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

被引:8
作者
Kim, James Y. [1 ]
Abdel-Haleem, Hussein [2 ]
Luo, Zinan [2 ]
Szczepanek, Aaron [2 ]
机构
[1] USDA ARS, 141 Expt Stn Rd, Stoneville, MS 38776 USA
[2] USDA ARS, Arid Land Agr Res Ctr, Maricopa, AZ 85138 USA
来源
SMART AGRICULTURAL TECHNOLOGY | 2023年 / 3卷
基金
美国食品与农业研究所;
关键词
Phenotyping; Irrigation; Sensor; Image processing; Arduino; Raspberry Pi; ARABIDOPSIS-THALIANA; IMAGE-ANALYSIS; LARGE-SCALE; PLATFORM; SYSTEM;
D O I
10.1016/j.atech.2022.100093
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
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 highthroughput 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 degrees C and 35 degrees 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.
引用
收藏
页数:11
相关论文
共 49 条
[1]  
Agrawal N, 2015, 2015 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION & AUTOMATION (ICCCA), P928, DOI 10.1109/CCAA.2015.7148526
[2]  
Ampatzidis Y., 2013, 2013 ASABE ANN INT M, DOI [10.13031/aim.20131596473, DOI 10.13031/AIM.20131596473]
[3]  
[Anonymous], 2012, Mod. Instrum, DOI DOI 10.4236/MI.2012.12002
[4]  
Arduino, 2020, Arduino Uno Rev3
[5]  
Arduino, 2020, Introduction to the Arduino Board
[6]   NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research [J].
Bai, Geng ;
Ge, Yufeng ;
Scoby, David ;
Leavitt, Bryan ;
Stoerger, Vincent ;
Kirchgessner, Norbert ;
Irmak, Suat ;
Graef, George ;
Schnable, James ;
Awada, Tala .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2019, 160 :71-81
[7]   Development of a field-based high-throughput mobile phenotyping platform [J].
Barker, Jared ;
Zhang, Naiqian ;
Sharon, Joshua ;
Steeves, Ryan ;
Wang, Xu ;
Wei, Yong ;
Poland, Jesse .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2016, 122 :74-85
[8]   Management and Characterization of Abiotic Stress via PhenoFieldR®, a High-Throughput Field Phenotyping Platform [J].
Beauchene, Katia ;
Leroy, Fabien ;
Fournier, Antoine ;
Huet, Celine ;
Bonnefoy, Michel ;
Lorgeou, Josiane ;
de Solan, Benoit ;
Piquemal, Benoit ;
Thomas, Samuel ;
Cohan, Jean-Pierre .
FRONTIERS IN PLANT SCIENCE, 2019, 10
[9]   Cave Pearl Data Logger: A Flexible Arduino-Based Logging Platform for Long-Term Monitoring in Harsh Environments [J].
Beddows, Patricia A. ;
Mallon, Edward K. .
SENSORS, 2018, 18 (02)
[10]   A High-Throughput Model-Assisted Method for Phenotyping Maize Green Leaf Area Index Dynamics Using Unmanned Aerial Vehicle Imagery [J].
Blancon, Justin ;
Dutartre, Dan ;
Tixier, Marie-Helene ;
Weiss, Marie ;
Comar, Alexis ;
Praud, Sebastien ;
Baret, Frederic .
FRONTIERS IN PLANT SCIENCE, 2019, 10