Identifying and mapping individual medicinal plant Lamiophlomis rotata at high elevations by using unmanned aerial vehicles and deep learning

Rapid identification of medicinal plants via visual feature-based deep learning

BACKGROUND

Traditional Chinese Medicinal Plants (CMPs) hold a significant and core status for the healthcare system and cultural heritage in China. It has been practiced and refined with a history of exceeding thousands of years for health-protective affection and clinical treatment in China. It plays an indispensable role in the traditional health landscape and modern medical care. It is important to accurately identify CMPs for avoiding the affected clinical safety and medication efficacy by the different processed conditions and cultivation environment confusion.

RESULTS

In this study, we utilize a self-developed device to obtain high-resolution data. Furthermore, we constructed a visual multi-varieties CMPs image dataset. Firstly, a random local data enhancement preprocessing method is proposed to enrich the feature representation for imbalanced data by random cropping and random shadowing. Then, a novel hybrid supervised pre-training network is proposed to expand the integration of global features within Masked Autoencoders (MAE) by incorporating a parallel classification branch. It can effectively enhance the feature capture capabilities by integrating global features and local details. Besides, the newly designed losses are proposed to strengthen the training efficiency and improve the learning capacity, based on reconstruction loss and classification loss.

CONCLUSIONS

Extensive experiments are performed on our dataset as well as the public dataset. Experimental results demonstrate that our method achieves the best performance among the state-of-the-art methods, highlighting the advantages of efficient implementation of plant technology and having good prospects for real-world applications.

The contemporary nexus of medicines security and bioprospecting: a future perspective for prioritizing the patient

Reacting to the challenges presented by the evolving nexus of environmental change, defossilization, and diversified natural product bioprospecting is vitally important for advancing global healthcare and placing patient benefit as the most important consideration. This overview emphasizes the importance of natural and synthetic medicines security and proposes areas for global research action to enhance the quality, safety, and effectiveness of sustainable natural medicines. Following a discussion of some contemporary factors influencing natural products, a rethinking of the paradigms in natural products research is presented in the interwoven contexts of the Fourth and Fifth Industrial Revolutions and based on the optimization of the valuable assets of Earth. Following COP28, bioprospecting is necessary to seek new classes of bioactive metabolites and enzymes for chemoenzymatic synthesis. Focus is placed on those performance and practice modifications which, in a sustainable manner, establish the patient, and the maintenance of their prophylactic and treatment needs, as the priority. Forty initiatives for natural products in healthcare are offered for the patient and the practitioner promoting global action to address issues of sustainability, environmental change, defossilization, quality control, product consistency, and neglected diseases to assure that quality natural medicinal agents will be accessible for future generations.