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亲缘选择理论预测亲缘植物之间可通过亲缘识别来实现相互合作.前期的相关研究也证实了植物的亲缘选择作用.以高粱(Sorghum vulgare)为研究对象,通过测度亲缘和非亲缘植物在表型(株高、根长、叶面积和种子数),各构件生物量(根、茎叶和种子)和生理(根系活力、叶绿素含量、丙二醛、脯胺酸、根系硝酸根含量和硝酸还原酶活性)上的表现差异,来探索高粱植物的亲缘识别.结果显示,与非亲缘组相比,亲缘组植物叶面积增加(P=0.032),但根系活力降低(P=0.044).除此之外,亲缘组和非亲缘组高粱在根长(P=0.811)、株高(P=0.435)、种子数(P=0.541),以及根(P=0.413)、茎叶(P=0.975)和种子(P=0.731)生物量方面都未表现出显著差异.而且,根系硝酸根含量(P=0.944)、硝酸还原酶含量(P=0.817)、叶绿素含量(P=0.941)、MDA含量(P=0.749)和脯胺酸含量(P=0.355)等生理指标在亲缘和非亲缘组也无显著差异.因此,亲缘植物在地上部分通过增加叶面积分配来提高地上空间和光捕获竞争,而在地下部分,亲缘植物通过降低根系活力来降低根系竞争,实现互让水分和养分.这说明高粱植物亲缘竞争和亲缘识别同时发生,亲缘识别不仅具表型响应,还存在生理响应,因此从不同指标层面研究植物的亲缘识别方能得出更为严谨的结论.
The kinship selection theory predicts that kinship plants can cooperate with each other through kinship identification.The previous researches also confirm the kin selection of plants.With Sorghum vulgare as the research object, (Plant height, root length, leaf area and number of seeds), biomass (root, stem, leaf and seed) and physiology (root activity, chlorophyll content, malondialdehyde, proline, nitrate content and nitrate reduction (P = 0.032), but the root activity decreased (P = 0.044), compared with the non-relatives, except for the relative activity of the sorghum plants (P = 0.811), plant height (P = 0.435), seed number (P = 0.541), and root (P = 0.413), stem and leaf (P = 0.975) (P = 0.944), nitrate reductase content (P = 0.817), chlorophyll content (P = 0.941), MDA content (P = P = 0.749) and proline content (P = 0.355), there was no significant difference in relatives and unrelated groups.Therefore, Marginal plants increase competition in aerial space and light harvesting by increasing leaf area distribution in the aerial part, whereas in the subsurface part, relatives reduce root system competition by reducing root activity and achieve mutual transfer of water and nutrients, indicating that both sorghum plantation competition and kinship identification Occurrence and kinship identification not only have phenotypic response, but also physiological responses. Therefore, we can draw more rigorous conclusions from the study of kinship identification of plants from different index levels.