BEIJING (PingWest) -- The "Artificial Intelligence (AI) Market in Agriculture - Growth, Trends, and Forecast (2019 - 2024)" report has been added to ResearchAndMarkets.com's offering.
The artificial intelligence (AI) market in agriculture is expected to register a CAGR of over 21.52%, during the forecast period of 2019-2024.
Driverless tractor is trending in market as these tractor can steer automatically using GPS-based technology, lift tools from the ground, recognize the boundaries of a farm, and can be operated remotely using a tablet. A fleet of smaller automated tractors could lift farmer revenue by more than 10 percent and can reduce farm labor costs.
- Maximize crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyze crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant.
- Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programs and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioral aspects in a group of cattle.
- Increase use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is driving the market as the use of drones in the agriculture industry can be use in crop field scanning with compact multispectral imaging sensors, GPS map creation through onboard cameras, heavy payload transportation, and livestock monitoring with thermal-imaging camera-equipped drones, which increases the demand of UAVs.
- However, lack of standardization is restraining the market growth as lack of standards in data collection, and lack of data sharing is high, and machine learning and artificial intelligence and advanced algorithm design have moved so fast, but the collection of well-tagged, meaningful agricultural data is way behind.
Source: Research and Markets