Abstract

Designing and implementing an affordable High-Throughput Phenotyping Platform (HTPP) for monitoring crops’ features in different stages of their growth can provide valuable information for crop-breeders to study possible correlation between genotypes and phenotypes. Conducting automatic field measurements can improve crop productions. In this research, we have focused on development of a mechatronic system, hardware and software, for a mobile, field-based HTPP for autonomous crop monitoring for wheat field. The system can measure canopy’s height, temperature, and vegetation indices and is able to take high quality photos of crops. The system includes. developed software for data and image acquisition. The main contribution of this study is autonomous, reliable, and fast data collection for wheat and similar crops.

Highlights

  • High-Throughput WheatBy continuous growth of population around the world, humanity’s needs for food resources increase, which leads to need for optimizing crop production

  • Analyzing genetic features of a plant is a necessary practice in agriculture related research to make an interaction between crop breeders and experts who use phenotyping to gather features of plants

  • This paper presents development of new ground-based wheeled-mobile platform for high throughput crop monitoring, wheat

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Summary

Introduction

By continuous growth of population around the world, humanity’s needs for food resources increase, which leads to need for optimizing crop production. More than 820 million people in the world were suffering hunger in 2018 [1]. There is a prediction that humanity’s demand for food and resources will double by 2050 within a 40-year period [2]. Analyzing genetic features of a plant is a necessary practice in agriculture related research to make an interaction between crop breeders and experts who use phenotyping to gather features of plants. Phenotyping needs to be more advanced to provide more information. Measuring characteristics, such as plant’s height, temperature, and greenness, and having high quality pictures for image processing are challenging and time consuming

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