Article | . 2018 Vol. 36, Issue. 3
Estimation of Lettuce Growth Characteristics Under Different LED Light Intensities in a Closed-type Plant Factory



Department of Biosystems Engineering,Chungbuk National University1
Major in Bio-Industry Mechanical Engineering,Kongju National University2
Laboratory of Agricultural and Food Process Engineering, Hokkaido University3




2018.. 350:361


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The objective of this research was to develop a model to measure the external quality traits using Multi-Spectral Image Sensor (MSIS) in lettuce. In addition, this study was conducted to examine the effect of different intensities of LED mixed light on the growth of lettuce in a closed-type plant factory. The prediction models of lettuce growth data (shoot fresh weight, shoot dry weight, and leaf area) were developed using the correlation between growth data and the number of pixels on an acquired image. Also, SPAD value prediction models were developed using the correlation between the reflectance of a lettuce leaf in an acquired multi-spectral image and the measured SPAD value of the lettuce leaf. The characteristics of lettuce growth according to the light intensity in a closed-type plant factory was conducted under light intensities of 100, 150, and 200 µmol· m-2·s-1. At 200 µmol·m-2·s-1 light intensity, the shoot fresh weight increased about 27.37-73.93% when compared to 100 and 150 µmol·m-2·s-1 on 20 days after sowing. The shoot dry weight showed a similar tendency. Lettuce leaf area increased by 6.89-52.52% on 20 days after sowing when compared to plants grown under 100 and 150 µmol·m-2·s-1. At a light intensity of 200 µmol·m-2·s-1, the SPAD value increased about 3.56-23.76% when compared to plants grown under 100 and 150 µmol·m-2·s-1. Using prediction models based on the number of pixels on a lettuce leaf image, lettuce growth data (shoot fresh weight, shoot dry weight, and leaf area) can be predicted with high precision. In addition, the prediction models for SPAD value were developed using the vegetation indices NDVI (Normalized Difference Vegetation Index), GNDVI (Green NDVI), NIR/Red ratio, NIR/Green ratio, and Red/Green ratio. The SPAD values were predicted with relatively high precision (R2 = 0.834) using the prediction model based on NIR/Red.



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