The evacuation of highly colored effluents in the ecosystem by textile industries generates extreme depredation to the environment and all living creatures. Sorption is preferred because of the wideness of biomass, and cost-efficient, minimized sludge in proportion to conventional treatment methods. A factorial experimental design and ANOVA techniques were utilized to examine the sorption of reactive Pr Red Hegxl dye by Daphne seed–based sorbents, and to optimize the operating conditions. The effects of main variables and their interaction effects on dye removal efficiency (%) were determined; pH was designated as significant at 95% confidence level for all types of sorbents. The maximum removal efficiencies (%) of Daphne seed and char were obtained as 70.8% and 83.2% when pH = 2, sorbent dosage = 0.4 g/50 mL, initial concentration = 50 mg/L, and temperature = 40 °C, respectively. 90.2% and 85.4% removal efficiencies were also attained for KOH- and K₂CO₃-activated carbons, respectively. Besides, artificial neural network models based on several back-propagation training algorithms and transfer functions were used to predict removal efficiency (%). The findings demonstrated that the proposed models had reasonable capabilities of predicting the removal efficiency (%). Daphne seed and carbonaceous products could be effectively used for the dye removal from aqueous solutions as affordable and abundant sorbent materials.

纺织工业将生态系统中颜色鲜艳的废水疏散到环境和所有生物中。吸附是优选的，因为与常规处理方法成比例的是，生物质的范围广，成本效益高，污泥最少。利用析因实验设计和ANOVA技术检查了达芙妮种子基吸附剂对反应性Pr Red Hegxl染料的吸附，并优化了操作条件。确定了主要变量的影响及其相互作用对染料去除率的影响（％）；对于所有类型的吸附剂，在95％的置信度下，pH均被指定为显着。达芙妮的最大去除效率（％）当pH = 2时，种子和炭的含量分别为70.8％和83.2％，吸附剂量= 0.4 g / 50 mL，初始浓度= 50 mg / L，温度= 40°C。对于KOH和K ₂ CO ₃活化的碳，去除效率也分别达到了90.2％和85.4％。此外，使用基于几种反向传播训练算法和传递函数的人工神经网络模型来预测去除效率（％）。研究结果表明，所提出的模型具有预测去除效率（％）的合理能力。达芙妮种子和碳质产品可以作为负担得起的丰富吸附材料有效地用于从水溶液中去除染料。