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1.
Data Brief ; 50: 109560, 2023 Oct.
Article in English | MEDLINE | ID: mdl-37753259

ABSTRACT

In-field data were collected in Costa Rica between 2018-2021 on newly planted grafted and non-grafted coffee plants grown under artificial shade nets and across an elevation gradient (1050, 1250 and 1450 m.a.s.l). The coffee plants consisted of Coffea arabica F1 hybrid plants ('H3 i.e. Caturra cv. X Ethiopian 531'), which were derived from a somatic embryogenesis clonal propagation process, an American C. arabica pure line ('Villa Sarchi') and C. canephora 'Nemaya' (the latter two both being produced by seed). Data from eight different coffee types (including these three genotypes) and different grafting combinations (including reverse and auto-grafting) were collected. Data concerned plant traits such as grafting compatibility (plant collar diameters above and below graft union), agronomic characteristics (aerial and root traits), leaf ecophysiology (leaf gas-exchange and chlorophyll fluorescence), yield and quality attributes (bean size, peaberry percentage, WB100 and SCA note). Climate data were also included for comparison on the farm plots along the elevation gradient. Linear mixed models were used to test for effects of elevation (test sites), coffee types (grafted or non-grafted combinations) and interaction between coffee types and elevations. Least square mean estimates were calculated for significant fixed effects and Tukey tests applied for pairwise tests. A tangential hyperbola curve was used to analyse leaf gas-exchange data. These datasets and R scripts can be re-used as a guide for future analyses concerning coffee agronomy or eco-physiological interactions for other plant species. Other potential re-uses could be meta-analyses aimed at comparing coffee yield, quality, or other agronomic traits across different environmental conditions (such as under shade of an agroforestry system or across different elevation sites).

2.
Ecol Evol ; 9(23): 13619-13631, 2019 Dec.
Article in English | MEDLINE | ID: mdl-31871671

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.

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