Published Technical Disclosure Archive

Intelligent AgTech: Sustainable Corn Breeding Innovation

Publication ID: 24-11856909_0002_PTD
Published: October 26, 2025
Category:New Applications & Use Cases

Legal Citation

pr1or.art Inc., “Intelligent AgTech: Sustainable Corn Breeding Innovation,” Published Technical Disclosure No. 24-11856909_0002_PTD, Published October 26, 2025, available at https://archive.pr1or.art/24-11856909_0002_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. 11,856,909.

Background and Problem Solved

The original patent, 'Plants and seeds of hybrid corn variety CH011205', primarily focused on corn breeding and seed production. However, the limitations of traditional agricultural practices, such as inefficient resource allocation and environmental degradation, necessitate innovative solutions. This invention addresses these challenges by applying the core technology of CH011205 to develop intelligent agricultural management systems that enhance crop yields, reduce waste, and promote sustainable farming practices.

Novelty and Inventive Step

The new claims introduce a paradigm shift in agricultural management by integrating the CH011205 hybrid corn variety with advanced sensing, machine learning, and autonomous navigation technologies. This fusion of biological and digital innovations creates a novel, non-obvious solution that significantly improves agricultural practices and sustainability.

Alternative Embodiments and Variations

Alternative embodiments of the invention could include the integration of additional sensors to monitor weather patterns, pest detection, or nutrient levels. Variations of the system could be tailored to specific crop types, farming practices, or regional conditions, ensuring broad applicability and adaptability.

Potential Commercial Applications and Market

The intelligent agricultural management systems have vast commercial potential in the agriculture technology (AgTech) industry, with applications in precision farming, sustainable agriculture, and environmental monitoring. The target market includes farmers, agricultural cooperatives, and companies focused on sustainable agricultural practices, with potential for expansion into related industries such as environmental consulting and agricultural equipment manufacturing.

CPC Classifications

SectionClassGroup
A A01 A01H6/4684
A A01 A01H5/10

Field of Art

Agricultural biotechnology and precision agriculture, specifically corn breeding and agricultural sensing technologies, requiring advanced degrees in plant genetics, agricultural engineering, or related fields with expertise in crop development and digital agricultural monitoring systems

Person of Ordinary Skill (PHOSITA) Profile

A skilled practitioner with knowledge of corn breeding techniques, sensor technologies, machine learning applications in agriculture, and understanding of integrating biological systems with digital monitoring platforms

Obviousness Rationale

A PHOSITA would recognize that combining agricultural sensing technologies with specific hybrid corn varieties represents a predictable extension of existing precision agriculture practices. The integration of soil health monitoring, machine learning, and autonomous navigation with a specific corn hybrid follows established technological convergence patterns in modern agricultural management. The disclosed variations represent logical combinations of known techniques applied to a specific genetic context.

Obvious Combinations & Variations

Source Patent Element
Hybrid corn variety CH011205 with specific genetic characteristics
PTD Variation
Integrating sensor networks and machine learning monitoring systems with the specific hybrid corn variety
Obviousness Reasoning
Combining crop-specific genetic information with digital monitoring is a known technique in precision agriculture, representing a predictable technological evolution
Source Patent Element
Corn breeding techniques focused on trait optimization
PTD Variation
Using machine learning algorithms to predict crop yields based on soil and genetic parameters
Obviousness Reasoning
Predictive modeling of crop performance is a standard approach in agricultural research, applying computational techniques to existing breeding knowledge
Source Patent Element
Agricultural field management principles
PTD Variation
Autonomous equipment navigation systems minimizing soil compaction based on real-time soil health data
Obviousness Reasoning
Developing equipment navigation strategies that protect soil integrity is a well-established goal in agricultural engineering with multiple known implementation approaches
Source Patent Element
Genetic variety development focused on performance optimization
PTD Variation
Smart irrigation systems dynamically adjusting water usage based on integrated sensor data
Obviousness Reasoning
Resource optimization through sensor-driven management is a predictable technological solution in agricultural system design
Source Patent Element
Corn variety characterization methodologies
PTD Variation
Generating topographical erosion risk maps using integrated sensor networks
Obviousness Reasoning
Spatial analysis of agricultural land characteristics using sensor data represents a standard approach in precision agriculture research
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11856909 and the disclosed technological variations, a person having ordinary skill in the art would find the claimed agricultural monitoring and management systems obvious and non-patentable, as they represent predictable combinations of known techniques in corn breeding and precision agriculture technologies.

Original Patent Information

Patent NumberUS 11,856,909
TitlePlants and seeds of hybrid corn variety CH011205
Assignee(s)MONSANTO TECHNOLOGY LLC