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

3.2K
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...
3.2K

You might also read

Related Articles

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

Sort by
Same author

Adoption of Standard Reference SNP Identifiers in Agricultural Genomics for Interoperability and Data Reuse.

Scientific data·2026
Same author

Floral Anatomy, Sporogenesis, and Gametogenesis in the Rubber Dandelion (<i>Taraxacum kok-saghyz</i>): Implications for Breeding and Crop Development.

Plants (Basel, Switzerland)·2026
Same author

A single genomic region controls primocane fruiting in tetraploid blackberry.

Genetics·2026
Same author

A high-recovery, high-density targeted genotyping platform for cranberry.

The plant genome·2025
Same author

Accounting for population structure in genomic prediction of strawberry sweetness at a global scale.

Scientific reports·2025
Same author

A public mid-density genotyping platform for cultivated cranberry (Vaccinium macrocarpon Aiton).

The plant genome·2025

Related Experiment Video

Updated: Sep 29, 2025

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
05:29

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

Published on: June 9, 2021

4.0K

Analysis of a Multi-Environment Trial for Black Raspberry (Rubus occidentalis L.) Quality Traits.

Matthew R Willman1, Jill M Bushakra2, Nahla Bassil2

  • 1Department of Horticulture and Crop Science, The Ohio State University, Wooster, OH 44691, USA.

Genes
|March 25, 2022
PubMed
Summary

Developing improved black raspberry (BR) cultivars requires understanding fruit trait genetics. This study identified stable genetic control for fruit size traits and linked several size-related quantitative trait loci (QTL).

Keywords:
QTL-by-environment interactiongenotype-by-environment interactionhigh-throughput genotypingmixed model analysispomological traits

More Related Videos

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

10.5K
Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K

Related Experiment Videos

Last Updated: Sep 29, 2025

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry
05:29

Profiling Volatile Compounds in Blackcurrant Fruit using Headspace Solid-Phase Microextraction Coupled to Gas Chromatography-Mass Spectrometry

Published on: June 9, 2021

4.0K
The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
13:02

The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics

Published on: October 5, 2016

10.5K
Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
10:25

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements

Published on: June 28, 2016

10.7K

Area of Science:

  • Plant genetics
  • Horticultural science
  • Quantitative genetics

Background:

  • U.S. black raspberry (BR) production faces limitations due to narrowly adapted germplasm.
  • Understanding the genetic basis and environmental stability of pomological traits is crucial for developing superior BR cultivars.

Purpose of the Study:

  • To analyze genetic variation, genotype-by-environment interactions (GxE), quantitative trait loci (QTL), and QTL-by-environment interactions (QxE) for fruit quality traits in a BR mapping population.
  • To characterize the genetic components and stability of fruit size and biochemical traits across diverse U.S. growing conditions.

Main Methods:

  • Evaluation of a black raspberry mapping population across four distinct locations over three years.
  • Analysis of genotype-by-environment interactions (GxE) and QTL-by-environment interactions (QxE) for fruit size and biochemical traits.
  • Identification and characterization of quantitative trait loci (QTL) influencing fruit quality.

Main Results:

  • Fruit size traits exhibited relatively stable genetic control across environments, while biochemical traits showed less stability.
  • Eleven of fifteen identified QTL demonstrated significant QTL-by-environment interactions (QxE).
  • Overlapping QTL indicated linkage between fruit mass, drupelet count, and seed fraction.

Conclusions:

  • Genetic control of black raspberry fruit size is generally stable across different environments.
  • Findings provide insights for targeted breeding strategies to enhance black raspberry fruit quality and develop improved cultivars.
  • Understanding QTLxE is vital for breeding stable and high-performing black raspberry varieties.