Arbuscular Mycorrhizal (AM) symbiosis is integral to sustainable agriculture and enhances plant resilience to abiotic and biotic stressors. Through their symbiotic association with plant roots, AM improves nutrient and water uptake, activates antioxidant defenses, and facilitates hormonal regulation, contributing to improved plant health and productivity. Plants release strigolactones, which trigger AM spore germination and hyphal branching, a process regulated by genes, such as D27, CCD7, CCD8, and MAX1. AM recognition by plants is mediated by receptor-like kinases (RLKs) and LysM domains, leading to the formation of arbuscules that optimize nutrient exchange. Hormonal regulation plays a pivotal role in this symbiosis; cytokinins enhance AM colonization, auxins support arbuscule formation, and brassinosteroids regulate root growth. Other hormones, such as salicylic acid, gibberellins, ethylene, jasmonic acid, and abscisic acid, also influence AM colonization and stress responses, further bolstering plant resilience. In addition to plant health, AM enhances soil health by improving microbial diversity, soil structure, nutrient cycling, and carbon sequestration. This symbiosis supports soil pH regulation and pathogen suppression, offering a sustainable alternative to chemical fertilizers and improving soil fertility. To maximize AM ’s potential of AM in agriculture, future research should focus on refining inoculation strategies, enhancing compatibility with different crops, and assessing the long-term ecological and economic benefits. Optimizing AM applications is critical for improving agricultural resilience, food security, and sustainable farming practices.

The role of modified biochar in enhancing phosphorus (P) availability is gaining attention as an environmentally friendly approach to address soil P deficiency, a global agricultural challenge. Traditional phosphatic fertilizers, while essential for crop yield, are costly and environmentally detrimental owing to P fixation and leaching. Modified biochar presents a promising alternative with improved properties such as increased porosity, surface area, and cation exchange capacity. This review delves into the variability of biochar properties based on source and production methods and how these can be optimized for effective P adsorption. By adjusting properties such as pH levels and functional groups to align with the phosphate’s zero point of charge, we enhance biochar’s ability to adsorb and retain P, thereby increasing its bioavailability to plants. The integration of nanotechnology and advanced characterization techniques aids in understanding the structural nuances of biochar and its interactions with phosphorus. This approach offers multiple benefits: it enables farmers to use phosphorus more efficiently, reducing the need for traditional fertilizers and thereby minimizing environmental impacts, such as greenhouse gas emissions and P leaching. This review also identifies existing research gaps and future opportunities for further biochar modifications. These findings emphasize the significant potential of modified biochar in sustainable agriculture.

Forests suffer from heavy losses due to the occurrence of fires. A prediction model based on environmental condition, such as meteorological and vegetation indexes, is considered a promising tool to control forest fires. The construction of prediction models can be challenging due to (i) the requirement of selection of features most relevant to the prediction task, and (ii) heavily imbalanced data distribution where the number of large-scale forest fires is much less than that of small-scale ones. In this paper, we propose a forest fire prediction method that employs a sparse autoencoder-based deep neural network and a novel data balancing procedure. The method was tested on a forest fire dataset collected from the Montesinho Natural Park of Portugal. Compared to the best prediction results of other state-of-the-art methods, the proposed method could predict large-scale forest fires more accurately, and reduces the mean absolute error by 3–19.3 and root mean squared error by 0.95–19.3. The proposed method can better benefit the management of wildland fires in advance and the prevention of serious fire accidents. It is expected that the prediction performance could be further improved if additional information and more data are available.

Rosin is a characteristic natural renewable resource. In view of the unique hydrogenated phenanthrene ring skeleton structure of rosin, it can be designed and synthesized to modify silicone rubber for improving its mechanical properties, thermal stability, and other properties. In this paper, the research progress of silicone rubber modified by rosin and its derivatives is reviewed, including internal or surface modification of room temperature or high temperature vulcanized silicone rubber. The different chemical modifications and polymerization pathways to obtain bio-based silicone rubber (e.g. rosin-based silicone cross-linking agent, filler compound rosin-based silicone cross-linking agent, rosin-based polymer, and rosin quaternary ammonium salt bifunctional antibacterial coating) are discussed and its research prospect is reviewed. Overall, the present review article will provide a quantitative experimental basis for rosin to produce bio-renewable multifunctional silicone rubber to increase our level of understanding of the behavior of this important class of silicone rubber and other similar bio-based polymers.