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.

The coffee research community has maintained a long ongoing debate regarding the implications of shade trees in coffee production. Historically, there has been contrasting results and opinions on this matter, thus recommendations for the use of shade (namely in coffee agroforestry systems) are often deemed controversial, particularly due to potential yield declines and farmers’ income. This study is one of the first demonstrating how several Coffea arabica cultivars respond differently to shade with respect to yield. By standardising more than 200 coffee yield data from various in-field trials, we assembled the so-called “Ristretto” data pool, a one of a kind, open-source dataset, consolidating decades of coffee yield data under shaded systems. With this standardised dataset, our meta-analysis demonstrated significant genotypic heterogeneity in response to shade, showing neutral, inverted U-shaped and decreasing trends between yield and shade cover amongst 18 different cultivars. These findings encourage the examination of C. arabica at the cultivar level when assessing suitability for agroforestry systems. Comparison of productivity is also encouraged across a range of low to moderate shade levels (10–40%), in order to help elucidate potential unknown optimal shade levels for coffee production.

Around 2 billion cups of coffee are consumed daily, worldwide (Reay, 2019). However, the coffee plant is under threat due to its vulnerability to a plethora of plant pests and diseases, exacerbated by climate change (Avelino, ten Hoopen, et al., 2012;Kumar et al., 2016).In fact, the typical coffee farmer faces a diverse onslaught by an assortment of beetles, bacteria, fungi and nematodes in just one production season (Waller et al., 2007). Traditional chemical pesticides (i.e., insecticides and fungicides) have been a mainstay of the Green Revolution, and thus commonly deployed in coffee production. With more than 470 licensed products approved for use in Brazil alone (Coelho et al., 2019), these agrochemicals are being used as a primary means of management in the onset of pests and diseases across all agricultural sectors including coffee (

Coffee is deemed to be a high-risk crop in light of upcoming climate changes. Agroforestry practices have been proposed as a nature-based strategy for coffee farmers to mitigate and adapt to future climates. However, with agroforestry systems comes shade, a highly contentious factor for coffee production in terms of potential yield reduction, as well as additional management needs and interactions between shade trees and pest and disease. In this review, we summarize recent research relating to the effects of shade on (i) farmers' use and perceptions, (ii) the coffee microenvironment, (iii) pest and disease incidence, (iv) carbon assimilation and phenology of coffee plants, (v) coffee quality attributes (evaluated by coffee bean size, biochemical compounds, and cup quality tests), (vi) breeding of new Arabica coffee F1 hybrids and Robusta clones for future agroforestry systems, and (vii) coffee production under climate change. Through this work, we begin to decipher whether shaded systems are a feasible strategy to improve the coffee crop sustainability in anticipation of challenging climate conditions. Further research is proposed for developing new coffee varieties adapted to agroforestry systems (exhibiting traits suitable for climate stressors), refining extension tools by selecting locally-adapted shade trees species and developing policy and economic incentives enabling the adoption of sustainable agroforestry practices.

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