Biological forecasting system to control Sigatoka leaf spot disease

Biological forecasting system to control Sigatoka leaf spot disease

The biological forecasting system to control Sigatoka leaf spot disease monitors the development of the disease in order to control it with a minimum of fungicide applications. The aim of the method is to block the development of the disease towards necroses. Since the efficiency of the treatments relies on a strong curative effect, systemic fungicides are preferred to contact fungicides. Adding mineral oil to the fungicide will also increase its curative effect. The method is not suitable for areas that receive rain all year round and works best when the logistics and decision-making is centralized and done by specialists. Besides lowering the cost of controlling leaf spot diseases, it also minimizes the impact on the environment. The forecasting system was later adapted to control black leaf streak disease.

Methodology

The timing of the decision to apply fungicides takes into account the development of the disease and of the plant, both of which are climate driven. The first step consists in setting up a field-based monitoring system. The main parameter that needs to be assessed is the stage of evolution of the disease (SED). The SED is also a good indicator of the efficiency of the fungicide applications. The complete protocol is published in Fruits1 .

Observation plot

In general, 10 banana plants that have between 8 to 10 leaves are used to monitor the progress of the disease. The 10 plants should be randomly selected two months after planting and labeled. The observation of symptoms is preferably done on non-flowering plants once a week. It is recommended to plant 20 new plants every 3 to 4 months to ensure that non-flowering plants are available for observation after the first ones have flowered.

The number of banana plots will depend on the area covered by the warning system and the presence of micro-climates. One plot will cover an area between 20 and 200 ha, depending on its uniformity.

Data collection

Every week, note down the number of banana leaves on each plant and the stage of unfolding of the cigar leaf, using Brun's scale. The stages of development of the cigar leaf are scored as follows: stage A=0, stage B=2, stage C=4, stage D=6 and Stage E=8.

Every week, for each plant, note down, for each of the first 5 leaves, the most advanced stage of the disease. On the data sheet, for each leaf number, put an 'x' in the corresponding disease stage column (leave blank if the leaf doesn't show any symptom):

• Stage 1: A minute yellowish-green speck (<1 mm) is just visible to the naked eye.
• Stage 2: The streak increases in size, notably in length (>1-2 mm), and remains yellowish-green.
• Stage 3: The streak begins to broaden slightly as well as to increase in length. It begins to turn rusty red.
• Stage 4: This is the first spot stage. The streak turns dark brown, is sunken and has reached its final size. A water-soaked yellow halo forms around the spot. Conidia are formed at this stage.
• Stage 5: This is the final stage of the lesion. The central area of the spot turns grey and the margins of the spot are black. Some minute black dots are visible in the central area. They are the perithecia and spermogonia that produce the ascospores and spermatia.

Estimation of the SED

Determining the SED requires the calculation of a coefficient, which represents the speed at which the disease develops, and of the foliar emission rate (FER).

Calculation of the coefficient

The stage of the disease and the leaf number (counting from the youngest leaf whose leaf number is 1) are used to determine the value of the coefficient (see table below). For a given leaf number, the more advanced the disease stage, the faster the disease develops. For a given disease stage, the younger the leaf, the faster the disease develops.

Calculation of the FER

Calculate the FER for each sampled plant as follows:
FER = ((Current number of leaves) + (0.1 x Current cigar stage)) - ((Previous number of leaves) + (0.1 x Previous cigar stage))

Add the FER of each sampled plant to obtain the Sum_FER.

Calculate the FER for 10 days as follows:
FER_10d = (Sum_FER x 10) / (Number of banana plants x Number of days between observations)

Calculate the FER for the current week as follows:
FER_{CURRENT WEEK} = (FER_{PREVIOUS WEEK} + FER_10d) / 2

Calculation of the weekly SED

SED = Sum_coef x FER_{CURRENT WEEK}

Timing of fungicide applications

Plot the SED over time to decide when to spray. The SED should not exceed 2,500 to maintain fungicide efficiency. The decision to spray will depend on the shape of the trend. A sharp increase in the SED will trigger a treatment. After a treatment the SED will decline and no other treatment will be scheduled until another significant increase in the SED.

Example of the timing of fungicide applications based on weekly fluctuations in SED.
(Source Ganry et al. 20081 )

Troubleshooting

A biological forecasting system is best used in regions where there is a dry period (even as short as one month), the disease pressure is low and fungicide resistance has not been observed. The disease will be better controlled if the data collecting, the decision to treat and the logistics of treatment are handled by a well-trained technical unit, instead of being left to the individual producers. Growers, however, can help keep inoculum level low through regular deleafing, especially before a scheduled treatment.

If the SED doesn't decline after an application, it means that the treatment hasn't been effective. It could be due to various factors, such as poor coverage, the choice of fungicide(s), the fungus is losing its susceptibility to the fungicide or the inoculum level is too high.

Using mineral oil as a carrier for the fungicide will improve the efficiency of the treatment. Only fungicide formulations that are compatible with pure oil should be used. The phytotoxic effect of the oil should also be known to determine the concentration to use.

Depending on the type of fungicide used, and the length of time the fungus is exposed to the fungicide, there is always a risk of fungal populations developing resistance to the fungicide. Monitoring this indicator and taking appropriate action, such as changing fungicides or alterning them, will reduce the selection for resistant fungal strains.

References

Also on this website

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