Abstract
The south of Minas Gerais, Brazil stands out among various regions through its capacity for production of specialty coffees. Its potential, manifested through being one of the most award-winning Brazilian regions in recent years, has been recognized by the Cup of Excellence (COE). With the evident relationship between product quality and the environment in mind, the need arises for scientific studies to provide a foundation for discrimination of product origin, creating new methods for combating possible fraud. The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model. Coffee samples were composed of ripe yellow and red fruits collected manually at altitudes below 1,000 m, from 1,000 to 1,200 m and above 1,200 m. The yellow and red fruits were subjected to dry processing and wet processing, with five replications. A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling. The model generated had an accuracy rate of 89% in discrimination of environments and was composed of the isotope variables of ?15N, ?13C, %C, %N, ?D, ?18O (meteoric water) and sensory analysis scores. In addition, for the first time, discrimination of environments on a local geographic scale, within a single municipality, was proposed and successfully concluded. This shows that isotope analysis is an effective method in verifying geographic origin for specialty coffees.
Highlights
Coffee is a popular product that moves the world economy
The aim of this study was to evaluate the use of carbon and nitrogen isotopes in discrimination of production environments of specialty coffees from the Serra da Mantiqueira of Minas Gerais by means of the discriminant model
A total of 119 samples were used for discrimination of specialty coffee production environments by means of stable isotopes and statistical modeling
Summary
Coffee is a popular product that moves the world economy. Ever more demanding domestic and international markets have awakened the interest of large producer countries in respect to indication of geographic origin to add value to the product. Elemental isotopic composition of a plant tissue or organ varies according to its geographic origin (Martinelli et al, 2009; Gonzalvez et al, 2009). In this context, many authors have used different isotopes, correlating them with environmental aspects, in an attempt to obtain an isotopic signature for the most diverse production origins of coffees on a more global scale (Serra et al, 2005; Martinelli et al, 2009; Rodrigues et al, 2009; Rodrigues et al, 2011; Weckerle et al, 2002). During the evaporation and condensation phases, they are affected by temperature and www.ccsenet.org/jas
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