Autonomous Plant Yield Optimization AI Technology

The original patent disclosed methods for manipulating yield of plants and identifying yield genes, but these methods are limited by their reliance on manual optimization and lack of precision. The present invention addresses these limitations by introducing autonomous plant yield optimization and genome-wide yield gene identification, enabling farmers to achieve unprecedented yields while reducing environmental impact.

The new claims introduce the use of machine learning, CRISPR-Cas9 genome editing, and precision agriculture to optimize plant yield, which is a significant departure from the original patent's manual optimization methods. The autonomous plant yield optimization and genome-wide yield gene identification capabilities are novel and non-obvious, and provide a paradigm shift in agricultural practices.

Alternative embodiments of the invention could include the use of different machine learning algorithms, genome editing tools, or precision agriculture infrastructure. The invention could also be adapted for use with other crop types or in different environmental conditions.

The invention has significant commercial potential in the agricultural industry, particularly in the areas of precision agriculture, crop breeding, and farm management. The target market includes farmers, agricultural companies, and research institutions, with potential applications in soybean production, as well as other crops.