Methods and systems for identifying progenies for use in plant breeding

Patent metadata

Field	Value
Publication number	US-11728010-B2
Application number	US-201816213596-A
Country	US
Kind code	B2
Filing date	Dec 7, 2018
Priority date	Dec 10, 2017
Publication date	Aug 15, 2023
Grant date	Aug 15, 2023

Abstract

Exemplary methods for identifying progenies for use in plant breeding are disclosed. One exemplary computer-implemented method includes accessing a data structure including data representative of a pool of progenies and determining a prediction score for at least a portion of the pool of progenies based on the data included in the data structure. The prediction score indicates a probability of selection of the progeny based on historical data. The method further includes selecting a group of progenies from the pool of progenies based on the prediction score, identifying a set of progenies, from the group of progenies, based on at least one of an expected performance of the group of progenies and at least one factor associated with the set of progenies, the pool of progenies and/or the group of progenies, and directing the set of progenies into a validation phase of a breeding pipeline.

First claim

What is claimed is:

1. A method for identifying progeny for use in a plant breeding pipeline, the method comprising:
accessing a data structure including data representative of a pool of progenies;
determining, by at least one computing device, a prediction score for at least a portion of the pool of progenies based on the data included in the data structure, the prediction score indicative of a probability of selection of the progeny based on historical selection data for the pool of progenies;
selecting, by the at least one computing device, a group of progenies from the pool of progenies based on the prediction score;
identifying, by the at least one computing device, a set of progenies from the group of progenies based on at least one of: an expected performance of the set of progenies and at least one factor associated with the set of progenies, the pool of progenies and/or the group of progenies;
wherein the at least one factor includes one or more of: risk, genetic diversity, trait(s) of the set of progenies, probability of success of base origins, probability of success of base pedigrees, and/or probability of success of heterotic groups; and

directing the set of progenies to a testing and cultivation phase of the plant breeding pipeline and/or to a validation phase of the breeding pipeline.

2. The method of claim 1 , further comprising generating, by the at least one computing device, a prediction model based on historical phenotypic data included in the data structure, the historical phenotypic data associated with plant material of a type consistent with a plant type of the pool of progenies; and
wherein determining the prediction score includes determining the prediction score based on the prediction model.

3. The method of claim 1 , wherein the data includes phenotypic data representative of the pool of progenies; and
wherein selecting the group of progenies includes selecting one or more progenies from the pool when the prediction score of the selected progeny satisfies one or more thresholds.

4. The method of claim 1 , wherein identifying the set of progenies is based on the following set identification algorithm:

x
opt

=

arg
⁢
max

x
∈

{

0
,
1

}

nN

⁢

(

λ
p

⁢

∑

i
=
1

nN

x
i

⁢

p
i

-

λ
r

⁢

∑

i
=
1

nN

x
i

⁢

r
i

-

λ

d
1

⁢

1
T

⁢
θ

-

λ

d
2

⁢

1
T

⁢
φ

-

λ

d
3

⁢

1
T

⁢
γ

)

;

wherein λ p Σ i=1 nN x i p i is associated with performance of the group of progenies; λ r Σ i=3 nN x i r i is associated with risk; λ d 1 1 T θ, λ d 2 1 T φ, and λ d 3 1 T γ are associated with deviations from one or more performance profiles; and p i , and r i are associated with performance and risk scores, respectively, for the group of progenies.

5. The method of claim 4 , wherein the set identification algorithm is subject to at least one of the following algorithms:

∑

i
=
1

nN

X
M

(
i
)

*

x
i

≥

α
M

·

Assignees

• Monsanto Technology Llc

Inventors

• Chavali Srinivas Phani Kumar
• Dasgupta Sambarta
• Jadaliha Mahdi
• Kovacs Anthony Paul
• Polavarapu Nalini
• Wang Zi

Classifications

• G16B40/00 Primary

  ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding · CPC title

• A01H1/02

  Methods or apparatus for hybridisation; Artificial pollination {; Fertility} · CPC title

• A01H1/04 Primary

  Processes of selection {involving genotypic or phenotypic markers; Methods of using phenotypic markers for selection} · CPC title

• G16B10/00

  ICT specially adapted for evolutionary bioinformatics, e.g. phylogenetic tree construction or analysis · CPC title

• G16B20/00

  ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations · CPC title