Phenolics are widespread dietary antioxidants. Among these, chlorogenic acids (CGAs) received considerable attention for their wide distribution and part of human diet with potential biological effects. CGAs (71 compounds), being esters of derivatives of cinnamic acids with quinic acid are widely distributed in plant materials. Coffee is among the highest found in plants, ranging from 4 to 14%. Besides, these are reported in plant foods such as apples, pears, carrot, tomato, sweet potato, Phyllostachys edulis, oilseeds, Prunus domestica L, cherries, and eggplant. The traditional Chinese medicinal plants such as flowers and buds of Lonicera japonica Thunb and the leaves of Eucommia ulmodies contained CGAs as bioactive compound. These play an important role in the formation of roasted coffee flavor and have a marked influence on coffee cup quality. CGAs are considered as main precursors of coffee flavor and pigments. Recent technological advancements in the separation and purification of CGAs such as molecular-imprinted polymer technique; microwave-assisted extraction; pH gradient counter current chromatography has also been described. The consumption of coffee correlated to several health benefits such as reducing the risk of human chronic diseases such as inflammation, diabetes, and cardiovascular disease owing to its antioxidant potential.

Internet of things (IoT) results in massive amount of streaming data, often referred to as "big data", which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-food systems. Following an introduction to the fields of IoT, big data, and AI, we discuss the role of IoT and big data analysis in agriculture (including greenhouse monitoring, intelligent farm machines, and drone-based crop imaging), supplychain modernization, social media (for open innovation and sentiment analysis) in food industry, food quality assessment (using spectral methods and sensor fusion), and finally, food safety (using gene sequencing and blockchain based digital traceability). A special emphasis is laid on the commercial status of applications and translational research outcomes.

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