【24h】

Optimization and drying kinetics of the convective drying of microalgal biomat (lab-lab)

机译:微藻生物垫对流干燥的优化及干燥动力学(实验室-实验室)

获取原文

摘要

Lab-lab, a periphyton that is composed of several microorganisms, is a potential commercial fish feed in the aquaculture industry due to its high protein content. However, the bottleneck in utilizing lab-lab as a fish feed is its cultivation process; it can only be mass produced during the dry season when the solar irradiation is high. To induce the availability of lab-lab all throughout the year, its moisture can be removed through drying, which will reduce its spoilage and will improve its product life. To effectively dry lab-lab with reduced operating costs and improved protein yield, its drying characteristics are investigated. In this study, lab-lab samples are dried in a convection oven dryer. A 3-factor, 2- level full-factorial design of experiment is used wherein the factors considered are drying temperature (60-100 °C) and the sample thickness (2-4 mm), and the responses that are observed are the drying time, drying rate and energy consumption. Mass data is instantaneously monitored using an Arduino-controlled load cell that is placed inside the convection oven dryer. A modified Aghbashlo model was used to represent the convective drying curve of lab-lab with low RMSE values (< 1.3196%) and high R2 values (>0.9988) at a significance level of 0.05. The effects of the factors on the drying time (p<.0152), drying rate (p<0.0174), and energy consumption (p<0.0393) are investigated, consisting only of one- degree effects with no interactions. Using the desirability function, the optimal temperature and thickness, where the drying time and drying rate are maximized while the energy consumption is minimized, is at 60°C and 3.45 mm with a desirability of 56.76%.
机译:Lab-lab是一种由几种微生物组成的附生植物,由于其蛋白质含量高,在水产养殖业中是一种潜在的商业鱼饲料。然而,利用实验室作为鱼类饲料的瓶颈在于其养殖过程。它只能在太阳辐射较高的干旱季节大量生产。为了使实验室实验室全年可用,可以通过干燥除去水分,这将减少其变质并延长产品寿命。为了有效地干燥实验室实验室,以降低操作成本和提高蛋白质产量,研究了其干燥特性。在这项研究中,实验室样品在对流烘箱干燥机中干燥。使用三因素,两水平全因素实验设计,其中考虑的因素是干燥温度(60-100°C)和样品厚度(2-4 mm),观察到的响应是干燥时间,干燥速度和能耗。使用置于对流烘箱干燥器内部的Arduino控制的称重传感器即时监视海量数据。修改后的Aghbashlo模型用于表示具有显着性水平0.05的RMSE值低(<1.3196%)和R2值高(> 0.9988)的实验室的对流干燥曲线。研究了这些因素对干燥时间(p <.0152),干燥速率(p <0.0174)和能耗(p <0.0393)的影响,这些影响仅由一度效应组成,没有相互作用。使用期望功能,在60°C和3.45 mm处,干燥时间和干燥速率最大化而能耗最小的最佳温度和厚度为56.76%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号