<![CDATA[Biomass-fired boilers are widely used in agro-industrial steam generation, yet their efficiency remains sensitive to fuel quality, boiler configuration, and the calorific value basis. This study developed a predictive thermal-efficiency assessment of four industrial biomass boilers, namely ZUG, Djaja Teknik, Vickers, and Isgec, by integrating biomass fuel characterisation, field operating data, and Hugot’s direct-efficiency model. Its novelty lies in linking calorific-value changes in torrefied tropical fruit residues and distilled water-washed wood waste to boiler-specific operating parameters, rather than treating fuel upgrading as laboratory fuel improvement alone. Gross Calorific Value (GCV) was used as the primary basis for modelling, while NCV efficiency was calculated only when supporting fuel data were available. Baseline results showed GCV-based efficiencies of 77.12% for ZUG and 80.63-81.05% for Djaja Teknik, whereas Vickers and Isgec corresponded more closely to NCV-based efficiencies of 72.24% and 68.71–70.34%, respectively. Distilled water washing changed wood-waste GCV from 3,891-4,812 to 4,343-5,323 kcal/kg, with champaca increasing by approximately 21.6%. Torrefaction yielded higher GCV values of 6,519.28, 6,661.58, and 6,875.60 kcal/kg for coffee husk, cocoa shell, and mangosteen shell, respectively. Under fixed-flow Hugot assumptions, higher GCV increased fuel-energy input and could reduce numerical ηGCV, indicating model sensitivity rather than poorer fuel performance. The findings support SDGs 7, 12, and 13 through renewable heat assessment, biomass residue valorisation, and low-carbon energy pathways, while remaining limited to predictive boiler thermal efficiency.]]>
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