Toward Accurate Detection: Protocol Adjustment for <i>Ascochyta rabiei</i> in Chickpea Seeds

This set of protocols was developed to detect Ascochyta rabiei, the fungus responsible for chickpea blight, in seeds. Given the significant impact of this disease and its potential to cause complete crop loss, even at low inoculum levels, optimizing detection protocols is crucial. This article proposes adjustments to key variables of a basic agar plate test-disinfection method, incubation, illumination, and culture medium-to improve microscopic identification (mainly using a stereomicroscope) and enhance differential growth of A. rabiei relative to other seed-borne fungi. Each step was carefully validated. Detection was verified through morphological and molecular confirmation of A. rabiei, as well as interlaboratory repeatability tests. In addition, the first distribution map of A. rabiei in Argentina was generated based on chickpea seed analyses conducted in the past decade and using the protocols outlined in this article. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Seed sampling procedure Basic Protocol 2: Preparation of culture medium Support Protocol: Sterilization of antibiotic Basic Protocol 3: Seed disinfection by washing Basic Protocol 4: Seed sowing and incubation Basic Protocol 5: Detection of infected seeds.

Authors

Institutions

Publication Details

Journal
Current Protocols
Published
2025-11-01
DOI
https://doi.org/10.1002/cpz1.70244
Primary Topic
Genetic and Environmental Crop Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Toward Accurate Detection: Protocol Adjustment for Ascochyta rabiei in Chickpea Seeds

Silvina Estela Pastor, Franco Daniel Fernández, Carlos Daniel Pinotti, Patricia Rodríguez Pardina et al.
Current Protocols
Genetic and Environmental Crop Studies
article

Toward Accurate Detection: Protocol Adjustment for Ascochyta rabiei in Chickpea Seeds

Silvina Estela Pastor, Franco Daniel Fernández, Carlos Daniel Pinotti, Patricia Rodríguez Pardina, Lucio Valetti, Clara Sonia Crociara, Bruno Daniel Pugliese, Alejandro Pérez, Ignacio Nahuel Rolhaiser
article en

Abstract

This set of protocols was developed to detect Ascochyta rabiei, the fungus responsible for chickpea blight, in seeds. Given the significant impact of this disease and its potential to cause complete crop loss, even at low inoculum levels, optimizing detection protocols is crucial. This article proposes adjustments to key variables of a basic agar plate test-disinfection method, incubation, illumination, and culture medium-to improve microscopic identification (mainly using a stereomicroscope) and enhance differential growth of A. rabiei relative to other seed-borne fungi. Each step was carefully validated. Detection was verified through morphological and molecular confirmation of A. rabiei, as well as interlaboratory repeatability tests. In addition, the first distribution map of A. rabiei in Argentina was generated based on chickpea seed analyses conducted in the past decade and using the protocols outlined in this article. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Seed sampling procedure Basic Protocol 2: Preparation of culture medium Support Protocol: Sterilization of antibiotic Basic Protocol 3: Seed disinfection by washing Basic Protocol 4: Seed sowing and incubation Basic Protocol 5: Detection of infected seeds.

Current ProtocolsVol. 5(11)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Universidad Nacional de Córdoba (AR), Instituto Nacional de Investigaciones Agropecuarias (EC)
Openalex Percentile: Top 75%
Genetic and Environmental Crop Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.