Project Summaries

10-759  Project Manager: E. M. Barnes


Pedro Andrade-Sanchez and Sam Wang, University of Arizona

Applied research in cotton production has demonstrated the value of using real-time, sensor-based data to guide the application of production inputs such as fertilizers and plant growth regulators to balance vegetative and reproductive growth, but the quantification of plant growth is particularly challenging due to the indeterminate growing pattern of this species. Cotton height node ratio (H:N) has been proved to be a reliable figure of merit for this application, but so far, field methods used to monitor this ratio have relied on manual measurements, and this is the reason behind the low rates of utilization. Our research in this area has been focused on developing technologies for the automated, continuous acquisition of cotton height node ratio from a moving platform that models a tractor performing operations such as cultivation or spraying. This approach has many advantages because our field instrumentation is based on sensors that can be deployed for extended periods of time and capture differences in every part of the field, implying extended capacity. Moreover, an electronic system removes potential issues with consistency of data acquisition that may result from differences in subjective evaluations.

A field experiment was conducted at the University of Arizona, Maricopa Agricultural Center using three varieties: bushy type (Stoneville ST-4498-B2RF), a columnar type Delta Pine (164-B2RF), and a high-yielding variety (PHY499-B2RF). The planter was set to deliver 75k seeds per acre. In early May after germination and emergence was completed, the field was subdivided in plots and thinned to obtain final plant populations of 25k, 50k and 75k (no thinning). Half of the field in this experiment had been treated with optimal water management according to standards developed at the Maricopa Agricultural Center, mainly allowing only 50% depletion.

At the core of this research project is the use of sensors to characterize cotton plant development conditions. Therefore, we have implemented a mobile platform to achieve this objective. Some of the components include Pulsar dB3 ultrasonic transducers and Blackbox 130D level controllers for displacement measurements aimed at solving plant height. In addition, we installed in the front boom of the platform a set of 8 infra-red radiometers (Apogee SI121) and four active canopy reflectance sensors (CropCircle ACS470). These sensors will provide continuous data on canopy temperature and light reflectance in three bands (720, 820, and 880nm) of 4 rows each run.

The use of sensors to characterize cotton growth has been tested in this project with satisfactory results. Canopy reflectance provided excellent treatment differentiation at the early stages of growth but lost sensitivity when the crop was reaching max height. Sonar sensors used to measure plant height provided excellent characterization of plant size, at the latter part of the growing season at canopy closure, but early measurements were highly affected by soil background. It seems plausible that a robust system would make use of both sensors as independent sources of plant characterization information. A method to use the data to estimate height to node ratio is still under development. The system has also proven a useful research tool and applied in another project to rapidly characterize differences in cotton varieties that will be of value to cotton breeders and geneticists.


Project Year: 2012

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