Summary

Pesticides Research No. 116 2008 of fungicide application in winter wheat

The control of leaf diseases in cereals is usually performed using the same dose in the entire field based on an assessment of disease incidence in the field as a whole. However, there may be large differences in the need for disease control in different parts of a field. A site-specific fungicide application therefore potentially offers several advantages, including a better overall yield response to applied fungicide, a smaller amount of fungicide deposited on the soil surface and a reduction in fungicide use.

The objectives of the project were to clarify which factors influence the need to spatially vary fungicide treatments in winter wheat, and how these factors can be monitored using available tractor mounted sensors. The following specific objectives were considered:

To study how the spatial variation in diseases in winter wheat (particularly mildew and septoria) depends on the variation in canopy structure (leaf area), nitrogen (N) concentration in leaves and variation in topography and soil type.
To study the effects of canopy structure for yield and deposition of fungicides on wheat, including the distribution of fungicides on the top three leaves and the soil surface.
To study how the yield increase from fungicide application depends on canopy structure, N-uptake, soil conditions, yield level and disease occurrence.
To describe and parameterise a model to be used for optimised spatially varying fungicide doses, and to assess the effect of application of this model on yield and fungicide use.

Field experiments were carried out in winter wheat in 2005 and 2006 at two sites in Denmark ín each year. The sites were Nissumgård and Schackenborg in 2005 and Nissumgård and Dybvad in 2006. All sites had high spatial variation in soil and terrain. Each experiment was conducted in a two-factorial design with fungicide dose (4 levels) and N strategy (4 levels). The fungicide treatments consisted of increasing doses of Opus (0 to 0.8 L ha^-1) applied at GS 39. The N strategies consisted of three different rates of mineral fertiliser N applied in a split treatment and a normal rate of N applied in a single treatment. The experimental factors were laid out in a randomised split-plot design with N-strategy as whole-plot factor and fungicide dose as sub-plot factor. These blocks were repeated 10 times across the field in an attempt to cover most of the soil variation between replicate blocks.

The soil and terrain variation were characterised in spring by measurements with RTK-GPS (for elevation, slope and aspect), EM38 (geoelectric measurement of soil texture) and MobilTDR (soil water capacity and soil impedance). There was a good relationship between measurements with EM38 and MobilTDR at all sites, except Schackenborg, most likely due to large organic matter contents in parts of the field at Schackenborg.

There was a consistent grain yield response to N strategy in all experiments, although this response was weak at Nissumgård in 2006 due to a very large spatial variation in crop establishment. However, the N strategies were primarily included to increase the variation in crop density and N status. There was only a small, but significant, yield response to fungicide rate in 2005, but a larger yield response to fungicide application in 2006, in particular at Dybvad. The yield gains of fungicide application became zero or negative in 2005, when the costs of applying fungicides were subtracted.

Measurements of crop status were taken by hand held sensors (SPAD, LAI2000 and VIScan) and using tractor-mounted sensors (MobilLas) at GS39. These measurements were taken in all plots. For comparison destructive plant sampling was performed in selected plots. This comparison showed that the SPAD measurements give good estimates of leaf N concentration and LAI2000 good estimates of crop leaf area index (LAI). The measurements of crop spectral reflectance with VIScan were expressed as the ratio vegetation index (RVI), which was found to correlate well with wheat LAI throughout the growing season, except for the measurements at Schackenborg at GS39, probably due to a high stand of weeds (mainly Poa annua) at this site and measurement time.

The diseases were assessed four times during the growing season. The diseases were dominated by Septoria tritici, and the coverage of septoria on the 2^nd leaf at GS65 and the flag leaf at GS75 were taken as indicators for disease occurrence. This disease index decreased with increasing fungicide rate. The occurrence of septoria varied spatially, in particular depending on leaf N concentration and possibly also related to LAI.

The deposition of fungicides on each of the top three leaves and on the soil surface was measured using a tracer mixed in the fungicide solution used for spraying the crop at GS39. The fungicide deposition in terms of tracer concentration per leaf area varied strongly between the top three leaves with the highest concentration on the upper leaves. There was a tendency for the highest concentrations at high LAI, which may be related to leaf inclination, as there was a significant correlation to mean leaf angle. However, this effect was strongest for leaf 3 and there were only weak relationships for leaf 1 and 2. As it is the disease control on the upper two leaves that provides the main effect on yield gain from disease control, the effect of varying leaf fungicide concentrations with varying canopy density was ignored in the development of the algorithms for sensor based fungicide application.

The low driving speed (4 km h^-1) used in the experiment may be supposed to give a deeper penetration into the canopy and thus less deposition on the upper part of the canopy compared to the deposition pattern obtained using a driving speed (8 km h^-1) closer to the situation in practical agriculture. A supplementary experiment showed such a deposition pattern. At 4 km h^-1 deposition of spray liquid per area unit leaf was only slightly reduced at the 2^nd leaf and the value on the 3^rd leaf was close to 75% of the deposit on the flag leaf. At 8 km h^{-1 a much steeper gradient in deposit was found, with a value on the 3rd} leaf close to 40% of the per area unit deposit on the flag leaf.

The grain yield without disease (disease free yield) was found to be better correlated to crop sensor measurements (LAI, leaf N concentration and RVI) at GS39 than to soil measurements taken in spring. However, the usefulness of the RVI measurements at Schackenborg was reduced due to a large weed population.

The generally low disease pressure in 2005 and 2006 gave a poor relationship between yield response to fungicide application and crop characteristics. Analysis of yield gain from fungicide application showed significant positive correlations between yield gain and leaf N concentration or RVI at GS39, in particular at Dybvad with the highest septoria attack and the smallest error variation in grain yields. There were also significant positive relationships between normalised disease response to fungicide application and the measurements of leaf N concentration and RVI, which indicates that fungicides may be less effective in controlling disease in dense and nutritious crops.

The relevant crop characteristics could be measured using handheld sensors. Analyses of the tractor-mounted measurements using the MobilLas measurements indicate that it is possible also to perform these measurements in practice for the RVI measurements, whereas it is considerably more difficult to measure leaf area index (LAI) with sufficient precision using tractor mounted sensors. This is due to the saturation of the laser sensor measurements at LAI above 2.5-3.0.

Two different algorithms (an empirical model and a causal model) for spatially varying fungicide application were developed. Both models make use of RVI and EM38 measurements. EM38 describes the soil characteristics, in particular the soil clay content. This measurement can be made only once and used subsequently, whereas the RVI measurement needs to be taken at GS39 at the time of fungicide application. Both types of measurements are operationally available today.

Both algorithms were estimated to give a higher need for fungicide application for crops having a higher RVI. This was an indirect effect for the empirical model, whereas both higher grain yield and a higher septoria occurrence and high RVI contributed to this effect for the causal model.

The applicability of the sensor-based models for spatially varying fungicide application was evaluated using data from the four experiments. However, only plots that had received the normal N fertiliser rate were used for this purpose.

The evaluation of the model showed that the estimated variation in fungicide rate within the field varied between experimental sites, but the standard deviation was generally in the order of 0.1 to 0.2 L ha^-1 Opus. There were only small yield gains from applying the spatially variable fungicide rate using data on variation in soil and crop conditions at the normal N rate in the field experiments conducted in this project, when comparing with a uniform fungicide rate of 0.4 L ha^-1 Opus. There was mostly a reduction in fungicide deposition on the soil from applying the sensor-based fungicide rates compared with the uniform fungicide rate.

The evaluation showed that the largest yield gains from sensor-based fungicide application were obtained in situations with either very low or high disease infestation. There may thus be some scope for applying sensor-based fungicide rates in winter wheat. However, this will require further testing under a wider range of soil and climatic conditions, and this should also include a larger variation in the selection of varieties.