Leaf area duration key to yield in HRZ

Green leaves.

Fungicides as canopy management tools can help extend leaf area duration.

Yield can be increased by keeping the crop canopy greener for longer with the use of fungicides, according to research by the Foundation for Arable Research Australia (FAR).

The research, funded by the Grains Research and Development Corporation (GRDC), found that in the high rainfall zone (HRZ), canopy greenness directly correlates with yield.

FAR managing director Nick Poole says while fungicides are agents for controlling disease, their action is on the crop canopy. Fungicides as canopy management tools can help extend leaf area duration (LAD) – a measure of green leaf retention over time. However, canopy greenness is not easy to measure.

“We don’t talk about LAD very often because it’s difficult to measure, but it is the number of square metres of green leaves there are on one square metre of ground over a period of time,” Mr Poole said. “That’s where it’s useful to think about what fungicides are doing. They’re keeping crops greener for longer and over time you need to measure that effect.”

Environmental conditions – specifically moisture availability – have an overriding influence on the effect of fungicides. Research conducted by Dr James Hunt, CSIRO, using the Agricultural Production Systems Simulator (APSIM) has produced a green leaf retention calculator, which tells growers what is at stake for different levels of yield potential if green leaf area is lost through the grain fill period (Figure 1).

Graph measuring relationship between leaf area duration and yield.

Figure 1: Relationship between LAD and yield

If growers want to increase LAD, Mr Poole said they should be thinking about which leaves to preserve.

“If you put out fungicides too early, then you may be preserving leaves that don’t persist during grain fill period – they’re dead in the finish,” he said.

“Broadly speaking, if you’re designing a fungicide strategy based around disease in any region, you need to remember it’s those top three leaves that you’re trying to keep green in wheat, and the three leaves under the flag leaf in barley. The strategy you develop needs to take account of that. Those leaves will be the ones that stay green during grain fill or post-anthesis.”

Chronologically, there are two sources of carbohydrates which are divided by being pre-anthesis – or pre-flowering – and post-flowering sources. Pre-anthesis, when the crop has grown its canopy and the crop is at ear emergence, plants produce a large amount of carbohydrates. However, at this development stage there are no grain sites to fill with this carbohydrate source, so it is stored in the stem.

Following flowering, when grain sites have been fertilised, the carbohydrate can be redirected to the head.

“That’s why sometimes if there is severe drought and little LAD after flowering, grain can still be produced because the pre-anthesis photosynthesis carbohydrate stored in the stem can be redistributed to the head,” Mr Poole said.

“But in the HRZ, where there are longer season scenarios with higher yield expectations, the carbohydrate source that’s more important is that derived from the top two leaves – the stem and the ear post-anthesis. The work of those leaves and stem puts carbohydrates straight into the developing grain. It might sound obvious, but that key difference relates to differences in fungicide response between drier and wetter regions.

“If you think back to the idea of maintaining green leaf, you can actually use APSIM to generate some expected yields, and these yields correlate to an absolute level of LAD. You can then use APSIM to calculate the effect of losing 5 percent to 60 percent of that LAD after flowering (Table 1). This gives you some kind of gauge as to how much that disease could cost you and how much one could spend to protect the crop from the disease.” 

Table 1: Simulated influence of green leaf loss (LAD) on yield based on different expected yield outcomes for the season (APSIM output for SFS00017 project).

Expected yield (t/ha)

5%

10%

20%

30%

40%

50%

60%

1.8

1.8

1.7

1.7

1.6

1.5

1.5

1.4

2.4

2.3

2.3

2.1

2.0

1.9

1.8

1.6

2.9

2.9

2.8

2.6

2.4

2.2

2.1

1.9

3.5

3.4

3.3

3.1

2.8

2.6

2.4

2.1

4.0

3.9

3.7

3.5

3.2

3.0

2.7

2.4

4.5

4.3

4.2

3.9

3.6

3.3

3.0

2.6

4.9

4.8

4.6

4.3

4.0

3.7

3.3

2.9

5.3

5.2

5.0

4.7

4.4

4.0

3.6

3.2

5.7

5.5

5.4

5.1

4.7

4.3

3.9

3.4

6.0

5.9

5.7

5.4

5.1

4.6

4.2

3.7

6.2

6.1

6.0

5.7

5.4

4.9

4.5

3.9

6.4

6.3

6.2

6.0

5.6

5.2

4.7

4.2

GRDC Project Code SFS00017

Region South