1. 1.4 Assessment of yield losses imposed by plant pathogens Introduction and definitions Effects of plant pathogens on host physiology Effects of plant pathogens on yield and its components Models for loss assessment Concluding remarks

2. Time Disease intensity Time Yield Loss prediction Why do we need (want) to assess yield loss? or What are the uses of yield loss records For identifying the time when control is needed and assisting to develope effective management procedures. For making decision concerning the need of disease management (cost/effective calculations).

3. Why do we need (want) to assess yield loss? or What are the uses of yield loss records For administrative decisions: making priorities in research, breeding, allocation of efforts, etc. For insurance purposes. Time Disease intensity Time Yield Loss assessment

4. Loss assessments can be made on several scales: Individual plants Small plots (e.g., experimental plots) Individual field Regions Nations The entire world

5. How plant pathogens affect their hosts ? Effects on host physiology Effects on host development Effects on yield quantity Effects on yield quality Leaf infection

6. Effects on host physiology Effects on host development Effects on yield quantity Effects on yield quality Stem infection How plant pathogens affect their hosts ?

7. Effects of plant pathogens on their hosts Effects on yield quantity Effects on yield quality Fruit rot Effects on host development Effects on host physiology

8. Effects on yield quantity Effects on yield quality Fruit ghost spots Effects on host development How plant pathogens affect their hosts ?

9. Effects on host physiology

10. Effects of plant pathogens on host physiology Effects of radiation interception (RI) Effects of radiation use efficiency (RIE) reflected radiation intercepted radiation transmitted radiation

11. Effects of plant pathogens on host physiology Effects of radiation interception Stand reducers Seedling diseases

12. Effects of plant pathogens on host physiology Effects of radiation interception Tissue consumers Alternaria macrospora in cotton

13. Effects of plant pathogens on host physiology Effects of radiation interception Leaf senescence accelerators Alternaria solani in tomatoes

14. Effects of plant pathogens on host physiology Effects of radiation interception Light “stealers” Smutty mold (Aspergillus sp.) in cotton

15. Disease severity (%) Photosynthesis rate (%) 050100 0 50 100 invaded area infected area Necrotic area Effects of plant pathogens on host physiology Effects of radiation use efficiency photosynthetic rate reducers

16. Effects of plant pathogens on host physiology Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 stomata Alternaria stomata

17. Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 Powdery mildew stomata

18. Effects of radiation use efficiency Turgor reducers Disease severity (%) Transpiration rate (%) 050100 0 50 100 rusts stomata rust pustules

19. Effects of radiation use efficiency assimilate suppers Powdery mildews

20. Quantification of yield losses

21. Effects of Alternaria macrospora on cotton yield (mean of 11 field experiments) Treatmentyield (t/ha)yield increment t/ha% Untreated Maneb 4.26 5.03 - 0.78 - 15.4 Tebuconazole5.701.4425.2

22. Measurement of yield loss: which reference to use? Commercially managed-plot yield (t/ha) Untreated-plot yield 3.0 5.0 Attainable yield 8.0 Potential yield 15.0 -40% +66% Healthy-plot yield 6.0 -50% +100%

23. Measurement of yield loss: what is the reference? Differences between yield of a reference plot and yield of a diseased plot Loss = [yield of reference plot] - [yield of diseased plot] Reference plots: A non-infected (healthy) plot The least infected plot in the experiment Average yield of commercial plot in the area

24. Measurement of yield loss: what is the reference? Differences between estimated yield of a healthy plot and yield of a diseased plot Loss = [estimated yield of healthy plot] - [yield of diseased plot] Disease severity (%) Yield (t/ha) 0100

25. The damage function The quantitative relationship between disease intensity and yield (or yield loss) Disease intensity ( %) Yield (t/ha) Disease intensity ( %) Yield loss (%)

26. The damage function Disease intensity Yield Linear Disease intensity Yield Logarithmic Disease intensity Yield Compensation Disease intensity Yield Optimum

27. The relationship between the time of disease development and the resultant yield loss

28. Yield components of cereals Emergence Tillering Boot stage Grain filling

29. Yield components of cereals no. of spikelets per ear no. of spikelets per unit area no. of grains per spikelet no. of grains per unit area Yield per unit area weight of a grain no. of plants per unit area no. of ears per plant no. of ears per unit area

30. The yield components that are affected by plant diseases are those that are created at, or soon after, the time of disease onset % difference No. of ears/plant No. spikelets/ear Grain wt. Yield 19.1* 7.6 4.2 28.5* Growth stage tillering Disease severity (%) untreated sprayed emergence Effects of powdery mildew in barley on yield and its components

31. milk Growth stage tillering Disease severity (%) Effects of Septoria tritici blotch in wheat on yield and its components untreated sprayed earing % difference No. of ears/plant No. spikelets/ear No. grains/spikelet Grain weight Yield 2.5 0.8 8.1* 8.0* 18.1*

32. In Israel, Septoria tritici blotch in wheat affects only the weight of individual grains. Thus, there is no need to control the disease before the earing stage. Similarly, the is no need to control the disease after most of the grain weight was accumulated.

33. Yield components of a board-leaf plant Emergence Vegetative growth Reproductive growth Yield production

34. Yield components of a broad-leaf plant weight of individual fruit Yield per unit area no. of plants per unit area no. of fruits per plant no. of fruits per unit area

35. Effects of Alternaria in cotton on yield and its components Boll weightBoll Number untreated sprayed Yield

36. A. macrospora affect only the number of bolls per plant. Bolls are shed only at the initial stages of their development. Thus, disease management is very important early in the season when the bolls are small, but not towards the end of the season, when the bolls had already developed enough.

37. Yield loss models

38. The critical point model Disease severity at time G1 (%) Yield (t/ha) Time Disease severity (%) G1 harvest disease assessment Y =  0 -  1 X Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 = reduction in yield for each percent increase in disease severity X = disease severity of the diseased plot

39. The critical point model is used mainly in cereals. In cereals have distinct growth stages and it is possible to determine precisely which crop growth stage is affected most by the disease. This stage should be chosen to be the “critical” stage - for assessment. Critical point models are used mainly for “after- season” loss assessment. Uses of critical point models

40. The multiple point model Time Disease severity (%) T1T2T3T4T5T6T7T8 Y =  0 -  1 X 1 -  2 X 2 -  3 X 3 -  4 X 4 -  5 X 5 -  6 X 6 -  7 X 7 -  8 X 8 Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 -  8 = reduction in yield in each sampling for each percent increase in disease severity X 1 -X 8 = disease severity of the diseased plot in each date harvest disease assessments

41. The multiple point model is used mainly in broad-leaf crops. In broad-leaf crops yield is accumulated during a long period and there are no distinct growth stages. In many cases, the disease affect yield during the whole period of its accumulation. Multiple point models are used mainly for “after-season” loss assessment. Uses of multiple point models

42. Time Disease severity (%) T1T2T3T4 Critical severity The critical time model Time for critical severity (days) Yield (t/ha) Y =  0 +  1 X Y = yield of a diseased plot  0 = estimated yield of a plot infected at day 0  1 =increase in yield for each day of delay in time to critical severity X = time for critical severity in diseased plot

43. Critical time models may be used in both cereals and broad-leaf crops. These models are applicable in situations where disease onset vary markedly from year to year and from location to location. The critical time models may be used for decision making. For that purpose, the critical severity level to be used should be low enough, to enable proper disease suppression. Uses of critical time models

44. The Area Under the Disease Progress Curve (AUDPC) model Time Disease severity (%) AUDPC (Disease*days) Yield (t/ha) Y =  0 -  1 X Y = yield of a diseased plot  0 = estimated yield of a healthy plot  1 =decrease in yield for each increase in AUDPC unit X = AUDPC units

45. The AUDPC models are used in both broad-leaf and cereal crops. In most cases, a very good relationship exist between AUDPC values and yield. The AUDPC models are used mainly for “after-season” loss assessment. Uses of the AUDPC models

46. Concluding remarks Losses may be predicted early in the season for management decision making or after the season for general analyses. Plant pathogens may affect the physiology of the host and result in yield losses directly or indirectly. Determination of the yield component to be affected by the disease is an important component of an IPM strategy. Yield loss should be determined in relation to a reference plot. Yield loss may be quantified by several models: the critical point model, the multiple point model, the critical time model and the AUDPC model.