Evidence map›Paper›PMID 40595117›Full record

ArticleScientific reports2025

Multi-model statistical approaches for assessing the stability of Cicer interspecific derivatives in the trans and upper gangetic regions of India.

Amool Singh Vadithya, Shayla Bindra, Narinder Sharma, Satish Kumar Sanwal, Shanmugavadivel P S, Inderjit Singh, Chellapilla Bharadwaj, Mohar Singh

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Amool Singh VadithyaDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India.
Shayla BindraDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India. shaylabindra@pau.edu.ORCID http://orcid.org/0000-0002-8155-6451
Narinder SharmaDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India.
Satish Kumar SanwalICAR-Central Soil Salinity Research Institute, Karnal, India.
Shanmugavadivel P SICAR-Indian Institute of Pulses Research, Kanpur, India.
Inderjit SinghDepartment of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, 141004, India.
Chellapilla BharadwajDivision of Genetics, ICAR- Indian Agricultural Research Institute, New Delhi, India.
Mohar SinghICAR-National Bureau of Plant Genetic Resources Regional Station, Shimla, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chickpea productivity remains low due to limited genetic variability and susceptibility to biotic and abiotic stresses. To address these challenges, the introgression of novel genes from wild relatives and multi-environment evaluations are essential for identifying high-yielding, stable interspecific derivatives (ISDs). Despite the availability of several statistical tools, few chickpea studies have used a comprehensive multi-model approach for stability analysis. This study fills the void by applying four models- AMMI, GGE, WAASB, and MTSI for the first time in chickpea to evaluate multi-trait stability across diverse environments. 19 ISDs developed from four interspecific crosses (BGD 72 × ILWC 229, PBG 5 × ILWC 229, BGD 72 × ILWC 246, and PBG 5 × ILWC 246), along with two checks (PBG 7 and PBG 8), were evaluated across six environments. Trials were conducted over three consecutive rabi seasons (2020-2023) at Ludhiana (ENV1-ENV3), followed by multi-location testing during rabi 2023-24 at Ludhiana (ENV4), Karnal (ENV5), and Kanpur (ENV6). Key yield traits, including number of pods per plant (NPP), 100-seed weight (HSW), and seed yield per plot (SYPP), were analyzed using all four models. Significant effects of genotype, environment, and genotype × environment interactions (GEIs) were detected through pooled ANOVA, and positive correlations were observed among all key traits. Genotypes GL21-1 (G1) and GL21-54 (G8) were superior performers with high trait values and stable performance across all environments, with yield variability up to 20% under stress-prone conditions. Among the models, GGE and WAASB were found effective for individual traits, while MTSI was superior for multi-trait selection. These promising ISDs can be released as high-yielding varieties or used as donor parents in climate-resilient chickpea breeding programs, addressing the rising global demand for chickpea production.

Indexed as

CicerModels, StatisticalCrosses, GeneticGenetic VariationIndiaPlant BreedingAMMIChickpeaG × E interactionGGE biplotMTSIWAASBY

Identifiers

PMID40595117
PMCPMC12218011

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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.