식량작물의 스마트농업 적용을 위한 수수 생육 지표 개발

Abstract

Smart farm could be a key solution to improving farm productivity and aging problem in rural areas. However, smart farm research in the field of facility horticulture is being actively carried out, while the field of field food crops is still very insufficient. And, image information collection and analysis technology will be the most important factor in smart farm for automatic growth measurement and detection of disease and pest. In addition, in order to know exactly the growth status of crops, it is very useful to use key growth indicators that can accurately grasp the growth information of a crop plant. As such, this study was carried out to select key growth indicators that can accurately identify the growth status of sorghum, and to collect and utilize image-based information of the growth indicators to determine the accurate growth of sorghum. We installed fertilizer(Control, Heavy, No) and soil moisture(Control, Excess, Drought) treatment plots to select key growth indicators showing a large growth difference from control plot among the treatments, and investigated the following 11 growth indicators; Culm length, Plant height, Stem diameter, Leaf age, Internode length 1~2, 2~3, 3~4, Ear length, Ear width, Upper leaf color, Lower leaf color; a total of 13 times a week after transplanting. As a result of the experiment, we selected meaningful key growth indicators through ANOVA variance analysis and DMRT as follows; (Fertilizer section) Culm length, Plant length, Stem diameter and Upper leaf color at no fertilizer plot during the vegetation stage; Plant length during the reproductive stage. (Irrigation section) Upper leaf color at excess moisture plot during the vegetation stage; Stem diameter, Upper leaf color and Lower leaf color at excess moisture plot; Upper leaf color and Lower leaf color at drought plot during the reproductive stage. As the experimental results, although not sufficient, we confirmed the possibility of ‘Culm length, Plant length, Stem diameter and Leaf color’ as the growth indicators of sorghum for the development of image-based digital agriculture. Follow-up experiments should be continued.