Identification and optimization of volatile organic compounds to enhance bait attractiveness for red imported fire ants (Solenopsis invicta Buren)

红火蚁 生物 人口 茴香脑 有害生物分析 毒理 食品科学 植物 膜翅目 人口学 社会学 精油
作者
Jiacheng Shen,Sheng‐Yen Wu,Lin Peng,Jiang Xin-yi,Youming Hou
出处
期刊:Pest Management Science [Wiley]
标识
DOI:10.1002/ps.8696
摘要

Abstract BACKGROUND The red imported fire ant (RIFA, Solenopsis invicta ), a highly destructive invasive pest, has rapidly spread through human trade, posing significant threats to agricultural and forest ecosystems. Due to its preference for high‐fat and high‐protein foods, ham sausage is commonly used as bait to monitor RIFA populations in invaded areas. However, the presence of volatile organic compounds (VOCs) in such baits may affect their effectiveness because VOCs can act as either attractants or repellents. Identifying VOCs that specifically attract RIFA is essential to improve bait efficacy. RESULTS This study aimed to identify attractant compounds within bait VOCs for RIFA, leveraging the highly‐expressed antennal odorant‐binding protein 1 (OBP1) and reverse chemical ecology approach. Additionally, we examined the effects of mixtures of these attractants on RIFA behavior. Our findings revealed that anethole, 1S‐(−)‐β‐pinene, and β‐caryophyllene individually attracted RIFA at 0.1 μg/μL. Notably, a combination of anethole and 1S‐(−)‐β‐pinene enhanced behavioral activity more than individual compounds, suggesting synergistic effects. Conversely, the addition of β‐caryophyllene to anethole significantly reduced RIFA activity. These results provide a theoretical basis for developing behavioral regulators targeting RIFA. CONCLUSION This study demonstrates that the integration of OBP‐based in vitro assays with computational simulations can effectively identify behaviorally active compounds for RIFA. Additionally, it clarifies the optimal ratios of active VOCs in baits, offering valuable theoretical guidance for enhancing RIFA population monitoring efforts. © 2025 Society of Chemical Industry.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
木瓜小五哥完成签到,获得积分10
刚刚
toda_erica完成签到,获得积分10
3秒前
Eton完成签到,获得积分10
3秒前
4秒前
慕青应助123采纳,获得10
4秒前
和谐的蜡烛完成签到,获得积分10
4秒前
李爱国应助灵巧一笑采纳,获得10
6秒前
iFan完成签到 ,获得积分10
8秒前
8秒前
ShishanXue完成签到 ,获得积分20
10秒前
一尘不染完成签到 ,获得积分10
10秒前
我刷的烧饼贼亮完成签到 ,获得积分10
10秒前
机智的小霸王完成签到,获得积分10
11秒前
12秒前
超帅连虎应助迷路安雁采纳,获得10
13秒前
慎独579发布了新的文献求助10
13秒前
安南完成签到 ,获得积分10
16秒前
17秒前
18秒前
18秒前
排骨炖豆角完成签到 ,获得积分10
19秒前
尚可完成签到 ,获得积分10
19秒前
灵巧一笑发布了新的文献求助10
19秒前
无异常完成签到,获得积分10
19秒前
19秒前
小鹿呀完成签到,获得积分10
20秒前
lq完成签到,获得积分10
21秒前
缥缈凡旋完成签到,获得积分10
22秒前
陈伟杰发布了新的文献求助10
22秒前
隐形皮卡丘完成签到,获得积分10
23秒前
853225598完成签到,获得积分10
23秒前
唯梦完成签到 ,获得积分10
23秒前
小鹿斑斑比完成签到,获得积分10
24秒前
feng发布了新的文献求助10
24秒前
及禾完成签到,获得积分10
24秒前
PhysicsXX完成签到,获得积分10
27秒前
赘婿应助西瓜刀采纳,获得10
29秒前
刘一鸣完成签到 ,获得积分10
32秒前
还原糖完成签到,获得积分10
32秒前
完美世界应助陈伟杰采纳,获得10
33秒前
高分求助中
【重要!!请各位用户详细阅读此贴】科研通的精品贴汇总(请勿应助) 10000
Semantics for Latin: An Introduction 1018
International Code of Nomenclature for algae, fungi, and plants (Madrid Code) (Regnum Vegetabile) 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 530
Apiaceae Himalayenses. 2 500
Maritime Applications of Prolonged Casualty Care: Drowning and Hypothermia on an Amphibious Warship 500
Tasteful Old Age:The Identity of the Aged Middle-Class, Nursing Home Tours, and Marketized Eldercare in China 350
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4081381
求助须知:如何正确求助?哪些是违规求助? 3620857
关于积分的说明 11487301
捐赠科研通 3336219
什么是DOI,文献DOI怎么找? 1834056
邀请新用户注册赠送积分活动 902877
科研通“疑难数据库(出版商)”最低求助积分说明 821335