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Application of Plant Phenomics Platform for Automatic Phenotyping of the Vegetable Crops
(A) Auto-phenotyping system, (C, E, G) 3D color images and (B, D, F) point cloud images of (B, C) rapeseed, (D, E) melon, and (F, G) soybean.
(A) Auto-phenotyping system, (C, E, G) 3D color images and (B, D, F) point cloud images of (B, C) rapeseed, (D, E) melon, and (F, G) soybean.

Author:Ssu-Yu Lin, Yuan-Kai Tu, Shuen-Chi You, Yue-Ying Fu, and Da-Gin Lin*

Abstract:

    With the vigorous development of genomic sequencing techniques, crop breeding has entered an era of high-throughput and big data in genomic analysis. However, the relative phenotyping techniques did not keep up with the development of genotyping techniques and have become a bottleneck for breeding development. The development of a high-throughput plant auto-phenotyping platform is becoming an important issue in crop breeding. For this purpose, a plant auto-phenotyping platform has been established deploying a 3-dimensional laser scanner. First, the auto-phenotyping parameters of soybean, rapeseed, and melons were validated by comparing them with the analysis of traditional manual phenotyping. The results indicate that the parameters of plant high, leaf area, and biomass all are highly correlated between the auto-phenotyping platform and the traditional one (r > 0.85***). Then, this platform has been applied to the phenotyping of the cultivation of the other 2 vegetables. The first case was conducted on the effects of different soil microbial agents for the growth of cucumber, and the second one was conducted on the effects of different nitrogen content formula for the growth of tomato. The results showed that 4 commercially available soil microbial products could improve the growth of cucumber and the formula with different nitrogen contents did significantly affect tomato growth. These results suggest that the established auto-phenotyping platform can save labor and collect continuously phenotyping data. It is applicable and useful for the users to analyze the diversities among plant growth stages as well as treatments. This platform has the advantages of fast, high-throughput, objective and non-invasive for phenotyping analysis, and is helpful for the development of crop breeding.

Key words:Plant phenomics platform, High-throughput phenotyping data, 3-dimensional laser scanner, Crop

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