Spatial analysis of soybean plant height and plant canopy temperature measured with on-the-go tractor mounted sensors

Authors: Fletcher, Reginald; Fisher, Daniel

Submitted to: Agricultural Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/24/2019
Publication Date: 11/27/2019
Citation: Fletcher, R.S., Fisher, D.K. 2019. Spatial analysis of soybean plant height and plant canopy temperature measured with on-the-go tractor mounted sensors. Agricultural Sciences. 10/1486-1496.
DOI: https://doi.org/10.4236/as.2019.1011109

Interpretive Summary: There is a growing interest in the Open Ag community to use inexpensive sensors controlled by open-source software to measure plant height and plant canopy temperature of agricultural crops. Plant height and plant canopy temperature are key indicators of plant health. ARS Scientists in Stoneville, MS, demonstrated the application of a mobile open-source plant-canopy monitoring system to measure in-field variability of plant height and plant canopy temperature of soybean plants. Data acquired by the system was adequate for determining the spatial correlation of plant height and plant canopy temperature. Within-field variability patterns of plant height and plant canopy temperature was similar from one year to the next, suggesting that the sensor technologies could be used as a historical record for monitoring growth patterns in soybean fields. The sensors and techniques used in this study can be easily adapted to other crops, thus providing two important layers of information for monitoring plant growth and potentially plant stress.

Technical Abstract: There is a growing interest in the Open Ag community to use inexpensive sensors controlled by open-source software to measure plant height and plant canopy temperature of agricultural crops. Plant height and plant canopy temperature are key indicators of plant health. This research study reports on an ongoing research initiative to test a compact and inexpensive mobile sensor to measure plant height and plant canopy temperature. The system is controlled by open source software and hardware. The specific objectives for this study were to analyze the relationship between plant height and plant canopy temperature of soybeans (Glycine max L.) measured with the mobile system and to analyze the spatial correlation of the plant height and plant canopy temperature measurements. Data were collected in a soybean plot in 2018 and 2019. Descriptive statistics, Pearson correlation, and geostatistical techniques were used to evaluate the data. A negative statistically significant (p = 0.05) relationship was observed between the plant height and the plant canopy temperature measurements. Also, both parameters were spatially correlated; however, plant height had a greater spatial continuity than plant canopy temperature. Furthermore, similar patterns were observed for the in-field variability of the plant height and plant temperature maps derived via kriging. Similarities in plant height and plant canopy temperatures were observed from one year to the next, suggesting that the sensor technologies could be used as a historical record for monitoring growth patterns in soybean fields. The sensors and techniques used in this study can be easily adapted to other crops, thus providing two important layers for monitoring plant growth and potentially plant stress.