Grain scans: fast X-ray fluorescence microscopy for high-throughput elemental mapping of rice seeds

Interfacial interactions between minerals and organic matter: Mechanisms and characterizations

Minerals and organic matter are essential components of soil, with minerals acting as the "bone" and organic matter as the "skin". The interfacial interactions between minerals and organic matter result in changes in their chemical composition, structure, functional groups, and physical properties, possessing a significant impact on soil properties, functions, and biogeochemical cycles. Understanding the interfacial interactions of minerals and organic matter is imperative to advance soil remediation technologies and carbon targets. Consequently, there is a growing interest in the physicochemical identification of the interfacial interactions between minerals and organic matter in the academic community. This review provides an overview of the mechanisms underlying these interactions, including adsorption, co-precipitation, occlusion, redox, catalysis and dissolution. Moreover, it surveys various methods and techniques employed to characterize the mineral-organic matter interactions. Specifically, the up-to-date spectroscopic techniques for chemical information and advanced microscopy techniques for physical information are highlighted. The advantages and limitations of each method are also discussed. Finally, we outline future research directions for interfacial interactions and suggests areas for improvement and development of characterization techniques to better understand the mechanisms of mineral-organic matter interactions.

Research progress of the detection and analysis methods of heavy metals in plants

Heavy metal (HM)-induced stress can lead to the enrichment of HMs in plants thereby threatening people's lives and health via the food chain. For this reason, there is an urgent need for some reliable and practical techniques to detect and analyze the absorption, distribution, accumulation, chemical form, and transport of HMs in plants for reducing or regulating HM content. Not only does it help to explore the mechanism of plant HM response, but it also holds significant importance for cultivating plants with low levels of HMs. Even though this field has garnered significant attention recently, only minority researchers have systematically summarized the different methods of analysis. This paper outlines the detection and analysis techniques applied in recent years for determining HM concentration in plants, such as inductively coupled plasma mass spectrometry (ICP-MS), atomic absorption spectrometry (AAS), atomic fluorescence spectrometry (AFS), X-ray absorption spectroscopy (XAS), X-ray fluorescence spectrometry (XRF), laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS), non-invasive micro-test technology (NMT) and omics and molecular biology approaches. They can detect the chemical forms, spatial distribution, uptake and transport of HMs in plants. For this paper, the principles behind these techniques are clarified, their advantages and disadvantages are highlighted, their applications are explored, and guidance for selecting the appropriate methods to study HMs in plants is provided for later research. It is also expected to promote the innovation and development of HM-detection technologies and offer ideas for future research concerning HM accumulation in plants.

Predicting rice diseases using advanced technologies at different scales: present status and future perspectives

The past few years have witnessed significant progress in emerging disease detection techniques for accurately and rapidly tracking rice diseases and predicting potential solutions. In this review we focus on image processing techniques using machine learning (ML) and deep learning (DL) models related to multi-scale rice diseases. Furthermore, we summarize applications of different detection techniques, including genomic, physiological, and biochemical approaches. In addition, we also present the state-of-the-art in contemporary optical sensing applications of pathogen-plant interaction phenotypes. This review serves as a valuable resource for researchers seeking effective solutions to address the challenges of high-throughput data and model recognition for early detection of issues affecting rice crops through ML and DL models.