Metal-organic frameworks (MOF)-mediated improvement of cotton germination and early seedling resilience under salinity stress through explainable machine learning and non-destructive terahertz time-domain spectroscopy (THz-TDS)

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Elsevier

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info:eu-repo/semantics/openAccess

Özet

Cobalt-based metal-organic framework (Co-MOF) and nickel-cobalt bimetallic MOF (Ni-Co-MOF) systems were evaluated for their effects on cotton germination under saline conditions induced through NaCl seed priming treatments. Temporal germination dynamics, germination-related indices, explainable machine learning (ML), and terahertz time domain spectroscopy (THz-TDS) were integrated to characterize treatment-associated germination and THz responses. The results demonstrated clear treatment-dependent differences in germination initiation, progression, synchronization, and cumulative germination behavior. Co-MOF at 50 mg/L produced the strongest early germination responses, whereas Ni-Co-MOF at 50 mg/L achieved the highest cumulative germination (91.0%). A 4 h priming duration produced the most coordinated germination pattern under saline conditions. The random forest-based multi-output regression framework showed variable predictive performance among germination indices, with an average R2 of 0.372 and a maximum R2 of 0.507 for mean germination rate. Feature importance analysis further revealed that intermediate germination stages contributed most strongly to predictive performance. THz-TDS analysis revealed clear treatment-associated differences in time-domain attenuation and frequency-dependent absorption profiles within cotton leaf tissues. Stronger attenuation and absorption responses observed under specific MOF treatments indicated treatment-associated variation in hydration-associated dielectric behavior. Compared with 100 mM NaCl reference treatment without MOF supplementation,selected MOF treatments exhibited higher cumulative germination and distinct THz responses. The integration of MOF treatments, THz-TDS, and explainable ML provided a combined analytical approach for characterizing early germination patterns and leaf THz responses under controlled saline conditions. However, However, there is a need of further biochemical, physiological, ion-homeostasis, and plant growth assessments are needed to clarify the underlying mechanism.

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Anahtar Kelimeler

Cotton, Explainable machine learning, Metal-organic framework, Multi-output regression, Terahertz time-domain spectroscopy

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Industrial Crops and Products

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251

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Altaf, M. T., Elmabruk, K., Soomro, S. N., Soomro, S. R., Aksoy, T., Pürlü, K. M., Ali, S. A., Biçer, E., Horoz, S., Liaqat, W., Kökten, K., & Aasim, M. (2026). Metal-organic frameworks (MOF)-mediated improvement of cotton germination and early seedling resilience under salinity stress through explainable machine learning and non-destructive terahertz time-domain spectroscopy (THz-TDS). Industrial Crops and Products, 251, 124180. https://doi.org/10.1016/j.indcrop.2026.124180

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