Detection of Spodoptera litura F. using an electronic nose: A novel approach for monitoring vegetable crop pests

IF 8.9 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Atirach Noosidum , Rattanawadee Onwong , Jarunee Phittayanivit , Chatchaloem Arkhan , Pisit Poolprasert , Benjakhun Sangtongpraow , Chatchawal Wongchoosuk
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Abstract

The common cutworm, Spodoptera litura, is an economically important insect pest worldwide. However, outbreaks and control failures are frequently reported, with infestations often detected by farmers only after severe damage has occurred. This study aimed to apply an electronic nose (e-nose) based on eight metal oxide semiconductor (MOS) gas sensors to detect insect odors emitted from different stages of S. litura and volatile organic compounds (VOCs) released from their infested host plants. In laboratory tests, a prototype e-nose equipped with eight TGS sensors successfully detected various insect odors from different developmental stages and numbers of individuals (0.31–41.04 %). Older larvae and higher numbers of insects induced higher sensor responses. The e-nose also distinguished between two closely related species, S. litura and S. exigua. Additionally, plant VOCs released from pak choi (Brassica rapa) leaves with more than 5 % damage caused by S. litura larvae were more readily detected by the e-nose compared to leaves cut with scissors or undamaged plants. The e-nose also detected insect odors from S. litura larvae and plant VOCs from infested plants at distances of up to 40 cm. In greenhouse tests, the e-nose began detecting differences in insect odors and plant VOCs measurements between S. litura-infested and healthy plants when neonate larvae invaded plant leaves. This study demonstrates the potential of the e-nose equipped with eight TGS sensors as a detection tool for S. litura infestations in crop production.
利用电子鼻检测斜纹夜蛾:一种监测蔬菜作物害虫的新方法
斜纹夜蛾(Spodoptera litura)是世界范围内重要的经济害虫。然而,经常报告疫情暴发和控制失败,农民往往在发生严重损害后才发现虫害。本研究旨在应用基于8个金属氧化物半导体(MOS)气体传感器的电子鼻(电子鼻)来检测斜纹夜蛾不同阶段散发的昆虫气味和被寄生植物释放的挥发性有机化合物(VOCs)。在实验室测试中,装有8个TGS传感器的原型电子鼻成功地检测了不同发育阶段和个体数量的各种昆虫气味(0.31 - 41.04%)。幼虫年龄越大,昆虫数量越多,传感器反应越强烈。电子鼻还能区分出两个密切相关的物种,S. litura和S. exigua。此外,被斜纹刺槐幼虫伤害超过5%的白菜叶片释放的植物挥发性有机化合物(VOCs)比被剪刀剪过的叶片和未受伤害的叶片更容易被电子鼻检测到。电子鼻还能在40厘米范围内检测到斜纹夜蛾幼虫的昆虫气味和受感染植物的挥发性有机化合物。在温室试验中,当新生幼虫侵入植物叶片时,电子鼻开始检测到受S. litura感染的植物和健康植物之间昆虫气味和植物挥发性有机化合物测量的差异。该研究证明了配备8个TGS传感器的电子鼻在作物生产中作为斜纹夜蛾侵染检测工具的潜力。
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来源期刊
Computers and Electronics in Agriculture
Computers and Electronics in Agriculture 工程技术-计算机:跨学科应用
CiteScore
15.30
自引率
14.50%
发文量
800
审稿时长
62 days
期刊介绍: Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.
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