In such a situation, it is necessary to build an information analytical system based on generative artificial intelligence, which, with the help of artificial neural networks in the process of deep learning, will be trained to recognize, identify, classify, name and describe specific plant species from scanned images. The initial databases should be digital libraries of photos, species names, their descriptions, characteristics, etc., developed on the basis of thousands of scientific publications about them available on the Internet. An important issue of a system built in this way is the inclusion of algorithms that will allow the identification of new, unknown, undescribed plant species or varieties. Identification of new plant species or varieties should be supported by providing the system with the names and characteristics of the closest evolutionarily related plant species.

I invite you to scientific cooperation in this problematic,

Best regards,

Dariusz Prokopowicz

The above text is entirely my own work written by me on the basis of my research.

In writing this text I did not use other sources or automatic text generation systems.

Copyright by Dariusz Prokopowicz

Just for a test I entered your question in Google Gemini Advanced.

here is the result which might help you frame further questions.

Sorry if this is worthless.

AI is revolutionizing plant identification and botany in various ways, enhancing the speed, accuracy, and accessibility of botanical knowledge:

1. Automated Plant Identification:

• Image Recognition: AI models trained on vast datasets of plant images can quickly and accurately identify plant species based on photographs taken in the field or from herbarium specimens. This technology is available through smartphone apps, making it accessible to both professionals and hobbyists.
• Feature Extraction: AI can analyze intricate details of plant morphology, such as leaf shape, venation patterns, and flower structure, to differentiate between closely related species.
• Taxonomic Classification: AI models can be trained to classify plants according to established taxonomic hierarchies, aiding in biodiversity studies and conservation efforts.

2. Biodiversity Assessment and Monitoring:

• Large-Scale Surveys: AI can rapidly process vast amounts of image data collected from camera traps or drones, enabling efficient monitoring of plant populations and the detection of invasive species.
• Species Distribution Modeling: AI can analyze environmental variables and predict the potential distribution of plant species under changing climate conditions, aiding in conservation planning.

3. Disease Diagnosis and Crop Management:

• Early Disease Detection: AI-powered image analysis can identify early signs of plant diseases, enabling timely intervention and preventing crop losses.
• Precision Agriculture: AI can optimize irrigation, fertilization, and pest control strategies by analyzing data from sensors and aerial imagery, leading to more sustainable and efficient farming practices.

4. Taxonomic Research and Curation:

• Digitization of Herbarium Specimens: AI can automate the process of extracting data from herbarium specimens, making valuable historical collections more accessible for research.
• Taxonomic Revision: AI can assist in the revision of plant classification by analyzing large datasets of morphological and genetic information.

5. Citizen Science and Education:

• Plant Identification Apps: AI-powered apps engage the public in botanical exploration, encouraging citizen scientists to contribute to data collection and species monitoring.
• Interactive Learning Tools: AI can provide interactive learning experiences, such as virtual plant identification guides and personalized recommendations for botanical exploration.

Challenges and Considerations:

• Data Bias: AI models are only as good as the data they are trained on. Biases in data collection can lead to inaccurate identification or misrepresentation of plant diversity.
• Ethical Concerns: The use of AI in botany raises questions about data ownership, intellectual property rights, and the potential for job displacement in taxonomic research.

Please don't go this way. Wouldn't you prefer to become a skilled botanist able to identify say one thousand of species basing on your knowledge and experience in field botany, taxonomical sources and your own herbarium? It's possible, and you will be esteemed as an expert. AI is designed to satisfy a lazy student and teaches how to bear no responsibility for what you retrieve from it. Would you like to go to an AI doctor with your disease, too? Would you also agree to have your publication reviewed by an AI professor of botany? My students are so "experienced" that they use AI tools for plant id and they even forget to switch the tool to the proper continent. Indeed.