The development of plant‐specific biosensors holds the potential to uncover new insights into plant physiology and advance precision agriculture. Current sensing platforms mainly focus on broad plant phenotypes (e.g., elongation and hydration) and local environmental monitoring (e.g., temperature and moisture). Here, an ion‐selective organic electrochemical transistor (IS‐OECT) is introduced that enables real‐time monitoring of variations in potassium ion concentration within the xylem of pine trees. This work demonstrates that the high sensitivity of the IS‐OECT enables the detection of subtle variations in potassium ion concentrations in the xylem sap of living trees, and the high stability of the sensor allows for in vivo measurements over five weeks. Furthermore, the implantable sensors are fabricated using processes that are compatible with low‐cost manufacturing (i.e., lithography‐free). This sensing technology, therefore, has great potential to be a game‐changer in precision forestry and could extend to precision agriculture and horticulture practices.

Rosemary (Salvia rosmarinus Spenn. syn. Rosmarinus officinalis L.) is a Mediterranean aromatic species used both as an official herb and as a spice. Different cultivars may exhibit diverse phytochemical compositions, making a comprehensive chemical characterization pivotal for a targeted selection of valuable cultivars. This study aimed to characterize and compare the phenolic and terpene composition and content of leaf extracts of six Mediterranean rosemary cultivars: ‘Alba’, ‘Arp’ ‘Ginger’, ‘Gorizia’, ‘Tuscan Blue’, and ‘Roseus’. HPLC-DAD analysis revealed a similar phenolic composition in all the cultivars, but quantitative differences were observed. The main compounds were carnosic acid derivatives, flavonoids (e.g., luteolin, apigenin, and quercetin glucosides), rosmarinic acid, caffeic acid, and other hydroxycinnamic acid derivatives. The highest phenolic content was found in ‘Alba’, with a predominance of carnosic acid derivatives, whereas the lowest was found in ‘Ginger’ and ‘Gorizia’. The GC-MS analysis evidenced quantitative differences among the cultivars. Particularly, ‘Alba’ contained the highest terpene content, whereas ‘Arp’ and ‘Gorizia’ showed the lowest values. Regarding the antioxidant activity, ‘Alba’ exhibited the highest values as regards phenols, while for terpenes, the highest ones were obtained for ‘Ginger’ and ‘Tuscan Blue’. Significant Pearson correlations were obtained between the total phenol/terpene content and the antioxidant activity. The chemical characterization of these cultivars provides relevant information to produce the rosemary phytocomplexes, finding multiple industrial applications.

Myrtle rust is a very damaging disease, caused by the fungus Austropuccinia psidii, which has recently arrived in New Zealand and threatens the iconic tree species pōhutukawa (Metrosideros excelsa). Canopy-level hyperspectral and thermal images were taken repeatedly within a controlled environment, from 49 inoculated (MR treatment) and 26 uninoculated (control treatment) pōhutukawa plants. Measurements were taken prior to inoculation and six times post-inoculation over a 14-day period. Using indices extracted from these data, the objectives were to (i) identify the key thermal and narrow-band hyperspectral indices (NBHIs) associated with the pre-visual and early expression of myrtle rust and (ii) develop a classification model to detect the disease. The number of symptomatic plants increased rapidly from three plants at 3 days after inoculation (DAI) to all 49 MR plants at 8 DAI. NBHIs were most effective for pre-visual and early disease detection from 3 to 6 DAI, while thermal indices were more effective for detection of disease following symptom expression from 7 to 14 DAI. Using results compiled from an independent test dataset, model performance using the best thermal indices and NBHIs was excellent from 3 DAI to 6 DAI (F1 score 0.81–0.85; accuracy 73–80%) and outstanding from 7 to 14 DAI (F1 score 0.92–0.93; accuracy 89–91%).

Climate change is a driver of biodiversity loss, often favouring invasive species such as in the case of Pittosporum undulatum in Eucalyptus forests of south-eastern Australia. We tested whether the invasiveness of P. undulatum is due to the release of secondary metabolites with allelopathic action inhibiting other species germination or to the content of antioxidant secondary metabolites. We compared the germination of P. undulatum and Eucalyptus ovata seeds on different substrates watered with different leachates. Polyphenolic compounds, saponins and tannins of Eucalyptus spp. and P. undulatum leaf extracts were quantified. Biogenic Volatile Organic Compounds were collected in the field and analyzed to compare the emissions in eucalypt forests with and without P. undulatum. Eucalyptus germination rates were not affected by different leachates and no allelopathic compounds were identified in P. undulatum leachate. Flavonoids and tannins characterized Eucalyptus leachates, while P. undulatum leachates showed high hydroxycinnamic acids content. The forests invaded by P. undulatum were characterized by high levels of monoterpenes, whereas the forest lacking P. undulatum were dominated by sesquiterpenes. Our results suggest that the invasiveness of P. undulatum may be due to the high content in secondary metabolites that play a protective role against abiotic stresses rather than the release of allelopathic compounds.

Biogenic Volatile Organic Compounds (BVOCs) include many chemical compounds emitted by plants into the atmosphere. These compounds have a great effect on biosphere–atmosphere interactions and may affect the concentration of atmospheric pollutants, with further consequences on human health and forest ecosystems. Novel methods to measure and determine BVOCs in the atmosphere are of compelling importance considering the ongoing climate changes. In this study, we developed a fast and easy-to-handle analytical methodology to sample these compounds in field experiments using solid-phase microextraction (SPME) fibers at the atmospheric level. An improvement of BVOCs adsorption from SPME fibers was obtained by coupling the fibers with fans to create a dynamic sampling system. This innovative technique was tested sampling Q. ilex BVOCs in field conditions in comparison with the conventional static SPME sampling technique. The results showed a great potential of this dynamic sampling system to collect BVOCs at the atmosphere level, improving the efficiency and sensitivity of SPME fibers. Indeed, our novel device was able to reduce the sampling time, increase the amount of BVOCs collected through the fibers and add information regarding the emissions of these compounds at the environmental level.