Evidence map›Paper›PMID 39962426›Full record

ArticleBMC plant biology2025

Revitalizing maize downy mildew management: harnessing new-generation fungicides and host plant resistance.

G Jadesha, M S Kitturmath, P Mahadevu, Chikkappa G Karjagi, Zahoor Ahmed Dar, H C Lohithaswa, D Deepak

Abstract read
In one paragraph

Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

G JadeshaZonal Agricultural Research Station, V.C. Farm, University of Agricultural Sciences, Bangalore, Karnataka, India. jadesha.uasb@gmail.com.ORCID https://orcid.org/0000-0001-5998-0937
M S KitturmathZonal Agricultural Research Station, V.C. Farm, University of Agricultural Sciences, Bangalore, Karnataka, India.ORCID https://orcid.org/0000-0001-7007-8012
P MahadevuZonal Agricultural Research Station, V.C. Farm, University of Agricultural Sciences, Bangalore, Karnataka, India.ORCID https://orcid.org/0000-0001-9617-9735
Chikkappa G KarjagiICAR-Indian Institute of Maize Research, Unit Office, PUSA Campus, New Delhi, India.ORCID https://orcid.org/0000-0002-9064-5237
Zahoor Ahmed DarDryland Agriculture Research Station, Srinagar, Jammu and Kashmir, India.ORCID https://orcid.org/0000-0001-7584-8477
H C LohithaswaZonal Agricultural Research Station, GKVK, University of Agricultural Sciences, Bangalore, Karnataka, India.ORCID https://orcid.org/0000-0002-6777-5965
D DeepakDepartment of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India. deepak.d@manipal.edu.ORCID https://orcid.org/0000-0001-7194-463X

Funding

University of agricultural science Bangalore 9331/6330 2019-20
6 · The paper itself

Abstract

backgroundMaize Downy Mildew (MDM) is a devastating disease in the humid sub-tropical/tropical regions of Asia. In this study, the prevalence of MDM during the rainy Kharif seasons of south Karnataka state (India) ranged between 6.8% (2018) and 19.1% (2022). The research evaluated new fungicidal treatments and assessed the genetic tolerance of maize lines to develop robust management strategies that enhance maize productivity and stability.

resultsDuring the Kharif seasons of 2021 and 2022, we conducted field trials to evaluate the effectiveness of six different fungicides, both individually and in combination. The most effective approach combined seed treatment with Metalaxyl (4%) and Mancozeb (64%) WP, followed by a foliar spray of Azoxystrobin (18.2%) and Difenoconazole (11.4%) SC. This treatment reduced MDM incidence by 97.6% and increased maize yield up to 85.6 quintals per hectare, with a benefit-cost ratio of 2.2. Additionally, screening of 317 maize inbred lines in Kharif 2019 identified 22 lines with stable MDM resistance over nine consecutive Rabi and Kharif seasons, indicating their potential for sustained resistance. Liquid Chromatography-Mass Spectrometry (LC-MS) analysis revealed significant increases in eighteen phenolic compounds and fifteen flavonoid compounds in resistant maize genotypes. Specifically, resistant genotypes exhibited elevated levels of salicylic acid (4.2 to 9.2-fold), p-Coumaric acid (3.7 to 4.8-fold), o-Coumaric acid (4.5 to 7.4-fold), Caffeic acid (2.4 to 3.1-fold), and Ferulic acid (2.3 to 2.8-fold). Flavonoid levels also increased, with Naringenin ranging from 34.4 µg/g in African Tall to 130 µg/g in MAI 224, Catechin from 22.9 µg/g in African Tall to 124.4 µg/g in MAI 10, and Epicatechin from 1.3 µg/g in African Tall to 8.2 µg/g in MAI 10. These heightened levels contribute to a robust chemical defence mechanism against Peronosclerospora sorghi.

conclusionsThis study provides crucial insights into managing MDM through host plant resistance and fungicidal treatments. We identified 22 resistant inbred lines as valuable genetic resources for breeding MDM-resistant maize hybrids. Enhanced levels of specific phenolic and flavonoid compounds in these resistant genotypes suggest a robust chemical defence mechanism, essential for developing resilient crops. Our findings offer practical recommendations for improving maize production and ensuring crop security in MDM-affected regions. Integrating these resistant maize lines and effective fungicidal treatments can significantly advance sustainable agricultural practices, contributing to crop resilience and food security in areas prone to MDM.

Indexed as

Disease ResistanceFungicides, IndustrialPlant DiseasesZea maysIndiaFungicides, IndustrialFungicidesHost plant resistanceLCMSMaize downy mildewPhenolics and flavonoidsSurvey

Identifiers

PMID39962426
PMCPMC11831823

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.