; G. De Sanctis; J. Doltra; T. Fumoto; D. Gaydon; Sebastian Gayler; R. Goldberg; R.F. Grant; P. Grassini; J.L. Hatfield; Toshihiro Hasegawa; L. Heng; S. Hoek; J. Hooker; L.A. Hunt; J. Ingwersen; Roberto Izaurralde; R.E.E. Jongschaap; J.W. Jones; Armen Kemanian; Kurt Christian Kersebaum; S.-H. Kim; J. Lizaso; M. Marcaida; Christoph Müller; H. Nakagawa; S. Naresh Kumar; C. Nendel; G.J. O’Leary; J.E. Olesen; P. Oriol; T.M. Osborne; Taru Palosuo; M.V. Pravia; E. Priesack; D. Ripoche; C. Rosenzweig; A.C. Ruane; F. Ruget; F. Sau; M.A. Semenov; I. Shcherbak; B. Singh; Upendra Singh; H.K. Soo; P. Steduto; C. Stöckle; P. Stratonovitch; Thilo Streck; I. Supit; L. Tang; F. Tao; Edmar Teixeira; P. Thorburn; Dennis Timlin; M. Travasso; Reimund Rötter; Katharina Waha; D. Wallach; J.W. White; P. Wilkens; J.R. Williams; J. Wolf; X. Yin; H. Yoshida; Z. Zhang; Y. Zhu. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology 2015, 214-215, 483 -493.
AMA StyleD. Makowski, S. Asseng, F. Ewert, S. Bassu, J.L. Durand, T. Li, P. Martre, Myriam Adam, P.K. Aggarwal, C. Angulo, Christian Baron, B. Basso, P. Bertuzzi, C. Biernath, H. Boogaard, K.J. Boote, B. Bouman, S. Bregaglio, N. Brisson, S. Buis, Davide Cammarano, A.J. Challinor, R. Confalonieri, Sjaak Conijn, M. Corbeels, D. Deryng, G. De Sanctis, J. Doltra, T. Fumoto, D. Gaydon, Sebastian Gayler, R. Goldberg, R.F. Grant, P. Grassini, J.L. Hatfield, Toshihiro Hasegawa, L. Heng, S. Hoek, J. Hooker, L.A. Hunt, J. Ingwersen, Roberto Izaurralde, R.E.E. Jongschaap, J.W. Jones, Armen Kemanian, Kurt Christian Kersebaum, S.-H. Kim, J. Lizaso, M. Marcaida, Christoph Müller, H. Nakagawa, S. Naresh Kumar, C. Nendel, G.J. O’Leary, J.E. Olesen, P. Oriol, T.M. Osborne, Taru Palosuo, M.V. Pravia, E. Priesack, D. Ripoche, C. Rosenzweig, A.C. Ruane, F. Ruget, F. Sau, M.A. Semenov, I. Shcherbak, B. Singh, Upendra Singh, H.K. Soo, P. Steduto, C. Stöckle, P. Stratonovitch, Thilo Streck, I. Supit, L. Tang, F. Tao, Edmar Teixeira, P. Thorburn, Dennis Timlin, M. Travasso, Reimund Rötter, Katharina Waha, D. Wallach, J.W. White, P. Wilkens, J.R. Williams, J. Wolf, X. Yin, H. Yoshida, Z. Zhang, Y. Zhu. A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration. Agricultural and Forest Meteorology. 2015; 214-215 ():483-493.
Chicago/Turabian StyleD. Makowski; S. Asseng; F. Ewert; S. Bassu; J.L. Durand; T. Li; P. Martre; Myriam Adam; P.K. Aggarwal; C. Angulo; Christian Baron; B. Basso; P. Bertuzzi; C. Biernath; H. Boogaard; K.J. Boote; B. Bouman; S. Bregaglio; N. Brisson; S. Buis; Davide Cammarano; A.J. Challinor; R. Confalonieri; Sjaak Conijn; M. Corbeels; D. Deryng; G. De Sanctis; J. Doltra; T. Fumoto; D. Gaydon; Sebastian Gayler; R. Goldberg; R.F. Grant; P. Grassini; J.L. Hatfield; Toshihiro Hasegawa; L. Heng; S. Hoek; J. Hooker; L.A. Hunt; J. Ingwersen; Roberto Izaurralde; R.E.E. Jongschaap; J.W. Jones; Armen Kemanian; Kurt Christian Kersebaum; S.-H. Kim; J. Lizaso; M. Marcaida; Christoph Müller; H. Nakagawa; S. Naresh Kumar; C. Nendel; G.J. O’Leary; J.E. Olesen; P. Oriol; T.M. Osborne; Taru Palosuo; M.V. Pravia; E. Priesack; D. Ripoche; C. Rosenzweig; A.C. Ruane; F. Ruget; F. Sau; M.A. Semenov; I. Shcherbak; B. Singh; Upendra Singh; H.K. Soo; P. Steduto; C. Stöckle; P. Stratonovitch; Thilo Streck; I. Supit; L. Tang; F. Tao; Edmar Teixeira; P. Thorburn; Dennis Timlin; M. Travasso; Reimund Rötter; Katharina Waha; D. Wallach; J.W. White; P. Wilkens; J.R. Williams; J. Wolf; X. Yin; H. Yoshida; Z. Zhang; Y. Zhu. 2015. "A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration." Agricultural and Forest Meteorology 214-215, no. : 483-493.
The agroecological zones (AEZ) of Mali fall within the semi-arid climate, the ability to determine efficiently or predict accurately the onset of growing season (OGS), and length of growing season (LGS) cannot be over-emphasized due to highly variable rainfall pattern and the dependence of smallholder farmers practising on rainfed farming agriculture. In this study, we determined the most suitable method for predicting the onset date of rainfall across AEZ that fitted with the planting windows of major cereal crops (maize, millet, and sorghum). Using long-term daily rainfall records from 22 meteorological stations spread across AEZ of Mali, four (4) known methods were applied to determine the onset dates of the rain. The mean onset dates were statistically compared with the farmer’s planting window for the selected weather stations to determine the suitable dates of OGS and LGS. The hypothesis considered a time lag minimum of 7 days between the mean onset date and traditional farmer sowing dates for the crops. Then, the preferred method was used to estimate OGS based on early, normal and late dates respectively across the stations. Also, the estimated LGS according to each zone was evaluated using probability distribution chart with duration to maturity for varieties of the same crops. The results showed that Def_4 was found appropriate for Sahelian and Sudano-Sahelian zones; Def_3 satisfied the criteria and exhibited superior capacity into farmer’s average planting date over Sudanian and Guinea Savannah zones. These results have an important application in cropping systems in order to prevent crop failure and ensure a better choice of crop variety according to LGS under climate variability and change being experienced across Mali.
F. M. Akinseye; S. O. Agele; Pierre C. Sibiry Traore; Myriam Adam; A. M. Whitbread. Evaluation of the onset and length of growing season to define planting date—‘a case study for Mali (West Africa)’. Theoretical and Applied Climatology 2015, 124, 973 -983.
AMA StyleF. M. Akinseye, S. O. Agele, Pierre C. Sibiry Traore, Myriam Adam, A. M. Whitbread. Evaluation of the onset and length of growing season to define planting date—‘a case study for Mali (West Africa)’. Theoretical and Applied Climatology. 2015; 124 (3-4):973-983.
Chicago/Turabian StyleF. M. Akinseye; S. O. Agele; Pierre C. Sibiry Traore; Myriam Adam; A. M. Whitbread. 2015. "Evaluation of the onset and length of growing season to define planting date—‘a case study for Mali (West Africa)’." Theoretical and Applied Climatology 124, no. 3-4: 973-983.
Predicting rice ([i]Oryza sativa[/i]) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperatur
Tao Li; Toshihiro Hasegawa; Xinyou Yin; Yan Zhu; Kenneth Boote; Myriam Adam; Simone Bregaglio; Samuel Buis; Roberto Confalonieri; Tamon Fumoto; Donald Gaydon; Manuel Marcaida; Hiroshi Nakagawa; Philippe Oriol; Alex C. Ruane; Françoise Ruget; Balwinder‐ Singh; Upendra Singh; Liang Tang; Fulu Tao; Paul Wilkens; Hiroe Yoshida; Zhao Zhang; Bas Bouman. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology 2014, 21, 1328 -1341.
AMA StyleTao Li, Toshihiro Hasegawa, Xinyou Yin, Yan Zhu, Kenneth Boote, Myriam Adam, Simone Bregaglio, Samuel Buis, Roberto Confalonieri, Tamon Fumoto, Donald Gaydon, Manuel Marcaida, Hiroshi Nakagawa, Philippe Oriol, Alex C. Ruane, Françoise Ruget, Balwinder‐ Singh, Upendra Singh, Liang Tang, Fulu Tao, Paul Wilkens, Hiroe Yoshida, Zhao Zhang, Bas Bouman. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions. Global Change Biology. 2014; 21 (3):1328-1341.
Chicago/Turabian StyleTao Li; Toshihiro Hasegawa; Xinyou Yin; Yan Zhu; Kenneth Boote; Myriam Adam; Simone Bregaglio; Samuel Buis; Roberto Confalonieri; Tamon Fumoto; Donald Gaydon; Manuel Marcaida; Hiroshi Nakagawa; Philippe Oriol; Alex C. Ruane; Françoise Ruget; Balwinder‐ Singh; Upendra Singh; Liang Tang; Fulu Tao; Paul Wilkens; Hiroe Yoshida; Zhao Zhang; Bas Bouman. 2014. "Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions." Global Change Biology 21, no. 3: 1328-1341.