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Coffee is one of the most important beverages in the world and is produced from Coffea spp. beans. Diterpenes with ent -kaurane backbones have been described in this genus, and substances such as cafestol and kahweol have been widely investigated, along with their derivatives and biological properties. Other coffee ent -kaurane diterpenoids have been reported with new perspectives on their biological activities. The aim of this review is to update the chemical diversity of ent -kaurane diterpenoids in green and roasted coffee, detailing each new compound and reporting its biological potential. A systematic review was performed using the bibliographic databases (SciFinder, Web of Science, ScienceDirect) and specific keywords such as "coffea diterpenes", "coffee diterpenes", "coffee ent-kaurane diterpenes" and "coffee diterpenoids". Only articles related to the isolation of coffee ent -kaurane compounds were considered. A total of 146 compounds were related to Coffea spp. since the first report in 1932. Different chemical skeletons were observed, and these compounds were grouped as furan-type, oxidation-type, rearrangement-type, lacton-type, and lactam-type, among others. In general, the new coffee diterpenoids showed potential as antidiabetic, antidiapogenic, α-glucosidade inhibition, antiplatelet activity, and Cav.3 inhibitors agents, revealing the possibilities for the design, discovery, and development of new drugs.

The microwave-assisted extraction (MAE) of 13 different green coffee beans (Coffea arabica L.) was compared to Soxhlet extraction for oil obtention. The full factorial design applied to the microwave-assisted extraction (MAE), related to time and temperature parameters, allowed to develop a powerful fast and smooth methodology (10 min at 45°C) compared to a 4h Soxhlet extraction. The quantification of cafestol and kahweol diterpenes present in the coffee oil was monitored by HPLC/UV and showed satisfactory linearity (R(2)=0.9979), precision (CV 3.7%), recovery (<93%), limit of detection (0.0130 mg/mL), and limit of quantification (0.0406 mg/mL). The space-time yield calculated on the diterpenes content for sample AT1 (Arabica green coffee) showed a six times higher value compared to the traditional Soxhlet method., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Optimisation of a microwave-assisted methanolysis was performed to obtain cafestol and kahweol directly from green coffee oil (Coffea arabica). A two-factor (the methanolysis period and temperature), three-level, factorial experimental design (3(2)) was adopted. The methanolysis procedure was performed under microwave irradiation, using closed vessel and accurate fast responding internal fibre-optic temperature probe. The effects on the responses were measured by HPLC. After 3 min of microwave irradiation (hold time) at 100°C, with 500 mg of green coffee oil, a yield higher than 99% was obtained. The yield of this reaction is 26% after 2h when working under conventional heating. The methods described in the literature lead to long reaction times, poor yields and formation of side products. The microwave-assisted technique proved to be faster, avoided undesired side products and gave better conversion, when compared to conventional heating process., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Coffee samples were analyzed by GC/MS in order to determine the most important peaks for the discrimination of the varieties Arabica and Robusta. The resulting peak tables from chromatographic analysis were aligned and pretreated before being submitted to multivariate analysis. A rapid and easy-to-perform peak alignment procedure, which does not require advanced programming skills to use, was compared with the tedious manual alignment procedure. The influence of three types of data pretreatment, normalization, logarithmic and square root transformations and their combinations, on the variables selected as most important by the regression coefficients of partial least squares-discriminant analysis (PLS-DA), are shown. Test samples different from those used in the calibration and comparison with the substances already known as being responsible for Arabica and Robusta coffees discrimination were used to determine the best pretreatments for both datasets. The data pretreatment consisting of square root transformation followed by normalization (RN) was chosen as being the most appropriate. The results obtained showed that the much quicker automated aligned method could be used as a substitute for the manually aligned method, allowing all the peaks in the chromatogram to be used for multivariate analysis., (Copyright © 2010 Elsevier B.V. All rights reserved.)