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

Trihybrid Crosses02:27

Trihybrid Crosses

23.6K
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...
23.6K
Chi-square Analysis02:46

Chi-square Analysis

38.7K
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...
38.7K
Dihybrid Crosses01:18

Dihybrid Crosses

75.6K
Overview
75.6K
Monohybrid Crosses01:20

Monohybrid Crosses

230.8K
Overview
230.8K

You might also read

Related Articles

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

Sort by
Same author

Comparative Effects of Non-Composted and Composted Sewage Sludge from Wastewater Treatment Plants on the Physiological and Antioxidative Responses of Maize.

Plants (Basel, Switzerland)·2025
Same author

Analysis of the dry matter and essential nutrient accumulation of maize (Zea mays L.) in the main phenophases.

Brazilian journal of biology = Revista brasleira de biologia·2025
Same author

Irrigation Management Strategies to Enhance Forage Yield, Feed Value, and Water-Use Efficiency of Sorghum Cultivars.

Plants (Basel, Switzerland)·2023
Same author

Selection of maize hybrids based on genotype × yield × trait (GYT) in different environments.

Brazilian journal of biology = Revista brasleira de biologia·2023
Same author

A potentially new thromboembolic event scoring system in polycythaemia vera patients: An audit of the Hungarian Philadelphia negative chronic myeloproliferative neoplasia register.

European journal of haematology·2023
Same author

Stability yield indices on different sweet corn hybrids based on AMMI analysis.

Brazilian journal of biology = Revista brasleira de biologia·2023

Related Experiment Video

Updated: Aug 28, 2025

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar
07:19

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar

Published on: August 6, 2018

20.5K

Quantitative and qualitative yield in sweet maize hybrids.

S M N Mousavi1, A Illés1, C Bojtor1

  • 1University of Debrecen, Faculty of Agricultural and Food Sciences and Environmental Management, Institute of Land Use, Engineering and Precision Farming Technology, Debrecen, Hungary.

Brazilian Journal of Biology = Revista Brasleira De Biologia
|September 14, 2022
PubMed
Summary

Sweet corn hybrids vary in yield and nutritional content. Sugar levels (fructose, glucose, sucrose) and minerals like potassium are key factors influencing yield indices and beneficial compounds like zeaxanthin.

More Related Videos

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.
05:55

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Published on: June 16, 2018

7.1K
Quantification of Fungal Colonization, Sporogenesis, and Production of Mycotoxins Using Kernel Bioassays
10:01

Quantification of Fungal Colonization, Sporogenesis, and Production of Mycotoxins Using Kernel Bioassays

Published on: April 23, 2012

18.2K

Related Experiment Videos

Last Updated: Aug 28, 2025

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar
07:19

Quantifying Plant Soluble Protein and Digestible Carbohydrate Content, Using Corn Zea mays As an Exemplar

Published on: August 6, 2018

20.5K
High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.
05:55

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Published on: June 16, 2018

7.1K
Quantification of Fungal Colonization, Sporogenesis, and Production of Mycotoxins Using Kernel Bioassays
10:01

Quantification of Fungal Colonization, Sporogenesis, and Production of Mycotoxins Using Kernel Bioassays

Published on: April 23, 2012

18.2K

Area of Science:

  • Agricultural Science
  • Plant Breeding
  • Nutritional Biochemistry

Background:

  • Sweet corn is a valuable vegetable crop, prized for its high sugar and low starch content.
  • Understanding genetic variation in sweet corn hybrids is crucial for optimizing yield and nutritional quality.
  • Key nutritional components like sugars, minerals, and carotenoids influence overall quality and health benefits.

Purpose of the Study:

  • To analyze yield variations among different sweet corn hybrids.
  • To investigate the relationship between nutritional factors (sugars, minerals, carotenoids) and yield indices.
  • To identify specific hybrids excelling in particular yield or nutritional traits.

Main Methods:

  • Cluster analysis and variance analysis were employed to assess yield index variations.
  • Factor analysis and biplot analysis were used to explore correlations between nutritional components and yield.
  • Performance of various hybrids (GB, DE, GS, SE, ME, NO, DB) was evaluated based on multiple parameters.

Main Results:

  • Hybrids exhibited significant variations in yield indices, with some showing similar performance (GB, DE, GS).
  • Sweet corn hybrids demonstrated stability in fructose, glucose, sucrose, and potassium content.
  • Positive correlations were observed between yield indices and various minerals (calcium, iron, zinc, magnesium, phosphorus) and carotenoids (α-Carotene, 9Z-β-Carotene, β-carotene).
  • Sugar content (fructose, glucose, sucrose) and potassium positively correlated with lutein, zeaxanthin, and β-Cryptoxanthin.
  • Specific hybrids showed maximum performance for certain traits: ME for the first yield factor, NO for the second yield factor, SE for zeaxanthin, and GS for zinc, phosphorus, and iron. DB hybrid showed stability in dry matter.

Conclusions:

  • Nutritional factors, particularly sugar content and potassium, are integral to sweet corn yield and the accumulation of health-beneficial compounds like zeaxanthin.
  • Specific sweet corn hybrids possess unique profiles for yield potential and nutritional value, offering opportunities for targeted breeding.
  • The study highlights the interconnectedness of various components, emphasizing a holistic approach to sweet corn quality assessment and improvement.