ABSTRACT
Vegetation indexes are important indicators of the health and yield of agricultural crops. Among the sensors used to evaluate vegetation indexes, proximal sensors can be used for real-time decision-making. Thus, the objective of this study was to develop a proximal sensor system based on phototransistors to acquire and store the following vegetation indexes: normalized difference vegetation index, simple ratio, wide dynamic range vegetation index, soil-adjusted vegetation index, and optimized soil-adjusted vegetation index. The sensor system was developed using an analog circuit to acquire reflectance data from red and near-infrared bands. The sensor system was calibrated according to the results of a spectroradiometer, using Zoysia japonica grass as the target. An algorithm that calculates and stores vegetation indexes in a file was developed. The Pearson correlation between the vegetation indexes obtained with the sensor system and the spectroradiometer was evaluated. The vegetation indexes presented a Pearson correlation higher than 0.92 to the estimated values by the spectroradiometer. Under the evaluation conditions, the proposed sensor system could be used to determine all vegetation indexes evaluated.
Key words:
precision agriculture; phototransistor; reflectance; proximal sensing
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AIN0 and AIN1 = analog ports of the BeagleBone Black (BBB); VDD 5V = voltage of 5 V of the BBB; DGND = voltage of 0 V of the BBB
F1 = phototransistor that captures the near-infrared band, Fairchild QSD124; F2 = phototransistor that captures the red band, Everlight PT334-6C; FPB = band-pass filter of red; A = lateral view; B = bottom view
** = Significant at p ≤ 0.01 by the F test
** = significant at p ≤ 0.01 by the t test; straight line (-) = (x = y); dots (●) = values found; dotted line (...) = fitted model; r = Pearson coefficient of correlation