Over the last 3,800 years, agro-pastoral activities have accelerated alpine soil erosion at a pace 4-10 times faster than their natural formation. The history of this erosion has just been revealed for the first time by a research team led by a CNRS scientist. The team has shown that high-altitude soil was degraded first, under the combined effect of pastoralism and forest clearing to facilitate the movement of herds. Medium- and low-altitude soil was then eroded with the development of agriculture and new techniques such as the use of ploughs, from the late Roman period to the contemporary period. The study has also revealed that the acceleration of soil erosion in mountain environments by human activities did not begin everywhere in the world in synchronous fashion.

Colombia’s biofortified rice provides 1.5 more zinc than normal rice. Consumers say the rice is as good as premium rice and are willing to pay more for it. Improving staple foods everywhere should be part of national nutrition policies.

With climate change exacerbating drought conditions, scientists in Japan have identified a hidden player in plant survival: myosin XI. This unexpected link between the motor protein and hormone signalling that regulates water loss deepens our understanding of plant stress responses. It also opens a promising avenue for engineering drought-resilient crops. Targeting myosin XI could enhance water-use efficiency and help reshape the future of agriculture in an increasingly arid world.

Scientists from the Marine Biological Association and the University of Plymouth have revisited turn-of-the-century forecasts about the many and varied threats they thought were likely to face the world’s shorelines in 2025. Their new study highlights that many of their forecasts were correct, either in whole or in part, while others haven’t had the impacts that were envisaged at the time. They have also charted some of the other threats to have emerged and/or grown in significance since their original work, with notable examples including global plastic pollution, ocean acidification, extreme storms and weather, and light and noise pollution.

The increase in precision agriculture has promoted the development of picking robot technology, and the visual recognition system at its core is crucial for improving the level of agricultural automation. This paper reviews the progress of visual recognition technology for picking robots, including image capture technology, target detection algorithms, spatial positioning strategies and scene understanding. This article begins with a description of the basic structure and function of the vision system of the picking robot and emphasizes the importance of achieving high-efficiency and high-accuracy recognition in the natural agricultural environment. Subsequently, various image processing techniques and vision algorithms, including color image analysis, three-dimensional depth perception, and automatic object recognition technology that integrates machine learning and deep learning algorithms, were analyzed. At the same time, the paper also highlights the challenges of existing technologies in dynamic lighting, occlusion problems, fruit maturity diversity, and real-time processing capabilities. This paper further discusses multisensor information fusion technology and discusses methods for combining visual recognition with a robot control system to improve the accuracy and working rate of picking. At the same time, this paper also introduces innovative research, such as the application of convolutional neural networks (CNNs) for accurate fruit detection and the development of event-based vision systems to improve the response speed of the system. At the end of this paper, the future development of visual recognition technology for picking robots is predicted, and new research trends are proposed, including the refinement of algorithms, hardware innovation, and the adaptability of technology to different agricultural conditions. The purpose of this paper is to provide a comprehensive analysis of visual recognition technology for researchers and practitioners in the field of agricultural robotics, including current achievements, existing challenges and future development prospects.