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With the development of digital agriculture, 3D reconstruction technology has been widely used to analyse crop phenotypes. To date, most research on 3D reconstruction of field crops has been limited to analysis of population characteristics. Therefore, in this study, we propose a method based on low-cost 3D reconstruction technology to analyse the phenotype development during the whole growth period. Based on the phenotypic parameters extracted from the 3D reconstruction model, we identified the “phenotypic fingerprint” of the relevant phenotypes throughout the whole growth period of soybean plants and completed analysis of the plant growth patterns using a logistic growth model. The phenotypic fingerprint showed that, before the R3 period, the growth of the five varieties was similar. After the R5 period, the differences among the five cultivars gradually increased. This result indicates that the phenotypic fingerprint can accurately reveal the patterns of phenotypic changes. The logistic growth model of soybean plants revealed the time points of maximum growth rate of the five soybean varieties, and this information can provide a basis for developing guidelines for water and fertiliser application to crops. These findings will provide effective guidance for breeding and field management of soybean and other crops.

Analysing the phenotype development of soybean plants using low-cost 3D reconstruction