Soybean Variety 01081409 Genomic Selection Breeding

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Solution Overview

Problem

Current soybean breeding methods face challenges in developing stable, high-yielding varieties with improved traits such as disease resistance, drought tolerance, and herbicide resistance, which are difficult to predict and require extensive research efforts due to the unpredictability of genetic combinations in conventional breeding procedures.

Innovation Solution

The development of the soybean variety 01081409, which includes specific genetic modifications and locus conversions using techniques like backcrossing and genetic transformation to introduce traits like herbicide resistance, disease resistance, and improved agronomic characteristics, along with methods for tissue culture and regeneration to produce stable and uniform soybean plants.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional breeding methods are used to develop new soybean varieties, then genetic diversity and adaptability are maintained, but the process is unpredictable and time-consuming

Engineering Contradiction:
Improvepredictability of breeding outcomesVSAvoidbreeding program duration
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent applies preliminary action by using genomic selection to predict breeding outcomes before actual crossing occurs. Genomic estimated breeding values (GEBV) are calculated for parental lines based on genomic data, allowing breeders to select and cross lines with predicted superior performance. This predictive approach enables more reliable breeding decisions to be made earlier in the process, reducing the time needed for traditional phenotypic evaluation and selection cycles.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The patent replaces the mechanical system of traditional phenotypic selection and field testing with a genomic-based predictive system. Instead of relying on physical observation and manual selection over multiple generations, the invention uses genomic data analysis, statistical models, and computational algorithms to predict and select superior breeding combinations, thereby increasing reliability and reducing breeding program duration.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If extensive breeding programs are implemented to achieve superior traits, then variety performance improves, but research effort and cost increase

Engineering Contradiction:
Improvevariety performance stabilityVSAvoidbreeding program complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent applies segmentation by dividing the complex breeding program into distinct modular components: (1) genomic data collection and processing, (2) genomic selection and prediction, (3) targeted crossing design, and (4) validation testing. This segmentation allows each component to be optimized independently and reduces overall program complexity by focusing resources on high-impact activities rather than conducting comprehensive evaluations of all possible breeding combinations.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent uses copying in the form of genomic data replication and verification. Genomic information is collected from multiple individuals and replicated across different populations to create robust predictive models. This copying approach allows the breeding program to rely on replicated genomic data rather than requiring extensive unique field testing for each potential parent line, thereby reducing program complexity while maintaining performance reliability.

Inventive Principle:
Principle #26Copying

3Adaptability or versatility

If multiple traits are combined in a single variety, then agronomic quality improves, but genetic combination unpredictability increases

Engineering Contradiction:
Improvemulti-trait performanceVSAvoidtrait combination predictability
Core Design Contradiction:
Adaptability or versatilityVSReliability

Solution Approach 1:

The patent applies universality through the use of a unified genomic selection framework that simultaneously predicts multiple traits. The genomic prediction models are designed to evaluate diverse traits including yield, disease resistance, drought tolerance, and quality characteristics using the same genomic data and analytical platform. This multi-functional approach allows breeders to combine multiple traits in a single variety while maintaining predictability, as the genomic system can assess the additive and interactive effects of multiple genes and loci across different traits.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentUS11266108B2Soybean variety 01081409
Publication Date: 2022.03.08 MONSANTO TECHNOLOGY LLC

AI summary

The invention relates to the soybean variety designated 01081409. Provided by the invention are the seeds, plants and derivatives of the soybean variety 01081409. Also provided by the invention are tissue cultures of the soybean variety 01081409 and the plants regenerated therefrom. Still further provided by the invention are methods for producing soybean plants by crossing the soybean variety 01081409 with itself or another soybean variety and plants produced by such methods.