Elemental composition of green coffee and its contribution to dietary intake

Şemen, Sevcan; Mercan, Selda; Yayla, Murat; Açıkkol, Münevver

doi:10.1016/j.foodchem.2016.07.176

Cited by 68 publications

(39 citation statements)

References 32 publications

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“…The same range of elements reflecting a nutritional and organoleptic qualitative profile important for human health and vitality (Şemen, Mercan, Yayla, & Açikkol, 2017) was detected by traditional elemental analytical methods in conventionally farmed coffee beans from the same geographical regions (Liu et al, 2014, Habte et al, 2016). No toxic metals were detected in the samples, although Habte et al (2016) reported levels well below the short-term tolerable intake values for arsenic, mercury, cadmium, and other toxic metals in conventionally farmed Ethiopian green coffee beans.…”

Section: Discussionmentioning

confidence: 88%

Physico-elemental analysis of roasted organic coffee beans from Ethiopia, Colombia, Honduras, and Mexico using X-ray micro-computed tomography and external beam particle induced X-ray emission

et al. 2019

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Section: Discussionmentioning

confidence: 88%

Physico-elemental analysis of roasted organic coffee beans from Ethiopia, Colombia, Honduras, and Mexico using X-ray micro-computed tomography and external beam particle induced X-ray emission

et al. 2019

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“…Coffee (Coffea arabica L.) is one of the most widely consumed beverages worldwide, second only to water and tea, and it is classified as the second most commercialized product worldwide after petroleum [1]. Most coffee is produced in Brazil, Vietnam and Colombia.…”

Section: Introductionmentioning

confidence: 99%

Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics

Flores-Valdez

Meza-Márquez

Osorio-Revilla

et al. 2020

Foods

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Food adulteration is an illegal practice performed to elicit economic benefits. In the context of roasted and ground coffee, legumes, cereals, nuts and other vegetables are often used to augment the production volume; however, these adulterants lack the most important coffee compound, caffeine, which has health benefits. In this study, the mid-infrared Fourier transform spectroscopy (FT-MIR) technique coupled with chemometrics was used to identify and quantify adulterants in coffee (Coffea arabica L.). Coffee samples were adulterated with corn, barley, soy, oat, rice and coffee husks, in proportions ranging from 1–30%. A discrimination model was developed using the soft independent modeling of class analogy (SIMCA) framework, and quantitative models were developed using such algorithms as the partial least squares algorithms with one variable (PLS1) and multiple variables (PLS2) and principal component regression (PCR). The SIMCA model exhibited an accuracy of 100% and could discriminate among all the classes. The quantitative model with the highest performance corresponded to the PLS1 algorithm. The model exhibited an R2c: ≥ 0.99, standard error of calibration (SEC) of 0.39–0.82, and standard error of prediction (SEP) of 0.45–0.94. The developed models could identify and quantify the coffee adulterants, and it was considered that the proposed methodology can be applied to identify and quantify the adulterants used in the coffee industry.

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“…Among the minerals present in green coffee beans are nitrogen (N), phosphorus (P), calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn), and boron (B), 8 whose relative importance changes in different stages of bean processing, 9 until reaching the cup, where they contribute to the daily intake of these elements. 10,11 The accumulation of some minerals in coffee beans has been related to the composition of soil 12 and environmental conditions where the coffee plant is grown, 13 and it has even been possible to determine the authenticity and geographical origin of some coffee samples 14,15 by using elemental analysis of the bean as a tool. However, the variability in the elemental content of coffee samples is wide, even for samples from the same region or country.…”

Section: Introductionmentioning

confidence: 99%

On the soil–bean–cup relationships in Coffea arabica L

et al. 2020

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BACKGROUND: The relationships between soil and coffee beans variables were evaluated and then the influence of bean composition on cup quality attributes was computed by means of relation studies. A total of 139 coffee and soil samples were collected directly from the same number of coffee plantations in Chiapas, Mexico. RESULTS: In the elemental composition, only phosphorus, potassium, calcium, and copper in coffee beans had a significant (P < 0.05) relationship with the content of the same elements in soil. The level of macro-and microelements in the coffee bean affected some of the cup quality attributes, but variables such as texture, titratable acidity, and pH of water in soil had a major influence on those attributes. Caffeine, trigonelline, and 5-caffeoylquinic acid in green coffee beans also had a significant influence (P < 0.05) on the sensory attributes of the beverage. CONCLUSION: The elemental composition of soil and coffee beans was important in explaining the cup quality attributes, but the most important variables influencing the sensory quality of coffee were altitude of plantations and moisture of coffee beans.

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Elemental composition of green coffee and its contribution to dietary intake

Cited by 68 publications

References 32 publications

Physico-elemental analysis of roasted organic coffee beans from Ethiopia, Colombia, Honduras, and Mexico using X-ray micro-computed tomography and external beam particle induced X-ray emission

Physico-elemental analysis of roasted organic coffee beans from Ethiopia, Colombia, Honduras, and Mexico using X-ray micro-computed tomography and external beam particle induced X-ray emission

Identification and Quantification of Adulterants in Coffee (Coffea arabica L.) Using FT-MIR Spectroscopy Coupled with Chemometrics

On the soil–bean–cup relationships in Coffea arabica L

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