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<p><i>Aquilaria malaccensis</i>, or agarwood is a critically endangered species, known for its high economic and medicinal values. Our study focuses on in vitro micropropagation of this elite species for mass propagation and comparing the growth matrices through machine learning models. We found the effect of several growth hormones for seed germination, shoot multiplication, root induction, callus propagation, and the overall growth of <i>Aquilaria malaccensis</i>. In Murashige and Skoog half-strength medium, Kinetin (KIN) (0.1–0.3&#xa0;mg/L) with Naphthalene Acetic Acid (NAA) (0.01–0.03&#xa0;mg/L) promoted higher germination rates of 28% than 6-Benzylaminopurine (BAP) (1.0&#xa0;mg/L) with NAA (0.01&#xa0;mg/L) of 12%. Shoot buds derived from germinated seeds were employed as explants for multiplication. Our results showed that moderate concentrations (0.5-2.0&#xa0;mg/L) of BAP or KIN significantly promoted shoot propagation, where maximum shooting found at 0.5&#xa0;mg/L BAP alone. Our study also found that combining 2,4-dichlorophenoxy-acetic acid (2,4-D) with KIN or BAP facilitated early-stage green compact callus formation from leaf explants of <i>Aquilaria malaccensis</i>, while combinations of NAA, Indole-3-Acetic Acid (IAA) promoted root induction. In our study, we employed several machine learning algorithms to compare, predict and refine the plant growth regulators’ effect optimization for growth metrics including leaf number, shoot number and shoot length in this species for the first time. XGBoost consistently performed better in predicting shoot number and shoot length, followed by Random Forest and Support Vector Regression. The present work offers a valuable perspective on optimal application of plant growth regulators and predictive models for efficient propagation of <i>Aquilaria malaccensis</i>.</p> Graphical abstract <p></p>

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In vitro micropropagation of the critically endangered Aquilaria malaccensis Lam. and comparing the effect of PGRs’ through machine learning models

  • 期刊论文

  • 发表日期：

    2025年6月19日

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  • Prasanna Sarmah,
  • Twinkle Borah,
  • Kalpataru Dutta Mudoi,
  • Jitendra Singh Verma,
  • Dipanwita Banik

摘要

Aquilaria malaccensis, or agarwood is a critically endangered species, known for its high economic and medicinal values. Our study focuses on in vitro micropropagation of this elite species for mass propagation and comparing the growth matrices through machine learning models. We found the effect of several growth hormones for seed germination, shoot multiplication, root induction, callus propagation, and the overall growth of Aquilaria malaccensis. In Murashige and Skoog half-strength medium, Kinetin (KIN) (0.1–0.3 mg/L) with Naphthalene Acetic Acid (NAA) (0.01–0.03 mg/L) promoted higher germination rates of 28% than 6-Benzylaminopurine (BAP) (1.0 mg/L) with NAA (0.01 mg/L) of 12%. Shoot buds derived from germinated seeds were employed as explants for multiplication. Our results showed that moderate concentrations (0.5-2.0 mg/L) of BAP or KIN significantly promoted shoot propagation, where maximum shooting found at 0.5 mg/L BAP alone. Our study also found that combining 2,4-dichlorophenoxy-acetic acid (2,4-D) with KIN or BAP facilitated early-stage green compact callus formation from leaf explants of Aquilaria malaccensis, while combinations of NAA, Indole-3-Acetic Acid (IAA) promoted root induction. In our study, we employed several machine learning algorithms to compare, predict and refine the plant growth regulators’ effect optimization for growth metrics including leaf number, shoot number and shoot length in this species for the first time. XGBoost consistently performed better in predicting shoot number and shoot length, followed by Random Forest and Support Vector Regression. The present work offers a valuable perspective on optimal application of plant growth regulators and predictive models for efficient propagation of Aquilaria malaccensis.

Graphical abstract