A thermal forecasting model for the overwintering generation of cotton bollworm by remote sensing in the southeast of Caspian Sea

Author:

Jokar MahmoudORCID

Abstract

Aim of study: Cotton bollworm (Helicoverpa armigera) is a key pest of cotton all around the world. The Degree-Day (DD) model, as a reliable forecasting approach, is based on the cumulatively effective temperature which must be received by the pests to complete their life cycle. The main objective of the current research was the feasibility of using two accessible thermal data to predict the emergence time of the first generation of H. armigera. Area of study: Golestan province of Iran Material and methods: The lower temperature threshold (T0) and the thermal constant (k) were calculated by separately incubating batches of 10 pupae ( 24 h) at a wide range of temperatures (20, 25, 30, 35, and 40 ) in laboratory conditions. The thermal requirements of the overwintering generation were estimated via two types of thermal data sources, i.e., Land Surface Temperature (LST) of Terra® satellite and synoptic meteorological stations from January 21st, 2020 to the end of May 2020. Main results: T0 and k of the pupal stage were found to be 9.75±1.41°C and 250.57±4.66 (DD), respectively, via the linear regression and 10.26±1.09°C and 240.85±6.71 (DD) through Ikemoto & Takai’s model. The time series of satellite thermal data (LST-day and LST-night) modified through laboratory DD parameters was validly identified to determine high-risk areas and predict the emergence times of the first generation of cotton bollworm. This was in agreement with the reports of the governmental Plant Protection Organization. Research highlights: Due to the lacking meteorological synoptic stations in some agricultural areas, the LST data of Terra® satellite could be replaced by the meteorological data for DD forecasting models.

Publisher

Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA)

Subject

Agronomy and Crop Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3