102
Views
1
CrossRef citations to date
0
Altmetric
Research articles

Logistic regression analysis of relationship between severity of fruit splitting and mineral element content of Prunus salicina Lindl.

, , &
Pages 2488-2495 | Received 19 Nov 2021, Accepted 02 Oct 2022, Published online: 07 Dec 2022
 

Abstract

To investigate the relationship between mineral elements and the severity of fruit splitting of Prunus salicina Lindl., 15 orchards with different degrees of fruit splitting were selected and divided into mild, moderate and severe splitting wards. The correlations of the severity of fruit splitting with soil physical and chemical properties and mineral element content in leaves were analyzed by logistic regression analysis. The results revealed that when the content of soil organic matters was high, the bulk density was low and the total porosity was high, or when the calcium (Ca) content in soil and leaves was high, the fruit splitting of Prunus salicina Lindl. was milder. It is worthy of noting that the higher the manganese (Mn) content in soil and leaves, the severer the fruit splitting of Prunus salicina Lindl. Whether its pathogenic mechanism works by inhibiting Ca absorption or triggering Mn toxicity requires further research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by Chongqing Technology Innovation and Application Development Special General Project (cstc2019jscx-msxmX0405).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 495.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.