Explain the juice quality analysis of sugarcane and oil extraction of medicinal crops
Answers
Answer:
Explanation:
The analysis of the quality indexes of sugarcane juice plays a vital role in the process of refining sugarcane, breeding, cultivation, and production management. The paper analyzes the dynamic laws of five quality indexes (i.e., brix, purity, polarization, sucrose content, and reducing sugar) combined with graphs over time along the course of crushing season (December–March) in Guangxi province of China. During this time, the sugarcane is in the mature stage and hypermature stage. At the beginning of December to early January, during which sugarcane is in the later stage of maturity, the nutrients are accumulating, causing brix, purity, polarization, and sucrose content increase. At the beginning of January to mid-February, due to low temperature and insufficient light, it is not conducive to accumulation of nutrients. However, there is the so-called “sugar back” phenomenon and reducing sugar rises gradually in March, leading to deterioration of the quality of sugarcane juice. The results show that timely harvest of sugarcane is beneficial for sugar making. The regression analysis results show that some of quality indexes have strong correlation between them and the regression models are extremely significant, indicating that the prediction results are ideal.1. Introduction
Sugarcane is an ancient agroindustrial crop, which contributes to more than ninety percent of the sugar production in China. Recently, this industry produces about 13 million tons of sugar and many other products such as pulp, paper, alcohol, yeast, xylitol, chemicals, drinking cane juice, biomanure, feed, and electricity (Li and Yang [1]). It is very important to analyze the quality of sugarcane juice in the role of refining sugarcane, breeding, cultivation, and production management. The mixed juice characteristics, along the course of crushing season, are influenced by variations in cane variety, changes in the agroclimatic conditions, and fluctuations in the process parameters (Ghosh and Balakrishnan [2]). Kumar and Chand [3] applied the response surface method and experimental design to optimize independent variables for clarification of sugarcane juice. In this study, regression model is established for the quality index of multi-input and single output. Kouzi [4] studied the effects of different cane conditions in the field on dextran level in cane juice (e.g., burning, chopping, delay between cutting and milling, and type of ratoon) and factors affecting levels of dextran during processing. The most important five criteria are, namely, polarization (Pol), apparent purity, pH, viscosity, and commercial cane sugar (CCS) of the cane juice; besides dextran content of juice has been used to measure the cane deterioration. Lingle et al. [5] provided evidence that sugarcane juice quality in late-harvested sugarcane has been increased by six cycles of recurrent selection for sucrose but that a limit may have been reached for further improvement. Wang et al. [6] analyzed the change rules of the cane juice purity, the polarization, and the reduction sugar and built the simple regression model between sucrose content (Suc) and the other five quality indexes, namely, reduction sugar (Rs), polarization (Pol), brix (Bx), apparent purity (Ap), and gravity purity (Gp). Nawi et al. [7] applied the Vis/SWNIR spectroscopy combined with PLS models to predict sugarcane quality (brix and polarization) from both clear and raw sugarcane juices. Sheikh [8] evaluated juice quality parameters ((percentage of cane), )) and the level of colouring materials in crushed cane (green or burned) and evaluated the effect of low doses of separan on juice quality and colour. Wang et al. [9] analyzed the changing law of the sugarcane juice purity by using seven main sugarcane varieties in the Zhanjiang area. The results show that when the ratio of the apparent purity and gravity purity is very close to 1, the sugar content almost reaches its apogee. Golabi et al. [10] evaluated the effect of irrigation water electrical conductivity on three varieties of sugarcane juice quality. Nawi et al. [11] identified the optimum sample form for predicting sugarcane quality using a low-cost and portable spectrometer. Mat et al. [12] explore the potential of spectroscopic method to predict sugarcane quality parameters by directly scanning the internode samples. Nawi et al. ([7, 13]) used visible and shortwave near infrared (Vis/SWNIR) spectroscopy to predict soluble solids content and sucrose content from sugarcane juice samples. The overall results indicated that Vis/SWNIR spectroscopy combined with PLS models could be applied to predict sugar content in both clear and raw sugarcane juices.