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

Wei Fang,Lizhong Xiong,Lingfeng Duan,Guoxing Chen,Wanneng Yang,Qian Liu,Hui Feng

doi:10.1142/s1793545816500371

Abstract

For many tiller crops, the plant architecture (PA), including the plant fresh weight, plant height, number of tillers, tiller angle and stem diameter, significantly affects 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 reconstruction from multiple images, plant model processing and phenotypic parameter estimation and analysis. This study was performed on 80 Triticum aestivum plants, and the results were analyzed. Comparing the automated measurements with manual measurements, the mean absolute percentage error (MAPE) in the plant height and the plant fresh weight was 2.71% (1.08[Formula: see text]cm with an average plant height of 40.07[Formula: see text]cm) and 10.06% (1.41[Formula: see text]g with an average plant fresh weight of 14.06[Formula: see text]g), respectively. The root mean square error (RMSE) was 1.37[Formula: see text]cm and 1.79[Formula: see text]g for the plant height and plant fresh weight, respectively. The correlation coefficients were 0.95 and 0.96 for the plant height and plant fresh weight, respectively. Additionally, the proposed methodology, including plant reconstruction, model processing and trait extraction, required only approximately 20[Formula: see text]s on average per plant using parallel computing on a graphics processing unit (GPU), demonstrating that the methodology would be valuable for a high-throughput phenotyping platform.

Highlights

IntroductionIt has been estimated that we will need to double the quantity of food produced to meet the demands of a rapidly growing population.[1] Increasing crop yields has become a major challenge for modern agriculture
In recent decades, it has been estimated that we will need to double the quantity of food produced to meet the demands of a rapidly growing population.[1]
Measurement results All the parameter results obtained from the volumetric models produced by applying our method to the wheat plant images are presented

Summary

Introduction

It has been estimated that we will need to double the quantity of food produced to meet the demands of a rapidly growing population.[1] Increasing crop yields has become a major challenge for modern agriculture. To meet this challenge, more productive crop varieties must be bred based on the identication of new plant characteristics. Considering the rapid development of functional genomics and gene technologies over the past decade, it is impractical to perform manual phenotypic analysis. It is imperative to develop better measurement technologies to automate the tedious task of collecting large amounts of phenotypic data with a high-throughput for agricultural crop improvement

Methods

Results

Discussion

Conclusion