Published Technical Disclosure Archive

Advanced Soybean Breeding Tech: AI-Driven Innovation

Publication ID: 24-11856918_0005_PTD
Published: October 27, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Advanced Soybean Breeding Tech: AI-Driven Innovation,” Published Technical Disclosure No. 24-11856918_0005_PTD, Published October 27, 2025, available at https://archive.pr1or.art/24-11856918_0005_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,856,918.

Background and Problem Solved

The original patent, 'Soybean variety 01084034,' provides a novel soybean variety with improved traits. However, traditional breeding methods are time-consuming and limited in their ability to address the complex needs of modern agriculture. The present invention addresses these limitations by introducing a paradigm shift in soybean breeding and production, leveraging cutting-edge technologies to drive innovation and sustainability.

Novelty and Inventive Step

The invention's novelty lies in the combination of advanced technologies to create a holistic system for soybean breeding and production. The integration of machine learning, robotic phenotyping, and precision irrigation represents a significant departure from traditional breeding methods, providing a non-obvious solution to the limitations of existing approaches.

Alternative Embodiments and Variations

Alternative embodiments of the invention may include the use of different machine learning algorithms, varying levels of autonomy in farming equipment, or incorporation of additional data sources, such as satellite imaging or IoT sensors. These variations can be tailored to specific regional or environmental conditions, ensuring broad applicability of the invention.

Potential Commercial Applications and Market

The invention has significant commercial potential in the agricultural industry, particularly in the soybean sector. The system's ability to accelerate breeding and improve trait prediction can increase crop yields, reduce production costs, and enhance environmental sustainability. Target markets include major soybean producers, agricultural technology companies, and research institutions.

CPC Classifications

SectionClassGroup
A A01 A01H6/542
A A01 A01H5/10

Field of Art

Agricultural biotechnology, specifically soybean breeding and genetic engineering, involving advanced techniques in plant genetics, machine learning, and precision agriculture

Person of Ordinary Skill (PHOSITA) Profile

A professional with a PhD in plant breeding or agricultural biotechnology, expertise in genomics, machine learning algorithms, and advanced agricultural technologies, familiar with genetic modification techniques and precision farming systems

Obviousness Rationale

A PHOSITA would recognize that the PTD's integration of machine learning, robotic phenotyping, and precision irrigation represents a predictable extension of existing soybean breeding technologies. The disclosed variations systematically apply known computational and engineering techniques to enhance traditional plant breeding methodologies. The combination of genome editing, artificial intelligence, and autonomous equipment would be considered a logical progression in agricultural innovation.

Obvious Combinations & Variations

Source Patent Element
Soybean variety breeding methodology focused on trait improvement
PTD Variation
Machine learning model for predicting trait expression and robotic phenotyping platform
Obviousness Reasoning
Applying computational predictive techniques to plant breeding is a known approach, representing an obvious technological progression with predictable results in trait selection and development
Source Patent Element
Genetic characterization of soybean varieties
PTD Variation
Genome editing techniques combined with artificial intelligence for accelerated variety development
Obviousness Reasoning
Integrating AI with genetic modification is a foreseeable technological advancement, utilizing well-established techniques in a systematic, predictable manner
Source Patent Element
Focus on improving soybean plant characteristics
PTD Variation
Enhanced photosynthetic efficiency through genetic engineering and precision irrigation
Obviousness Reasoning
Optimizing plant performance through targeted genetic modifications and advanced irrigation represents a logical extension of existing breeding objectives
Source Patent Element
Soybean variety development process
PTD Variation
Vertically integrated production system with autonomous farms and centralized data analytics
Obviousness Reasoning
Implementing networked, data-driven agricultural systems is an obvious technological progression in precision agriculture
Source Patent Element
Soybean genetic research for improved characteristics
PTD Variation
Biodegradable soybean-based bioplastic composition with enhanced genetic properties
Obviousness Reasoning
Exploring alternative material applications through genetic engineering represents a predictable and obvious technological exploration
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856918 and the comprehensive technological disclosures herein, a person having ordinary skill in the art would find the claimed innovations obvious and lacking inventive step. The systematic integration of machine learning, genetic engineering, and precision agricultural technologies represents a predictable advancement in soybean breeding methodologies, thereby rendering potential patent claims obvious and non-patentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,856,918
TitleSoybean variety 01084034
Assignee(s)MONSANTO TECHNOLOGY LLC