Climate-induced yield variability and yield gaps of maize (Zea mays L.) in the Central Rift Valley of Ethiopia

Kassie, Belay T.; Ittersum, M.K. van; Hengsdijk, H.; Asseng, Senthold; Wolf, J.; Rötter, Reimund P.

doi:10.1016/j.fcr.2014.02.010

Cited by 108 publications

(64 citation statements)

References 76 publications

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“…Other studies have underscored the importance of rainfall variability for yield stability. Kassie et al (2014), in a study undertaken in a semi-arid region of Ethiopia, attributed about 60% of maize yield variability to the uncertainty in rainfall. Muller et al (2011) reported that rainfall variability was the main cause of yield variability in sub-Saharan Africa.…”

Section: Economic Analysis Of Enhanced Nutrient Usementioning

confidence: 99%

“…Thus, foreknowledge of the weather could assist the farmer in the choice of planting time. Studies by MacCarthy et al (2017) and Kassie et al (2014) indicated the utility of climate forecast for efficient rain-water management in rain-fed agriculture. Climate forecast studies are limited in Ghana but there is some indication that seasonal onset and rainfall correlated with the El Niño-Southern Oscillation (Adiku and Stone 1995;Adiku et al 2007;MacCarthy et al 2017).…”

Section: Economic Analysis Of Enhanced Nutrient Usementioning

confidence: 99%

“…Even though climate risk has been identified as a major constraint to crop production for farmers, particularly in sub-Saharan Africa, quantified information on climateinduced risk and magnitude of yield gaps are scarce (van Ittersum and Rabbinge 1997;Kassie et al 2014). Hence, there is the demand for the quantification of impact of climate variability on yield in the region (Muller et al 2011;Kassie et al 2014).…”

mentioning

confidence: 99%

“…Hence, there is the demand for the quantification of impact of climate variability on yield in the region (Muller et al 2011;Kassie et al 2014).…”

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confidence: 99%

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Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

MacCarthy

Adiku

Freduah

et al. 2017

South African Journal of Plant and Soil

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Section: Economic Analysis Of Enhanced Nutrient Usementioning

confidence: 99%

Section: Economic Analysis Of Enhanced Nutrient Usementioning

confidence: 99%

mentioning

confidence: 99%

“…Hence, there is the demand for the quantification of impact of climate variability on yield in the region (Muller et al 2011;Kassie et al 2014).…”

mentioning

confidence: 99%

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Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

MacCarthy

Adiku

Freduah

et al. 2017

South African Journal of Plant and Soil

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“…This "wet soil" assumption is unrealistic for the dry regions of Europe such as the Mediterranean, especially for the case of spring crops that are sown later in the year, as we could be neglecting important soil moisture depletion happening before the start of the growing season. We can solve this issue by using soil moisture data-for instance, the ERA-Interim reanalysis product (Dee et al, 2011) The WOFOST model has been extensively used for research on crop yield and yield gap all over the world, notably in Europe (Bussay et al, 2015;Eitzinger et al, 2013;Foltescu, 2000;Kogan et al, 2013), Africa (Bregaglio et al, 2014;Kassie et al, 2014;Wolf et al, 2015), Middle East (Sargordi et al, 2013), India (Dua et al, 2013), and China (Wang et al, 2011). However, to our knowledge we are the first to apply WOFOST to estimate surface carbon exchange fluxes and to verify these against observations of GPP, TER, and NEE.…”

Section: Performance and Limits Of The Frameworkmentioning

confidence: 99%

Grain Yield Observations Constrain Cropland CO₂ Fluxes Over Europe

et al. 2017

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Carbon exchange over croplands plays an important role in the European carbon cycle over daily to seasonal time scales. A better description of this exchange in terrestrial biosphere models—most of which currently treat crops as unmanaged grasslands—is needed to improve atmospheric CO2 simulations. In the framework we present here, we model gross European cropland CO2 fluxes with a crop growth model constrained by grain yield observations. Our approach follows a two‐step procedure. In the first step, we calculate day‐to‐day crop carbon fluxes and pools with the WOrld FOod STudies (WOFOST) model. A scaling factor of crop growth is optimized regionally by minimizing the final grain carbon pool difference to crop yield observations from the Statistical Office of the European Union. In a second step, we re‐run our WOFOST model for the full European 25 × 25 km gridded domain using the optimized scaling factors. We combine our optimized crop CO2 fluxes with a simple soil respiration model to obtain the net cropland CO2 exchange. We assess our model's ability to represent cropland CO2 exchange using 40 years of observations at seven European FluxNet sites and compare it with carbon fluxes produced by a typical terrestrial biosphere model. We conclude that our new model framework provides a more realistic and strongly observation‐driven estimate of carbon exchange over European croplands. Its products will be made available to the scientific community through the ICOS Carbon Portal and serve as a new cropland component in the CarbonTracker Europe inverse model.

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Evaluating agronomic factors for maize production in a semi‐arid Loess Plateau

Gao

Bao-liang

et al. 2021

Agronomy Journal

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Crop production is often affected by multiple agronomic factors. However, little has been reported on the synergistic effects of multiple factors on crop production. Here, we reported the effects of five factors (i.e., variety, planting density, nitrogen application, This article is protected by copyright. All rights reserved.supplementary irrigation and plastic mulching) on crop yields, using data from a 5-year experiment at Dongyang, Shanxi province of China. An incomplete factorial design with these factors comprised 12 treatments, including two controls: optimized technology (OT) and conventional technology (CT), comprising all five factors applied at the added or subtracted level, respectively. The result showed that, on 5-year average, OT significantly increased maize yield by 3.5 Mg ha -1 (44.3% more) as compared to CT (7.9 Mg ha -1 ), showing a huge potential for increasing yields. Among the five factors, plastic mulching contributed the most in yield increase (11.5%), high density, improved variety and irrigation contributed 9.9%, 6.9% and 5.1% increase in yield, respectively. There were no significant differences in yield between two N input levels (i.e., 225 and 300 kg N ha -1 ), suggesting the N input of 225 kg N ha -1 was sufficient to realize yield level of 8-11 Mg ha -1 in the studied area. In conclusion, reducing yield gap can only be achieved by optimizing multiple factors simultaneously because the effects of single measure are relatively small and inconsistent among years. The results of our study would help develop adaptive management practices for increasing crop yield stability in other semi-arid regions.

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Climate-induced yield variability and yield gaps of maize (Zea mays L.) in the Central Rift Valley of Ethiopia

Cited by 108 publications

References 76 publications

Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

Grain Yield Observations Constrain Cropland CO₂ Fluxes Over Europe

Evaluating agronomic factors for maize production in a semi‐arid Loess Plateau

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Climate-induced yield variability and yield gaps of maize (Zea mays L.) in the Central Rift Valley of Ethiopia

Cited by 108 publications

References 76 publications

Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

Evaluating maize yield variability and gaps in two agroecologies in northern Ghana using a crop simulation model

Grain Yield Observations Constrain Cropland CO2 Fluxes Over Europe

Evaluating agronomic factors for maize production in a semi‐arid Loess Plateau

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Grain Yield Observations Constrain Cropland CO₂ Fluxes Over Europe