|Slaughter, David -|
Submitted to: UJNR Food & Agricultural Panel Proceedings
Publication Type: Proceedings
Publication Acceptance Date: July 15, 2009
Publication Date: February 10, 2009
Citation: Haff, R.P., Slaughter, D.C. 2009. Automatic Weed Control System For Transplanted Processing Tomatoes Using X-ray Stem Sensing. UJNR Food & Agricultural Panel Proceedings. Interpretive Summary: A machine has been developed that is dragged behind a tractor over rows of transplanted tomato seedlings and uses knives below the soil surface to kill weeds. This report describes the x-ray detection system that tells the knives when a tomato plant is present so they can stop cutting long enough to leave the plants intact. A field trial was conducted in a 15 meter section of row containing 39 tomato seedlings. At a speed of 1.6 km/h, the detection system identified all 39 stems of standing plants with no false positives (identifying a tomato plant that was not there).
Technical Abstract: A stem detection system was developed for automatic weed control in transplanted tomato fields. A portable x-ray source projected an x-ray beam perpendicular to the crop row and parallel to the soil surface. The plant’s main stem absorbs x-ray energy, decreasing the detected signal and allowing stem detection even in the presence of leaves. This signal is used to control the operation of a pair of weed knives. Minimizing the source to detector distance as the system moved along the row allowed for differences in signal strength between stems and background as high as 180 mV (vs. background noise levels around 30 mV) at low x-ray energy and current levels (25 keV, 7 mA), which is a significant advantage for safety reasons. The detector consisted of a linear array of photodiodes aligned perpendicular to the soil. This configuration helps differentiate branches, which are angled and block only some of the photodiodes, and stems which have the same vertical alignment as the array and hence block all photodiodes. A field trial was conducted in a 15 meter section of row containing 39 tomato seedlings. At a speed of 1.6 km/h, the detection system identified all 39 stems of standing plants with no false positives.