Big Data and Machine Learning to Improve European Grapevine Moth () Predictions.

Machine Learning (ML) techniques can be used to convert Big Data into valuable information for agri-environmental applications, such as predictive pest modeling. (Denis & Schiffermüller) 1775 (Lepidoptera: Tortricidae) is one of the main pests of grapevine, causing high productivity losses in some vineyards worldwide. This work focuses on the optimization of the Touzeau model, a classical correlation model between temperature and development using data-driven models.

Phytochemical Profiling of L. Flower and Leaf Extracts and Their Antimicrobial Potential against Almond Tree Pathogens.

Despite extensive research on the chemical composition of elderberries and their numerous uses in pharmaceutical, beverage, and food production, there is still a lack of knowledge about leaves and flowers' antimicrobial activity against plant pathogens. In this study, the phytoconstituents of their aqueous ammonia extracts were first characterized by infrared spectroscopy and gas chromatography-mass spectrometry. The major phytocompounds identified in the flower extract were octyl 2-methylpropanoate; 3,5-dihydroxy-6-methyl-2,3-dihydropyran-4-one; propyl malonic acid; adenine; and 1-methyl-2-piperidinemethanol.

Valorization of L. Bark as a Source of Phytochemicals with Antimicrobial Activity against Apple Tree Diseases.

Cork, an anatomic adaptation of the bark of L. through its suberization process, finds its main application in the production of bottle stoppers. Its processing results in a large waste stream of cork fragments, granulates, and dust, which may be susceptible to valorization.