Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)

Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)

In a previous study, we found a positive and significant correlation between leaf number per plant and bulb yield in Leucojum aestivum. In the present study, to develop a leaf area prediction model was aimed for this plant. To achieve this objective, a total of 200 leaves were selected randomly from...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of botany : IJB 2005-01, Vol.1 (1), p.12-14
Hauptverfasser: Cirak, C, Odabas, MS, Ayan, A K
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 14
container_issue 1
container_start_page 12
container_title International journal of botany : IJB
container_volume 1
creator Cirak, C
Odabas, MS
Ayan, A K
description In a previous study, we found a positive and significant correlation between leaf number per plant and bulb yield in Leucojum aestivum. In the present study, to develop a leaf area prediction model was aimed for this plant. To achieve this objective, a total of 200 leaves were selected randomly from Leucojum aestivum plants cultivated in experimental area of Black Sea Agricultural Research Institute, Turkey. Leaf width, length and leaf area were measured. The actual leaf area of the plant was measured by PLACOM Digital Planimeter and multiple regression analysis with Excel 7.0 was performed. The leaf area model developed was LA = (-5.902) + (-4.12xL) + (0.19xL super(2)) + [-4.8*(LxW super(2))] + [0.201x (L super(2)xW super(2))] + [-0.42x (L super(2)xW)] + [10.65 x (LxW) where LA is leaf area, L is leaf length, W is leaf width. R super(2) value (0.97) and standard error were found to be significant at the p
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_miscellaneous_19402069</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>19402069</sourcerecordid><originalsourceid>FETCH-proquest_miscellaneous_194020693</originalsourceid><addsrcrecordid>eNqNyrsKwjAUgOEMCtbLO5xJdKgktWgzilgcKgi6l9CeQGoumjT6-nbwAZy-f_hHJGEFYynfUzoh0xA6SvMi51lCygqFhINHAVePrWp65SxcXIsapPNwi8bggHUfqcUDYVVhbFwXDQgMvXoPUW3WczKWQgdc_JyRZXm6H8_p07tXHMbaqNCg1sKii6FmPKcZ3fHt3-MXUHE8ww</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>19402069</pqid></control><display><type>article</type><title>Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)</title><source>Science Alert</source><creator>Cirak, C ; Odabas, MS ; Ayan, A K</creator><creatorcontrib>Cirak, C ; Odabas, MS ; Ayan, A K</creatorcontrib><description>In a previous study, we found a positive and significant correlation between leaf number per plant and bulb yield in Leucojum aestivum. In the present study, to develop a leaf area prediction model was aimed for this plant. To achieve this objective, a total of 200 leaves were selected randomly from Leucojum aestivum plants cultivated in experimental area of Black Sea Agricultural Research Institute, Turkey. Leaf width, length and leaf area were measured. The actual leaf area of the plant was measured by PLACOM Digital Planimeter and multiple regression analysis with Excel 7.0 was performed. The leaf area model developed was LA = (-5.902) + (-4.12xL) + (0.19xL super(2)) + [-4.8*(LxW super(2))] + [0.201x (L super(2)xW super(2))] + [-0.42x (L super(2)xW)] + [10.65 x (LxW) where LA is leaf area, L is leaf length, W is leaf width. R super(2) value (0.97) and standard error were found to be significant at the p&lt;0.001 level.</description><identifier>ISSN: 1811-9700</identifier><language>eng</language><ispartof>International journal of botany : IJB, 2005-01, Vol.1 (1), p.12-14</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784</link.rule.ids></links><search><creatorcontrib>Cirak, C</creatorcontrib><creatorcontrib>Odabas, MS</creatorcontrib><creatorcontrib>Ayan, A K</creatorcontrib><title>Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)</title><title>International journal of botany : IJB</title><description>In a previous study, we found a positive and significant correlation between leaf number per plant and bulb yield in Leucojum aestivum. In the present study, to develop a leaf area prediction model was aimed for this plant. To achieve this objective, a total of 200 leaves were selected randomly from Leucojum aestivum plants cultivated in experimental area of Black Sea Agricultural Research Institute, Turkey. Leaf width, length and leaf area were measured. The actual leaf area of the plant was measured by PLACOM Digital Planimeter and multiple regression analysis with Excel 7.0 was performed. The leaf area model developed was LA = (-5.902) + (-4.12xL) + (0.19xL super(2)) + [-4.8*(LxW super(2))] + [0.201x (L super(2)xW super(2))] + [-0.42x (L super(2)xW)] + [10.65 x (LxW) where LA is leaf area, L is leaf length, W is leaf width. R super(2) value (0.97) and standard error were found to be significant at the p&lt;0.001 level.</description><issn>1811-9700</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNqNyrsKwjAUgOEMCtbLO5xJdKgktWgzilgcKgi6l9CeQGoumjT6-nbwAZy-f_hHJGEFYynfUzoh0xA6SvMi51lCygqFhINHAVePrWp65SxcXIsapPNwi8bggHUfqcUDYVVhbFwXDQgMvXoPUW3WczKWQgdc_JyRZXm6H8_p07tXHMbaqNCg1sKii6FmPKcZ3fHt3-MXUHE8ww</recordid><startdate>20050101</startdate><enddate>20050101</enddate><creator>Cirak, C</creator><creator>Odabas, MS</creator><creator>Ayan, A K</creator><scope>7SN</scope><scope>C1K</scope></search><sort><creationdate>20050101</creationdate><title>Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)</title><author>Cirak, C ; Odabas, MS ; Ayan, A K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_miscellaneous_194020693</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Cirak, C</creatorcontrib><creatorcontrib>Odabas, MS</creatorcontrib><creatorcontrib>Ayan, A K</creatorcontrib><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><jtitle>International journal of botany : IJB</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cirak, C</au><au>Odabas, MS</au><au>Ayan, A K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)</atitle><jtitle>International journal of botany : IJB</jtitle><date>2005-01-01</date><risdate>2005</risdate><volume>1</volume><issue>1</issue><spage>12</spage><epage>14</epage><pages>12-14</pages><issn>1811-9700</issn><abstract>In a previous study, we found a positive and significant correlation between leaf number per plant and bulb yield in Leucojum aestivum. In the present study, to develop a leaf area prediction model was aimed for this plant. To achieve this objective, a total of 200 leaves were selected randomly from Leucojum aestivum plants cultivated in experimental area of Black Sea Agricultural Research Institute, Turkey. Leaf width, length and leaf area were measured. The actual leaf area of the plant was measured by PLACOM Digital Planimeter and multiple regression analysis with Excel 7.0 was performed. The leaf area model developed was LA = (-5.902) + (-4.12xL) + (0.19xL super(2)) + [-4.8*(LxW super(2))] + [0.201x (L super(2)xW super(2))] + [-0.42x (L super(2)xW)] + [10.65 x (LxW) where LA is leaf area, L is leaf length, W is leaf width. R super(2) value (0.97) and standard error were found to be significant at the p&lt;0.001 level.</abstract></addata></record>
fulltext fulltext
identifier ISSN: 1811-9700
ispartof International journal of botany : IJB, 2005-01, Vol.1 (1), p.12-14
issn 1811-9700
language eng
recordid cdi_proquest_miscellaneous_19402069
source Science Alert
title Leaf Area Prediction Model for Summer Snowflake (Leucojum aestivum L.)
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T17%3A23%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Leaf%20Area%20Prediction%20Model%20for%20Summer%20Snowflake%20(Leucojum%20aestivum%20L.)&rft.jtitle=International%20journal%20of%20botany%20:%20IJB&rft.au=Cirak,%20C&rft.date=2005-01-01&rft.volume=1&rft.issue=1&rft.spage=12&rft.epage=14&rft.pages=12-14&rft.issn=1811-9700&rft_id=info:doi/&rft_dat=%3Cproquest%3E19402069%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=19402069&rft_id=info:pmid/&rfr_iscdi=true