GRANDES: An online decision support tool for grafting nurseries

In today's competitive and global market, unceasing improvement of resource efficiency is an obligatory requirement for production facilities in order to survive. In any production facility, especially those concerning bioproducts such as seedling propagation nurseries, an optimized resource and space allocation can lead to lower production costs and polish their competitive edge. To reduce production costs without surrendering quality, we have developed an online GRAfting Nursery DEcision Support (GRANDES) tool (i.e., https://www.grandes.arizona.edu) which provides assistance in terms of design and resource management. GRANDES has a friendly user-interface where inputs such as demand patterns, propagation stages, and machinery can be submitted and a backend in which simulation and optimization models are run based on the given inputs to find efficient solutions within as low as ten hours. At the website, users can set their product (e.g., tomato, watermelon) and grafting mode (i.e., manual, semi-automated, or fully automated). They have the option to completely customize the machinery level of their ideal setup by defining the speed, price, power consumption, needed labor, and success rate for different operations such as seeding, mixing, sorting, and grafting. They also can modify the duration of propagation stages such as germination, pre-sorting growth, or post-graft growth for summer and winter. The users can adjust the utility, labor, and operations related expenditures by setting the electricity rate, salary of skilled and unskilled labor, tray type, size, and price, price of substrate and fertilizer, over seeding rate, and many other features. In addition, the users can adapt the greenhouse, headhouse, and germination chamber expenses by defining construction cost, the utilized glazing material (e.g., polyethylene double layer, corrugated polycarbonate, or glass), operational days per year, and floor utilization rate. In this work, multiple experiments were conducted to demonstrate the capabilities of GRANDES and explain the logic behind it.