To increase crop yields, achieve financial goals, and eliminate time-consuming work, farmers have begun employing machine vision in the agriculture industry. Problems like world hunger and labor shortages are pushing the agricultural sector to find innovative solutions to these problems. Machine vision is promising to be a ground-breaking solution that can assist farmers with improved planting methods, better weed control, and more efficient irrigation practices.
Applications for Machine Vision in the Agriculture Industry
One of the most valuable ways machine vision is helping agribusiness is through improving their operations. Thanks to machine vision, farmers are better at planning, managing, and controlling their crops. With better farming practices in place, crop yields are increasing while costs are going down. Machine vision has the potential to touch all stages of crop development.
Sowing - Planting is usually the most laborious part of farming. Seeds must be evenly distributed across the field to achieve optimal yields. Robots equipped with machine vision can perform the work of sowing faster and more accurately than conventional methods, helping to ensure profitable crops and healthy produce. The robots can also capture detailed images of the land, identify where seeds are to be sown and plant them perfectly.
Weeding - Currently, farmers use large amounts of herbicides to control weeds that compete with other plants for nutrients and damage valuable crops. Due to time constraints, farmers will spray entire fields, targeting weed-infested and weed-free crops alike. With machine vision systems, farmers are able to capture images of a field, analyze the photos, and send out robots to kill the weeds.
Watering - Farmers know they get the best crop yields when their crops receive the perfect amount of water throughout the growing season. Vision systems can monitor soil moisture content and crop health autonomously. Robots are then tasked to deliver the right supply of water at the appropriate time.
Machine Vision Ensures Safe Food Products
Food growers can also count on machine vision systems to help them deliver safe food products to consumers. Computer vision can look for problems like fungal infections, crop diseases, and pests. Even after harvesting, the data logged by machine vision systems can later be used to track down potential causes for foodborne illness and help keep it out of kitchens.
Additionally, some crop-picking robots can skip over plants that are diseased or that have begun to rot. During the sorting process, machine vision can even be used to eliminate other undesirable crops so that they are never sent to be packaged. After food is packaged, inspection stations can identify faulty packaging that won’t survive the trip to the table. So, machine vision can have a very beneficial impact on just about all stages of the packing and inspection process for farm produce.
Discover more ways that Vision Systems Bring Agriculture into a Smarter, Automated Future.