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Coffee, an important global commodity, is threatened by climate change. Agroforestry has been considered as one option to maintain or enhance coffee production. In this study, we use a machine learning ensemble consisting of MaxEnt, Random Forest and Boosted Regression Trees to assess climate change impacts on the suitability to grow Arabica coffee, Robusta coffee and bananas in Uganda by 2050. Based on this, the buffering potential of Cordia africana and Ficus natalensis, the two commonly used shading trees in agroforestry systems is assessed. Our robust models (AUC of 0.7–0.9) indicate temperature-related variables as relevant for Arabica coffee suitability, while precipitation-related variables determine Robusta coffee and banana suitability. Under current climatic conditions, only a quarter of the total land area is suitable for growing Arabica coffee, while over three-quarters are suitable for Robusta coffee and bananas. Our results suggest that climate change will reduce the area suitable to grow Arabica coffee, Robusta coffee and bananas by 20%, 9% and 3.5%, respectively, under SSP3-RCP7.0 by 2050. A shift in areas suitable for Arabica coffee to highlands might occur, leading to potential encroachment on protected areas. In our model, implementing agroforestry with up to 50% shading could partially offset suitable area losses for Robusta coffee—but not for Arabica coffee. The potential to produce valuable Arabica coffee thus decreases under climate change and cannot be averted by agroforestry. We conclude that the implementation and design of agroforestry must be based on species, elevation, and regional climate projections to avoid maladaptation.

Summary Coffee species such as Coffea canephora P. (Robusta) and C. arabica L. (Arabica) are important cash crops in tropical regions around the world. C. arabica is an allotetraploid (2n = 4x = 44) originating from a hybridization event of the two diploid species C. canephora and C. eugenioides (2n = 2x = 22). Interestingly, these progenitor species harbour a greater level of genetic variability and are an important source of genes to broaden the narrow Arabica genetic base. Here, we describe the development, evaluation and use of a single‐nucleotide polymorphism (SNP) array for coffee trees. A total of 8580 unique and informative SNPs were selected from C. canephora and C. arabica sequencing data, with 40% of the SNP located in annotated genes. In particular, this array contains 227 markers associated to 149 genes and traits of agronomic importance. Among these, 7065 SNPs (~82.3%) were scorable and evenly distributed over the genome with a mean distance of 54.4 Kb between markers. With this array, we improved the Robusta high‐density genetic map by adding 1307 SNP markers, whereas 945 SNPs were found segregating in the Arabica mapping progeny. A panel of C. canephora accessions was successfully discriminated and over 70% of the SNP markers were transferable across the three species. Furthermore, the canephora‐derived subgenome of C. arabica was shown to be more closely related to C. canephora accessions from northern Uganda than to other current populations. These validated SNP markers and high‐density genetic maps will be useful to molecular genetics and for innovative approaches in coffee breeding.

The current study investigates the phytochemical composition of coffee plant organs and their corresponding antioxidant capacities compared to green and roasted coffee beans. HPLC analysis indicated that the investigated compounds were present in all organs except mangiferin, which was absent in roots, stems and seeds, and caffeine, which was absent in stems and roots. Total phytochemicals were highest in the green beans (GB) at 9.70 mg g−1 dry weight (DW), while roasting caused a 66% decline in the roasted beans (RB). This decline resulted more from 5–CQA and sucrose decomposition by 68% and 97%, respectively, while caffeine and trigonelline were not significantly thermally affected. Roasting increased the total phenolic content (TPC) by 20.8% which was associated with an increase of 68.8%, 47.5% and 13.4% in the antioxidant capacity (TEAC) determined by 2,2–diphenyl–1–picryl hydrazyl radical (DPPH), 2,2–azino bis (3–ethyl benzothiazoline–6–sulphonic acid) radical (ABTS) and Ferric ion reducing antioxidant power (FRAP) assays, respectively. Amongst the leaves, the youngest (L1) contained the highest content at 8.23 mg g−1 DW, which gradually reduced with leaf age to 5.57 mg g−1 DW in the oldest (L6). Leaves also contained the highest TPC (over 60 mg g−1 GAE) and exhibited high TEAC, the latter being highest in L1 at 328.0, 345.7 and 1097.4, and least in L6 at 304.6, 294.5 and 755.1 µmol Trolox g−1 sample for the respective assays. Phytochemical accumulation, TPC and TEAC were least in woody stem (WS) at 1.42 mg g−1 DW; 8.7 mg g−1 GAE; 21.9, 24.9 and 110.0 µmol Trolox g−1 sample; while herbaceous stem (HS) contained up to 4.37 mg g−1 DW; 27.8 mg g−1 GAE; 110.9, 124.8 and 469.7 µmol Trolox g−1 sample, respectively. Roots contained up to 1.85 mg g−1 DW, 15.8 mg−1 GAE and TEAC of 36.8, 41.5 and 156.7 µmol Trolox g−1 sample. Amongst the organs, therefore, coffee leaves possessed higher values than roasted beans on the basis of phytochemicals, TPC and TEAC. Leaves also contain carotenoids and chlorophylls pigments with potent health benefits. With appropriate processing methods, a beverage prepared from leaves (coffee leaf tea) could be a rich source of phytochemicals and antioxidants with therapeutic and pharmacological values for human health.

Plants experience physiological and metabolic changes in response to water deficit during critical stages, such as fruiting. In coffee, the allocation of fresh assimilates and interplay between leaf orientation, leaf age, and carbon changes are unknown. Understanding these strategies would reveal how coffee plants enhance their survival and productivity under water scarcity. Four-year-old Venecia Arabica coffee clones under water stress were pulse labelled with 13 C-CO 2 in a greenhouse. Three hours after labelling, leaf punches from young and old leaf pairs were collected at 10, 11, 12, and 13 days of water deficit (50% pot capacity/PC). These were analysed to assess 13 C enrichment in relation to carbon assimilation and leaf carbon changes over time. Water deficit significantly decreased carbon assimilation by 20-52% compared to well-watered plants, especially in young leaves (p< 0.05). In addition, old leaves on the sun-exposed side performed better in terms of carbon assimilation than those on the shaded side; however, the orientation effect was not evident under stress. At harvest, approximately 15 days of water deficit, carbon allocation exhibited a marked decline, particularly in young leaves. The plants prioritised the allocation of newly assimilated carbon to roots and shoots, and to a lesser extent, to the fruits to support survival, storage, and production. Notably, carbon redistribution resulted in elevated levels of starch and sugar in fruits (by 33% and 51%, respectively), shoots, and roots, accompanied by a reduction in foliar sugar and cellulose contents in young leaves. These findings highlight the complex survival strategies employed by coffee plants, demonstrating their capacity to optimise resource allocation to storage organs and the potential of old leaves in response to drought. The results offer valuable guidance for coffee breeding programs aimed at enhancing the resilience of Coffea arabica to climate-induced water scarcity.

Coffee ripeness monitoring is a key indicator for defining the moment of starting the harvest, especially because the coffee quality is related to the fruit ripeness degree. The most used method to define the start of harvesting is by visual inspection, which is time-consuming, labor-intensive, and does not provide information on the entire area. There is a lack of new techniques or alternative methodologies to provide faster measurements that can support harvest planning. Based on that, this study aimed at developing a vegetation index (VI) for coffee ripeness monitoring using aerial imagery. For this, an experiment was set up in five arabica coffee fields in Minas Gerais State, Brazil. During the coffee ripeness stage, four flights were carried out to acquire spectral information on the crop canopy using two quadcopters, one equipped with a five-band multispectral camera and another with an RGB (Red, Green, Blue) camera. Prior to the flights, manual counts of the percentage of unripe fruits were carried out using irregular sampling grids on each day for validation purposes. After image acquisition, the coffee ripeness index (CRI) and other five VIs were obtained. The CRI was developed combining reflectance from the red band and from a ground-based red target placed on the study area. The effectiveness of the CRI was compared under different analyses with traditional VIs. The CRI showed a higher sensitivity to discriminate coffee plants ready for harvest from not-ready for harvest in all coffee fields. Furthermore, the highest R2 and lowest RMSE values for estimating the coffee ripeness were also presented by the CRI (R2: 0.70; 12.42%), whereas the other VIs showed R2 and RMSE values ranging from 0.22 to 0.67 and from 13.28 to 16.50, respectively. Finally, the study demonstrated that the time-consuming fieldwork can be replaced by the methodology based on VIs.

Temperature increase may cause some regions in the world to become marginal or unsuitable for Arabica coffee cultivation, due to either heat and/or marked water deficit. The feasibility of sustainable coffee production in these regions promotes good opportunity of income and value addition for rural producers within an expanding market. This study aimed to identify short-stature Arabica coffee cultivars with the best agronomic and qualitative performance in a low-altitude region. The experiment was located in northeastern São Paulo state, Brazil, at 565 m above sea level. During the experimental period (2014–2018) the average annual and November temperatures were 23.0 and 24.3°C, respectively, with an average annual water deficit of 109 mm. The experimental design was randomized blocks, with four replicates, and the treatments consisted of 17 short-stature cultivars. The cultivars Catuaí Amarelo IAC 62, Catuaí Vermelho IAC 99, IAC Ouro Amarelo, Obatã IAC 1669-20, Obatã IAC 4739, Tupi IAC 1699-33, IAC 125 RN and IPR 100 stood out in terms of yield, reaching approximately 50 bags/ha. The appropriate choice of Arabica coffee cultivar in a low-altitude region may result in yield increment of up to 74%. The cultivars Catuaí Vermelho IAC 99, Tupi IAC 1699-33 and IAC 125 RN produced grains with the best quality and highest hundred-grain weight, processing yield and percentage of grains retained on sieve 17. Therefore, it is possible for an Arabica coffee cultivar to have high yield and high grain and beverage quality in a low-altitude region, promoting production alternatives for farmers.

Polyploidy has occurred throughout the evolutionary history of plants and led to diversification and plant ecological adaptation. Functional plasticity of duplicate genes is believed to play a major role in the environmental adaptation of polyploids. In this context, we characterized genome-wide homoeologous gene expression in Coffea arabica, a recent allopolyploid combining two subgenomes that derive from two closely related diploid species, and investigated its variation in response to changing environment. The transcriptome of leaves of C. arabica cultivated at different growing temperatures suitable for one or the other parental species was examined using RNA-sequencing. The relative contribution of homoeologs to gene expression was estimated for 9959 and 10 628 genes in warm and cold conditions, respectively. Whatever the growing conditions, 65% of the genes showed equivalent levels of homoeologous gene expression. In 92% of the genes, relative homoeologous gene expression varied < 10% between growing temperatures. The subgenome contributions to the transcriptome appeared to be only marginally altered by the different conditions (involving intertwined regulations of homeologs) suggesting that C. arabica's ability to tolerate a broader range of growing temperatures than its diploid parents does not result from differential use of homoeologs.

Coffee beverage quality is highly correlated with the degree of fruit ripeness. In this sense, monitoring fruit ripeness is of utmost importance for harvest planning and, especially for obtaining high-quality beverages. Currently, this process is carried out through manual counts of unripe fruits, which is laborious and limited to a few plants within the field. This study aimed at evaluating the potential of a low-cost multispectral camera for coffee ripeness monitoring in the Zona da Mata region of Minas Gerais State, Brazil. For that, five fields of Arabica coffee with distinct characteristics were evaluated. During the coffee ripeness period, four flights were carried using a Phantom 4 Pro quadcopter equipped with a Mapir Survey 3W camera for imagery acquisition. After that, nine vegetation indices (VIs) were obtained. For the same dates, the percentage of unripe fruits was obtained using an irregular grid in all fields. The data was split into two ripeness classes: suitable for harvest (R) with < 30% of unripe fruits; and not suitable for harvest (U), with > 30% of unripe fruits. Then, a principal component analysis was used to infer the importance of the VIs to discriminate plants with unripe fruits from those with ripe fruits. The first two principal components explained > 75% of the variance in the datasets from all coffee fields. The VIs were able to discriminate the ripeness classes (U and R) in most fields; however, their performance was directly influenced by the crop yield and canopy volume.

Brown eye spot ( Cercospora coffeicola) is one of the main diseases of coffee ( Coffea arabica L.) and represents a serious phytosanitary problem for the crop. Among the disease management strategies, the use of balanced mineral nutrition is recommended. In this context, the supply of micronutrients and elements in a nanoparticle (NP) form has been studied due to the unique properties of NPs. The objective of this study was to evaluate the effects of different NPs on the C. coffeicola x coffee pathosystem. The effect of five NPs (copper-Cu, manganese-Mn, zinc-Zn, silver-Ag, and boron-B) and the fungicide azoxystrobin + cyproconazole at five doses (3, 50, 100, 250, 500 mg L −1 ), on the sporulation and mycelial growth rate (MGR) of C. coffeicola were quantified. The most effective in vitro dose (500 mg L −1 ) was applied to coffee seedlings Mundo Novo 376/4 cultivar inoculated with C. coffeicola . The area under the disease progress curve (AUDPC), compound phenolic, lignin soluble and chlorophyll content were evaluated. The AgNP, CuNP, MnNP, ZnNP and fungicide reduced the germination of C. coffeicola spores. The addition of fungicide, BNP, CuNP, ZnNP and MnNP to the culture medium at the dose of 500 mg L −1 reduced the mycelial growth by approximately 100%, compared to the control. Lower AUDPC’s were recorded for coffee seedlings sprayed with fungicide and AgNP.

Coffee genetic improvement programs have been evolving very quickly, with frequent launches of new cultivars. The adoption of these new genetic materials by rural producers requires knowledge of agronomic performance in different production systems. Thus, this research aimed to evaluate the agronomic performance of irrigated and rainfed Arabica coffee (Coffea arabica L.) cultivars in the Cerrado Mineiro region. Evaluations were conducted in experimental fields across 22 farms of Arabica coffee producers, and 11 used an irrigated production system and 11 used a rainfed system. Twelve cultivars were evaluated as follows: Catuaí Vermelho IAC 144, Bourbon Amarelo IAC J10, Topázio MG 1190, MGS Epamig 1194, Catiguá MG2, MGS Catiguá 3, MGS Ametista, Pau Brasil MG1, MGS Paraíso 2, MGS Aranãs, Sarchimor MG 8840, and IAC 125 RN. Based on grain yield, processing yield, seed density, grain size, and cup quality, agronomic performance evaluations were conducted annually for the 2019, 2020, 2021, and 2022 harvests. The results showed that the grain yield was higher in the irrigated system compared to the rainfed system. In irrigated fields, the average increases in grain yield were 38%. Irrigation improved the performance of the cultivars in terms of processing yield, although it reduced cup quality. MGS Paraíso 2 cultivar showed the best productive performance, with an average of over four harvests of 52 and 42 bags ha−1 (1 bag = 60 kg) in irrigated and rainfed systems, respectively. The cultivars least responsive to irrigation were IAC 125 RN, MGS Catiguá 3, MGS Ametista, and MGS Paraíso 2, with grain yield increases of 24%, 26%, 27%, and 28%, respectively. The most responsive cultivars were MGS EPAMIG 1194, Sarchimor MG 8840, and Pau Brasil MG1, with grain yield increases of 33%, 35%, and 39%, respectively. The agronomic performance results of coffee cultivars in irrigated and rainfed production systems will allow rural producers to adopt cultivars that are more suitable for the Cerrado Mineiro region.