► We reviewed 221 papers that used crop models to assess impacts of climate change. ► Crops most frequently assessed were wheat, maize, soybean and rice. ► Models predominantly used radiation use ...efficiency-based approaches. ► Assumed low baseline CO
2 may exaggerate projected impacts of increased CO
2. ► Coordinated data resources and model intercomparisons may enhance impact studies.
Ecophysiological models are widely used to forecast potential impacts of climate change on future agricultural productivity and to examine options for adaptation by local stakeholders and policy makers. However, protocols followed in such assessments vary to such an extent that they constrain cross-study syntheses and increase the potential for bias in projected impacts. We reviewed 221 peer-reviewed papers that used crop simulation models to examine diverse aspects of how climate change might affect agricultural systems. Six subject areas were examined: target crops and regions; the crop model(s) used and their characteristics; sources and application of data on CO
2 and climate; impact parameters evaluated; assessment of variability or risk; and adaptation strategies. Wheat, maize, soybean and rice were considered in approximately 170 papers. The USA (55 papers) and Europe (64 papers) were the dominant regions studied. The most frequent approach used to simulate response to CO
2 involved adjusting daily radiation use efficiency (RUE) and transpiration, precluding consideration of the interacting effects of CO
2, stomatal conductance and canopy temperature, which are expected to exacerbate effects of global warming. The assumed baseline CO
2 typically corresponded to conditions 10–30 years earlier than the date the paper was accepted, exaggerating the relative impacts of increased CO
2. Due in part to the diverse scenarios for increases in greenhouse gas emissions, assumed future CO
2 also varied greatly, further complicating comparisons among studies. Papers considering adaptation predominantly examined changes in planting dates and cultivars; only 20 papers tested different tillage practices or crop rotations. Risk was quantified in over half the papers, mainly in relation to variability in yield or effects of water deficits, but the limited consideration of other factors affecting risk beside climate change per se suggests that impacts of climate change were overestimated relative to background variability. A coordinated crop, climate and soil data resource would allow researchers to focus on underlying science. More extensive model intercomparison, facilitated by modular software, should strengthen the biological realism of predictions and clarify the limits of our ability to forecast agricultural impacts of climate change on crop production and associated food security as well as to evaluate potential for adaptation.
► Identifying genetic markers for yield requires rapid quantification of crop traits. ► Proximal sensing offers promise for field-based phenotyping (FBP). ► Efficient data integration and ...modeling-assisted analysis are key for FBP. ► FBP scaled to thousands of field plots is a feasible, attainable goal. ► FBP systems require new, integrative collaborations that cross disciplines.
A major challenge for crop research in the 21st century is how to predict crop performance as a function of genetic architecture. Advances in “next generation” DNA sequencing have greatly improved genotyping efficiency and reduced genotyping costs. Methods for characterizing plant traits (phenotypes), however, have much progressed more slowly over the past 30 years, and constraints in phenotyping capability limit our ability to dissect the genetics of quantitative traits, especially those related to harvestable yield and stress tolerance. As a case in point, mapping populations for major crops may consist of 20 or more families, each represented by as many as 200 lines, necessitating field trials with over 20,000 plots at a single location. Investing in the resources and labor needed to quantify even a few agronomic traits for linkage with genetic markers in such massive populations is currently impractical for most breeding programs. Herein, we define key criteria, experimental approaches, equipment and data analysis tools required for robust, high-throughput field-based phenotyping (FBP). The focus is on simultaneous proximal sensing for spectral reflectance, canopy temperature, and plant architecture where a vehicle carrying replicated sets of sensors records data on multiple plots, with the potential to record data throughout the crop life cycle. The potential to assess traits, such as adaptations to water deficits or acute heat stress, several times during a single diurnal cycle is especially valuable for quantifying stress recovery. Simulation modeling and related tools can help estimate physiological traits such as canopy conductance and rooting capacity. Many of the underlying techniques and requisite instruments are available and in use for precision crop management. Further innovations are required to better integrate the functions of multiple instruments and to ensure efficient, robust analysis of the large volumes of data that are anticipated. A complement to the core proximal sensing is high-throughput phenotyping of specific traits such as nutrient status, seed composition, and other biochemical characteristics, as well as underground root architecture. The ability to “ground truth” results with conventional measurements is also necessary. The development of new sensors and imaging systems undoubtedly will continue to improve our ability to phenotype very large experiments or breeding nurseries, with the core FBP abilities achievable through strong interdisciplinary efforts that assemble and adapt existing technologies in novel ways.
Even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals. Recently, ecophysiological and crop models have begun to ...represent such phenomena. Most models use air temperature (Tair) in their heat stress responses despite evidence that crop canopy temperature (Tc) better explains grain yield losses. Tc can deviate significantly from Tair based on climatic factors and the crop water status. The broad objective of this study was to evaluate whether simulation of Tc improves the ability of crop models to simulate heat stress impacts on wheat under irrigated conditions. Nine process-based models, each using one of three broad approaches (empirical, EMP; energy balance assuming neutral atmospheric stability, EBN; and energy balance correcting for the atmospheric stability conditions, EBSC) to simulate Tc, simulated grain yield under a range of temperature conditions. The models varied widely in their ability to reproduce the measured Tc with the commonly used EBN models performing much worse than either EMP or EBSC. Use of Tc to account for heat stress effects did improve simulations compared to using only Tair to a relatively minor extent, but the models that additionally use Tc on various other processes as well did not have better yield simulations. Models that simulated yield well under heat stress had varying skill in simulating Tc. For example, the EBN models had very poor simulations of Tc but performed very well in simulating grain yield. These results highlight the need to more systematically understand and model heat stress events in wheat.
Gas exchange and water relations were evaluated under full-season in situ infrared (IR) warming for hard red spring wheat (Triticum aestivum L. cv. Yecora Rojo) grown in an open field in a semiarid ...desert region of the southwest USA. A temperature free-air controlled enhancement (T-FACE) apparatus utilizing IR heaters maintained canopy air temperature above 3.0 m Heated plots of wheat by 1.3 and 2.7 °C (0.2 and 0.3 °C below the targeted set-points of Reference plots with dummy heaters) during daytime and nighttime, respectively. Control plots had no apparatus. Every 6 weeks during 2007-2009 wheat was sown under the three warming treatments (i.e., Control, Heated, Reference) in three replicates in a 3 × 3 Latin square (LSQ) design on six plantings during 4 months (i.e., January, March, September, December), or in a natural temperature variation treatment (i.e., Control) in three replicates in a randomized complete block (RCB) design on nine plantings during 7 months (i.e., January, February, April, June, July, August, October). Soil temperature (Ts) and volumetric soil-water content (θs) were 1.3 °C warmer and 14% lower in Heated compared with Reference plots, respectively. Other than a 1% shading effect, no artifacts on gas exchange or water relations were associated with the IR warming apparatus. IR warming increased carbon gain characteristic of an increase in metabolic rates to higher temperature that may have been attributed to the well-watered wheat crop and the supplemental irrigation that minimized plant-to-air water vapor pressure differences between IR-warmed and nonwarmed plots. Nevertheless, seasonal oscillations in the IR warming response on carbon gain occurred. IR warming decreased leaf water status and provided thermal protection during freeze events. IR warming is an effective experimental methodology to investigate the impact of global climate change on agronomic cropping and natural ecosystems to a wide range of natural and artificially imposed air temperatures.
WINDS Model Simulation of Guayule Irrigation Katterman, Matthew E.; Waller, Peter M.; Elshikha, Diaa Eldin M. ...
Water (Basel),
10/2023, Letnik:
15, Številka:
19
Journal Article
Recenzirano
Odprti dostop
The WINDS (Water-Use, Irrigation, Nitrogen, Drainage, and Salinity) model uses the FAO56 dual crop coefficient and a daily time-step soil–water balance to simulate evapotranspiration and water ...content in the soil profile. This research calibrated the WINDS model for simulation of guayule under full irrigation. Using data from a furrow irrigated two-season guayule experiment in Arizona, this research developed segmented curves for guayule basal crop coefficient, canopy cover, crop height and root growth. The two-season guayule basal crop coefficient (Kcb) curve included first and second season development, midseason, late-season and end-season growth stages. For a fully irrigated guayule crop, the year one midseason Kcb was 1.14. The second year Kcb development phase began after the crop was semi-dormant during the first winter. The second year Kcb value was 1.23. The two-season root growth curve included a growth phase during the first season, no growth during winter, and a second growth phase during the second winter. A table allocated fractions of total transpiration to soil layers as a function of root depth. With the calibrated tables and curves, the WINDS model simulated soil moisture content with a root mean squared error (RMSE) of 1- to 3-% volumetric water content in seven soil layers compared with neutron probe water contents during the two-year growth cycle. Thus, this research developed growth curves and accurately simulated evapotranspiration and water content for a two-season guayule crop.
Guayule (Parthenium argentatum, A. Gray) is a perennial desert shrub with ratoon-cropping potential for multiple harvests of its natural rubber, resin, and bagasse byproducts. However, yield ...expectations, water use requirements, and irrigation scheduling information for ratooned guayule are extremely limited. The objectives of this study were to evaluate dry biomass (DB), contents of rubber (R) and resin (Re) and yields of rubber (RY) and resin (ReY) responses to irrigation treatments, and develop irrigation management criteria for ratooned guayule. The water productivity (WP) of the yield components were also evaluated. Guayule plants that were direct-seeded in April 2018 were ratooned and regrown starting in April 2020, after an initial 2-year harvest at two locations in Arizona: Maricopa and Eloy on sandy loam and clay soils, respectively. Plots were irrigated with subsurface drip irrigation (SDI) at 50, 75, and 100% replacement of crop evapotranspiration (ETc), respectively, and furrow irrigation at 100% ETc replacement, as determined by soil water balance measurements. The Eloy location did not include the 100% irrigation treatment under SDI due to unsuccessful regrowth for this specific treatment. The irrigation treatments at the locations were replicated three times in a randomized complete block design. After 21–22 months of regrowth, the guayule plants were harvested in plots. The results showed that DB increased with the amount of total water applied (TWA, irrigation plus precipitation), while R and Re were reduced at the highest TWA received at both locations. Ultimately, the SDI treatments with 75% ETc replacement resulted in the best irrigation management in terms of maximizing RY and ReY, and WP for both locations and soil types. Compared to the initial 2-year direct-seeded guayule crop, ratooned guayule required less TWA and attained higher DB, RY, and ReY, as well as higher WP, with average increases of 25% in dry biomass, 33% in rubber yield, and 32% in resin yield. A grower’s costs for planting the initial direct-seeded guayule crop would be offset by the additional yield revenue of the ratooned crop, which would have comparatively small startup costs.
Atmospheric CO₂ concentration (Cₐ) is rising, predicted to cause global warming, and alter precipitation patterns. During 1994, spring barley (Hordeum vulgare L. cv. Alexis) was grown in a ...strip-split-plot experimental design to determine the effects that the main plot Cₐ treatments A: Ambient at 370μmol (CO₂) mol⁻¹; E: Enriched with free-air CO₂ enrichment (FACE) at ∼550μmol (CO₂) mol⁻¹ had on several gas exchange properties of fully expanded sunlit primary leaves. The interacting strip-split-plot irrigation treatments were Dry or Wet 50% (D) or 100% (W) replacement of potential evapotranspiration at ample nitrogen (261kg N ha⁻¹) and phosphorous (29kg P ha⁻¹) fertility. Elevated Cₐ facilitated drought avoidance by reducing stomatal conductance (gₛ) by 34% that conserved water and enabled stomata to remain open for a longer period into a drought. This resulted in a 28% reduction in drought-induced midafternoon depression in net assimilation rate (A). Elevated Cₐ increased A by 37% under Dry and 23% under Wet. Any reduction in A under Wet conditions occurred because of nonstomatal limitations, whereas under Dry it occurred because of stomatal limitations. Elevated Cₐ increased the diurnal integral of A (A′) that resulted in an increase in the seasonal-long integral of A′ (A″) for barley leaves by 12% (P=0.14) under both Dry and Wet – 650, 730, 905 and 1020±65g (C) m⁻²y⁻¹ for AD, ED, AW and EW treatments, respectively. Elevated Cₐ increased season-long average dry weight (DWS; crown, shoots) by 14% (P=0.02), whereas deficit irrigation reduced DWS by 7% (P=0.06), although these values may have been affected by a short but severe pea aphid Acyrthosiphon pisum (Harris) infestation. Hence, an elevated-Cₐ-based improvement in gas exchange properties enhanced growth of a barley crop.
► Spring wheat phenology was compared for treatments of free-air controlled enhancement (T-FACE) and sowing dates. ► The T-FACE achieved warming of +1.3/+2.8
°C (day/night). T-FACE and sowing dates ...had large effects on phenology. ► Analyses with the CSM-CROPSIM-CERES Wheat model suggested that responses to T-FACE and sowing dates were similar. ► T-FACE is an effective means to mimic effects of global warming. ► Cardinal temperatures for development in CSM-CROPSIM-CERES Wheat appear to require further testing and revision.
Reliable prediction of the potential impacts of global warming on agriculture requires accurate data on crop responses to elevated temperatures. Controlled environments can precisely regulate temperature but may impose unrealistic radiation, photoperiod and humidity regimes. Infrared warming with automatic control of temperature rise has shown potential for warming field plots above ambient temperatures, while avoiding such biases. In a field experiment conducted at Maricopa, AZ, we assessed the utility of a temperature free-air controlled enhancement (T-FACE) approach by comparing phenology of wheat from a series of six sowing date treatments using T-FACE and an additional nine sowing dates that exposed crops to an exceptionally wide range of air temperatures (<0
°C to >40
°C). The T-FACE treatments were intended to achieve a warming of +1.5
°C during the daytime and +3.0
°C at night; the achieved warming averaged +1.3
°C during daytime and +2.8
°C at night. T-FACE and sowing date treatments had large effects on phenology. A regression-based analysis of simulations with the CSM-CROPSIM-CERES model showed that effects of T-FACE on phenology were similar to what would be expected from equivalent changes in air temperature. However, systematic deviations from the expected 1-to-1 relation suggested that assumed cardinal temperatures for phenology should be revised. Based on the single cultivar and location, it appeared that the base temperature for emergence to anthesis should be reduced from 0
°C to −5
°C, whereas the base temperature for grain filling should be increased from 0
°C to 4
°C and the optimal temperature, from 30
°C to 34
°C. Both T-FACE and extreme sowing date treatments proved valuable for improving understanding of high temperature effects on plant processes, as required for accurate prediction of crop responses to elevated temperatures under climate change.
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