Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Multiple Regression01:25

Multiple Regression

4.2K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.2K
Multiple Allele Traits01:49

Multiple Allele Traits

38.4K
The Concept of Multiple Allelism
38.4K
Light Acquisition02:16

Light Acquisition

9.7K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
9.7K
Trihybrid Crosses02:27

Trihybrid Crosses

26.3K
Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal...
26.3K
Polygenic Traits01:18

Polygenic Traits

69.5K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
69.5K
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

7.9K
Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
7.9K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Translating functional molecular knowledge into crop-breeding success.

Nature reviews. Genetics·2026
Same author

Correction: DeltaBreed: A BrAPI-centric breeding data information system.

PloS one·2026
Same author

GrainGenes: genetics, genomes, and pangenomes.

Genetics·2025
Same author

DeltaBreed: A BrAPI-centric breeding data information system.

PloS one·2025
Same author

Author Correction: A pangenome and pantranscriptome of hexaploid oat.

Nature·2025
Same author

Global genomic population structure of wild and cultivated oat reveals signatures of chromosome rearrangements.

Nature communications·2025

Related Experiment Video

Updated: Feb 26, 2026

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

10.9K

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic

Jin Sun, Jessica E Rutkoski, Jesse A Poland

    The Plant Genome
    |July 21, 2017
    PubMed
    Summary

    Incorporating secondary traits measured by high-throughput phenotyping improves wheat grain yield prediction by 70%. Different statistical models showed varied impacts, with the multitrait model excelling in severe drought conditions.

    More Related Videos

    A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
    15:30

    A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

    Published on: August 5, 2020

    12.7K
    High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot
    07:12

    High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

    Published on: January 9, 2026

    413

    Related Experiment Videos

    Last Updated: Feb 26, 2026

    Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
    07:10

    Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

    Published on: March 13, 2020

    10.9K
    A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
    15:30

    A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

    Published on: August 5, 2020

    12.7K
    High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot
    07:12

    High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot

    Published on: January 9, 2026

    413

    Area of Science:

    • Agricultural Science
    • Plant Breeding
    • Genetics

    Background:

    • High-throughput phenotyping (HTP) enables measurement of genetically correlated secondary traits over time.
    • Integrating these secondary traits into prediction models can enhance indirect selection for wheat grain yield.

    Purpose of the Study:

    • To evaluate statistical models (SR, MT, RR) for longitudinal secondary trait data.
    • To compare the impact of these models on predictive abilities for wheat grain yield.

    Main Methods:

    • Collected grain yield and secondary traits (canopy temperature, NDVI) across five environments for 557 wheat lines.
    • Applied a two-stage analysis using pedigree and genomic selection.
    • Fitted secondary traits using SR, MT, or RR models and used their BLUPs in multivariate prediction models.

    Main Results:

    • Predictive ability for grain yield improved by an average of 70% when including secondary traits.
    • Predictive abilities varied slightly among MT, RR, and SR models.
    • The MT model performed best in severe drought, while the RR model was slightly superior under drought conditions.

    Conclusions:

    • Multivariate models incorporating secondary traits significantly improve indirect selection for wheat grain yield.
    • Model choice (MT, RR, SR) can influence predictive performance, particularly under drought stress.
    • HTP-derived secondary traits are valuable for enhancing wheat breeding strategies.