Relationship between secondary metabolites and insect loads in cabbage with different leaf shapes and positions.

IF 3 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Phytochemical Analysis Pub Date : 2024-10-01 Epub Date: 2024-06-25 DOI:10.1002/pca.3406
Samreen Ghulam Rasool, Muhammad Abdullah, Dezhi Li, Liu Yanping
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引用次数: 0

Abstract

Introduction: Secondary metabolites in plants play a crucial role in defense mechanisms against insects, pests, and pathogens. These metabolites exhibit varying distributions within and among plant parts under different biotic and abiotic conditions. Understanding the intricate relationships between secondary metabolites and insect populations can be helpful for elucidating plant defense mechanisms and enhancing agricultural managing efficiencies.

Objective: To investigate the influence of the glucosinolate profile in the leaves of three cabbage (Brassica oleracea var. capitata L.) varieties on insect loads.

Methods: Glucosinolate profiles across different leaf positions (such as bottom, middle, and center) and leaf shapes (such as curly and non-curly leaf) of three cabbage varieties (Xiagan [XGA], Xiaguang [XGU], and Qiangxia [QIX]) were analyzed by using high-performance liquid chromatography-mass spectrometry (LC-MS). The insect loads were recorded by visually inspecting the upper and lower layers of each target leaf.

Results: Increasing concentrations of four glucosinolates, namely, glucoiberin, progoitrin, glucoraphanin, and glucobrassicin, were positively related to insect loads. While increasing concentrations of the other four glucosinolates, such as neoglucobrassicin, 4-methoxyglucobrassicin, sinigrin, and gluconapin, were negatively related to insect loads. Furthermore, both glucosinolate synthesis and insect loads were significantly higher in the curly-shaped and middle-position leaves than in the non-curly-shaped and bottom- and central-position leaves across the cabbage varieties.

Conclusion: Differences in glucosinolate profiles across leaf positions and shapes strongly influenced the insect loads of the three Brassica varieties. This link may further extend our understanding of the real defense power of a particular variety against herbivore damage.

不同叶片形状和位置的卷心菜次生代谢物与昆虫数量的关系
导言:植物中的次生代谢物在抵御昆虫、害虫和病原体的防御机制中发挥着至关重要的作用。在不同的生物和非生物条件下,这些代谢物在植物各部分内部和之间的分布各不相同。了解次生代谢物与昆虫种群之间错综复杂的关系有助于阐明植物防御机制和提高农业管理效率:研究三个甘蓝(Brassica oleracea var. capitata L.)品种叶片中葡萄糖苷酸含量对昆虫数量的影响:方法:采用高效液相色谱-质谱法(LC-MS)分析了三个甘蓝品种(厦甘[XGA]、厦光[XGU]和羌峡[QIX])不同叶片位置(如底部、中部和中央)和叶片形状(如卷曲叶和非卷曲叶)的葡萄糖苷酸谱。通过目测每片目标叶片的上下层来记录昆虫数量:结果:四种葡萄糖苷酸盐(即葡萄糖纤维素、原果糖苷、葡萄糖萘苷和葡萄糖巴西苷)浓度的增加与虫量呈正相关。而其他四种葡萄糖苷酸盐(如新葡萄糖苷、4-甲氧基葡萄糖苷、山奈苷和葡萄糖苷)浓度的增加与昆虫数量呈负相关。此外,在不同卷心菜品种中,卷曲叶片和中间位置叶片的葡糖苷酸合成量和虫量都明显高于非卷曲叶片和底部及中央位置叶片:结论:不同叶片位置和形状的葡萄糖苷酸含量差异对三个甘蓝品种的虫量有很大影响。这一联系可进一步加深我们对特定品种抵御食草动物危害的实际防御能力的了解。
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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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