FORECASTING LOSSES FROM SEED BORNE DISEASES & ACCESSING DISEASE TOLERANCE FOR SEED HEALTH TESTING OUTLINES DISEASE FORECASTING METHODS OF DISEASE FORECASTING USES OF DISEASE FORCASTING EXAMPLES ACCESSING DISEASE TOLERANCE IN SEED HEALTH TESTING FACTOR AFFECTING THE YIELD REDUCTION SOME PATHOGENS RESPONSIBLE FOR YIELD REDUCTION EXAMPLES DISEASE FORECASTING Forecasting involves all the activities in determining and notifying the growers of community that conditions are sufficiently favourable for certain diseases, that application of control measures will result in economic gain or on the other hand and just as important that the amount expected is unlikely to be enough to justify the expenditure of time, energy and money for control. METHODS OF DISEASE FORECASTING FORECASTING BASED ON PRIMARY INNOCULUM FORECASTING BASED ON WEATHER CONDITIONS FORECASTING BASED ON CORELATIVE INFORMATION USE OF COMPUTER FOR DISEASE FORECASTING USES OF DISEASE FORECAST FOR TIMELY PLANT PROTECTION MEASURES LOSS ASSESSMENT FOR MAKING STRATEGIC DECISION FOR MAKING TACTICAL DECISION Stewarts wilt of maize c.o.- Erwinia stewartia Based on average air temperature in December, January and February. Pea root rot c.o.- Aphanomyces euteiches Based on initial inoculation level. Soils collected from prospective fields are brought to green house and peas planted, if severe root rot is observed then plot is not recommended for pea cultivation. Root and Crown rot of Sugar Beet: C.O.- Sclerotium rolfsii Sclerotia found in soil. (1-3mm) Depends on the number of sclerotia present in soil. Apple scab C.O.- Venturia inequalis By monitoring air temperature, relative humidity, rainfall and leaf wetness. High RH (>90%) for 10hrs or more and warm temperature period favours infection rate. Yellowing in Beet: C.O.- BMYV (Beet Mild Yellowing Virus) Vector- Aphid (Myzus persicae) Watson et. Al. (1975) determined that the severity depends on number of frost days and mean temperature during April. ACCESSING DISEASE TOLERANCE IN SEED HEALTH TESTING Neergaard (1962a, 1962b) presented some fundamental ideas for establishing disease tolerances in seed health testing. These principles include consideration of the importing country's quarantine requirements, the geographic destinations of the seed lot, the frequency of occurrence of the pathogen with the seed, the planting rate and the possibility of successful disinfection. Factor affecting the yield reduction The main factor is the degree of correlation between seed-borne inoculum potential and crop losses. As per the principle mentioned above the seed transmission / yield reduction ratio is more or less established between them. Some pathogens responsible for yield reduction: Three pathogens produced crop losses in terms of percent yield reduction different from that of the degree of the severity of seed

2. OUTLINES
• DISEASE FORECASTING
• METHODS OF DISEASE FORECASTING
• USES OF DISEASE FORCASTING
• EXAMPLES
• ACCESSING DISEASE TOLERANCE IN SEED HEALTH TESTING
• FACTOR AFFECTING THE YIELD REDUCTION
• SOME PATHOGENS RESPONSIBLE FOR YIELD REDUCTION
• EXAMPLES

3. DISEASE FORECASTING
Forecasting involves all the activities in determining and
notifying the growers of community that conditions are
sufficiently favourable for certain diseases, that
application of control measures will result in economic
gain or on the other hand and just as important that the
amount expected is unlikely to be enough to justify the
expenditure of time, energy and money for control.
Miller and O’Brien, 1952

4. METHODS OF DISEASE
FORECASTING
1. FORECASTING BASED ON PRIMARY INNOCULUM
2. FORECASTING BASED ON WEATHER CONDITIONS
3. FORECASTING BASED ON CORELATIVE INFORMATION
4. USE OF COMPUTER FOR DISEASE FORECASTING
Aktaruzzaman, M, 2013

5. USES OF DISEASE FORECAST
• FOR TIMELY PLANT PROTECTION MEASURES
• LOSS ASSESSMENT
• FOR MAKING STRATEGIC DECISION
• FOR MAKING TACTICAL DECISION
Patel, S, 2015

6. Stewarts wilt of maize
c.o.- Erwinia stewartia
• Based on average air temperature in
December, January and February.
Pea root rot
c.o.- Aphanomyces euteiches
• Based on initial inoculation level.
• Soils collected from prospective fields are
brought to green house and peas planted, if
severe root rot is observed then plot is not
recommended for pea cultivation. Patel, S, 2015

7. Root and Crown rot of Sugar Beet:
C.O.- Sclerotium rolfsii
• Sclerotia found in soil. (1-3mm)
• Depends on the number of sclerotia
present in soil.
Few Sclerotia in
the soil sample
Sow Sugar beet
as planned
Many sclerotia in
the soil sample
Do not sow sugar
beet at all or Use
resistant variety
Patel, S, 2015

8. Apple scab
C.O.- Venturia inequalis
• By monitoring air temperature,
relative humidity, rainfall and
leaf wetness.
• High RH (>90%) for 10hrs or
more and warm temperature
period favours infection rate.
Patel, S, 2015

9. Yellowing in Beet:
C.O.- BMYV (Beet Mild Yellowing
Virus)
Vector- Aphid (Myzus persicae)
• Watson et. Al. (1975) determined that the
severity depends on number of frost days
and mean temperature during April.
Patel, S, 2015

10. ACCESSING DISEASE TOLERANCE
IN SEED HEALTH TESTING
• Neergaard (1962a, 1962b) presented some fundamental ideas
for establishing disease tolerances in seed health testing.
• These principles include consideration of the importing
country's quarantine requirements, the geographic
destinations of the seed lot, the frequency of occurrence of
the pathogen with the seed, the planting rate and the
possibility of successful disinfection.
Neergaard, P, 1977

11. FACTOR AFFECTING THE YIELD
REDUCTION
• The main factor is the degree of correlation between seed-borne
inoculum potential and crop losses.
• As per the principle mentioned above the seed transmission / yield
reduction ratio is more or less established between them.
Neergaard, P, 1977

12. SOME PATHOGENS RESPONSIBLE
FOR YIELD REDUCTION:
• Three pathogens produced crop losses in terms of percent yield reduction
different from that of the degree of the severity of seed.
Ascochyta pisi 11% yield reduction
Mycosphaerella pinodes 45% yield reduction
Phoma medicaginis var. pinodella 25% yield reduction
Neergaard, P, 1977

13. EXAMPLES
• The infection percentage identified in the laboratory for Ustilago nuda may
readily be converted into the percent yield reduction to be expected, with the
ratio 1:0.8 being applicable, resulting in minimum crop losses to be predicted.
• Corynebacterium insadiosum, commonly known as bacterial wilt of lucerne.
The disease normally does not appear until the lucerne stands are approximately
two years old, and then it gradually kills the plant during the following years.
• In seed-borne downy mildew the optimal tolerance must be zero. If it is not for
this type of pathogen so the pathogens should be quarantined.
Neergaard, P, 1977