Distinguishing between yield advances and yield plateaus in historical crop production trends

Food security and land required for food production largely depend on rate of yield gain of major cereal crops. Previous projections of food security are often more optimistic than what historical yield trends would support. Many econometric projections of future food production assume compound rates of yield gain, which are not consistent with historical yield trends. Here we provide a framework to characterize past yield trends and show that linear trajectories adequately describe past yield trends, which means the relative rate of gain decreases over time. Furthermore, there is evidence of yield plateaus or abrupt decreases in rate of yield gain, including rice in eastern Asia and wheat in northwest Europe, which account for 31% of total global rice, wheat and maize production. Estimating future food production capacity would benefit from an analysis of past crop yield trends based on a robust statistical analysis framework that evaluates historical yield trajectories and plateaus

Distinguishing between yield advances and yield plateaus in historical crop production trends

Food security and land required for food production largely depend on rate of yield gain of major cereal crops. Previous projections of food security are often more optimistic than what historical yield trends would support. Many econometric projections of future food production assume compound rates of yield gain, which are not consistent with historical yield trends. Here we provide a framework to characterize past yield trends and show that linear trajectories adequately describe past yield trends, which means the relative rate of gain decreases over time. Furthermore, there is evidence of yield plateaus or abrupt decreases in rate of yield gain, including rice in eastern Asia and wheat in northwest Europe, which account for 31% of total global rice, wheat and maize production. Estimating future food production capacity would benefit from an analysis of past crop yield trends based on a robust statistical analysis framework that evaluates historical yield trajectories and plateaus

Changes in Cultural Practices of Farmers in Southeast Nebraska as a Result of Their Adoption of Transgenic Crops

How do cultural practices change as producers adopt transgenic crops? A group of progressive producers in southeast Nebraska were surveyed to learn how practices changed as RR soybeans were adopted. These producers were found conservative in changing their management practices to use transgenic crops most efficiently. Tillage and planting practices were unchanged from conventional crops. Seed dealers and on-farm research were the top educational resources used in determining which varieties of soybeans to plant. Based on this study, on-farm research offers Extension an avenue for providing needed information to producers

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

Effect of Leaf Phosphorus and Potassium Concentration on Chlorophyll Meter Reading in Rice

Chlorophyll meter (SPAD) is a convenient tool to estimate leaf nitrogen (N) concentration of rice plants. There is no information on the effects of leaf phosphorus (P) and potassium (K) concentration on SP AD readings and on the relationship between SPAD values and leaf N concentration in the literature. In 1996 dry season, cv IR72 was grown at the International Rice Research Institute (IRRI) and the Philippine Rice Research Institute (PhilRice) under various N, P and K fertilizer combinations. SPAD measurements were made on the topmost fully expanded leaves at mid-tillering and panicle initiation. The leaves were then detached, dried and analyzed for N, P and K. The SPAD values were highly correlated with leaf N concentration (r = 0.93 to 0.96). Fertilizer-K application did not affect SP AD values, leaf N concentration, or the relationship between the two. Phosphorus deficiency reduced leaf N concentration at mid-tillering, but increased leaf N concentration at panicle initiation when the same amount of N was applied. The SPAD values were 1 to 2 units greater for zero-P plants than P-treated plants at a given leaf N concentration at mid-tillering. At panicle initiation, the relationship between SPAD values and leaf N concentration was not significantly affected by leaf P status. These results suggest that a different regression equation between SP AD values and leaf N concentration should be used to estimate leaf N concentration of P-deficient and P-sufficient rice leaves at vegetative stage using a SPAD

Rice yields decline with higher night temperature from global warming

The impact of projected global warming on crop yields has been evaluated by indirect methods using simulation models. Direct studies on the effects of observed climate change on crop growth and yield could provide more accurate information for assessing the impact of climate change on crop production. We analyzed weather data at the International Rice Research Institute Farm from 1979 to 2003 to examine temperature trends and the relationship between rice yield and temperature by using data from irrigated field experiments conducted at the International Rice Research Institute Farm from 1992 to 2003. Here we report that annual mean maximum and minimum temperatures have increased by 0.35°C and 1.13°C, respectively, for the period 1979–2003 and a close linkage between rice grain yield and mean minimum temperature during the dry cropping season (January to April). Grain yield declined by 10% for each 1°C increase in growing-season minimum temperature in the dry season, whereas the effect of maximum temperature on crop yield was insignificant. This report provides a direct evidence of decreased rice yields from increased nighttime temperature associated with global warming

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 georeferenced 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 74mm 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

Robust spatial frameworks for leveraging research on sustainable crop intensification

Meeting demand for food, fiber, feed, and fuel in a world with 9.7 billion people by 2050 without negative environmental impact is the greatest scientific challenge facing humanity. We hypothesize that this challenge can only be met with current and emerging technologies if guided by proactive use of a broad array of relevant data and geospatial scaling approaches to ensure local to global relevance for setting research priorities and implementing agricultural systems responsive to real-time status of weather, soils, crops, and markets. Despite increasing availability of field-scale agricultural data, robust spatial frameworks are lacking to convert these data into actionable knowledge. This commentary article highlights this knowledge gap and calls attention to the need for developing robust spatial frameworks that allow appropriate scaling to larger spatial domains by discussing a recently developed example of a data-driven strategy for estimating yield gaps of agricultural systems. To fully leverage research on sustainable intensification of cropping systems and inform policy development at different scales, we call for new approaches combining the strengths of top-down and bottom-up approaches which will require coordinated efforts between field scientists, crop modelers, and geospatial researchers at an unprecedented level