Published Technical Disclosure Archive

Advanced Seed Yield Optimization System for Agriculture

Publication ID: 24-11856903_0003_PTD
Published: October 26, 2025
Category:Synergistic Combinations

Legal Citation

pr1or.art Inc., “Advanced Seed Yield Optimization System for Agriculture,” Published Technical Disclosure No. 24-11856903_0003_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856903_0003_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. 11,856,903.

Background and Problem Solved

The original patent disclosed methods for manipulating yield of plants and identifying yield genes, but these methods were limited to specific growing conditions and lacked integration with modern technologies. This new invention addresses these limitations by combining the original methods with advanced technologies to create a more powerful and effective system for optimizing seed yield.

Novelty and Inventive Step

The new claims introduce a synergistic combination of advanced technologies, including AI, IoT, blockchain, and nanomaterials, which is not obvious from the original patent. The integration of these technologies with the original methods for manipulating yield of plants and identifying yield genes provides a novel and non-obvious solution for optimizing seed yield in soybean plants.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include the use of different AI algorithms, IoT sensor configurations, or blockchain platforms. Additionally, the system could be adapted for use with other types of crops or in different environmental conditions.

Potential Commercial Applications and Market

The Synergistic Seed Yield Optimization System has significant commercial potential in the agricultural industry, particularly in the soybean market. The system could be marketed as a comprehensive solution for farmers, agricultural companies, and research institutions, offering a more efficient, data-driven, and sustainable approach to optimizing seed yield.

CPC Classifications

SectionClassGroup
A A01 A01H3/02
A A01 A01H5/10
A A01 A01H6/542

Field of Art

Agricultural biotechnology and plant breeding, specifically focused on soybean yield optimization, involving genetic manipulation, environmental condition control, and advanced agricultural technologies

Person of Ordinary Skill (PHOSITA) Profile

A professional with advanced degrees in plant science, biotechnology, or agricultural engineering, possessing expertise in crop genetics, precision agriculture techniques, data analysis, and emerging agricultural technologies

Obviousness Rationale

A PHOSITA would recognize that the PTD's integration of AI, IoT, and machine learning represents predictable technological extensions of the source patent's core methodology for manipulating soybean plant yield. The disclosed variations apply standard technological approaches to enhance the existing yield optimization framework by introducing data-driven precision agriculture techniques. These technological integrations represent logical progressions in agricultural research that would be obvious to a skilled practitioner seeking to improve plant yield management.

Obvious Combinations & Variations

Source Patent Element
Method for manipulating soybean plant yield under controlled light and temperature conditions
PTD Variation
Machine learning module predicting optimal growing conditions based on historical climate data
Obviousness Reasoning
Applying machine learning to optimize agricultural conditions is a known technique in precision agriculture, representing a predictable application of data analysis to existing yield manipulation methods
Source Patent Element
Identifying yield genes in soybean plants
PTD Variation
Correlating genomic data with IoT sensor data to identify optimal growing conditions
Obviousness Reasoning
Integrating genomic information with real-time sensor data is a standard approach in biotechnology for enhancing understanding of plant performance, representing an obvious extension of existing gene identification techniques
Source Patent Element
Growing soybean plants under controlled environmental conditions
PTD Variation
Using nanomaterials to enhance seed germination and nutrient delivery
Obviousness Reasoning
Applying nanomaterials to improve seed performance is a well-known technique in agricultural biotechnology, representing a predictable method of enhancing existing plant growth strategies
Source Patent Element
Methods for manipulating plant yield through environmental control
PTD Variation
AI-powered image analysis using drone and satellite imaging to predict plant growth conditions
Obviousness Reasoning
Remote sensing and AI-based image analysis are established techniques in agricultural monitoring, representing an obvious technological progression for yield optimization
Source Patent Element
Tracking and verifying seed yield parameters
PTD Variation
Blockchain-based platform for recording and verifying seed yield data
Obviousness Reasoning
Using blockchain for data verification is a standard approach in technological record-keeping, representing a predictable application of distributed ledger technology to agricultural data management
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856903 and the disclosed technological variations, a person having ordinary skill in the art would find the claimed innovations obvious and lacking inventive step. The integration of AI, IoT, blockchain, and nanomaterial technologies represents predictable extensions of existing plant yield manipulation methodologies, thereby rendering potential patent claims obvious and unpatentable under 35 U.S.C. Section 103.

Original Patent Information

Patent NumberUS 11,856,903
TitleMethods for manipulating yield of plants and identifying yield genes
Assignee(s)MONSANTO TECHNOLOGY LLC