Advertisement

Epidemiological Assessments and Postharvest Disease Incidence

  • Themis J. MichailidesEmail author
  • David P. Morgan
  • Yong Luo
Chapter
Part of the Plant Pathology in the 21st Century book series (ICPP, volume 2)

Abstract

Postharvest plant disease can be measured by “incidence,” by recording the presence or absence of symptoms, and “severity,” the degree to which the symptoms are expressed. Weather and other environmental conditions play a significant role by causing stress in plants and lowering natural defenses, and by creating conditions suitable for pathogens to infect the plants. Specifically for postharvest diseases of fruit, infections can start as early as fruit set and continue until harvest. Although weather conditions influence the epidemiology of a disease in the field, the incidence of postharvest disease depends on the incidence of latent infections that initiate in the field during the season, contamination with fungal propagules during harvest, the effectiveness of postharvest treatments, and storage and marketing conditions. True latent infection, defined as a parasitic relationship that eventually induces macroscopic symptoms (Verhoeff, K., Annu. Rev. Phytopathol. 12:99-107, 1974) plays a major role in both the incidence and severity of postharvest disease. If conditions are favorable, incidence and severity of latent infections will be higher and the risk for postharvest disease development will increase and vice versa. For example, in California kiwifruit there is a positive relationship between the incidence of latent infection of sepals or stem ends, and the incidence of gray mold of fruit in cold storage. We visualize kiwifruit and other kinds of fruit as recording devices that copy the environmental conditions as latent infections. And in some cases, quantification of these latent infections can predict postharvest disease (i.e. BOTMON (Botrytis monitoring in kiwifruit sepals and/or fruit stems and in stems of grape berries) and ONFIT (overnight freezing incubation technique in stone fruit, other fleshy fruit, and in nut crops)). The source of inoculum that can drive an epidemic of a disease in the field can also affect the ­incidence of postharvest decay, by affecting the incidence of latent infection. Reducing the source of inoculum (sanitation) can reduce the incidence of latent infection of fruit, with the ultimate result in reducing postharvest disease (i.e., stone and pome fruit). Environmental conditions during bloom in various crops can have detrimental effects on the incidence of postharvest disease (i.e., grapes, pomegranates, prunes, etc.) by affecting the levels of latent infection or affecting the plant host directly. Altering cultural practices that may affect environmental conditions in the field or the physiology and histology of fruit can also affect the incidence of fruit diseases both in the field and postharvest. The development of efficient, accurate, and rapid molecular techniques (including real-time PCR assays) can facilitate the detection and quantification of disease inoculum and latent infection of fruit (i.e., stone fruit) and help predict incidence of postharvest disease. In addition, development of allele-specific RT-PCR methods for rapidly detecting fungicide resistant fungal pathogens will help growers to manage fungicide resistance and make correct decisions to reduce postharvest disease. The goal of our laboratory is to develop less expensive molecular techniques that determine latent infections and assess populations of fungi resistant to fungicides and enable us to process large numbers of samples at our laboratory and to provide the protocols to private laboratories.

Keywords

Latent Infection Botrytis Cinerea Gray Mold Stone Fruit Polymerase Chain Reaction Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

We thank M. Doster, D. Felts, L. Boeckler, H. Reyes, R. Puckett, and J. Windh for technical assistance. We also thank Drs. Z. Ma, H. Avenot, and E. Boehm, Postdoctoral Associates, and visiting Professor M. Yoshimura, for their research contributions. Funding for this research was ­provided by the California Kiwifruit Commission, California Pistachio Commission, California Dried Plum Board, California Tree Fruit Agreement, and the California Fig Institute.

References

  1. Boehm EWA, Ma Z, Michailides TJ (2001) Species-specific detection of Monilinia fructicola from California stone fruits and flowers. Phytopathology 91:428-439CrossRefPubMedGoogle Scholar
  2. Cerkauskas RF, Sinclair JB (1980) Use of paraquat to aid detection of fungi in soybean tissues. Phytopathology 70:1036-1038CrossRefGoogle Scholar
  3. Curtis KM (1928) The morphological aspect of resistance to brown rot in stone fruit. Ann Bot 42:39-68Google Scholar
  4. Eckert JW, Sommer NF (1967) Control of diseases of fruits and vegetables by postharvest treatments. Annual Rev. of Phytopathology 5:391-432Google Scholar
  5. Förster H, Adaskaveg JE (2000) Early brown rot infections in sweet cherry fruit are detected by Monilinia-specific DNA primers. Phytopathology 90:171-178CrossRefPubMedGoogle Scholar
  6. Förster H, Kanetis L, Adaskaveg JE (2004) Spiral gradient dilution, a rapid method for determining growth responses and 50% effective concentration values in fungus-fungicide interactions. Phytopathology 94:163-170CrossRefPubMedGoogle Scholar
  7. Luo Y, Michailides TJ (2001) Factors affecting latent infection of prune fruit by Monilinia fructicola. Phytopathology 91:864-872CrossRefPubMedGoogle Scholar
  8. Luo Y, Michailides TJ (2003) Threshold conditions that lead latent infection to prune fruit rot caused by Monilinia fructicola. Phytopathology 93:102-111CrossRefPubMedGoogle Scholar
  9. Luo Y, Morgan DP, Michailides TJ (2001) Risk analysis of brown rot blossom blight of prune caused by Monilinia fructicola. Phytopathology 91:759-768CrossRefPubMedGoogle Scholar
  10. Ma Z, Luo Y, Michailides TJ (2003a) Nested PCR assays for detection of Monilinia fructicola in stone fruit orchards and Botryosphaeria dothidea from pistachios in California. J Phyto­pathology 151:312-322CrossRefGoogle Scholar
  11. Ma Z, Yoshimura MA, Michailides TJ (2003b) Identification and characterization of benzimidazole resistance in Monilinia fructicola from stone fruit orchards in California. Appl Environ Microbiol 69:7145-7152CrossRefPubMedGoogle Scholar
  12. Michailides TJ, Elmer PAG (2000) Botrytis gray mold of kiwifruit caused by Botrytis cinerea in the United States and New Zealand. Plant Dis 84:208-223CrossRefGoogle Scholar
  13. Michailides TJ, Manganaris GA (2009) Harvesting and handling effects on postharvest decay. Steward Postharvest Rev 2:3-7Google Scholar
  14. Michailides TJ, Morgan DP (1996a) New technique predicts gray mold in stored kiwifruit. California Agric 50(3):34-40CrossRefGoogle Scholar
  15. Michailides TJ, Morgan DP (1996b) Using incidence of Botrytis cinerea in kiwifruit sepals and receptacles to predict gray mold decay in storage. Plant Dis 80:248-254CrossRefGoogle Scholar
  16. Michailides TJ, Ogawa JM, Opgenorth (1987) Shift of Monilinia spp. and distribution of isolates sensitive and resistant to benomyl in California prune and apricot orchards. Plant Dis 71:893-896Google Scholar
  17. Michailides TJ, Morgan DP, Felts D (2000) Detection and significance of symptomless latent infection of Monilinia fructicola in California stone fruits. (Abstr.) Phytopathology 90:S53Google Scholar
  18. Northover J, Cerkauskas RF (1994) Detection and significance of symptomless latent infections of Monilinia fructicola in plums. Can J Plant Pathol 16:30-36CrossRefGoogle Scholar
  19. Prusky D, Fuchs Y, Zauberman G (1981) A method for pre-harvest assessment of latent infection in fruits. Ann Appl Biol 98:79-85CrossRefGoogle Scholar
  20. Rosenberger DA (1983) Observations on quiescent brown rot infections in Grand Prize plums. In: Burr TJ (ed) Deciduous tree fruit disease workers. American Phytopathological Society, Ithaca, New York, pp 19-22Google Scholar
  21. Sinclair JB, Cerkauskas RF (1996) Latent infection vs. endophytic colonization by fungi. In: Redlin SC, Carris LM (eds) Endophytic fungi in woody plants. Systematics, ecology, and evolution. APS, St. Paul, MN, Chapter 1, pp 3-29Google Scholar
  22. Tate KG, Corbin JB (1978) Qiescent fruit infections of peach, apricot, and plum in New Zealand caused by the brown rot fungus Sclerotinia fructicola. NZ J Exp Agric 6:319-325Google Scholar
  23. Verhoeff K (1974) Latent infections by fungi. Ann Rev Phytopathol 12:99-107CrossRefGoogle Scholar
  24. Wade GC (1956) Investigations on brown rot of apricots caused by Sclerotinia fructicola (Wint.) Behm. I. The occurrence of latent infection in fruit. Austr J Agric Res 7:504-515Google Scholar
  25. Wade GC, Cruickshank RH (1992) The establishment and structure of latent infections with Monilinia fructicola on apricots. J Phytopathol 136:95-106CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Themis J. Michailides
    • 1
    Email author
  • David P. Morgan
    • 1
  • Yong Luo
    • 1
  1. 1.Department of Plant Pathology, Kearney Agricultural CenterUniversity of California-DavisParlierUSA

Personalised recommendations