Two-Dimensional Simulation of Barley Growth and Yield Using a Model Integrated with Remote-Controlled Aerial Imagery

Ashifur Rahman Shawon,Taehwan Shin,Seungtaek Jeong,Kyung Do Lee,Sang In Shim,Jonghan Ko

doi:10.3390/rs12223766

Abstract

It is important to be able to predict the yield and monitor the growth conditions of crops in the field to increase productivity. One way to assess field-based geospatial crop productivity is by integrating a crop model with a remote-controlled aerial system (RAS). The objective of this study was to simulate spatiotemporal barley growth and yield based on the development of a crop-modeling system integrated with RAS-based remote sensing images. We performed field experiments to obtain ground truth data and RAS images of crop growth conditions and yields at Chonnam National University (CNU), Gwangju, South Korea in 2018, and at Gyeongsang National University (GNU), Jinju, South Gyeongsang, South Korea in 2018 and 2019. In model calibration, there was no significant difference (p = 0.12) between the simulated barley yields and measured yields, based on a two-sample t-test at CNU in 2018. In model validation, there was no significant difference between simulated yields and measured yields at p = 0.98 and 0.76, according to two-sample t-tests at GNU in 2018 and 2019, respectively. The remote sensing-integrated crop model accurately reproduced geospatial variations in barley yield and growth variables. The results demonstrate that the crop modeling approach is useful for monitoring at-field barley conditions.

Highlights

Barley (Hordeum vulgare), a major cereal grain grown in temperate climates globally, is an important staple crop in the Korean peninsula and worldwide
We estimated the specific barley growth parameters of radiation use efficiency (RUE), specific leaf area (SLA), and light extinction coefficient (k) from the data set obtained at Chonnam National University (CNU) in 2018 for effective calibration of the model
The RUE (ε) was determined from the slope of the linear regression model between the amounts of accumulated photosynthetically active radiation (PAR) absorbed by barley canopies and above-ground dry mass (AGDM) for four barley cultivars (Figure 2a)

Summary

Introduction

Barley (Hordeum vulgare), a major cereal grain grown in temperate climates globally, is an important staple crop in the Korean peninsula and worldwide. It is used as animal fodder, a fermentable source material for beer, and a constituent of various health foods [1]. Remote sensing is useful for surveying geospatial variability in crop growth conditions over the growing season [4]. Each technique for crop modeling and remote sensing has certain advantages, e.g., crop models are able to simulate growth sequentially, while RS can monitor geospatial variations in crop conditions dependably [5,6]

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Conclusion