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

3.7K
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...
3.7K
Chi-square Analysis02:46

Chi-square Analysis

42.5K
The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...
42.5K
Light Acquisition02:16

Light Acquisition

9.2K
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.
9.2K
Regression Analysis01:11

Regression Analysis

7.5K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
7.5K
Trihybrid Crosses02:27

Trihybrid Crosses

25.0K
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...
25.0K
Dihybrid Crosses01:18

Dihybrid Crosses

80.4K
Overview
80.4K

You might also read

Related Articles

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

Sort by
Same author

Impact of environmental covariates summarization on predictive ability in genomic selection.

The plant genome·2026
Same author

Using Structural Equation Models to Interpret Genome-Wide Association Studies for Morphological and Productive Traits in Soybean [<i>Glycine max</i> (L.) Merr.].

Plants (Basel, Switzerland)·2025
Same author

Genetic Diversity and Disease Resistance Genes Profiling in Cultivated <i>Coffea canephora</i> Genotypes via Molecular Markers.

Plants (Basel, Switzerland)·2025
Same author

Optimizing drought tolerance in cassava through genomic selection.

Frontiers in plant science·2024
Same author

Enhancing genomic prediction with Stacking Ensemble Learning in Arabica Coffee.

Frontiers in plant science·2024
Same author

Identification of SNP Markers and Candidate Genes Associated with Major Agronomic Traits in <i>Coffea arabica</i>.

Plants (Basel, Switzerland)·2024

Related Experiment Video

Updated: Dec 13, 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

1.4K

Adaptability and stability evaluation of maize hybrids using Bayesian segmented regression models.

Tâmara Rebecca A Oliveira1, Hélio Wilson L Carvalho2, Moysés Nascimento3

  • 1Núcleo de Graduação de Agronomia, Universidade Federal de Sergipe, Campus Sertão, Nossa Senhora da Glória, Sergipe, Brazil.

Plos One
|July 31, 2020
PubMed
Summary
This summary is machine-generated.

Genotype by environment interaction (G x E) complicates maize cultivar recommendations. A Bayesian segmented regression model with informative priors effectively evaluated maize hybrid adaptability and stability, identifying P4285HX as a top choice for farmers.

More Related Videos

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.6K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.7K

Related Experiment Videos

Last Updated: Dec 13, 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

1.4K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.6K
Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM

Published on: October 11, 2016

13.7K

Area of Science:

  • Agricultural Science
  • Genetics and Breeding
  • Biostatistics

Background:

  • Genotype by environment interaction (G x E) significantly impacts maize cultivar performance, posing challenges for accurate recommendations.
  • Understanding genotype phenotypic adaptability and stability requires methods that can capture nonlinear responses to environmental variations.
  • Bayesian approaches offer a framework for incorporating prior knowledge into complex statistical models for agricultural research.

Purpose of the Study:

  • To assess the adaptability and stability of maize hybrids using a Bayesian segmented regression model.
  • To evaluate the effectiveness of informative versus minimally informative prior distributions in cultivar selection.
  • To identify superior maize genotypes for cultivation in Northeastern Brazil.

Main Methods:

  • Conducted randomized complete-block design experiments with 25 maize hybrids across 22 environments in Northeastern Brazil.
  • Employed a Bayesian segmented regression model to analyze yield (kg/ha) data, accounting for genotype by environment interactions.
  • Compared model performance using informative and minimally informative prior distributions, assessing credibility intervals and Deviance Information Criterion (DIC).

Main Results:

  • The Bayesian segmented regression model fitted with informative prior distributions yielded lower credibility intervals and Deviance Information Criterion values, indicating a better model fit.
  • This model was deemed superior for evaluating the adaptability and stability of maize genotypes.
  • Maize genotype P4285HX demonstrated high yield performance and adaptability, particularly in unfavorable environments.

Conclusions:

  • Informative prior distributions enhance the performance of Bayesian segmented regression models for analyzing genotype by environment interactions in maize.
  • The Bayesian segmented regression model is a valuable tool for assessing maize hybrid adaptability and stability.
  • Genotype P4285HX is recommended for cultivation by farmers in Northeastern Brazil, especially those with limited capital, due to its robust performance across diverse environments.