Crop signal markers facilitate crop detection and weed removal from lettuce and tomato by an intelligent cultivator

Author:

Kennedy HannahJoy,Fennimore Steven A.ORCID,Slaughter David C.,Nguyen Thuy T.,Vuong Vivian L.,Raja Rekha,Smith Richard F.

Abstract

AbstractIncreasing weed control costs and limited herbicide options threaten vegetable crop profitability. Traditional interrow mechanical cultivation is very effective at removing weeds between crop rows. However, weed control within the crop rows is necessary to establish the crop and prevent yield loss. Currently, many vegetable crops require hand weeding to remove weeds within the row that remain after traditional cultivation and herbicide use. Intelligent cultivators have come into commercial use to remove intrarow weeds and reduce cost of hand weeding. Intelligent cultivators currently on the market such as the Robovator, use pattern recognition to detect the crop row. These cultivators do not differentiate crops and weeds and do not work well among high weed populations. One approach to differentiate weeds is to place a machine-detectable mark or signal on the crop (i.e., the crop has the mark and the weed does not), thereby facilitating weed/crop differentiation. Lettuce and tomato plants were marked with labels and topical markers, then cultivated with an intelligent cultivator programmed to identify the markers. Results from field trials in marked tomato and lettuce found that the intelligent cultivator removed 90% more weeds from tomato and 66% more weeds from lettuce than standard cultivators without reducing yields. Accurate crop and weed differentiation described here resulted in a 45% to 48% reduction in hand-weeding time per hectare.

Publisher

Cambridge University Press (CUP)

Subject

Plant Science,Agronomy and Crop Science

Reference34 articles.

1. Seed treatments: phytotoxicity amelioration and tracer uptake

2. The Challenges of Specialty Crop Weed Control, Future Directions

3. [CDFA] California Department of Food and Agriculture (2017) California Agricultural Statistics Review 2016–2017. pp 1–126 https://www.cdfa.ca.gov/Statistics/PDFs/2017-18AgReport.pdf Accessed July 17, 2019

4. Robotic weeders can improve weed control options for specialty crops

5. The Biological Engineer: Sensing the Difference Between Crops and Weeds

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