Open Access

Conventional agriculture faces escalating environmental and economic challenges. Intensive monoculture farming and the extensive use of chemical additives, such as fertilizers and pesticides, contribute to environmental pollution, biodiversity loss, and soil and water degradation, threatening both natural resources and the long-term resilience of agricultural systems. Mixed cropping, the cultivation of multiple crop species together, presents a promising alternative by optimizing resource use, enhancing soil and water quality, and reducing dependency on chemical inputs. However, its industrial application remains limited due to complexities and the lack of technical solutions, particularly in harvesting. Computer vision technology holds great potential to address these technical limitations. This paper supports agricultural machinery manufacturers by presenting a technology assessment of computer vision applications in harvesting machines for industrial mixed crop cultivation. Functional capabilities of computer vision were categorized and matched against the requirements of various functions within industrial mixed-crop harvesting, creating impact matrices that evaluate the relevance of computer vision per function. The results demonstrate the substantial potential of computer vision to facilitate, or even enable, the harvesting of mixed cropping systems at an industrial scale. The findings offer a technological foundation for developing mixed crop harvesters, informing evaluation and selection processes for final design solutions.

The following paper presents functionalities of harvesting machines for industrial intercropping use cases and a typology of their applications. The aim is to support the design and development of novel intercropping harvesting machines that are required for the implementation of industrial intercropping systems. Building upon established intercropping use cases, distinctive features and their variations are outlined, and a morphology created. The morphology is then used to develop typologies of industrial intercropping use cases, which capture various manifestations of future industrial intercropping harvesting. Based on the types, functionalities for harvesting machines are derived. Given the transformative potential of this research, it is evident that substantial modifications to existing systems are essential. The envisioned machinery requires for most use cases sophisticated software integration, encompassing data analysis, artificial intelligence, and robotics. This paper identifies the unmet needs within the realm of industrial intercropping. It also creates an understanding of the industrial use cases and presents a concept of the required harvesting technologies, thereby contributing to a more sustainable future in agriculture.