Spatial Analysis of Soybean Plant Height and Plant Canopy Temperature Measured with On-the-Go Tractor Mounted Sensors

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 (r = − 0.54, 2018; r = − 0.37, 2019). 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.