In order to meet the food needs of the world’s fast-growing population, crop growing needs to be optimized, and yields need to be boosted. One of the tools to help achieve this could be a robot like Mineral, developed by X (formerly Google X Lab).
To better understand the water or nutrient needs, the idea is to gather a maximum amount of data in real time. Then, farmers will be able to act directly on the information gathered by the robot.
For example, Mineral can count the number of strawberries, peas, berries or lettuce, from sprout to harvest, present on its path to analyze crops and help predict yields. It can also detect the presence of a bacterium or its undesirable effects on a given plot so that the farmer can take fast action to prevent the problem from spreading further. The rover’s data can also help optimize water consumption.
The goal of the team working on Mineral today is to create new hardware and software tools to help farmers deal with the complexity of food production. This prototype has already analyzed strawberry fields in California and soybean fields in Illinois to find new ways to help farmers produce more and better. Eventually, by combining the imagery collected by the robot with other data (soil composition, weather conditions, etc.), the aim is to use machine learning to predict, over time, how plants will grow and interact with their environment.