Mint differentiation produced by conventional, organic and permaculture agricultural method by SPME-HS-GC-MS

The Intergovernmental Panel on Climate Change (IPCC) recently published a report demonstrating that environmental damage from the extensive conventional model of agriculture such as loss of biodiversity, loss of soil and desertification, excessive water use, greenhouse gas emissions and imbalance biogeochemical cycles have reached such high levels that they can affect human food security. Another problem associated with the conventional model is the use of pesticides that promote environmental pollution causing adverse effects to live beings including humans, where many studies demonstrate the harmful effects on human health for the rural population most exposed to these products. Consequently, the discussion about alternative models of agriculture is growing. The consumption of food produced by alternative methods is increasing, the global market is around the $ 94 billion, in the United States 4% of the population consumes these products, in Europe varies from 3 to 20% between each country, while in Brazil this number rises to 15%. Among alternative farming models, permaculture has gained a lot of public interest because it is a sustainable model that seeks to mimic the natural ecosystem of the region. However, this model still lacks scientific work. This paper seeks to differentiate between conventional, organic and permaculture agricultural products. An SPME-GC/MS was used to differentiate 20 peppermint samples from three groups of different agricultural, conventional, organic and permaculture methods from different producers of the São Paulo state campinas region. The software XCMS and metaboanalyst were used to develop classification model. With this model it was possible to differentiate the mint samples from permaculture, however it was not possible to differentiate organic and conventional samples using Principal Exploratory Analysis Component Analysis, Hierarchical Clusters Analysis or supervised Partial Least Driscriminant. It was possible to identify two candidate biomarkers Dihydrocarveol acetate and Dihydrocarveol that have flavor and antimicrobial properties respectively.