Assessing the Impact of Ramularia Leaf Spot on Barley: Prospects for Fungicide Protection Strategies and Weather-Based Prediction Models in Argentina

被引:0
|
作者
Erreguerena, Ignacio Antonio [1 ]
Quiroz, Facundo Jose [2 ]
Cambareri, Matias [3 ]
Pereyra, Silvia [4 ]
Havis, Neil David [5 ]
Carmona, Marcelo Anibal [6 ]
机构
[1] Natl Inst Agr Technol, Plant Pathol Crop Protect Grp, Cordoba, Argentina
[2] Natl Inst Agr Technol, Plant Hlth Grp, Balcarce, Argentina
[3] Cabure AgTech, Balvanera, Argentina
[4] Natl Inst Agr Res, INIA Estanzuela, Colonia, Uruguay
[5] Scotlands Rural Coll, Crop & Soil Res Grp, Edinburgh, Scotland
[6] Univ Buenos Aires, Fac Agron, Catedra Fitopatol, Buenos Aires, Argentina
关键词
barley; control strategy; forecast model; fungicide spraying time; <italic>Ramularia collo-cygni</italic>; COLLO-CYGNI; EMERGING PATHOGEN; REACTIVE OXYGEN; DISEASE; SEVERITY;
D O I
10.1111/ppa.14056
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Ramularia leaf spot (RLS), caused by the fungus Ramularia collo-cygni (Rcc), has become a threat to barley production in Argentina and the world, causing grain yield and quality losses. Characteristics of the pathogen such as a long latency period, high evolutionary potential, numerous transposonic regions and the ability to infect alternative hosts facilitate Rcc adaption to environmental changes and/or control measures such as fungicides. RLS is considered a sporadic disease in Argentina and its occurrence is highly dependent on weather conditions. The objectives of this work were to quantify the impact of RLS on grain yield and its commercial quality, to establish an optimal protection period (PP) for barley with fungicides, and to describe the association between environmental variables and levels of RLS with the purpose of designing prediction models and more efficient protection strategies. Based on the results from field trials (n = 8), we estimated grain yield losses up to 16%, and these occurred due to reduced grain weight (8.7%) and size (20%). We also determined that the PP begins from the third detectable node (GS33) to first visible awns (GS49) and concluded that the flag leaf fully emerged stage (GS39) was the most efficient fungicide spraying time. Four possible forecast models were proposed based on the daily average temperature accumulated from early tillering (GS21) to GS39 stage, in combination with the number of days of soil water availability, number of days with water excess and duration of leaf wetness or accumulated rainfall from tillering to GS39 (n = 10).
引用
收藏
页数:15
相关论文
共 6 条
  • [1] Fungicide strategies for Ramularia Leaf Spot control recommended in Uruguay and its residues in barley grains
    Palladino, C.
    Perez, C.
    Pareja, L.
    Perez-Parada, A.
    Franco, J.
    Pereyra, S.
    AGROCIENCIA URUGUAY, 2024, 28
  • [2] Weather-based models for predicting risk of zonate leaf spot disease in Sorghum
    Nitish Rattan Bhardwaj
    Ashlesha Atri
    Upasana Rani
    Devinder Kumar Banyal
    Ajoy Kumar Roy
    Tropical Plant Pathology, 2021, 46 : 702 - 713
  • [3] Weather-based models for predicting risk of zonate leaf spot disease in Sorghum
    Bhardwaj, Nitish Rattan
    Atri, Ashlesha
    Rani, Upasana
    Banyal, Devinder Kumar
    Roy, Ajoy Kumar
    TROPICAL PLANT PATHOLOGY, 2021, 46 (06) : 702 - 713
  • [4] Development of weather-based prediction models for leaf rust in wheat in the Indo-Gangetic plains of India
    Kumar, P. Vijaya
    EUROPEAN JOURNAL OF PLANT PATHOLOGY, 2014, 140 (03) : 429 - 440
  • [5] Development of weather-based prediction models for leaf rust in wheat in the Indo-Gangetic plains of India
    P. Vijaya Kumar
    European Journal of Plant Pathology, 2014, 140 : 429 - 440
  • [6] Weather-based risk assessment models for common leaf spot and black seed disease of strawberry caused by Mycosphaerella fragariae
    Carisse, O.
    PHYTOPATHOLOGY, 2016, 106 (12) : 5 - 5