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A network of agronomists, researchers, and practitioners associated with cacao farming provided open access to their independent field trials across Latin America and the Caribbean (LAC). A centralized dataset was assembled using qualitative and quantitative data from 25 experimental field trials (hereafter referred to as “CacaoFIT”) spanning several LAC agroecosystems. This dataset was used to document the main traits and agroclimatic attributes of the cacao cultivation model being tested within the CacaoFIT network. By synthesizing data from an entire network of cacao trials, this study aimed to highlight specific design features and management practices that may contribute to better cacao farming sustainability. The CacaoFIT network comprises 200 ha of field trials testing over 150 cacao genotypes and set up under different shade canopy design, management, and research goals. Small-sized trials were common across Mesoamerica, whereas medium to large-size trials were distinct to South America. Cacao trials were 15 years old (on average) and ranged from 3 to 25 years of establishment. Most cacao trials were managed conventionally (i.e., 55%), while 20% were under organic practices, and the remaining 25% presented both conventional and organic management approaches. Most field trials (ca. 60%) planted an average of 10 international clones or national cultivars at high (1,230–1,500 plants ha−1) and medium density (833–1,111 plants ha−1). Mixed shade canopies were the dominant agroforestry model, while timber vs. leguminous shade canopies were also common. The diversity and depth of research domains examined across the CacaoFIT network varied widely. Agronomy and agroforestry topics dominated the research agenda across all trials, followed by environmental services domains. Cacao physiology and financial performance were researched to a lesser extent within the network. Five featured field trials from CacaoFIT offered technical guidelines to inform cacao farming within similar contexts. This collaborative work is a scaffold to encourage public–private partnerships, capacity building, and data sharing amongst cacao researchers across the tropics.

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).

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.

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.