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

Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

6.5K
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...
6.5K
Gene-Environment Interactions01:20

Gene-Environment Interactions

250
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
250
Epistasis Analysis01:09

Epistasis Analysis

4.9K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
4.9K
Monohybrid Crosses01:20

Monohybrid Crosses

229.1K
Overview
229.1K
Factorial Design02:01

Factorial Design

13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Trihybrid Crosses02:27

Trihybrid Crosses

23.1K
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...
23.1K

You might also read

Related Articles

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

Sort by
Same author

From root to result: Portable NIRS-based non-destructive prediction of cassava quality traits.

PloS one·2025
Same author

Near-Infrared Spectroscopy Prediction of Dry Matter and Starch Content in Cassava Using Optimized Calibration Models.

Journal of food science·2025
Same author

Optimizing the single-step model for predicting fumonisins resistance in maize hybrids accounting for the genotype-by-environment interaction.

Frontiers in genetics·2025
Same author

Genomic selection of maize test-cross hybrids leveraged by marker sampling.

The plant genome·2025
Same author

Historic manioc genomes illuminate maintenance of diversity under long-lived clonal cultivation.

Science (New York, N.Y.)·2025
Same author

High-Throughput Phenotyping for Agronomic Traits in Cassava Using Aerial Imaging.

Plants (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jun 5, 2025

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

712

Genotype x environment interaction in cassava multi-environment trials via analytic factor.

Juraci Souza Sampaio Filho1, Isadora Cristina Martins Oliveira2, Maria Marta Pastina2

  • 1Federal University of Recôncavo da Bahia, Centro de Ciências Agrárias, Ambientais e Biológicas, Cruz das Almas, Bahia, Brazil.

Plos One
|December 9, 2024
PubMed
Summary

Understanding genotype × environment interactions (G×E) is key for cassava breeding. Factor analytic multiplicative mixed models (FAMM) effectively identified stable, high-performing cassava genotypes across diverse environments.

More Related Videos

Environmentally Induced Heritable Changes in Flax
08:10

Environmentally Induced Heritable Changes in Flax

Published on: January 26, 2011

10.2K
JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning
09:23

JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning

Published on: March 21, 2025

722

Related Experiment Videos

Last Updated: Jun 5, 2025

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

712
Environmentally Induced Heritable Changes in Flax
08:10

Environmentally Induced Heritable Changes in Flax

Published on: January 26, 2011

10.2K
JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning
09:23

JenaTron - An Experimental Approach to Study the Effects of Plant History and Soil History on Grassland Ecosystem Functioning

Published on: March 21, 2025

722

Area of Science:

  • Agricultural Science
  • Plant Breeding
  • Genetics

Background:

  • Genotype × environment interaction (G×E) variability complicates selecting accurate, high-performing crop varieties.
  • Cassava (Manihot esculenta) breeding programs require methods to navigate complex G×E effects for traits like yield and quality.

Purpose of the Study:

  • To analyze G×E interactions in cassava using factor analytic multiplicative mixed models (FAMM).
  • To identify stable, high-performing cassava genotypes.
  • To predict genotype performance in new environments.

Main Methods:

  • Multi-environment trials (METs) involving 22 cassava genotypes across 55 Brazilian environments.
  • Evaluation of fresh root yield (FRY), dry root yield (DRY), shoot yield (ShY), and dry matter content (DMC).
  • Application of FAMM to estimate genetic values, environmental loads, and genetic correlations.

Main Results:

  • FAMM revealed significant genetic variance for all traits, with broad-sense heritability above 0.70 for FRY.
  • Analytic factor FA4 explained over 88% of genetic variation, despite data imbalance and high G×E.
  • Identified genotype-specific adaptations and correlations between environmental factors and model loadings.

Conclusions:

  • FAMM offers a robust framework for G×E analysis in cassava breeding.
  • The study provides practical insights for selecting stable and high-yielding cassava genotypes.
  • Understanding G×E interactions is crucial for optimizing cassava performance in diverse agricultural settings.