James Nuttall

Response of wheat growth, grain yield and water use to elevated CO2 under a Free-Air CO2 Enrichment (FACE) experiment and modelling in a semi-arid environment

Abstract The response of wheat crops to elevated CO 2 (eCO 2) was measured and modelled with the Australian Grains Free‐Air CO 2 Enrichment experiment, located at Horsham, Australia. Treatments included CO 2 by water, N and temperature. The location represents a semi‐arid environment with a seasonal VPD of around 0.5 kPa. Over 3 years, the observed mean biomass at anthesis and grain yield ranged from 4200 to 10 200 kg ha−1 and 1600 to 3900 kg ha−1, respectively, over various sowing times and irrigation regimes. The mean observed response to daytime eCO 2 (from 365 to 550 μmol mol−1 CO 2) was relatively consistent for biomass at stem elongation and at anthesis and LAI at anthesis and grain yield with 21%, 23%, 21% and 26%, respectively. Seasonal water use was decreased from 320 to 301 mm (P = 0.10) by eCO 2, increasing water use efficiency for biomass and yield, 36% and 31%, respectively. The performance of six models (APSIM‐Wheat, APSIM‐Nwheat, CAT‐Wheat, CROPSYST, OLEARY‐CONNOR and SALUS) in simulating crop responses to eCO 2 was similar and within or close to the experimental error for accumulated biomass, yield and water use response, despite some variations in early growth and LAI. The primary mechanism of biomass accumulation via radiation use efficiency (RUE) or transpiration efficiency (TE) was not critical to define the overall response to eCO 2. However, under irrigation, the effect of late sowing on response to eCO 2 to biomass accumulation at DC65 was substantial in the observed data (~40%), but the simulated response was smaller, ranging from 17% to 28%. Simulated response from all six models under no water or nitrogen stress showed similar response to eCO 2 under irrigation, but the differences compared to the dryland treatment were small. Further experimental work on the interactive effects of eCO 2, water and temperature is required to resolve these model discrepancies.

‘Haying-off' in wheat is predicted to increase under a future climate in south-eastern Australia

Abstract. Under a future climate for south-eastern Australia there is the likelihood that the net effect of elevated CO2, (eCO2) lower growing-season rainfall and high temperature will increase haying-off thus limit production of rain-fed wheat crops. We used a modelling approach to assess the impact of an expected future climate on wheat growth across four cropping regions in Victoria. A wheat model, APSIM-Nwheat, was performance tested against three datasets: (i) a field experiment at Wagga Wagga, NSW; (ii) the Australian Grains Free Air Carbon dioxide Enrichment (AGFACE) experiment at Horsham, Victoria; and (iii) a broad-acre wheat crop survey in western Victoria. For down-scaled climate predictions for 2050, average rainfall during October, which coincides with crop flowering, decreased by 32, 29, 26, and 18% for the semiarid regions of the northern Mallee, the southern Mallee, Wimmera, and higher rainfall zone, (HRZ) in the Western District, respectively. Mean annual minimum and maximum temperature over the four regions increased by 1.9 and 2.2°C, respectively. A pair-wise comparison of the yield/anthesis biomass ratio across climate scenarios, used for assessing haying-off response, revealed that there was a 39, 49 and 47% increase in frequency of haying-off for the northern Mallee, southern Mallee and Wimmera, respectively, when crops were sown near the historically optimal time (1 June). This translated to a reduction in yield from 1.6 to 1.4 t/ha (northern Mallee), 2.5 to 2.2 t/ha (southern Mallee) and 3.7 to 3.6 t/ha (Wimmera) under a future climate. Sowing earlier (1 May) reduced the impact of a future climate on haying-off where decreases in yield/anthesis biomass ratio were 24, 28 and 23% for the respective regions. Heavy textured soils exacerbated the impact of a future climate on haying-off within the Wimmera. Within the HRZ of the Western District crops were not water limited during grain filling, so no evidence of haying-off existed where average crop yields increased by 5% under a future climate (6.4–6.7 t/ha). The simulated effect of eCO2 alone (FACE conditions) increased average yields from 18 to 38% for the semiarid regions but not in the HRZ and there was no evidence of haying-off. For a future climate, sowing earlier limited the impact of hotter, drier conditions by reducing pre-anthesis plant growth, grain set and resource depletion and shifted the grain-filling phase earlier, which reduced the impact of future drier conditions in spring. Overall, earlier sowing in a Mediterranean-type environment appears to be an important management strategy for maintaining wheat production in semiarid cropping regions into the future, although this has to be balanced with other agronomic considerations such as frost risk and weed control.

Managing Wheat From Space: Linking MODIS NDVI and Crop Models for Predicting Australian Dryland Wheat Biomass

This study explored the relationships between moderate resolution imaging spectroradiometer (MODIS) NDVI observations with both measured and simulated fractional green cover (FGrC), leaf area index (LAI), and above ground biomass (AGB) for dryland wheat in Australia. A total of 37 paddocks in north-western Victoria, Australia, were sampled during 2003-2006 for AGB at anthesis, and for FGrC, NDVI (from an active optical sensor), and AGB during 2012. The 2012 FGrC and NDVI measurements were fitted to MODIS NDVI, resulting in positive, linear relationships when the MODIS NDVI values were ≤ 0.80. Measured AGB was also positively, linearly related to MODIS summed NDVI, resulting in an overall R2 of 0.81 and root mean square error (RMSE) of 1397 kg/ha. Crop simulations were run for the fourteen paddocks from 2003 to 2006, and six paddocks from 2012. Four crop phenological points were selected to extract corresponding NDVI and simulated crop parameters: emergence, peak LAI, the mid-point between emergence and peak LAI, and anthesis. Linear models were fit between the MODIS NDVI and simulated values of FGrC, LAI, and AGB. Overall, the highest R2 values corresponded to using all of the dates for FGrC (R2 = 0.82) and AGB (R2 = 0.92), and anthesis dates for LAI (R2 = 0.74). For FGrC and AGB, the RMSE with simulated parameters were comparable or better than the equivalent results from the in situ measurements (note that there were no LAI in situ measurements to compare with). The results support the notion for extending the value of the MODIS NDVI using crop simulation models. The combination of remotely sensed and simulation data might offer regional maps of spatial AGB and ultimately grain yield, which would have high value for research, resource management, policy, and potentially, crop management.

In-field methods for rapid detection of frost damage in Australian dryland wheat during the reproductive and grain-filling phase

Abstract. Frost damage causes significant production losses and costs to Australian dryland wheat, and frost impacts are not expected to decline in the near future, despite global warming. Rapid estimation of frost damage to crops on a spatial basis would allow for timely management decisions to reduce the economic impact of frost events. In this paper, we take a first step in evaluating the utility of hyperspectral reflectance and active light fluorescence for detecting frost damage to wheat during its reproductive phase. Two experiments were conducted immediately after the first observation of frost damage, (i) in 2006, five plots in an existing trial were opportunistically subdivided to take spectral reflectance measurements on frost damaged plants along with yield measurements, and (ii) in 2015, a transect across 31 rows within a commercial paddock was established to evaluate spectral reflectance, fluorometer measurements, and yield along a gradient from non-frosted to frost damaged plants. The results of the hyperspectral reflectance data appeared variable in response across the two experimental sites where frost was observed in-crop. In 2006, hyperspectral-derived indices showed significant differences (P < 0.05) between measurements of frosted and non-frosted canopies, but this was not the case for observations taken in 2015, where the mean response was reversed between experimental sites for several of the indices. In contrast, fluorometer measurements in the 2015 trial resulted in higher correlations with yield and observed frost damage compared with the reflectance measurements. Seven of the nine fluorometer indices evaluated were correlated with yield (used as an indicator of frost damage) at P < 0.01. An index of compounds which absorbs at 375 nm, FLAV, had the best correlation coefficients of 0.91 and 0.90 for the two dates in 2015. The fluorescence index FLAV was selected to evaluate whether it could be used to classify the canopy as frost affected or not, using discriminant analysis for the 2015 transect data. The overall classification accuracy, defined as the number of correctly classified measurements (57) divided by the total number (62) was 92%. The present study was not able to provide insight into how rapidly the sensors could detect frost damage before detection with the naked eye, as the survey data constituted a transect based on early visual symptoms, however this study does provide important insight into what sensors and/or indices may be sensitive to ‘seeing’ early frost damage in-crop. The next steps, which build on this work and need to be resolved are (i) what is the nominal scale of measurements required, and for which portions of the plant canopy? (ii) How robust (over space and time) are any relationships between frost damage and index response? (iii) Can frost damage be detected before the onset of visual damage?

Managing wheat from space: Linking MODIS NDVI and crop models for Australian dryland wheat

The purpose of this study was to begin to explore the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI observations with both measured and simulated above ground biomass (AGB), fractional green cover (FGrC), and leaf area index (LAI) for wheat in Victoria. These initial comparisons of MODIS NDVI with both measurements and simulation results indicate positive, linear relationships for FGrC, LAI, and AGB and either NDVI or summed NDVI. Measurements of AGB from 2012 were fitted with a linear model to summed NDVI from MODIS, resulting in an R2 of 0.83. The results support the potential for extending the value of the MODIS NDVI using crop simulation models. The combination of remotely sensed and simulation data might offer regional maps of AGB and yield, which would have high value for research, resource management, policy, and potentially, crop management.

Modelling soil carbon in agricultural systems: a way to widen the experimental space

Mechanistic and explanatory simulation models provide robust and objective methods to extrapolate likely responses of crops and soils to climate change over different landscapes and time periods. Central to such simulation models are the supply of mineralised nutrients, in particular nitrogen, to crops through linked crop and nutrient sub-models that is achieved through modelling soil carbon dynamics. Attention to soil processes is therefore an essential part of building robust and sustainable production systems and understanding the potential impacts of climate change. To the farmer, focus must be on the productive capacity of the land and its rejuvenation to sustain production. In the broader context of reducing atmospheric CO2 concentration through soil C sequestration, understanding soil processes and the immediate environment likewise require attention to productivity issues. This is because without maintaining productivity a better understanding of soil organic carbon (SOC) processes is unlikely to lead to increased SOC sequestration in Australias farming land. Some gaps in knowledge of how to manage SOC are being addressed in a national research effort, including the scant measured data against which models can be tested. Nevertheless, continuing to apply models to push the boundaries well beyond what can be achieved in practice widens the experimental space, allowing new ideas to be tested where physical experiments are not possible. This raises optimism that new ways may be discovered to explain change in SOC and increase SOC where it is possible in a beneficial way.