To identify any diseases, it is always advisable to:
- Look at the leaves: brown or black spots may indicate scab (apple, pear), anthracnose, rust or fungal infections; yellowed or curled drops could be caused by nutrient deficiency, aphids, powdery mildew (white powdery coating) or viruses; gnawed edges could indicate the presence of insects such as caterpillars or beetles.
- Analyze the fruits: some molds can be symptoms of monilia (moldy and dry fruits), botrytis (gray mold) or anthracnose; some deformations can instead derive from sudden changes in water levels.
- Check the trunk and branches: cracks in the bark can indicate fungal infections and the release of resin, common in peach, apricot and cherry trees, is often caused by fungi or bacteria.
- Identify visible pests such as aphids (small green, black or yellow sap-sucking insects, often accompanied by ants), scale insects (small white or brown shields attached to branches and leaves), thrips and mites (tiny insects that cause silver spots or deformations in leaves).
- Pay attention to environmental conditions: high humidity can promote the growth of fungi such as downy mildew and powdery mildew.
The PlantVoice app is designed to simplify the identification of plant diseases through continuous and advanced monitoring. Unlike conventional methods, which rely on manual inspections and laboratory tests, PlantVoice technology uses an innovative sensor, inserted directly into the plant stem, to collect biochemical data.
When a fungal, bacterial or parasitic infection begins to develop, the plant undergoes internal physiological changes that PlantVoice can detect before visible symptoms appear. The data collected is analyzed by artificial intelligence algorithms, which notify farmers of any anomalies.
Through the app, it is possible to
✔ Receive early warnings on possible diseases, allowing timely interventions.
✔ Consult detailed reports with the analysis of the physiological parameters of the plant.
✔ Integrate the data with other agricultural tools, such as drones or meteorological sensors, for even more precise management.
This approach reduces the risk of production losses and limits the excessive use of pesticides, improving the quality of the harvest and optimizing management costs.