From weed management to bioenergy production: An integrated BMP –kinetic– MCDM framework for evaluating terrestrial weeds

Abstract Weeds are abundant lignocellulosic biomasses that represent a largely underutilized resource for renewable energy production. This study evaluated the biomethane production potential of five terrestrial weed species— Amaranthus retroflexus , Medicago sativa , Lactuca serriola , Chenopodium album , and Onopordum acanthium —using an integrated framework combining biochemical methane potential (BMP) assays, kinetic modeling, and multi‐criteria decision‐making (MCDM) techniques. Batch anaerobic digestion experiments were conducted under mesophilic conditions (37 ± 1°C), and methane production performance was assessed through cumulative methane yield, specific methane yield, methane concentration, and hydrolysis kinetics. First‐order kinetic modeling provided excellent agreement with experimental data ( R 2 = 0.9496–0.9896), with hydrolysis rate constants ranging from 0.0305 to 0.0539 d −1 . Among the investigated substrates, C. album achieved the highest cumulative methane production (9.32 L CH 4 ) and specific methane yield (95.83 mL CH 4 g −1 OM), whereas L. serriola exhibited the lowest specific methane yield (63.50 mL CH 4 g −1 OM). To support substrate prioritization, experimental and kinetic indicators were integrated using AHP, TOPSIS, VIKOR, and SMAA approaches. The MCDM analyses consistently ranked C. album as the most promising substrate due to its balanced performance in methane yield, hydrolysis kinetics, and process stability. The results demonstrate that anaerobic digestion performance of terrestrial weeds cannot be reliably assessed using a single parameter and highlight the value of integrating experimental and decision‐support methodologies. The proposed framework provides a practical tool for evidence‐based substrate selection and sustainable weed valorization within circular bioeconomy‐oriented biogas systems.