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Crop production is increasingly threatened by unusual weather, water shortages, and insufficient available land. In order to feed the world, protect the environment, improve health, and achieve economic growth, a new form of agricultural cultivation is required; indoor vertical farming, namely a plant factory system with artificial lighting, is expected to provide efficient production of food crops (Kozai et al., 2015). However, production in plant factories incurs several costs. Kozai (2007) and Ohyama (2015) previously studied the production costs; as the size of the plant factory increases, fixed costs increase, for example, large-scale air conditioning systems, automatic control systems for nutrient solutions (Son and Takakura, 1987; Ko et al., 2013) and high-throughput seedling diagnosis system (Moriyuki and Fukuda, 2016). Moreover, individual differences in plant growth (growth distribution) are also directly linked to profits. Therefore, a profit model is required to consider fixed costs, running costs, and growth distribution information in plant factories. In the profit model for plant factory, we should focus on shipping type and growth distribution at each growth stage (nursing stage and cultivating stage). The shipping type usually depends on a shipping threshold based on fresh weight of harvested plant. Plants over this threshold are able to be sold at a standard (good) price, one by one (yen plant ). On the other hand, plants less than this threshold are sold at a lower price, by unit of fresh weight (yen g ). Therefore, profit depends on the distribution of plant size at harvest, particularly on the ratio of standard plants that are over the shipping threshold. Moreover, because profit often fluctuates with growth fluctuations, the profit model also requires detailed information of growth dynamics (distribution of plant size and its time variation). However, growth dynamics in plant factory and their influence on profit as a function of shipping threshold have not been widely studied. Variables in the profit model included number of cultivation days, shipping threshold, cost-related parameters such as fixed costs and running costs, and growth-related parameters. Furthermore, parameters in the profit model depend on the plant factory. Therefore, total optimization for all parameters requires time and expense (Shuku and Nishimura, 2015); thus, it is also important to analyze the sensitivity of each parameter for profit and to identify the priority of these parameters. In this study, we investigated the growth dynamics of lettuce populations cultivated in a large scale commercial plant factory and established a profit model with various shipping types. In addition, the sensitivity analysis of this profit model was performed for each parameter, and significant parameters for profit were clarified.

Profit Models Based on the Growth Dynamics of Lettuce Populations in a Plant Factory