High-throughput volumetric reconstruction for 3D wheat plant architecture studies  

作　　者：Wei Fang Hui Feng Wanneng Yang Lingfeng Duan Guoxing Chen Lizhong Xiong Qian Liu 

机构地区：[1]Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology 1037 Luoyu Rd.Wuhan 430074,P.R.China [2]National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research Huazhong Agricultural University Wuhan 430070,P.R.China [3]College of Engineering Huazhong Agricultural University Wuhan 430070,P.R.China [4]MOA Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River Huazhong Agricultural University Wuhan 430070,P.R.China

出　　处：《Journal of Innovative Optical Health Sciences》2016年第5期101-113,共13页创新光学健康科学杂志（英文）

基　　金：supported by grants from the National Program on High Technology Development(2013AA102403);the Program for New Century Excellent Talents in University(NCET-10-0386);the National Natural Science Foundation of China(30921091,31200274);the Fundamental Research Funds for the Central Universities(2013PY034).

摘　　要：For many tller crops,the plant archit ecture(PA),including the plant fresh weight,plant height,number of tllrs,tller angle and stem diameter,sigificantly afects the grain yield.In this study,we propose a method based on volumetric reconstruction for high-throughput three-dimensional(3D)wheat PA studies.The proposed methodology involves plant volumetric reconst ruction from multiple images,plant model processing and phenotypic parameter estimation and analysis.This study was performed on 80 Triticum aestium plants,and the results were analyzed.Comparing the automated measurements with manual measurements,the mean absolute per-centage error(MAPE)in the plant height and the plant fresh weight was 2.71%(1.08cm with an average plant height of 40.07cm)and 10.06%(1.41g with an average plant fresh weight of 14.06 g),respectively.The root mean square error(RMSE)was 137 cm and 1.79g for the plant height and plant fresh weight,respectively.The correlation cofficients were 0.95 and 0.96 for the plant height and plant fresh weight,respectively.Additionally,the proposed methodology,in-cluding plant reconstruction,model processing and trait ext raction,required only approximately 20s on average per plant using parallel computing on a graphics processing unit(GPU),dem-onstrating that the methodology would be valuable for a high-throughput phenotyping platform.

关 键 词：THREE-DIMENSIONAL volumetric reconstruction plant architecture graphics processing unit HIGH-THROUGHPUT 

分 类 号：S51[农业科学—作物学]