Using the DSSAT Model to Support Decision Making Regarding Fertilizer Microdosing for Maize Production in the Sub-humid Region of Benin

Tovihoudji, Pierre G.; Akponikpè, P. B. Irénikatché; Agbossou, Euloge Kossi; Bielders, Charles

doi:10.3389/fenvs.2019.00013

Cited by 26 publications

(21 citation statements)

References 51 publications

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“…Their recommendations that higher yields will be obtained under intensification are in line with [29], who warn about the production risks associated with non-adopters of crop management strategies. However, since intensification is yet to be achieved, despite being effective, mostly due to limited income for many farmers in the SSA, there is an ongoing shift toward advocating MD [21,22,30,[43][44][45]. The findings of this study ( Figure 3) provide a unique understanding of the sustainability, and the associated limitations, of MD for pearl millet farmers.…”

Section: Discussionmentioning

confidence: 97%

“…Long-term experiments are best for the evaluation of feasible cropping strategies; however, such information is rarely available for crops in SSA, as experiments are typically conducted for two to three seasons. Consequently, combining results from short-term experiments with validated crop models is a less costly, yet reliable, method for deriving sustainable cropping strategy recommendations [43]. In this study, the DSSAT CERES Millet model is calibrated and evaluated for different crop parameters (anthesis days, maturity days, as well as tops weight and grain yield) ( Table 3).…”

Section: Discussionmentioning

confidence: 99%

“…Nine planting dates spread across three planting windows-early (5 December, 25 December, and 25 December), mid (also referred to as "normal" growing period) (5 January, 15 January, and 25 January), and late (5 February, 15 February, and 25 February)-were used to assess the yield Sustainability 2019, 11, 4330 7 of 18 stability of pearl millet and its susceptibility to seven levels of temperature increments (0 to +3 • C at +0.5 • C increment steps) under NF and MD. The MD is recommended in literature as an adoptable option for low income farmers in semi-arid SSA as it provides significant yield improvements over NF practices [21,22,30,[43][44][45]. The most stable planting date in terms of yield was evaluated for combined scenarios of temperature increments and seven levels of change in precipitation (−30 to +30% at 10% increment steps).…”

Section: Simulation Of Planting Dates Temperature Increments Changementioning

confidence: 99%

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Modelling Rainfed Pearl Millet Yield Sensitivity to Abiotic Stresses in Semi-Arid Central Tanzania, Eastern Africa

et al. 2019

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Drought and heat-tolerant crops, such as Pearl millet (Pennisetum glaucum), are priority crops for fighting hunger in semi-arid regions. Assessing its performance under future climate scenarios is critical for determining its resilience and sustainability. Field experiments were conducted over two consecutive seasons (2015/2016 and 2016/2017) to determine the yield responses of the crop (pearl millet variety "Okoa") to microdose fertilizer application in a semi-arid region of Tanzania. Data from the experiment were used to calibrate and validate the DSSAT model (CERES Millet). Subsequently, the model evaluated synthetic climate change scenarios for temperature increments and precipitation changes based on historic observations (2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018). Temperature increases of +0.5 to +3.0 • C (from baseline), under non-fertilized (NF) and fertilizer microdose (MD) conditions were used to evaluate nine planting dates of pearl millet from early (5 December) to late planting (25 February), based on increments of 10 days. The planting date with the highest yields was subjected to 49 synthetic scenarios of climate change for temperature increments and precipitation changes (of −30% up to +30% from baseline) to simulate yield responses. Results show that the model reproduced the phenology and yield, indicating a very good performance. Model simulations indicate that temperature increases negatively affected yields for all planting dates under NF and MD. Early and late planting windows were more negatively affected than the normal planting window, implying that temperature increases reduced the length of effective planting window for achieving high yields in both NF and MD. Farmers must adjust their planting timing, while the timely availability of seeds and fertilizer is critical. Precipitation increases had a positive effect on yields under all tested temperature increments, but Okoa cultivar only has steady yield increases up to a maximum of 1.5 • C, beyond which yields decline. This informs the need for further breeding or testing of other cultivars that are more heat tolerant. However, under MD, the temperature increments and precipitation change scenarios are higher than under NF, indicating a high potential of yield improvement under MD, especially with precipitation increases. Further investigation should focus on other cropping strategies such as the use of in-field rainwater harvesting and heat-tolerant cultivars to mitigate the effects of temperature increase and change in precipitation on pearl millet yield.

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Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Simulation Of Planting Dates Temperature Increments Changementioning

confidence: 99%

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Modelling Rainfed Pearl Millet Yield Sensitivity to Abiotic Stresses in Semi-Arid Central Tanzania, Eastern Africa

et al. 2019

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“…Agricultural systems models have a large potential to assist with assessing microdosing new techniques and risks. For example, a recent study in Benin, West Africa, using DSSAT with the Crop Environment Resource Synthesis (CERES)‐Maize model found that combining manure with microdosing techniques was slightly riskier but returned better yields in the long term (Tovihoudji et al, 2019). This study did not simulate P directly, and further research is needed to investigate crop P requirements to predict the depletion of available P. Other factors such as climatic effects on crop growth, P loss pathways, and additional nutrient requirements should be incorporated to improve temporal predictions of P supply through the model.…”

Section: Research Gap 1: Agricultural Systems Modeling To Improve Phomentioning

confidence: 99%

Soil Phosphorus Modeling for Modern Agriculture Requires Balance of Science and Practicality: A Perspective

et al. 2019

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The use of phosphorus (P) fertilizers in arable crop and pastoral systems is expected to change as modern agriculture is challenged to produce more food with fewer inputs. Agricultural systems models offer a dual purpose to support and integrate recent scientific advances and to identify strategies for farmers to improve nutrient efficiency. However, compared with nitrogen and carbon, advances in P modeling have been less successful. We assessed the potential opportunity of P modeling to increase P efficiency for modern agriculture and identified the current challenges associated with modeling P dynamics at the field scale. Three major constraints were (i) a paucity of detailed field datasets to model strategies aimed at increasing P use efficiency, (ii) a limited ability to predict P cycling and availability under the local effects of climate change, and (iii) a restricted ability to match measured soil P fractions to conceptual and modelable pools in soils with different mineral properties. To improve P modeling success, modelers will need to walk a tightrope to balance the roles of assisting detailed empirical research and providing practical land management solutions. We conclude that a framework for interdisciplinary collaboration is needed to acquire suitable datasets, continually assess the need for model adjustment, and provide flexibility for progression of scientific theory. Such an approach is likely to advance P management for increased P use efficiency. Core Ideas Models can complement research and identify strategies to increase P efficiency. A variety of quality long‐term field trials is needed to advance model capabilities. Well‐calibrated soil models are needed to assess climate change impacts on P cycling. A framework is needed to streamline multidisciplinary research to improve P management.

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“…Over the years, the use of the CERES-maize model in making management decisions has been increasing in Africa. For instance, it was used to; evaluate climate-sensitive farm management practices in the Northern Regions of Ghana ( MacCarthy et al, 2017 ); identify appropriate sowing dates and nitrogen rates in Zambia ( Chisanga et al, 2014 ); simulate nitrogen and phosphorus uptakes and soil moisture dynamics in West Africa ( Amouzou et al, 2018 ); and recently used in Benin Republic to provide support decision making regarding fertilizer micro-dosing for maize production ( Tovihoudji et al, 2019 ). In Nigeria, the model has been used for the determination of the nitrogen fertilization requirements and optimum planting dates of maize ( Adnan et al, 2017a , 2017b ).…”

Section: Introductionmentioning

confidence: 99%

CERES-Maize model for simulating genotype-by-environment interaction of maize and its stability in the dry and wet savannas of Nigeria

Adnan

Diels

Jibrin

et al. 2020

Field Crops Research

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Highlights Genotype by Environment Interaction (GEI) makes it difficult for breeders and growers to select stable, high yielding varieties across different environments thereby reducing the effectiveness of the selection process. Determining the magnitude of GEI and the stability of varieties can be challenging, as such, crop models can be employed to complement this process. Dynamic models that can simulate the response of growth and development of crops to varying abiotic environmental factors have the potential to explain yield differences due to temporal and spatial variability. Crop Simulation Models were used to complement multi environment trials (METs) with a view to enhancing selection of high yielding varieties across multiple locations. The model simulations matched actual observations and produced similar ranking, indicating that properly calibrated and evaluated CERES-Maize model can complement METs.

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Using the DSSAT Model to Support Decision Making Regarding Fertilizer Microdosing for Maize Production in the Sub-humid Region of Benin

Cited by 26 publications

References 51 publications

Modelling Rainfed Pearl Millet Yield Sensitivity to Abiotic Stresses in Semi-Arid Central Tanzania, Eastern Africa

Modelling Rainfed Pearl Millet Yield Sensitivity to Abiotic Stresses in Semi-Arid Central Tanzania, Eastern Africa

Soil Phosphorus Modeling for Modern Agriculture Requires Balance of Science and Practicality: A Perspective

CERES-Maize model for simulating genotype-by-environment interaction of maize and its stability in the dry and wet savannas of Nigeria

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