Automatic estimation of heading date of paddy rice using deep learning

Sai Vikas Desai,Vineeth N Balasubramanian,Wei Guo,Seishi Ninomiya,Tokihiro Fukatsu

doi:10.1186/s13007-019-0457-1

Abstract

BackgroundAccurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location. The heading date also plays a vital role in determining grain yield for research experiments. Visual examination of the crop is laborious and time consuming. Therefore, quick and precise estimation of heading date of paddy rice is highly essential.ResultsIn this work, we propose a simple pipeline to detect regions containing flowering panicles from ground level RGB images of paddy rice. Given a fixed region size for an image, the number of regions containing flowering panicles is directly proportional to the number of flowering panicles present. Consequently, we use the flowering panicle region counts to estimate the heading date of the crop. The method is based on image classification using Convolutional Neural Networks. We evaluated the performance of our algorithm on five time series image sequences of three different varieties of rice crops. When compared to the previous work on this dataset, the accuracy and general versatility of the method has been improved and heading date has been estimated with a mean absolute error of less than 1 day.ConclusionAn efficient heading date estimation method has been described for rice crops using time series RGB images of crop under natural field conditions. This study demonstrated that our method can reliably be used as a replacement of manual observation to detect the heading date of rice crops.

Highlights

Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location
Heading date is primarily used to measure the response of the rice plant to various environmental and genetic conditions
Our aim is to estimate the heading date in a rice crop using a fast automatic system based on computer vision and deep learning

Summary

Introduction

Accurate estimation of heading date of paddy rice greatly helps the breeders to understand the adaptability of different crop varieties in a given location. A good understanding of the growth stages in rice crops would enable one to use the right amount of water, fertilizers and pesticides to ensure maximum yield. This has great economical consequences since timely and high yield of rice can potentially address the food shortage problem prevailing in many parts of the world. When rice paddies grow from their seeds to mature plants, they go through a variety of transformations They develop tillers, begin to grow leaves and gradually increase in height. Heading date is primarily used to measure the response of the rice plant to various environmental and genetic conditions This makes it an indispensable parameter useful to breeders and researchers. By estimating the heading date and thereby observing the heading stage, a farmer can make informed crop management decisions such as: (1) deciding the optimum amount of

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