Analytical hierarchy process for automated fertigation blending system in reducing nutrient and water losses

Fertigation is one of the agricultural methods of farming techniques which is can produce high productivity crops and efficiency in using resources. This research attempt to design and select the best criteria for an Automated Fertigation Blending System (AFBS) for reducing the eutrophication problem. Eutrophication is caused by the excessive use of nutrients and water runoff into the fresh water. The criteria had been selected based on the customer requirements (CRs) from the survey. The CRs and ECs are the two criteria for the four best design alternatives using the House of Quality (HoQ) selection method. A new methodological framework that integrated the design optional consisting of an Analytical Hierarchy Process (AHP) was developed. The AHP was developed to evaluate the selection criteria in each design developed by using a pairwise-comparison matrix. Seven criteria were implied in selecting the best design, covering ease of installation, compact and portable, safety, low equipment maintenance cost, user friendly, durability, and reduce nutrient and water runoff. The best AFBS is Design 4 with the highest performance and higher score 73.7% because of its safety, durability, user friendly, compact and portable, and reduces nutrient excess and water runoff. Conclusively, this proposed framework provides the decision to select criteria and ECs for future AFBS without an extensive experiment by saving time, and money, and reducing the negative impact on sustainabilit

Optimal fertigation for automated fertilizer blending system by minimising fertilizer cost and utility consumption

In agricultural industries, efficient nutrient and water management are crucial to saving costs maximising crop yields, and increasing profit. A fertigation system is used to irrigate sufficient nutrients and water for the growing needs of the crops. However, the water and nutrient volume needed for each crop remains unknown due to various crop phases and the dynamics of nutritional demand. Therefore, this research work presents the optimisation modeling for an Automated Fertilizer Blending System (AFBS) to minimise the operational cost of nutrients, water, and electricity. The proposed optimisation model considers for the AFBS: (i) operational status of irrigation pump and stock tanks; (ii) stocks level for nutrient and water at each stock tank; (iii) inventory level for nutrient solutions in an AFBS tank; and (iv) nutrient and water level of the plants. The mathematical model is developed as mixed-integer linear programming (MILP). The optimisation problem is modeled using GAMS v-38.2.1 and solved by CPLEX 12 with a zero-optimality gap. In conclusion, cost comparison analysis between electricity, fertilizer, and supplied water represents the optimal cost percentage in engaging with nutrient losses minimised by 30%, water runoff, and electricity costs for optimal condition-based fertigation systems