Abstract
Coffee leaf rust (CLR), caused by the fungal pathogen Hemileia vastatrix, has plagued coffee production worldwide for over 150 years. Hemileia vastatrix produces urediniospores, teliospores, and the sexual basidiospores. Infection of coffee by basidiospores of H. vastatrix has never been reported and thus far, no alternate host, capable of supporting an aecial stage in the disease cycle, has been found. Due to this, some argue that an alternate host of H. vastatrix does not exist. Yet, to date, the plant pathology community has been puzzled by the ability of H. vastatrix to overcome resistance in coffee cultivars despite the apparent lack of sexual reproduction and an aecidial stage. The purpose of this study was to introduce a new method to search for the alternate host(s) of H. vastatrix. To do this, we present the novel hypothetical alternate host ranking (HAHR) method and an automated text mining (ATM) procedure, utilizing comprehensive biogeographical botanical data from the designated sites of interests (Ethiopia, Kenya and Sri Lanka) and plant pathology insights. With the HAHR/ATM methods, we produced prioritized lists of potential alternate hosts plant of coffee leaf rust. This is a first attempt to seek out an alternate plant host of a pathogenic fungus in this manner. The HAHR method showed the highest‐ranking probable alternate host as Psychotria mahonii, Rubus apetalus, and Rhamnus prinoides. The cross‐referenced results by the two methods suggest that plant genera of interest are Croton, Euphorbia, and Rubus. The HAHR and ATM methods may also be applied to other plant–rust interactions that include an unknown alternate host or any other biological system, which rely on data mining of published data.
Highlights
The genus Coffea is composed of over one hundred species, which grow wild in equatorial Africa and Madagascar (Lashermes, Bertrand, & Ettienne, 2009; McCook, 2006)
The hypothetical alternate host ranking (HAHR) and automated text mining (ATM) methods may be ap‐ plied to other plant–rust interactions that include an unknown alternate host or any other biological system, which rely on data mining of published data
We present the hypothetical alternate host ranking (HAHR) and automated text mining (ATM) methods to address this gap in knowledge based on a series of assumptions relating to the disease biology of this given pathogen
Summary
The genus Coffea is composed of over one hundred species, which grow wild in equatorial Africa and Madagascar (Lashermes, Bertrand, & Ettienne, 2009; McCook, 2006). Only the teliospores are capable of long‐term survival away from a living host plant (Schumann & Leonard, 2000) By producing both asexual and sexual spore types, rust fungi increase the chance of transmission to multiple hosts (Shattock & Preece, 2000). For this reason, many rusts are observed to have complex disease cycles with different spore types or reproductive structures being defined as either mac‐ rocyclic (producing five spore types: spermatia, aeciospores, ured‐ iniospores, teliospores, and basidiospores) or microcyclic (species often lacking aeciospores and urediniospores, with or without sper‐ matia) (Shattock & Preece, 2000). Others have speculated that based on Tranzschel's Law (Shattock & Preece, 2000), the alternate host of H. vastatrix is an orchid (Rodrigues, 1990)
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