Harvesting and post-harvesting technologies enable growers to mechanise the labour-intensive harvesting process. With improvements in machine learning, artificial intelligence and mechatronics, this technology is set to have big impacts in areas including safety, resource management, and logistics and value chain efficiencies.
Post-harvest automation includes product handling and sorting, packaging and inventory management.
Automating your operations will usually require on-farm connectivity and a workplace design that allows machines to work effectively.
Harvesting and Post-Harvesting Technology that combines artificial intelligence and machine learning with precision robotics and sensors will allow growers to:
Generate real-time analysis about harvest quantity and quality.
Support selective harvesting thereby more accurately targeting quality and/or yield specifications.
Reduce the cost of labour for picking, packing, and sorting.
Operate around-the-clock and perform multiple functions (e.g. picking and sorting) simultaneously.
The difficulty of harvest automation in horticulture, compared to broadacre cropping, is that horticultural produce requires a higher degree of accuracy and manual dexterity. This means robots need improved perception and sensors to detect produce specifications and then selectively harvest without causing damage to other produce or the supporting plant. Such sophisticated technology can come with a hefty price tag, and it is important to consider whether automating your harvest will provide sufficient return on investment.
Despite these challenges, robotic pickers and harvesters offer a number of valuable opportunities to growers. For example, in orchards and greenhouses, automated harvesting solutions use artificial intelligence and machine learning to recognise and pick fruit ready for harvest while leaving the unripe fruits on tree or vine.
