Development of a System for Predicting and Simulating the Growth of Spinach (Spinacia oleracea)

Abstract

In the production of processing spinach (Spinacia oleracea), prespecified fresh weights of produce must be shipped to a processing factory at prespecified times by contract. However, this is not easy, because the growth of spinach, which is raised outdoors, is subject to meteorological conditions. This paper presents SukuSuku Hourensou as a system for predicting and simulating the growth of processing spinach to assist farmers in planning harvests and shipments. SukuSuku Hourensou predicts and simulates spinach growth under meteorological conditions specified by the user after automatically obtaining necessary meteorological data from the Agro-Meteorological Grid Square Data, which was developed and is managed by the National Agriculture and Food Research Organization, Japan. It can adjust prediction and simulation results by using vegetation cover rates obtained from airborne images taken by drones. To support planning of harvests and shipments, SukuSuku Hourensou can suggest harvest times that smooth shipment fresh weights over a harvest season. In the smoothing, SukuSuku Hourensou moves harvest times of farm fields under the condition that the weight of a predicted yield per unit area is included in a range specified by the user. Here, we outline the growth model implemented in SukuSuku Hourensou, describe the procedure for smoothing predicted yields over a harvest season, and present the usage of SukuSuku Hourensou.