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タイトル: | Evaluation of antixenosis in soybean against <i>Spodoptera litura</i> by dual-choice assay aided by a statistical analysis model: Discovery of a novel antixenosis in Peking |
著者: | Yano, Mariko Inoue, Takato Nakata, Ryu Teraishi, Masayoshi https://orcid.org/0000-0002-6768-8052 (unconfirmed) Yoshinaga, Naoko https://orcid.org/0000-0002-6476-0610 (unconfirmed) Ono, Hajime https://orcid.org/0000-0002-8042-2697 (unconfirmed) Okumoto, Yutaka Mori, Naoki https://orcid.org/0000-0003-3770-0759 (unconfirmed) |
著者名の別形: | 矢野, まりこ 井上, 貴斗 中田, 隆 寺石, 政義 吉永, 直子 小野, 肇 奥本, 裕 森, 直樹 |
キーワード: | Glycine max Spodoptera litura antixenosis |
発行日: | May-2021 |
出版者: | Pesticide Science Society of Japan |
誌名: | Journal of Pesticide Science |
巻: | 46 |
号: | 2 |
開始ページ: | 182 |
終了ページ: | 188 |
抄録: | The method for evaluating soybean (Glycine max) antixenosis against the common cutworm (Spodoptera litura) was developed based on a dual-choice assay aided by a statistical analysis model. This model was constructed from the results of a dual-choice assay in which Enrei, a soybean cultivar susceptible to S. litura, was used as both a standard and a test leaf disc for 2nd–5th instar larvae. The statistical criterion created by this model enabled the evaluation of the presence of antixenosis. This method was applied to four soybean varieties, including Tamahomare (susceptible), Himeshirazu (resistant), IAC100 (resistant), and Peking (unknown), as well as Enrei. Subsequently, the degrees of antixenosis were also compared by F-test, followed by maximum likelihood estimation (MLE). According to the results, the antixenosis of Tamahomare, Himeshirazu, and IAC100 was statistically reevaluated and Peking exhibited a novel antixenosis, which was stronger for 3rd–5th instar larvae than for 2nd instar. |
著作権等: | © Pesticide Science Society of Japan 2021. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License. |
URI: | http://hdl.handle.net/2433/276525 |
DOI(出版社版): | 10.1584/jpestics.d21-006 |
PubMed ID: | 34135679 |
出現コレクション: | 学術雑誌掲載論文等 |
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