Coffee Cultivars Research Articles

Initial vegetative development and early selection of arabica coffee cultivars in a low-altitude region

Initial vegetative development and early selection of arabica coffee cultivars in a low-altitude region

Multiple-trait model by Bayesian inference applied to environment efficient Coffea arabica with low-nitrogen nutrient

Identifying Coffea arabica cultivars that are more efficient in the use of nitrogen is an important strategy and a necessity in the context of environmental and economic impacts attributed to excessive nitrogen fertilization. Although Coffea arabica breeding data have a multi-trait structure, they are often analyzed under a single trait structure. Thus, the objectives of this study were to use a Bayesian multitrait model, to estimate heritability in the broad sense, and to select arabica coffee cultivars with better genetic potential (desirable agronomic traits) in nitrogen-restricted cultivation. The experiment was carried out in a greenhouse with 20 arabica coffee cultivars grown in a nutrient solution with low-nitrogen content (1.5 mM). The experimental design used was in randomized blocks with three replications. Six agromorphological traits of the arabica coffee breeding program and five nutritional efficiency indices were used. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. The agromorphological traits were considered highly heritable, with a credibility interval (95% probability): H2 = 0.9538 – 5.89E-01. The Bayesian multitrait model presents an adequate strategy for the genetic improvement of arabica coffee grown in low-nitrogen concentrations. Coffee arabica cultivars Icatu Precoce 3282, Icatu Vermelho IAC 4045, Acaiá Cerrado MG 1474, Tupi IAC 1669-33, Catucaí 785/15, Caturra Vermelho and Obatã IAC 1669/20 demonstrated greater potential for cultivation in low-nitrogen concentration.

Genetic variability and phylogenetic characterization of different populations of Meloidogyne izalcoensis and reaction of coffee genotypes to this new species detected in Brazil

AbstractA new root‐knot nematode (RKN), Meloidogyne izalcoensis, was detected on coffee in Brazil. This species was first described on coffee from El Salvador and later detected in Asia and Africa. There are no reports on the genetic diversity of this species and resistance to M. izalcoensis has not yet been studied in coffee cultivars. All populations were identified by esterase phenotype and sequence‐characterized amplified region (SCAR) species‐specific markers. Based on random amplified polymorphic DNA (RAPD) and amplified fragment length polymorphism (AFLP) markers, low intraspecific variability was detected among M. izalcoensis populations from Africa, Vietnam and Brazil, but the population from El Salvador showed fewer genetic differences from the other populations. Phylogenetically, all populations of M. izalcoensis from different locations (El Salvador, Kenya, Tanzania, Vietnam and Brazil) grouped with 90% and 69% bootstrap support for COII and HSP90 regions, respectively, indicating that these markers are highly conserved for the species. In addition, both markers enabled separation of M. izalcoensis populations from other important coffee Meloidogyne species, including M. exigua, M. paranaensis, M. incognita, M. arabicida and M. lopezi. In resistance studies, most genotypes tested that had resistance to other Meloidogyne spp. (Amphillo × Catuaí, Hybrid of Timor, IAPAR 59, IPR 99, IPR 100, IPR 102, IPR 103, IPR 105, IPR 106, IPR 107 and IPR 108) were found to be susceptible to M. izalcoensis, except for the rootstock cv. Apoatã IAC 2258, which proved to be moderately resistant, with a genetic segregation for this character of 43.8%.

Brazilian Canephora coffee evaluation using NIR spectroscopy and discriminant chemometric techniques

High-quality Brazilian Canephora coffees are rising to the level of specialty coffees in the face of a new industry perception. In this framework, spectra from 527 coffees were analyzed in the near-infrared (NIR) region. Principal component analysis distinguished Brazilian Canephora producing states, botanical varieties, low and high-quality Canephora, Canephora and Arabica, and Canephora with geographical indication (GI) from those without GI. Also, Canephora coffee cultivars from Western Brazilian Amazon were distinguished. Three multi-class PLS-DA (traditional, hard, and soft versions) were compared to discriminate 5 classes: Robusta Amazônico from traditional (1) and indigenous (2) producers of Rondônia, Conilon from Espírito Santo (3), Conilon from Bahia (4), and specialty Arabica (5). Binary PLS-DA discriminated GI Canephora and non-GI Canephora with 100% sensitivity and specificity. Carbohydrates, chlorogenic acids, lipids, caffeine, and proteins were dominant absorption bands in coffee classifications. The proposed method is objective, simple, fast, and could be used in the routine analysis of coffee to verify claims of identity, variety, and origin.

THE COFFEE NDVI MODELING USING BUILT-IN RGB PASSIVE SENSOR IN UAS

Studies carried out used different sensors and field applications can be accomplished to obtain information and make decisions related to coffee management. The objective of this work was to train machine learning algorithms to estimate the NDVI based on the GreenseekerTM active optical sensor in 20 arabica coffee cultivars in the experimental area of the National Institute of Coffee Science and Technology (INCT of Coffee) using a passive RGB sensor. in unmanned aerial system (UAS) and its relationship with foliage. With the spectral signatures recorded in the RGB images of the 20 coffee cultivars, the relationships with the foliage and the NDVI data obtained with the Greenseeker™ active optical sensor were analyzed. Through machine learning and digital image processing techniques, it was possible to obtain an NDVI equation using the RGB bands based on the NDVI of the Greenseeker TM active optical sensor. The results were satisfactory when compared to in situ data, providing the use of a simple and effective method of evaluating the vegetative vigor of different coffee cultivars.

Early Detection of Coffee Leaf Rust Caused by Hemileia vastatrix Using Multispectral Images

Conventional methodology in the field for the sampling of coffee leaf rust, caused by Hemileia vastatrix, has proven to be impractical. This paper proposes a method for the early detection of this disease, which is the most significant pathogen of coffee plants worldwide, using multispectral images acquired using a Mapir Survey3W camera and an unmanned aerial vehicle (UAV). For this purpose, 160 coffee seedlings of the coffee cultivar ‘Mundo Novo’ were inoculated with urediniospores of H. vastatrix and compared with 160 control (non-inoculated) seedlings to determine the most favorable interval for distinguishing healthy and infected plants. The 320 seedlings were placed on a dark surface to perform the imaging flights. In vitro analyses of the physiological parameters of 20 specimens were then performed for each condition (inoculated/non-inoculated) to obtain the hyperspectral curves, and this process was repeated three times at 15, 30, and 45 days after inoculation (DAI). Based on the simulated hyperspectral curves, a discrepancy between the red and near-infrared (NIR) bands was identified at 15 DAI, with the inoculated plants showing greater absorption in the red band and a greater spectral response in the NIR band. Thus, multispectral images were able to distinguish H. vastatrix infection in coffee seedlings at an asymptomatic stage (15 DAI) using a support vector machines (SVM) algorithm. Detection accuracy was 80% and the Kappa index of agreement was moderate (0.6). The early detection of this pathogen in the field using low-cost technology can be an important tool for the monitoring of coffee leaf rust and, consequently, a more sustainable management of the pathogen, causing farmers to make applications of chemical fungicides only when necessary.

Digital imaging of coffee leaves under different nitrogen concentrations applied to soil

Brazil is the largest Coffea arabica L. producer and exporter in the world market. In view of the need for nitrogen fertilization, the objective of this work was to evaluate the use of digital images of coffee leaves as a function of nitrogen concentration and cultivars, as well as to evaluate the most adequate sampling of this technique to predict leaf nitrogen. The experiment was set in a greenhouse, at UNESP - Experimental Campus of Registro-SP, using 12L pots with medium sand. A completely randomized design was adopted, in a 4 x 2 factorial scheme, with four concentrations of N (0, 50, 100 and 200 mg dm-3), and two coffee cultivars (Mundo Novo and Obatã), with ten replications. The variables evaluated were: hue, dark green color index (DGCI), leaf area and leaf nitrogen content. The hue and DGCI were influenced by N concentration, cultivar and are dependent on the day after treatment application and the number of leaves used. The use of five leaves per replication was more adequate to estimate leaf N content. Hue, DGCI and leaf area were higher in Obatã depending on the day after application of the treatment and N concentration.

Agronomic performance of Arabica coffee cultivars in the subtropical humid environment of Vale do Ribeira Paulista, Brazil

This research is related to the evaluation of vegetative growth parameters, initial yield and incidence of pests and diseases of twelve Arabica coffee cultivars submitted to the subtropical humidity environment of Vale do Ribeira Paulista, Brazil. The experiment was performed in the Experimental Campus of the UNESP in Registro, in a randomized block design, with three replications. Stem diameter, number of plagiotropic branches, plant height, number of internodes of plagiotropic branches, length of the first plagiotropic branch, incidence of brown eye spot and phoma leaf spot on coffee leaves, infestation by leaf miner and the yield of cultivars were evaluated. The results obtained allowed to conclude that: i) cultivars Catuaí Amarelo IAC 62, Catuaí Vermelho IAC 99 and Mundo Novo IAC 379-1 were higher than the others, with yield above the national average in 2020 and percentage of flat beans below 10%; ii) all cultivars evaluated showed a similar level of increment of variables that indicate plant growth and reproductive development; iii) the cultivation environment is favorable to infestation by the leaf miner and unfavorable to the incidence of rust; iv) The prevailing climatic conditions in the Vale do Ribeira Paulista is suitable for the production of Arabica coffee.

Multiplex CRISPR/Cas9-mediated knockout of the phytoene desaturase gene in Coffea canephora

Coffea canephora (2n = 2x = 22 chromosomes) is a species with extensive genetic diversity and desirable agronomic traits for coffee breeding programs. However, obtaining a new coffee cultivar through conventional breeding techniques may require more than 30 years of crossing cycles and selection, which hampers the effort of keeping up with market demands and rapidly proposing more resilient to climate change varieties. Although, the application of modern biotechnology tools such as precision genetic engineering technologies may enable a faster cultivar development process. Therefore, we aimed to validate the CRISPR/Cas9 system to generate mutations on a selected genotype of C. canephora, the clone 14. Embryogenic calli and a multiplex binary vector containing two sgRNAs targeting different exons of the CcPDS gene were used. The sgRNAs were under the C. canephora U6 promoter regulation. The target gene encodes phytoene desaturase, an enzyme essential for photosynthesis involved in β-carotene biosynthesis. Somatic seedlings and embryos with albino, variegated and green phenotypes regenerated after Agrobacterium tumefaciens-mediated genetic transformation were analyzed by verifying the insertion of the Cas9 gene and later by sequencing the sgRNAs target regions in the genome of Robusta modified seedlings. Among them, 77% had the expected mutations, and of which, 50% of them had at least one target with a homozygous mutation. The genotype, temperature of co-cultivation with the bacteria, and light intensity used for subsequent embryo regeneration appeared to strongly influence the successful regeneration of plants with a mutated CcPDS gene in the Coffea genus.

Worldwide Population Structure of the Coffee Rust Fungus Hemileia vastatrix Is Strongly Shaped by Local Adaptation and Breeding History.

The devastating disease coffee leaf rust, caused by Hemileia vastatrix, has been a major constraint to worldwide coffee production. Recently, H.vastatrix populations were shown to be structured into three divergent genetic lineages with marked host specialization (C1, C2, and C3). However, there is yet no overall understanding of the population dynamics and adaptation of the most widespread and epidemiological relevant H.vastatrix group (C3). We used restriction site-associated DNA sequencing to generate 13,804 single nucleotide polymorphisms (SNPs) across a worldwide collection of 99 H. vastatrix isolates. Phylogenetic analyses uncovered a well-supported structuring within C3, with three main subgroups (SGs; SGI, SGII, and SGIII), which seem to reflect the historical distribution, breeding, and exchange of coffee cultivars. SGI shows a ladder-like diversification pattern and occurs across all four continents sampled, SGII is mainly restricted to Africa, and SGIII is observed only in Timor, revealing a higher genetic differentiation. Outlier and association tests globally identified 112 SNPs under putative positive selection, which impacted population structure. In particular, 29 overlapping SNPs per se seemed to have an extremely strong effect on H. vastatrix population divergence. We also found exclusive and fixed alleles associated with the SGs supporting local adaptation. Functional annotation revealed that transposable elements may play a role in host adaptation. Our study provides a higher-resolution perspective on the evolutionary history of H. vastatrix on cultivated coffee, showing its strong ability to adapt and the strength of the selective force imposed by coffee hosts, which should be taken into account when designing strategies for pathogen dissemination control and selective breeding.

Genome-Wide Identification, Characterization, and Comparative Analysis of NLR Resistance Genes in Coffea spp.

The largest family of disease resistance genes in plants are nucleotide-binding site leucine-rich repeat genes (NLRs). The products of these genes are responsible for recognizing avirulence proteins (Avr) of phytopathogens and triggering specific defense responses. Identifying NLRs in plant genomes with standard gene annotation software is challenging due to their multidomain nature, sequence diversity, and clustered genomic distribution. We present the results of a genome-wide scan and comparative analysis of NLR loci in three coffee species (Coffea canephora, Coffea eugenioides and their interspecific hybrid Coffea arabica). A total of 1311 non-redundant NLR loci were identified in C. arabica, 927 in C. canephora, and 1079 in C. eugenioides, of which 809, 562, and 695 are complete loci, respectively. The NLR-Annotator tool used in this study showed extremely high sensitivities and specificities (over 99%) and increased the detection of putative NLRs in the reference coffee genomes. The NLRs loci in coffee are distributed among all chromosomes and are organized mostly in clusters. The C. arabica genome presented a smaller number of NLR loci when compared to the sum of the parental genomes (C. canephora, and C. eugenioides). There are orthologous NLRs (orthogroups) shared between coffee, tomato, potato, and reference NLRs and those that are shared only among coffee species, which provides clues about the functionality and evolutionary history of these orthogroups. Phylogenetic analysis demonstrated orthologous NLRs shared between C. arabica and the parental genomes and those that were possibly lost. The NLR family members in coffee are subdivided into two main groups: TIR-NLR (TNL) and non-TNL. The non-TNLs seem to represent a repertoire of resistance genes that are important in coffee. These results will support functional studies and contribute to a more precise use of these genes for breeding disease-resistant coffee cultivars.

Preliminary Characterization of Phytochemicals and Polysaccharides in Diverse Coffee Cascara Samples: Identification, Quantification and Discovery of Novel Compounds.

Coffee cascara is the first and most significant by-product of the coffee processing industry, whose valorization has become an urgent priority to reduce harmful environmental impacts. This work aimed to provide an improved understanding of phytochemicals and polysaccharides in coffee cascara in order to offer information for the better evaluation of potential applications. Phytochemicals in 20 different coffee cascara samples were ultrasonically extracted and analyzed by HPLC-UV and HPLC-MS/MS. Four novel compounds were isolated for the first time from coffee cascara, including two still unknown tautomers (337 Da), and two dihydroflavonol glycosides (dihydromyricetin glycoside and dihydromyricetin rhamnosylglycoside). Their presence can contribute to the design of new value-added applications of coffee cascara. Chemical characterization of two polysaccharides from two of the coffee cascara pulp samples showed that they were mainly composed of homogalacturonan, with rhamnose and arabinose as minor neutral sugars. In addition, principal component analysis results indicated that coffee cultivar and/or country significantly impacted the phytochemical composition of coffee cascara, although differences may be reduced by the external environment and processing method. It is suggested that processing method should be carefully designed when generating coffee cascara from the same cultivar and country/farm.

Molecular characterization and genetic structure analysis of Coffea arabica and Coffea canephora cultivars from India using SCoT markers

Coffee is the second most traded community after oil and provides a livelihood for more than 125 million people worldwide. It is cultivated in 80 countries spreading over Africa, Asia and Latin America. In recent years, there is an increasing demand for high quality planting material because of the changing dynamics of pests and disease occurrence possibly triggered by climate change. This calls for a better understanding of the existing genetic diversity and its utilization in the breeding program. In this study, we investigated the molecular characterization and genetic structure of twenty coffee cultivars predominantly bred and cultivated in India using Start Codon Targeted (SCoT) molecular markers. Thirty-six SCoT primers amplified 368 bands of which 192 (52.17%) are polymorphic. The mean values of PIC, Resolving power (RP), mean effective multiplex ratio (EMR) and marker index (MI) were 0.27, 16.04, 3.26 and 1.12 respectively indicating the usefulness of these markers for the genetic analysis of coffee cultivars. Four cultivars produced 17 unique bands due to their specific genetic constituents and these bands could be useful for fingerprinting diagnostics. UPGMA clustering based on SCoT markers separated the accessions into two major clusters which accommodated five sub-clusters which are supported by the principal coordinate analysis (PCoA). The STRUCTURE analysis showed K = 5 as the optimum number of groups and completely separated the cultivars mainly according to their development and genetic constitution. Our results represent the first-of-its-kind attempt to shed light on the genetic diversity among coffee cultivars grown in India using the functional marker.

Progeny Selection to Develop a Sustainable Arabica Coffee Cultivar

The objective of this study was to investigate the most efficient way to select F4:5 progenies derived from the Icatu and Catimor groups of Coffea arabica and to study the genotypic correlations between the traits related to coffee grain physical quality, diseases, and productivity. A combination of the predicted additive values for production capacity when considering seven harvests and a simultaneous selection for a high sieve percentage and resistance to specific diseases during the last harvest was used. Analyses that selected progenies without considering the genotype × harvest interaction provided inaccurate results, distorting the progeny ranking. Coffee leaf rust and brown eye spot were correlated, showing the possibility of simultaneously selecting for resistance to both diseases. Of the 68 progenies studied here, five showed satisfactory agronomic traits. Our findings will contribute substantially to the development of new coffee cultivars that will allow us to reduce pesticide use.

UV spectroscopy for discrimination of two arabica coffee cultivars in West Java Indonesia: a feasibility study

Arabica coffee variety is one of the key parameters that highly influence the cup quality of arabica coffee. The objective of this current research is to evaluate the possible application of UV spectroscopy for the discrimination of arabica coffee with different cultivars. Green beans from two arabica coffee cultivars (Coffea arabica) of Typica and Sigarar Utang were collected from the same origin in Papandayan mountain West Java, Indonesia. The samples were subjected to the same postharvest treatments (wet cherry processing method). All samples were roasted in medium roasting with 200°C for 16 minutes using a portable roasting machine. A total of 40 samples of Typica and Sigarar Utang were provided by weighing 1 gram of coffee powder (mesh 40) for each sample. The extraction of coffee samples was performed based on previously reported work. The UV-visible spectral data of aqueous coffee samples were acquired by using a benchtop of UV-vis spectrometer in the range of 190-1100 nm. The first two PCs (principal components) with 94% of CEV (cumulative explained variance) could be used to separate between the Typica and Sigarar Utang samples. The Typica samples were situated on the left of PC1 (PC1<0) and Sigarar Utang samples were on the right of PC1 (PC1>0). In the future, it is promising to apply UV spectroscopy for simple and reliable discrimination of arabica coffee cultivar.

Diagnosis of the nutritional status of coffee tree according to fruit phenology

The appropriate time for leaf collection to evaluate the nutritional status of the coffee tree should be carried out when the nutrient is in higher levels in the leaves, which may vary according to the phenological stage of the fruits. Macro and micronutrients do not show the same pattern regarding the period of highest leaf content. Therefore, it is coherent to define different times of leaf collection for each nutrient. The objective of this study was to verify the most suitable times for collecting leaves to evaluate the nutritional status of coffee plants based on the phenological development of coffee fruits. The experiment was carried out in a commercial field, in which six coffee cultivars were used (Acauã Novo, Bourbon Amarelo, Catuaí Vermelho IAC 144, Catucaí 20/15, IAC 125 RN and IPR 100). The collections were carried out in four phenological phases of coffee fruit development (floral bud maturation, chumbinho, fruit expansion, and fruit granulation). The periods with the highest concentrations varied based on the phenological stages of the fruits, and differences in concentrations were also observed between the cultivars examined. The highest zinc concentration in the leaves was observed in the maturation phase of the floral bud. Foliar collection for the diagnosis of the nutritional state of the coffee plant should be done for each nutrient based on the phenology of the fruits.

Arabica coffee yields and profitability improved by reducing the spacing within the rows

AbstractPlant spacing influences the yield of Arabica coffee (Coffea arabica L.) cultivars and affects profitability; however, there are few studies on it. Thus, the objective of this study was to evaluate the yield and economic performance of Arabica coffee cultivars at different plant spacings. The experiment, conducted in Mandaguari, Paraná, Brazil, used a randomized block design with three replicates of seven plants in a split‐plot scheme. The treatments were eight cultivars (IPR 98, IPR 99, IPR 100, IPR 102, IPR 103, IPR 106, IPR 107, and Mundo Novo IAC 376‐4) at 2.75‐m inter‐rows and four plant spacings within the rows (0.45, 0.60, 0.75, and 0.90 m). The experiment was conducted between 2016 and 2020. Revenue, cost, and profit indicators were considered in the economic analysis. In general, the yields of the cultivars at closer spacings of 0.45 and 0.60 m were higher than at wider spacings of 0.75 and 0.90 m. Different plant spacing influenced the yields of IPR 98, IPR 102, and IPR 103 cultivars. High yields (&gt;90 green coffee 60‐kg bags ha–1) were achieved with IPR 98, IPR 99, IPR 102, and IPR 103 cultivars, particularly IPR 98, which yielded 7,002.60 kg ha–1 at a spacing of 0.45 m. At 0.45‐m spacing, the IPR 98 cultivar presented the best economic result, with a positive impact on profitability.

Initial vegetative and reproductive development of coffee cultivars in Vale do Ribeira Paulista

This research is related to the performance evaluation of twelve Coffea arabica cultivars in Vale do Ribeira Paulista, in order to generate consistent information for the technical recommendation for cultivation in the region. The experiment was set in February 2018, at the Experimental Campus of the São Paulo State University “Júlio de Mesquita Filho” - UNESP in Registro, SP, Brazil, in a spacing of 3.00 x 0.60 m, in a randomized block design with three replications. The following parameters were evaluated: stem diameter, number of plagiotropic branches, plant height, number of internodes of plagiotropic branches, length of the first plagiotropic branch, incidence of brown spots and phoma leaf spot, infestation by leaf miner and yield. The results showed a good adaptation of all cultivars to growing conditions in Vale do Ribeira Paulista, with higher and faster vegetative development of large coffee cultivars. The productive potential of cultivars in the first harvest was similar to the performance of the same cultivars in traditional growing regions, with emphasis on ‘Arara’ and ‘Catucaí Amarelo 24/137’, with about 55 bags ha-1 of processed coffee. There was no incidence of rust disease in the experimental evaluation period, unlike other biotic agents such as leaf miner, phoma-spot and brown eye spot.

Estimate and Temporal Monitoring of Height and Diameter of the Canopy of Recently Transplanted Coffee by a Remotely Piloted Aircraft System

Digital agriculture is fundamental to potential improvements in the field by optimizing processes and providing intelligent decision making. This study aims to calculate the height and canopy diameter of recently transplanted coffee plants over three periods of crop development using aerial images, verify statistical differences between field measurements and aerial images, estimate linear equations between field data and aerial images, and monitor the temporal profile of the growth and development of the cultivar understudy in the field based on information extracted from aerial images through a Remotely Piloted Aircraft System (RPAS). The study area comprises a recently transplanted five-month-old Coffea arabica L. cultivar IAC J10 with information of height and crown diameter collected in the field and aerial images obtained by RPAS. As a result, it was possible to calculate the height and diameter of the canopy of coffee plants by aerial images obtained by RPAS. The linear estimation equation for height and crown diameter was determined with satisfactory results by coefficients R and R2 and performance metrics MAE, RMSE, and regression residuals, and it was possible to monitor the temporal profile of the height of the coffee cultivar in the field based on aerial images.

The Impacts of Current Climate Variability on Coffee Production in the Northern and Southern Highlands of Tanzania

Coffee is the most traded commodity in the world. In Tanzania, Coffee is the second largest traditional commodity. However, several climate change studies have predicted that coffee production will be reduced as a result of climate change. Therefore, the study aimed to assess the impact of current climate change on Tanzania&amp;rsquo;s Arabica coffee production and determine the most significant climatic variables, which influence coffee production in the respective regions. Global interpolated climatic database (Worldclim dataset) and official historical coffee production data from Tanzania Coffee Board for a period of 40 years (1970-2018) were used. Climatic parameters and coffee production were compared through descriptive statistics, correlation analysis, and multiple regressions. The Mann-Kendall method was used to detect significant trends in climatic data. The minimum temperature has been increasing at a higher rate than the maximum temperature in the Northern and Southern Highlands zones. A 1 &amp;deg;C increase in minimum temperature (Tmin) during short rains and annual mean temperature (Tmean) resulted in a significant coffee production decrease (-6,041 and -4,450 tons) in Kilimanjaro and Arusha regions respectively. In the Southern Highlands zone coffee production positively correlated with temperature. A significant reduction in coffee production due to a decline in long rains was also observed in the Kilimanjaro region. The warming and drought trends are likely to continue with significant implications on coffee production and this, calls for the development of suitable adaptation strategies to sustain production. Such strategies may include, re-adapting the coffee agronomic practices to climate change, improving water and nutrient use efficiency in coffee trees, and developing genetically improved coffee cultivars that will tolerate the impact of climate change.