A Preliminary Open-field Study Investigating Commercial Smart Farming of a Potential Alternative Crop, Aster koraiensis

• Published in: Horticulture journal Vol. 89; no. 3; pp. 244 - 250
• Main Authors: Won, Hyo Jun, Lee, Jae Hoon, Ahn, Hong Ryul, Jung, Sang Hoon, Hyeong Jung, Je
• Format: Journal Article
• Language: English
• Published: Tokyo The Japanese Society for Horticultural Science 01.01.2020; Japan Science and Technology Agency
• Subjects: Agricultural practices; alternative crop; Alternative crops; Aster koraiensis; Crop yield; Cultivation; cultivation practices; Digital agriculture; Dry matter; Fertilizers; Food production; Functional foods & nutraceuticals; Indigenous plants; Land use; NDVI; Normalized difference vegetative index; Plant growth; Planting; Planting density; Precision farming; Regression models; Remote sensing; Remote sensors; Soil conditions; Soil density; Soil fertility; Soil investigations; Soils; Transplantation
• ISSN: 2189-0102; 2189-0110
• DOI: 10.2503/hortj.UTD-093

Aster koraiensis, a plant indigenous to Korea, has recently attracted a great deal of attention as a potential functional food and pharmaceutical product due to its preventive and therapeutic efficacy against various diseases. Despite increasing demand, supply of A. koraiensis is limited to wild populations and small-scale wild plant growers. In an attempt to establish cultivation practices in open-field production platforms, this study investigated the effects of soil mulching, planting density, and fertilizer treatment on the above-ground dry matter yield of A. koraiensis for two years after transplantation. The maximum dry matter yield was obtained at 1,935 kg DW·ha−1 and 3,803 kg DW·ha−1 in the first and second years, respectively, under soil mulching and 15 × 15 cm planting density conditions. Soil mulching during the first year after transplanting significantly promoted plant growth, and increased yield, indicating its beneficial effects on the establishment and early growth of A. koraiensis plants. Fertilizer treatment increased yields up to 3.7-fold in the second year after transplantation. In addition, this study employed remote sensing technologies using a drone equipped with a multispectral sensor to evaluate the normalized difference vegetation index (NDVI) of experimental plots across different plant growth stages. The results revealed that NDVI values at 60 days after shoot emergence in the second year after transplantation produced the highest correlation with dry matter yield in a simple exponential regression model. Remote sensing technologies and the proposed regression model could be applied to optimize cultivation practices and enable precision agriculture for A. koraiensis crops.