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Open-source electronics for plant phenotyping and irrigation in controlled environment

Smart Agricultural Technology · 11 Jul 2022 · 10.1016/j.atech.2022.100093

Abstract

Integration of plant phenotyping and irrigation is particularly advantageous for identifying genetic variation associated with crop productivity. Collecting phenotypic data and water management under controlled or open environment can be expensive and laborious. This study aims to design a cost-effective solution for high-throughput phenotyping (HTP) and automated irrigation using open-source electronics. A portable HTP system was developed using a microcontroller and a single-board computer Raspberry Pi and was extended to include soil water monitoring and water pump control. An Arduino board was integrated with a multispectral camera, mini LiDAR sensors, infrared thermometers, soil moisture sensors, water pumps, and a temperature/humidity sensor. Sensor calibration and power management enhanced the accuracy and reliability of the system. Two genotypes (CAM212 and Giessen#4) of camelina were used to evaluate the system to measure phenotypic responses to abiotic stress in growth chambers under two temperatures (25 °C and 35 °C) and two water treatments (40% and 90% water holding capacity). The HTP system monitored 24 plants periodically, and data were wirelessly accessed by a smartphone and transferred to a computer for further analyses. The system revealed that camelina genotype 1 (CAM212) showed superior resistance to heat and drought stress. The results showed that the developed HTP system offers a cost-effective and portable solution for phenotyping and water management in controlled environment and can be modified for field applications.

Plant phenotyping relevance

植物表現型取得システムの開発と校正・評価が研究の中心であり、センサーを統合した高スループット表現型解析基盤を構築している。

abstractThis study aims to design a cost-effective solution for high-throughput phenotyping (HTP) and automated irrigation using open-source electronics.
abstractA portable HTP system was developed using a microcontroller and a single-board computer Raspberry Pi
abstractSensor calibration and power management enhanced the accuracy and reliability of the system.
abstractThe system revealed that camelina genotype 1 (CAM212) showed superior resistance to heat and drought stress.

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