Development of Tree Vigor Prediction Method at an Early Stage Based on Stem Hydraulic Conductance of Seedlings in Citrus Rootstocks
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- Iwasaki Mitsunori
- Kuchinotsu Citrus Research Station, National Institute of Fruit Tree Science
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- Fukamachi Hiroshi
- Kuchinotsu Citrus Research Station, National Institute of Fruit Tree Science
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- Satoh Keiko
- Okitsu Citrus Research Station, National Institute of Fruit Tree Science
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- Nesumi Hirohisa
- National Agricultural Research Center for Western Region
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- Yoshioka Terutaka
- Okitsu Citrus Research Station, National Institute of Fruit Tree Science
Bibliographic Information
- Other Title
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- カンキツ台木における枝内水通導性を利用した早期樹勢予測法の開発
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Abstract
Assessment of the tree vigor of grafted rootstocks in citrus requires intense labor, a long period, and large fields because tree vigor is judged through cultivation tests with adult trees. We have developed a method to predict tree vigor at an early stage based on the stem hydraulic conductance of 5-month-old seedlings. We used 15 cultivars (strains), including 11 crossed strains, 3 cultivars of commonly used trifoliate orange (common type, ‘Pomeroy’, and ‘USDA’), and ‘Swingle citrumelo’. The growth characteristics of 7-year-old satsuma mandarin trees grafted onto those rootstocks were compared with those of 5-month-old rootstock seedlings. The results revealed a relatively high correlation (r2 = 0.633) between the trunk circumference of 7-year-old trees and the stem hydraulic conductance of seedlings, and furthermore, control cultivars existed approximately on that regression line. Therefore, it seems possible to predict tree vigor from the stem hydraulic conductance of seedlings in a very short period without using a large field and intense labor.<br>
Journal
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- Journal of the Japanese Society for Horticultural Science
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Journal of the Japanese Society for Horticultural Science 80 (4), 390-395, 2011
THE JAPANESE SOCIETY FOR HORTICULTURAL SCIENCE
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Details 詳細情報について
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- CRID
- 1390282680266918784
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- NII Article ID
- 130004951638
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- NII Book ID
- AA12177046
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- ISSN
- 1882336X
- 18823351
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- NDL BIB ID
- 11277526
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed