Soybean Yield, Evapotranspiration, Water Productivity, And Soil Water Extraction Response To Subsurface Drip Irrigation And Fertigation

Soybean [Glycine max (L.) Merr.] yield, irrigation water use efficiency (IWUE), crop water use efficiency (CWUE), evapotranspiration water use efficiency (ETWUE), and soil water extraction response to eleven treatments of full, limited, or delayed irrigation versus a rainfed control were investigated using a subsurface drip irrigation (SDI) system at a research site in south-central Nebraska. The SDI system laterals were 0.40 m deep in every other row middle of 0.76 m spaced plant rows. Actual evapotranspiration (ETa) was quantified in all treatments and used to schedule irrigation events on a 100% ETa replacement basis in all but three of the eleven treatments (i.e., 75% ETa replacement was used in two, and 60% ETa replacement was used in one). The irrigation amount (Ia) applied at each event was 100% of the ETa amount, except for two 100% ETa treatments in which only 65% or 50% of the water needed to cover the treatment plot area was applied to enable a test of a partial surface area-based irrigation approach. The first irrigation event was delayed until soybean stage R3 (begin pod) in two 100% Ia treatments, but thereafter they were irrigated with either 100% or 75% ETa replacement. Two 100% ETa and 100% Ia treatments also were used to evaluate soybean response to nitrogen (N) application methods (i.e., a preplant method versus N injection using the SDI system). Soybean ETa varied from 452 mm for the rainfed treatment to 600 mm (30% greater) for the fully irrigated treatment (100% ETa and 100% Ia) in 2007, and from 473 to 579 mm (20% greater) for the same treatments, respectively, in 2008. Among the irrigated treatments, 100% ETa and 65% Ia had the lowest 2007 ETa value (557 mm), whereas 100% ETa and 50% Ia had the lowest 2008 ETa (498 mm). The 100%, 75%, and 60% ETa treatments with 100% Ia had respective actual ETa values that declined linearly in 2008 (i.e., 579, 538, and 498 mm), but not in 2007. Seasonal totals for ETa versus Ia exhibited a linear relationship (R2 = 0.68 in 2007 and R2 = 0.67 in 2008). Irrigation enhanced soybean yields from rainfed yield baselines of 4.04 ton ha-1 in 2007 and 4.82 ton ha-1 in 2008) to a maximum of 4.94 ton ha-1 attained in 2007 with the delay to R3 irrigation treatment (its yield was significantly greater, p \u3c 0.05, than that of the seven other treatments) and 4.97 ton ha-1 attained in 2008 with the 100% ETa and 100% Ia preplant N treatment. Seed yield had a quadratic relationship with irrigation water applied and a linear relationship with ETa that was stronger in the drier year of 2007. Each 25.4 mm incremental increase in seasonal irrigation water applied increased soybean yield by 0.323 ton ha-1 (beyond the intercept) in 2007 and by 0.037 ton ha-1 in 2008. Each 25.4 mm increase in ETa generated a yield increase of 0.114 ton ha-1 (beyond the intercept) in 2007, but only 0.02 ton ha-1 in the wetter year of 2008. This research demonstrated that delaying the onset of irrigation until the R3 stage and practicing full irrigation thereafter for soybean grown on silt loam soils resulted in yields (and crop water productivity) that were similar to full-season irrigation scheduling strategies, and this result may be applicable in other regions with edaphic and climatic characteristics similar to those in south-central Nebraska

Soybean Yield, Evapotranspiration, Water Productivity, And Soil Water Extraction Response To Subsurface Drip Irrigation And Fertigation

Soybean [Glycine max (L.) Merr.] yield, irrigation water use efficiency (IWUE), crop water use efficiency (CWUE), evapotranspiration water use efficiency (ETWUE), and soil water extraction response to eleven treatments of full, limited, or delayed irrigation versus a rainfed control were investigated using a subsurface drip irrigation (SDI) system at a research site in south-central Nebraska. The SDI system laterals were 0.40 m deep in every other row middle of 0.76 m spaced plant rows. Actual evapotranspiration (ETa) was quantified in all treatments and used to schedule irrigation events on a 100% ETa replacement basis in all but three of the eleven treatments (i.e., 75% ETa replacement was used in two, and 60% ETa replacement was used in one). The irrigation amount (Ia) applied at each event was 100% of the ETa amount, except for two 100% ETa treatments in which only 65% or 50% of the water needed to cover the treatment plot area was applied to enable a test of a partial surface area-based irrigation approach. The first irrigation event was delayed until soybean stage R3 (begin pod) in two 100% Ia treatments, but thereafter they were irrigated with either 100% or 75% ETa replacement. Two 100% ETa and 100% Ia treatments also were used to evaluate soybean response to nitrogen (N) application methods (i.e., a preplant method versus N injection using the SDI system). Soybean ETa varied from 452 mm for the rainfed treatment to 600 mm (30% greater) for the fully irrigated treatment (100% ETa and 100% Ia) in 2007, and from 473 to 579 mm (20% greater) for the same treatments, respectively, in 2008. Among the irrigated treatments, 100% ETa and 65% Ia had the lowest 2007 ETa value (557 mm), whereas 100% ETa and 50% Ia had the lowest 2008 ETa (498 mm). The 100%, 75%, and 60% ETa treatments with 100% Ia had respective actual ETa values that declined linearly in 2008 (i.e., 579, 538, and 498 mm), but not in 2007. Seasonal totals for ETa versus Ia exhibited a linear relationship (R2 = 0.68 in 2007 and R2 = 0.67 in 2008). Irrigation enhanced soybean yields from rainfed yield baselines of 4.04 ton ha-1 in 2007 and 4.82 ton ha-1 in 2008) to a maximum of 4.94 ton ha-1 attained in 2007 with the delay to R3 irrigation treatment (its yield was significantly greater, p \u3c 0.05, than that of the seven other treatments) and 4.97 ton ha-1 attained in 2008 with the 100% ETa and 100% Ia preplant N treatment. Seed yield had a quadratic relationship with irrigation water applied and a linear relationship with ETa that was stronger in the drier year of 2007. Each 25.4 mm incremental increase in seasonal irrigation water applied increased soybean yield by 0.323 ton ha-1 (beyond the intercept) in 2007 and by 0.037 ton ha-1 in 2008. Each 25.4 mm increase in ETa generated a yield increase of 0.114 ton ha-1 (beyond the intercept) in 2007, but only 0.02 ton ha-1 in the wetter year of 2008. This research demonstrated that delaying the onset of irrigation until the R3 stage and practicing full irrigation thereafter for soybean grown on silt loam soils resulted in yields (and crop water productivity) that were similar to full-season irrigation scheduling strategies, and this result may be applicable in other regions with edaphic and climatic characteristics similar to those in south-central Nebraska

Can yield gap analysis be used to inform R & D prioritisation?

The phrase “biggest bang for a buck” is associated with the policy making question that governments and development agencies face: “Where and which crops should receive highest priority for improving local and global food supply?”. A first step of prioritisation is to identify region x crop combinations for which high impact can be anticipated. We developed a new method for this prioritisation exercise and applied it to data from the Global Yield Gap and Water Productivity Atlas (GYGA). Our prioritisation distinguishes between two policy objectives (humanitarian and economic) and builds upon the relative yield gap and climate risk. Results of the prioritisation are presented and visualised in Google Earth

Beyond the plot: technology extrapolation domains for scaling out agronomic science

Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland.Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate ‘technology extrapolation domains’ based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment

Distillers Grains and Livestock are Important to Ethanol Energy and Greenhouse Gas Balance

A life cycle assessment of the impact of distillers grains plus solubles (DGS) on mitigation of energy and greenhouse gas (GHG) emissions comparing corn ethanol to gasoline demonstrates the importanceof feeding wet DGS (WDGS) to feedlot cattle to optimize the environmental benefit of ethanol production relative to gasoline. Ethanol produced in Nebraska has a superior environmentalimpact compared to ethanol produced in Iowa or Texas

Beyond the plot: technology extrapolation domains for scaling out agronomic science

Open Access Journal; Published online: 14 May 2018Ensuring an adequate food supply in systems that protect environmental quality and conserve natural resources requires productive and resource-efficient cropping systems on existing farmland. Meeting this challenge will be difficult without a robust spatial framework that facilitates rapid evaluation and scaling-out of currently available and emerging technologies. Here we develop a global spatial framework to delineate 'technology extrapolation domains' based on key climate and soil factors that govern crop yields and yield stability in rainfed crop production. The proposed framework adequately represents the spatial pattern of crop yields and stability when evaluated over the data-rich US Corn Belt. It also facilitates evaluation of cropping system performance across continents, which can improve efficiency of agricultural research that seeks to intensify production on existing farmland. Populating this biophysical spatial framework with appropriate socio-economic attributes provides the potential to amplify the return on investments in agricultural research and development by improving the effectiveness of research prioritization and impact assessment

Rooting for food security in Sub-Saharan Africa

There is a persistent narrative about the potential of Sub-Saharan Africa (SSA) to be a 'grain breadbasket' because of large gaps between current low yields and yield potential with good management, and vast land resources with adequate rainfall. However, rigorous evaluation of the extent to which soils can support high, stable yields has been limited by lack of data on rootable soil depth of sufficient quality and spatial resolution. Here we use location-specific climate data, a robust spatial upscaling approach, and crop simulation to assess sensitivity of rainfed maize yields to root-zone water holding capacity. We find that SSA could produce a modest maize surplus but only if rootable soil depths are comparable to that of other major breadbaskets, such as the US Corn Belt and South American Pampas, which is unlikely based on currently available information. Otherwise, producing surplus grain for export will depend on expansion of crop area with the challenge of directing this expansion to regions where soil depth and rainfall are supportive of high and consistent yields, and where negative impacts on biodiversity are minimal

Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled geo-referenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74 mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available