Literature DB >> 30781299

Azoxystrobin Rate and Timing Effects on Rice Head Blast Incidence and Rice Grain and Milling Yields.

D E Groth1.   

Abstract

Growing blast susceptible rice (Oryza sativa) cultivars often requires farmers to use fungicides to prevent significant reductions in rice grain and milling yields. Studies were conducted to determine the optimum rate and rice growth stage for single or multiple applications of azoxystrobin to control blast (Pyricularia grisea). Azoxystrobin was applied foliarly to naturally infected field plots in 2001 to 2005 at rates of 0.11, 0.17, and 0.22 kg a.i. ha-1 at boot (B) and heading (H) or only at H growth stages, and at 0.17 kg a.i. ha-1 at 5 (H+5), 10 (H+10), and 15 (H+15) days after H and B with low or high blast pressure. Head blast incidence (percent heads infected) was assessed 1 to 2 weeks before harvest. A fungicide application made at H, H+5, and B+H significantly reduced blast incidence with high and low disease pressure, resulting in significantly higher grain and head rice milling yields compared with unsprayed plots with high blast pressure. There were no significant effects of fungicide rate on blast development or yield following the H, B+H, and H+5 applications. With fungicide applications made at B, H+10, and H+15 days postheading, rice had higher disease incidence, resulting in lower grain and milling yields compared with rice receiving a heading application.

Entities:  

Keywords:  application timing; reduced rate; yield loss

Year:  2006        PMID: 30781299     DOI: 10.1094/PD-90-1055

Source DB:  PubMed          Journal:  Plant Dis        ISSN: 0191-2917            Impact factor:   4.438


  2 in total

1.  Selection of Candidate Genes Conferring Blast Resistance and Heat Tolerance in Rice through Integration of Meta-QTLs and RNA-Seq.

Authors:  Tian Tian; Lijuan Chen; Yufang Ai; Huaqin He
Journal:  Genes (Basel)       Date:  2022-01-25       Impact factor: 4.096

2.  Predicting rice blast disease: machine learning versus process-based models.

Authors:  David F Nettleton; Dimitrios Katsantonis; Argyris Kalaitzidis; Natasa Sarafijanovic-Djukic; Pau Puigdollers; Roberto Confalonieri
Journal:  BMC Bioinformatics       Date:  2019-10-22       Impact factor: 3.169

  2 in total

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