This study aimed to determine the nitrogen content of spinach leaves by using computer imaging technology. The application of Color Co-occurrence Matrix (CCM) texture analysis was used to recognize the pattern of nitrogen content in spinach leaves. The texture analysis consisted of 40 CCM textural features constructed from RGB and grey colors. From the 40 textural features, the best features-subset was selected by using features selection method. Features selection method can increase the accuracy of image analysis using ANN model to predict nitrogen content of spinach leaves. The combination of ANN with Ant Colony Optimization resulted in the most optimal modelling with mean square error validation value of 0.0000083 and the R2 testing-set data = 0.99 by using 10 CCM textural features as the input of ANN. The computer vision method using ANN model which has been developed can be used as non-invasive sensing device to predict nitrogen content of spinach and for guiding farmers in the accurate application of their nitrogen fertilization strategies using low cost computer imaging technology.
Flavonoids Microwave Assisted Extraction Polyphenols Torbangun Leaves Torbangun leaves (Coleus ambonicus, L.) contain polyphenol compounds, flavonoids and antioxidant compounds that can be obtained by extraction methods. However, with the conventional extraction method it has the disadvantage of long extraction time and requires a lot of solvents. Therefore, this study discusses the use of microwave assisted extraction (MAE) method to extract the leaves of Torbangun. This study uses two treatment factors on MAE i.e. power variations (100, 180 and 300 Watts) and extraction time (1, 2 and 3 minutes). This study aims to analyze the effect of MAE on the content of polyphenol compounds and flavonoids in the extraction process of Torbangun leaf. The results showed that the highest total phenol (4196.59 mg GAE/g extract) was found in the treatment of 300 watt of power with extraction time of 3-minutes with IC50 value of 9.89 mg/ml. The highest total flavonoid value was 300 watt of power with 1-minute extraction time which was 4.54 mg QE/g DW.
The purification process of sugarcane juice in a sugar factory mostly uses sulphitation process, separating clear juice from dirty juice using a sedimentation system. Impurities on the processing of sugarcane juice will further cause difficulties, the formation of color, an increase in viscosity, and reducing sugar recovery. Membrane purification technology is offered to overcome these problems. This study aims to determine the effect of chitosan and acetic acid on the performance of chitosan membranes in the clearance of sugarcane juice and to find the best concentration of chitosan and acetic acid for the purification process of sugarcane juice. The filtration process was performed by using the chitosan membrane to process a clear sugarcane juice sample from the pretreatment result, which is assumed as clear juice product from sulphitation process in sugar factory. The results showed that (1) the result of pretreatment had the value from TSS (Total Soluble Solids) of 15.4%; turbidity of 82.33 NTU; and the ICUMSA (International Commission for Uniform Methods of Sugar Analysis) colour of 14970.02 IU. (2) After filtration using membrane, better quality of pretreatment clear sugarcane juice is obtained, characterized by increasing chitosan concentration at each acetic acid level, rejection value of TSS, turbidity, and ICUMSA colour. (3) The best treatment result based on Zeleny multiple attribute method is found in chitosan membrane with concentration of 4%, acetic acid concentration of 1.5% to inject TSS until reaching 12.64%, ICUMSA until reaching 9.89%, and rejection of turbidity until reaching 63.61%. Higher chitosan concentration caused small pore size of the membrane.
Some outstanding features in the use of pervaporation technology are light, low maintenance, low energy consumption, and eco-friendly. The optimization of membrane mechanical properties is vital to determine the strength of the membrane against the force which comes from outside and is unfortunately destructive, one of which is tensile strength. The purpose of this research is to find out the best combination of alginate and chitosan concentration, which produces polyether sulfone-biopolymer based pervaporation membrane with optimal tensile strength. Several membrane compositions have been prepared and varied in a way to obtain optimal membranes. The modeling and optimization method, which was applied by the researcher is the Response Surface Methodology (RSM). In the Central Composite Design (CCD) design, the low level included for both factors is 2% concentration, and the high level is 4% concentration, with a total of 13 experimental designs. The result of the suggested model is a quadratic model. While on the optimization result, the optimum solution result is from a combination of 3.25% alginate and 2.91% chitosan concentration, which yield tensile strength value of 0.24 kgf/cm 2 with a desirability value of 0.84. The validation results are withdrawn from the three test samples resulted in an average tensile strength of 0.25 kgf/cm 2 where this value differed 1.2% from the predicted results. The validation results are considered acceptable because the value is still within the acceptable error threshold or below 5%.
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