GainTKW: A Measurement System of Thousand Kernel Weight Based on the Android Platform

Wenhua Wu,Lei Zhou,Yong He,Zhengjun Qiu,Jian Chen

doi:10.3390/agronomy8090178

Abstract

Thousand kernel weight (TKW) is an important parameter for the evaluation of grain yield. The traditional measurement method relies on manual steps: weighing and counting. In this paper, we developed a system for the automated evaluation of thousand kernel weight that combines a weighing module and Android devices, called “gainTKW”. The system is able to collect the weight information from the weighing module through a serial port using the RS232-micro USB cable. In the imaging process, we adopt a k-means clustering segmentation algorithm to solve the problem of uneven lighting. We used the marker-controlled watershed algorithm and area threshold method to count the number of kernels that are touching one another. These algorithms were implemented based on the OpenCV (Open Source Computer Vision) libraries. The system tested kernel images of six species taken with the Android device under different lighting conditions. The algorithms in this study can solve the segmentation problems caused by shadows, as well. The appropriate numbers of kernels, of different species, are counted with an error ratio upper limit of 3%. The application is convenient and easy to operate. For the experiments, we can prove the efficiency and accuracy of the developed system by comparing the results between the manual method and the proposed application.

Highlights

As a complex agronomic trait, grain yield is multiplicatively determined by three components: the number of spikes per area, grain number per spike, and grain weight
Thousand kernel weight (TKW) was found to be closely associated with kernel size traits as well, such as kernel length (KL), kernel width (KW), kernel thickness (KT), and the kernel length/width ratio (L/W) [2]
This paper presents a measurement system of thousand kernel weight based on the Android platform, called “gainTKW”, which provides agricultural practitioners with a powerful tool for and automatically assessing thousand grain weight and providing useful information for yield estimation

Summary

Introduction

As a complex agronomic trait, grain yield is multiplicatively determined by three components: the number of spikes per area, grain number per spike, and grain weight. Grain weight is usually represented by 1000-kernel weight. Thousand kernel weight (TKW) is an important parameter for the evaluation of variety breeding. TKW is directly related to the grain yield and milling quality of grain, and has an impact on the seedling vigor and growth indirectly affecting the yield [1]. TKW was found to be closely associated with kernel size traits as well, such as kernel length (KL), kernel width (KW), kernel thickness (KT), and the kernel length/width ratio (L/W) [2]. TKW is frequently used in crop research as a measurement indicator [3]

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