In November 2010, FAO and WHO defined the term, pesticide, as follows: to embrace active ingredients in any form, irrespective of whether, or to what extent, they have been formulated for application. The term is usually associated with materials intended to kill or to control pests (insecticides, fungicides, herbicides, etc.) but, for the present purposes, it also embraces certain materials to control the behaviour or physiology of pests (e.g., insect repellents and insect growth regulators) or of crops during production or storage. Obviously, the term pesticide has close relationships with chemistry, environment, ecology, biology, food safety, public health, and toxicology. The history of pesticides shows that people have employed pesticides to protect their crops since before 2000 BC. In the 20th century, the research and discovery of pesticides have been developed. Up to now, the data sets involving chemistry, ecology, environment, ecology, biology, food safety, public health, and toxicology generated in pesticide discovery were huge. Unfortunately, the data are not used efficiently because most people have not realized their important role and are used to doing discovery in the traditional mode: people design a new product by experience or inspiration, then do experiments without predictions. Herein, we propose a mode of pesticide discovery which combines the traditional mode while employing big data: design new products by experience or inspiration, make predictions and do experiments, and introduce a platform of prediction.

Mode of pesticide discovery in the big data era

248th National Meeting (2014)

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