Skip to main content
padlock icon - secure page this page is secure

Prediction of germination of commercially available seed lots by regression models developed by artificial and natural ageing and electrical conductivity in leek

Buy Article:

$35.00 + tax (Refund Policy)

This work aimed to determine whether measurements of electrical conductivity of solute leakage of leek seeds could be used to predict germination in commercially available seed lots. Prediction of germination was conducted through logit regression equations developed between EC and germination for either artificially or naturally aged seed samples. For artificial ageing, 16 serial samples that differed in germination were produced by storing seeds at 45°C with 20% seed moisture content for 72 hours. Twenty-two naturally aged seed lots obtained from different sources were tested. Logit regression models (generalised linear models) were developed between EC and total (R 2 = 0.958, R 2 = 0.958, P < 0.001) and normal (R 2 = 0.946, R 2 = 0.823, P < 0.001) germination percentages for artificially and naturally aged seeds, respectively. The actual total and normal germination percentages of 13 seed lots were predicted by logit regression equations of artificial and natural ageing. The predicted germinations from the developed logit regression equations with EC were highly related (linear regression analysis) to actual total (R 2 = 0.716, P < 0.001 artificial; R 2 = 0.648, P < 0.001 natural) and normal germination (R 2 = 0.843, P < 0.001 artificial; R 2 = 0.821, P < 0.001 natural). The relationship between EC and normal and total germination of thiram treated and untreated seed lots were tested and R 2 values ranged between 0.576 and 0.959 (P < 0.05).
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Publication date: July 1, 2017

This article was made available online on May 29, 2017 as a Fast Track article with title: "Prediction of germination of commercially available seed lots by regression models developed by artificial and natural ageing and electrical conductivity in leek".

More about this publication?
  • Seed Science and Technology (SST) is one of the leading international journals featuring original papers and review articles on seed quality and physiology as related to seed production, harvest, processing, sampling, storage, distribution and testing. This widely recognised journal is designed to meet the needs of researchers, advisers and all those involved in the improvement and technical control of seed quality.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Membership Information
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more