| dc.description.abstract | Total soluble solids (TSS) and fruit fresh weight are two indicatcrs to show the quality of tomato fruits. To gain high values of TSS and fruit fresh EC it is important to consider the concentration of nutrient solution, which is commonly represented by Electrical Conductivity (EC) value. Generally, the increasing of EC value not or~lyin creases the number of TSS. but also decreases fiuit fresh weight. Therefore. it is important to optimix the EC value fbr both indicators of quality of tomato fruits. The objective of this research is to optimize the EC value of nutrient solution on each generative stage using Artiticial Neural Net\vork (ANN) and Genetic Algorithms (GA). ANN was used to identi@ the relationship between different EC value treatments with TSS value and h i t fresh wei&t. GA was applied to determine the optimal EC value in generative growth. 11-hich is divided into three stags. Results showed that the optimal EC values in the flowering stage. the fiuitin? stage and the harvesting stage wen: 1 .d mSlcm 10.2 mS/cm and 9.7 mSIcm. rcspcctively. Keywords: artificial neural network;, generic algorithm, Hydropnics: tomato fruit quality. | id |
