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Correspondence to Author:  Ltti Herrmann, Reeven K. Vosber, Shilip A. Townsen, Thawn P. Coley. 

Department of Agronomy, University of Wisconsin-Madison, 1575 Linden Drive, Madison, WI 53706, USA.

Abstract: The use of hyperspectral data for crop management and phenotyping while overcoming the difficulty of fluctuating atmospheric conditions is becoming more and more popular. Using a single spectrometer, the Piccolodual field-of-view device gathers up- and downwelling radiation almost simultaneously. For crop monitoring in extremely fluctuating atmospheric circumstances, such devices hold out a lot of potential. Here, a case study of assessing soybean plant numbers in early vegetative stages was used to illustrate the system’s usefulness from a tractor mounted boom. Two replicas of the same experiment are used to describe the Piccolo system and evaluate its performance under various sky conditions. Partial least squares regression (PLSR) was used to estimate the plant population, and models calibrated and validated under sunny and overcast or cloudy and sunny conditions, respectively, produced stable results. We demonstrate the Piccolo system’s operational viability for precision agricultural research and possible commercial applications, and we draw the conclusion that it is efficient for gathering data in a variety of atmospheric circumstances.

Citation:

Reeven K. Vosber. A Case Study Of Predicting Early Season Soybean Populations Using Dual Field-Of-View System For Spectral Data Collection In Changing Atmospheric Conditions. Journal of Advances in Plant Sciences 2025.