Operating performance of manual, semi-automatic, and automatic tractor guidance systems for precision farming

Abstract

Precision agriculture is increasingly relying on tractor auto-steer systems to boost productivity and optimize crop inputs. Identifying field variations and performance, on the other hand, is necessary for giving site-specific recommendations. This study reports the field operating performance indicators of manual (MG), semi-automatic (SG), and automatic (AG) tractor guidance for weed control in wheat production in Southern Italy. Performance indicators include effective worked area, overall working time, effective field capacity, field efficiency, fuel consumption, and product usage. The SG tractor guidance working times were similar to the MG, but with significant savings in the herbicide spray solution and work quality. In terms of all parameters examined, the AG outperformed the SG and MG. The AG was 54% faster than the MG, resulting in an increased area worked and effective field capacity of 5 and 46%, respectively. The total time (effective time plus non-productive time) was reduced by 28%, while overlapped areas by 88.9%. Herbicide and fuel input was reduced by 30 and 11.5%, respectively. A streamlined environmental analysis indicated that AG could reduce the energy and carbon intensity of the one-time weed control process by 25 and 27% for each hectare. Our results confirm that auto guidance provides numerous benefits (e.g., machining uniformity, increased work quality, reduced resource use, and reduced environmental burdens), supporting the larger goal of agricultural production sustainability.

Keywords

• automated guidance system
• smart agriculture
• self-steering tractors
• variable rate technology