Advances and Challenges in Computational Prediction of Effectors from Plant Pathogenic Fungi

  • Sperschneider J
  • Dodds P
  • Gardiner D
  • et al.
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Abstract

The base temperature for germination of corn is approximately 10°C, which results in slow germination and emergence of corn crops sown into cool soils. The eVects of plant-growth-promoting rhizobacteria (PGPR) and kinetin on grain and sweet corn emergence, plant growth and yield were studied under short season conditions in 1996 and 1997. Two PGPR strains (Serratia proteamaculans 1-102 and Serratia liquefaciens 2-68) were used. The kinetin concentrations were 0, 1 and 5 mM. The experiment was structured as a randomized complete block design with four replicates. The plant growth responses were variable and depended on the PGPR strain, harvest date and growth parameters evaluated. There were interactions among PGPR, kinetin and corn hybrid. PGPR provided a greater stimulation of seedling emergence than kinetin. PGPR strain 1-102 was best at promoting emergence. One month after planting, both PGPR and kinetin increased plant growth, and PGPR strain 2-68 resulted in a greater growth than that of strain 1-102. PGPR strain 2-68 plus 1 mM kinetin was the best treatment for promoting plant growth. The plant height and root dry weight of sweet corn were less aVected than those of grain corn. The eVects of PGPR on plant growth decreased as the plants developed. Two months after planting, there were no effects of kinetin on plant growth, however, PGPR still had positive eVects on the leaf area of grain corn, but they decreased the leaf area of sweet corn. The plant dry weight of grain corn was increased by PGPR strain 2-68. The grain corn yield was increased by PGPR strain 2-68 in both years. In 1997, PGPR strain 2-68 increased the sweet corn yield. Kinetin alone had no effects on yields in either year for the two cultivars studied.

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Sperschneider, J., Dodds, P. N., Gardiner, D. M., Manners, J. M., Singh, K. B., & Taylor, J. M. (2015). Advances and Challenges in Computational Prediction of Effectors from Plant Pathogenic Fungi. PLOS Pathogens, 11(5), e1004806. https://doi.org/10.1371/journal.ppat.1004806

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