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In present study, single and consecutive applications of xylanase and lignin peroxidase were performed in an XOQP TCF sequence to bleach pine and eucalypts kraft pulp. The consecutive use of Geobacillus sp. strain 71 xylanase and Rhodococcus jostii RHA1 lignin peroxidase was more effective than the single uses. XyzGeo71 treatment (X) indicates a 9.76% and 28.52% reduction in kappa number for pine and eucalypts kraft pulps, respectively. LiPRHA1 treatment (X) showed a 7.88% and 20.9% reduction a in kappa number for pine and eucalypts kraft pulps, respectively. The consecutive treatment of XyzGeo71 and LiPRHA1 (X), however, indicated a 13.67% and 37.2% reduction in kappa number for pine and eucalypts kraft pulps, respectively. The results showed that delignification with the consecutive xylanase and lignin peroxidase treatment was very significant.

The purpose of this study was to develop artificial neural network (ANN) models for predicting the effects of wood species, sodium perborate tetrahydrate (SPBTH) ratio, time, and beating degree on tensile index and brightness in bleaching pulp. Unbleached kraft-AQ bamboo and poplar pulps were exposed to first stage oxygen delignification for bleaching under 0,5 MPa, 3% NaOH and 12% consistency conditions. SPBTH bleaching was then carried out as the final stage. SPBTH bleached pulp was next beaten using two different degrees (55 SR° and 65 SR°). Tensile index and brightness data for training, validation and testing of the models were elicited from these experimental investigations. The models were established using the resulting data. The lowest R2 value was 0,98 among training, testing and validation data sets in the prediction of both tensile index and brightness. The networks therefore explain at least 98% of the experimental data for all data sets. The results indicate that ANN is a useful and effective tool for predicting tensile index and brightness. This study thus describes a novel and alternative approach to predicting tensile index and brightness in bleaching pulp compared to the literature.