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| 广西喀斯特地区五个桑树品种叶功能性状及其抗旱性评价 |
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覃兰丽1,陈观榕1,李燕婷1,谢彦军1,李晓东1, 黄康东2,文柳璎3,史沉鱼1*
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1.广西蚕桑生态学与智能化技术应用重点实验室,广西现代蚕桑丝绸协同创新中心,微生物及植物资源开发利用广西高校重点实验室,河池学院化学与生物工程学院,广西 河池 546300；3. 河池学院化学与生物工程学院,广西 河池 546300；2. 河池市蚕业技术推广站,河池市蚕种场,广西 河池 546300；3.百色市蚕业发展中心,广西 百色 533000
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| 摘要: |
| 为筛选出适合广西喀斯特地区种植的抗旱性强的桑树品种，该研究以环江地区桂桑5号、桂桑6号、桂桑优12、农桑14号、育711号5个桑树品种作为试验材料，通过测定叶绿素、渗透调节物质、花青素、丙二醛、抗氧化酶活性以及导管直径、导管加固系数、叶片厚度、上下表皮厚度、栅栏组织厚度、海绵组织厚度、气孔大小、气孔密度等24个叶功能性状指标，利用主成分分析、隶属函数和聚类分析，筛选出与抗旱性相关的叶功能性状指标及抗旱性较强的品种。结果表明：（1）主成分分析表明，与抗旱性相关的主要叶功能性状指标为叶绿素a、叶绿素b、总叶绿素、胡萝卜素、丙二醛、超氧化物歧化酶、气孔大小、气孔密度、导管加固系数、海绵组织。（2）根据隶属函数分析，5个桑树品种的抗旱性排名为，农桑14号 > 桂桑优12 > 桂桑5号 > 桂桑6号 > 育711号；进一步的聚类分析结果表明，农桑14号、桂桑优12、桂桑5号成为一类，桂桑6号、育711号组成另一类；两种分析结果很好地互相吻合。（3）农桑14号、桂桑优12、桂桑5号表现出更好的抗旱性，与它们具有更为高效的生理调节机制和优化的解剖结构有关。该研究结果为广西喀斯特地区桑树抗旱品种的筛选提供科学依据和理论参考。 |
| 关键词: 喀斯特地区，桑树，叶功能性状，隶属函数，聚类分析，抗旱性 |
| DOI：10.11931/guihaia.gxzw202407044 |
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| 基金项目:广西自然科学基金（2024GXNSFAA010145）；河池学院科研项目（2021GCC023，2023XJYB011）；广西现代蚕桑丝绸协同创新中心基金资助（2024GXCSSC07）；河池市中央引导地方科技发展资金项目（河科ZY230301）；2023年度广西蚕桑生态学与智能化技术应用重点实验室运行补助项目（23-026-08）。 |
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| Functional traits and drought resistance evaluation of leaves from five mulberry varieties in the Guangxi karst region |
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QIN Lanli1, CHEN Guanrong1, LI Yanting1, XIE Yanjun1, LI Xiaodong1, HUANG Kangdong2, WEN Liuying3, SHI Chenyu1 *
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1. Guangxi Colleges Universities Key Laboratory of Exploitation and Utilization of Microbial and Botanical Resources, Guangxi Collaborative Innovation Center of Modern Sericulture and Silk, Guangxi Key Laboratory of Sericulture Ecology and Applied Intelligent Technology, Hechi University School of Chemistry and Bioengineering, Hechi 546300, Guangxi, China; 2. Hechi Sericulture Technology Extension Station, Hechi Silkworm Egg Production Center, Hechi 546300, Guangxi, China;3. Baise Sericulture Development Center, Baise 533000, Guangxi, China
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| Abstract: |
| In order to select drought-resistant Morus alba varieties suitable for planting in the karst areas of Guangxi, this study investigated five mulberry varieties from Huanjiang county, namely Guisang 5, Guisang 6, Guisangyou 12, Nongsang 14, and Yu 711. A total of 24 leaf functional traits were measured, including chlorophyll, osmotic regulatory substances, anthocyanins, malondialdehyde, antioxidant enzyme activities, as well as anatomical traits such as conduit diameter, conduit wall reinforcement, leaf thickness, upper and lower epidermis thickness, palisade mesophyll thickness, spongy mesophyll thickness, stomatal size, and stomatal density. These traits were evaluated through principal component analysis, membership function, and cluster analysis to identify leaf functional traits associated with drought resistance and to select the varieties with the strongest drought resistance. The results were as follows： (1) Principal component analysis revealed that the key leaf functional traits associated with drought resistance in the five mulberry varieties were chlorophyll a, chlorophyll b, total chlorophyll, carotene, malondialdehyde, superoxide dismutase activity, stomatal size, stomatal density, conduit wall reinforcement, and spongy tissue thickness. These traits were found to have significant correlations with the drought resistance of the varieties. (2) The membership function analysis ranked the drought resistance of the five varieties as follows: Nongsang 14 > Guisangyou 12 > Guisang 5 > Guisang 6 > Yu 711. This ranking was confirmed by the subsequent cluster analysis, which grouped Nongsang 14, Guisangyou 12, and Guisang 5 together, while Guisang 6 and Yu 711 were placed in a separate group. The clustering results were consistent with the membership function analysis. (3) Nongsang 14, Guisangyou 12, and Guisang 5 exhibited the best drought resistance, which was attributed to their more efficient physiological regulation mechanisms and optimal anatomical features. The findings of this study provide a solid scientific foundation and valuable theoretical insights for the selection of drought-resistant mulberry varieties in the karst regions of Guangxi. |
| Key words: karst areas, Morus alba, leaf functional traits, membership function, clustering analysis, drought resistant |
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