Sugarcane harvesting requires a significant amount of energy and time to manage dry leaves after the harvesting process. Therefore, the objective of this study was to minimize the energy requirement to process the cane and dry leaves’ harvesting (CDLH) for sugarcane while, at the same time, maximizing sugar production from cane and energy from dry leaves in Sri Lanka. The CDLH was conceptualized using a novel approach to optimize sugarcane harvesting to maximize biomass supply for energy production while reducing supply chain sugar-loss. The CDLH was investigated for manual harvesting capacity, energy consumption, sugar loss, and biomass energy potential. It was observed that CDLH consumed higher energy compared to the present practices of harvesting. However, the energy used for fieldwork was reduced because of the shifting of cane chopping and cleaning from the field to the factory. Low bulk density of the harvested cane of the CDLH system had a higher energy requirement in transportation. Comparatively, CDLH showed higher biomass energy potential and less sugar loss. High energy potential increases the energy potential to consumption ratio compared to the existing method. Therefore, the theoretical evaluation showed that the CDLH system can produce more than 20 kg of sugar and 879 MJ of electricity when processing 1 t of sugarcane.

- This study was conducted treating with Milk of Lime to reach different pH levels (T1- with Initial pH, T2, T3 and T4 with 6.5, 7.5 and 8.5 of pH respectively) to determine the optimum pre-liming pH which could result in best cane juice clarification in Sri Lankan sugar industries. The experiment design used was RCBD with five replicates. ANOVA followed by Duncan’s Multiple Range Test (DNMRT) were used to identify significant mean differences. Regression analyses were carried out to model the variation of turbidity, mud volume and CaO with change of juice pH. Quadratic model (R2 = 99.2 %, p <0.001) best fitted to explain the effect of pH on turbidity of juice. Effect of pH on deposited mud volume and CaO were explained by cubic models with R2 = 99.4 % (p <0.001) and R2 = 93.9 %, (p <0.001) respectively. Among tested treatments, pH 7.5 is selected as the best for turbidity improvement of the clarified juice while pH 8.5 is the second best. However pH 8.5 (370 ml) was able to deposited significantly high mud volume than pH 7.5 (270 ml). Further, the amount of residual Ca2+ ions in the clarified juice at pH 7.5 (2715 ppm) is clearly lower than the amount of Ca2+ ions remaining in the clarified juice at pH 8.5 (2945 ppm). It is expected to obtain high turbidity and higher mud volume with low sugar inversion at optimum pH. Therefore the results suggest optimum pH range lie around pH 7.5 to 8.5. Conducting similar experiment by using mixed juice extracted from sugar factory mills with pH range around 7.0 to 8.4 at 0.2 increments is suggested to validate the optimum pH.

This study was conducted treating with Milk of Lime to reach different pH levels (T1- with Initial pH, T2, T3 and T4 with 6.5, 7.5 and 8.5 of pH respectively) to determine the optimum pre-liming pH which could result in best cane juice clarification in Sri Lankan sugar industries. The experiment design used was RCBD with five replicates. ANOVA followed by Duncan’s Multiple Range Test (DNMRT) were used to identify significant mean differences. Regression analyses were carried out to model the variation of turbidity, mud volume and CaO with change of juice pH. Quadratic model (R 2 = 99.2%, p <0.001) best fitted to explain the effect of pH on turbidity of juice. Effect of pH on deposited mud volume and CaO were explained by cubic models with R 2 = 99.4% (p <0.001) and R 2 = 93.9%, (p <0.001) respectively.Among tested treatments, pH 7.5 is selected as the best for turbidity improvement of the clarified juice while pH 8.5 is the second best. However pH 8.5 (370 ml) was able to deposited significantly high mud volume than pH 7.5 (270 ml). Further, the amount of residual Ca2+ ions in the clarified juice at pH 7.5 (2715 ppm) is clearly lower than the amount of Ca2+ ions remaining in the clarified juice at pH 8.5 (2945 ppm). It is expected to obtain high turbidity and higher mud volume with low sugar inversion at optimum pH. Therefore the results suggest optimum pH range lie around pH 7.5 to 8.5. Conducting similar experiment by using mixed juice extracted from sugar factory mills with pH range around 7.0 to 8.4 at 0.2 increments is suggested to validate the optimum pH.