This review examines how indigenous water-harvesting systems have helped dryland communities manage scarce water for centuries. It shows that many are now declining due to groundwater pumping, migration, climate change, policy shifts, weak maintenance, urbanization and natural disasters. The authors argue that revitalizing these systems can improve water access, agriculture, livestock production, groundwater recharge and flood control, while preserving traditional knowledge. Combined with appropriate modern technologies and supportive policies, these systems can strengthen water resilience in arid and semi-arid regions.

An RMIT innovation uses ultrasound to extract leaf protein from discarded cauliflower leaves, identifying a potential new use for vegetable scraps.

New research shows that the nutritional value of Indian millets includes a rich diversity of lipids, including a previously undetected group that may offer potential health benefits.

Vaccination has saved millions of lives and is regarded as one of modern medicine's most important successes. Effective vaccination programs should be based on risk assessment that considers demographic and occupational factors. When developing a vaccination program, it is essential to identify the target groups, including travelers, infants, high-risk workers, and those in critical roles such as farming and agriculture. In biosafety and biosecurity, vaccines are a key component of measures designed to protect laboratory personnel, the community, and the environment. Guidelines from global health organizations such as the Centers for Disease Control and Prevention are tailored to specific pathogens and depend on the type of work performed and the associated risk. These guidelines are continuously revised and updated to ensure the effectiveness of vaccination programs. Vaccines also play a role in One Health approaches that are focused on the interconnectedness of animals, humans, and the environment. Targeted vaccination strategies for both domestic animals and wildlife are necessary to maintain animal health, improve livestock productivity, and prevent the spread of zoonotic and foodborne diseases to humans. In this paper, we aimed to provide an overview regarding the crucial roles of vaccines in biosafety, biosecurity, and One Health approaches, as well as to highlight the importance of targeted and personalized strategies to improve the effectiveness of vaccination programs. Herein, we also discuss various vaccines aimed at specific target groups as recommended by global health organizations, with a particular emphasis on laboratory workers and the vaccines necessary to reduce laboratory-acquired infections. Finally, we discuss animal vaccines and targeted strategies for vaccinating domestic and wildlife populations.

Global climate change is reshaping agricultural ecosystems. As warmer winters become more prevalent, snow droughts caused by insufficient snowfall are becoming more frequent. This leaves winter wheat, which relies on snow cover for insulation and water supply, vulnerable to low-temperature frost damage and water stress, posing a major threat to global food security. A research team from The Hong Kong Polytechnic University (PolyU) has utilised innovative explainable machine learning to uncover the persistent and significant negative impact of snow droughts on winter wheat yields, highlighting that global food security is facing unprecedented challenges. This breakthrough study provides key scientific evidence for building climate-resilient agriculture, ensuring food security and promoting sustainable development.

Drought is one of the most damaging environmental stresses facing forests, but the genetic switches that help trees withstand water shortage remain only partly understood. 

In spectroscopic analysis, the development of cost-effective handheld infrared spectrometers has revolutionized monitoring practices, particularly in industries like agriculture and food production. Analysis time and efficiency of processing the raw spectral data are further boosted by the implementation of machine learning models for identification and quantification purposes. However, the inherent spectral variations arising from the random spatial arrangement of inhomogeneous granular media pose accuracy challenges. To enable real-time monitoring with enhanced precision, a scanning approach is presented herein. It involves the utilization of microelectromechanical systems-based infrared spectral sensors with spot sizes of 3 to 20 mm, facilitating spectrospatial averaging by scanning over the sample surface. A model is developed for the absorbance repeatability of the nonhomogeneous samples. It takes into account the effects of spatial and temporal noise, the sample scanned area, and the optical throughput of the device, also revealing an optimum point for the light spot size. Through experimental validation performed on wheat, chosen among the major cereals, we demonstrate that the spatial scanning method considerably improves absorbance repeatability of the 10-mm sensor by up to 5 times compared to stationary measurements, showing a good agreement with the theoretical model. The impact of sample scanning on artificial intelligence-based chemometrics model accuracy is rigorously assessed using heterogeneous feed samples, revealing substantial enhancements in the accuracy of prediction models. The 10-mm sensor exhibits a substantial reduction in root mean square error for protein (−60%) and for moisture (−43.5%), 2 major nutritional quality indicators of cereal grains.