Agriculture

To address the restricted operating space in reserved maize sowing strips, surface soil compaction, the poor trafficability of conventional tillage machinery, and the risk of disturbing adjacent wheat rows under wheat–maize relay intercropping in Xinjiang, a front-mounted narrow-strip tillage device for a maize interseeder was designed. The device comprises a rotary tillage assembly and a soil-lifting device. An IT225 rotary blade was selected, and the structures of the rotary tillage assembly and the pointed-shovel soil-lifting device were designed. Kinematic and force analyses established operating ranges of 3–5 km·h⁻¹ for forward speed, 240–360 r·min⁻¹ for blade-shaft rotational speed, and 80–120 mm for rotary tillage depth. A discrete element model of the soil–tillage device interaction was developed in EDEM. A three-factor, three-level Box–Behnken experiment was conducted with forward speed, blade-shaft rotational speed, and rotary tillage depth as factors and soil fragmentation rate and soil bulk density as responses. Quadratic regression models were developed using Design-Expert and subjected to constrained numerical optimization. Both regression models were highly significant, whereas their lack-of-fit terms were nonsignificant, indicating good predictive performance. The optimum combination comprised a forward speed of 3.88 km·h⁻¹, a blade-shaft rotational speed of 348 r·min⁻¹, and a rotary tillage depth of 120 mm; the corresponding predicted soil fragmentation rate and soil bulk density were 92.40% and 1.38 g·cm⁻³, respectively. Field validation produced a soil fragmentation rate of 93.64% and a soil bulk density of 1.35 g·cm⁻³; the corresponding relative errors were 1.34% and 2.17%, respectively, both below 5%. These findings provide a basis for the design and operating-parameter matching of tillage components for maize interseeders used in wheat–maize relay intercropping in Xinjiang.

Neglected and underutilized species, also known as minor or orphan crops, are a core component of local food systems in Africa. Roots, tubers, and bananas (RTB) are a particular group of these crops characterized by vegetative propagation. This reproductive system poses challenges for their conservation. Community seed banks commonly conserve seeds of grains, oil crops, pulses, and vegetables. However, little is known about whether and how community seed banks around the world include roots, tubers, and bananas, which cannot be easily stored in conventional seed-bank facilities. The objective of this review was to contribute to the design of a method that can be effectively used by community seed banks to conserve RTB while complementing the conservation method already used for other crops. We conducted a systematic literature review and assessed the initial results of a pilot study involving a new community-based conservation mechanism introduced in Ghana: the community field bank. The strengths and challenges of the two methods were compared. Field bank and seed bank can become complementary components, both conceptually and practically, of a dynamic conservation system that farmers can master through learning by doing. Initial observations from the field in Ghana suggest that farmers have grasped the concept and are now monitoring the practicalities of RTB field-bank plots, with the distribution of the first vegetatively propagated planting materials taking place toward the end of 2026. Further research, both within and beyond the pilot study sites, is warranted to refine the field-bank method.

In agricultural environments, foliage occlusions present a significant challenge for crop inspection. While fully autonomous systems often struggle to generalize across these occluded conditions, human operators possess an inherent cognitive and visual adaptability that provides a valuable alternative for navigating such complexities. This work introduces an approach for crop inspection that combines Virtual Reality teleoperation with an Active Vision strategy to address occlusion limitations in agricultural environments. This specific configuration, leveraging human-driven active vision for detailed crop inspection, has not yet been widely explored. The system enables users to remotely explore a simulated crop plant through natural body and head movements, while a robot arm equipped with an RGB camera replicates these motions in real time. The proposed system was experimentally validated in a controlled laboratory setup using real sweet peppers with artificial leaves, where 30 participants without prior knowledge of the system performed peduncle localization tasks. Cycle completion time, Peduncle Detection Interaction (PDI) recall and precision, and subjective task workload (NASA-TLX) were evaluated. The results demonstrated an average cycle completion time of 12 s for each sweet pepper peduncle, a PDI recall of 96.7%, a PDI precision of 92.1%, and a mean NASA-TLX score of 32.7. Overall, the findings indicate that the proposed Virtual Reality-based Active Vision framework offers an intuitive and efficient means of viewpoint control, demonstrating its potential as a human–robot interaction solution for agricultural inspection tasks.