Alejandra Ledda, M. Yanniccari, M. C. Franco, M. T. Sobrero
{"title":"Thermal time and extreme weather events determine the emergence of Amaranthus palmeri","authors":"Alejandra Ledda, M. Yanniccari, M. C. Franco, M. T. Sobrero","doi":"10.51694/advweedsci/2022;40:amaranthus006","DOIUrl":null,"url":null,"abstract":"most widespread weed of agricultural land in large parts of North and South America. Understanding its population dynamics and the influence of meteorological variables becomes important for decision-making in an integrated management context. The hypothesis is that the emergence of A. palmeri is influenced by thermal time and extreme weather events that occurred in the previous 45, 30 or 15 days. Objective: The work was aimed to detect the influence of meteorological variables and extreme weather events on the emergence of A. palmeri under field conditions. Methods: A field experiment was carried out in order to record seedling emergence of A. palmeri in two growing seasons, 2017/2018 (S1) and 2018/2019 (S2), in Argentina. Associations between weed emergence and thermal time (in growing degree-days GDD), meteorological variables or extreme weather events recorded at 15, 30 and 45 days before to each evaluation time were studied by regression, principal components and multiple correspondence analyses. Results: Thermal time was closely associated to the progress of cumulative emergence in both seasons, but the emergence periodicity was conditional with rainfall. The high precipitation during the spring determined a short lag period (121.8 GDD) in S2. Contrarily, the largest lag period (236.6 GDD) was detected in S1 related to a drought that concentrated the emergence in the beginning of the summer when the rainfall increased. Conclusions: Thermal time allows the cumulative emergence prediction; however, extreme weather events like drought induce quiescence, concentrating the emergence in a short period.","PeriodicalId":29845,"journal":{"name":"Advances in Weed Science","volume":"1 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Weed Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.51694/advweedsci/2022;40:amaranthus006","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 1
Abstract
most widespread weed of agricultural land in large parts of North and South America. Understanding its population dynamics and the influence of meteorological variables becomes important for decision-making in an integrated management context. The hypothesis is that the emergence of A. palmeri is influenced by thermal time and extreme weather events that occurred in the previous 45, 30 or 15 days. Objective: The work was aimed to detect the influence of meteorological variables and extreme weather events on the emergence of A. palmeri under field conditions. Methods: A field experiment was carried out in order to record seedling emergence of A. palmeri in two growing seasons, 2017/2018 (S1) and 2018/2019 (S2), in Argentina. Associations between weed emergence and thermal time (in growing degree-days GDD), meteorological variables or extreme weather events recorded at 15, 30 and 45 days before to each evaluation time were studied by regression, principal components and multiple correspondence analyses. Results: Thermal time was closely associated to the progress of cumulative emergence in both seasons, but the emergence periodicity was conditional with rainfall. The high precipitation during the spring determined a short lag period (121.8 GDD) in S2. Contrarily, the largest lag period (236.6 GDD) was detected in S1 related to a drought that concentrated the emergence in the beginning of the summer when the rainfall increased. Conclusions: Thermal time allows the cumulative emergence prediction; however, extreme weather events like drought induce quiescence, concentrating the emergence in a short period.