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Research Article Volume 9 Issue 1
Cooking temperature and time optimization in kraft pulping for apus bamboo (Gigantochloa apus Kurz)
Rambu Noventis Lamba Awang, Vendy Eko Prasetyo, Sigit Sunarta, Ganis Lukmandaru, Djoko Soeprijadi
Received: September 15, 2026 | Published: October 5, 2026
Citation: Awang RNL, Prasetyo VE, Sunarta S, et al. Cooking temperature and time optimization in kraft pulping for apus bamboo (Gigantochloa apus Kurz). Open Access J Sci. 2026;9(1):474-480. DOI: 10.15406/oajs.2026.09.00331
Abstract
Research on pulp production using apus bamboo (Gigantochloa apus Kurz) stem through the kraft process is conducted to address the availability of raw materials for the pulp and paper industry in Indonesia. The purpose of this study is to determine the effect of temperature and cooking time on the properties of apus bamboo pulp and to develop mathematical models and optimize the process based on the applied factors. Process optimization was conducted using response surface methodology through central composite design analysis. The kraft pulping process was performed in a micro-digester with a stem powder-to-cooking solution ratio of 1:4, utilizing 10 g of stem powder, an active alkali concentration of 17%, and a sulfidity level of 25%. The optimized variables were cooking temperature (155, 165, and 175 oC) and cooking time (60, 120, and 180 min). The increase in temperature and cooking time resulted in optimal values for yield, kappa number, hexeneuronic acid content of the pulp, as well as total solids value of the black liquor. Process optimization was achieved at a cooking temperature of 165.71 oC and a cooking time of 143.14 min due to the minimum level of kappa number or lignin dissolved. The calculated optimization conditions resulted a pulp yield of 60.22%, a kappa number of 22.96, a viscosity of 16.05 cP, a hexeneuronic acid content of 21.50 μmol/g, a brightness of 17.07%, a total solids concentration of 16.19 g/L, and a pH value of 11.85.
Keywords: non-wood pulp, sulfate process, black liquor, regression analysis, long fiber
©2026 Awang, et al. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and build upon your work non-commercially.