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<p>Green gram (<i>Vigna radiata</i> (L.) R. Wilczek) is an important short-duration pulse crop valued for its high nutritional content and suitability to diverse agro-climatic conditions. However, its productivity is significantly threatened by insect pests, particularly the polyphagous defoliator <i>Spodoptera litura</i> (Fabricius). This noctuid pest causes extensive leaf damage, leading to substantial economic losses. Host plant resistance, governed by biophysical and biochemical traits, is a fundamental component of Integrated Pest Management (IPM). These traits influence pest behaviour by affecting host preference and insect survival, thereby shaping population dynamics. This study investigated the mechanisms of resistance, with a focus on antixenosis (non-preference), in green gram against <i>S. litura</i>. Seventy germplasm accessions, along with a standard check, were evaluated under both field and laboratory conditions. The results demonstrated that more than half of the tested germplasms exhibited lower pest preference compared to the check. Biophysical traits (Trichome density and leaf thickness) showed a positive correlation with pest preference whereas Biochemical traits (Total soluble sugars and catalase activity) exhibited a negative correlation with pest preference, while peroxidase activity played a significant defensive role. Identification of traits for host plant resistance is important for the searching the source of resistance. Multivariate statistical analysis may play an important role to assess the key parameters for host plant resistance. For this purpose, Grey Relational Analysis (GRA) has been used to identify the biophysical parameters for the antixenosis mechanism against <i>S. litura</i> infesting green gram. This analysis (Grey relational coefficients) revealed that, among these traits, Trichome density (0.719) and Peroxidase (0.599) were found to be the most significant variables associated antixenosis resistance mechanism against larva of <i>S. litura.</i> This study highlights the critical role of specific morphological and enzymatic traits in conferring resistance to <i>S. litura</i> in green gram. Furthermore, it establishes Grey Relational Analysis as an effective tool for pinpointing key resistance characteristics, thereby facilitating the selection and breeding of resistant varieties for sustainable crop protection.</p> Graphical abstract <p></p>

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A novel application of grey relational analysis in screening of advanced breeding lines for antixenosis of Spodoptera litura (Fabricius) infesting green gram

  • 期刊论文

  • 发表日期：

    2026年3月13日

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  • Prafull Sati,
  • J. P. Purwar,
  • Narne Kavya,
  • Ritu Mishra,
  • Dharanikota Lalithambica Devi,
  • Aditya Pratap

摘要

Green gram (Vigna radiata (L.) R. Wilczek) is an important short-duration pulse crop valued for its high nutritional content and suitability to diverse agro-climatic conditions. However, its productivity is significantly threatened by insect pests, particularly the polyphagous defoliator Spodoptera litura (Fabricius). This noctuid pest causes extensive leaf damage, leading to substantial economic losses. Host plant resistance, governed by biophysical and biochemical traits, is a fundamental component of Integrated Pest Management (IPM). These traits influence pest behaviour by affecting host preference and insect survival, thereby shaping population dynamics. This study investigated the mechanisms of resistance, with a focus on antixenosis (non-preference), in green gram against S. litura. Seventy germplasm accessions, along with a standard check, were evaluated under both field and laboratory conditions. The results demonstrated that more than half of the tested germplasms exhibited lower pest preference compared to the check. Biophysical traits (Trichome density and leaf thickness) showed a positive correlation with pest preference whereas Biochemical traits (Total soluble sugars and catalase activity) exhibited a negative correlation with pest preference, while peroxidase activity played a significant defensive role. Identification of traits for host plant resistance is important for the searching the source of resistance. Multivariate statistical analysis may play an important role to assess the key parameters for host plant resistance. For this purpose, Grey Relational Analysis (GRA) has been used to identify the biophysical parameters for the antixenosis mechanism against S. litura infesting green gram. This analysis (Grey relational coefficients) revealed that, among these traits, Trichome density (0.719) and Peroxidase (0.599) were found to be the most significant variables associated antixenosis resistance mechanism against larva of S. litura. This study highlights the critical role of specific morphological and enzymatic traits in conferring resistance to S. litura in green gram. Furthermore, it establishes Grey Relational Analysis as an effective tool for pinpointing key resistance characteristics, thereby facilitating the selection and breeding of resistant varieties for sustainable crop protection.

Graphical abstract