Increasing 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.

Specialty crops, like flowers, herbs, and vegetables, generally do not have an adequate spectrum of herbicide chemistries to control weeds and have been dependent on hand weeding to achieve commercially acceptable weed control. However, labor shortages have led to higher costs for hand weeding. There is a need to develop labor-saving technologies for weed control in specialty crops if production costs are to be contained. Machine vision technology, together with data processors, have been developed to enable commercial machines to recognize crop row patterns and control automated devices that perform tasks such as removal of intrarow weeds, as well as to thin crops to desired stands. The commercial machine vision systems depend upon a size difference between the crops and weeds and/or the regular crop row pattern to enable the system to recognize crop plants and control surrounding weeds. However, where weeds are large or the weed population is very dense, then current machine vision systems cannot effectively differentiate weeds from crops. Commercially available automated weeders and thinners today depend upon cultivators or directed sprayers to control weeds. Weed control actuators on future models may use abrasion with sand blown in an air stream or heating with flaming devices to kill weeds. Future weed control strategies will likely require adaptation of the crops to automated weed removal equipment. One example would be changes in crop row patterns and spacing to facilitate cultivation in two directions. Chemical company consolidation continues to reduce the number of companies searching for new herbicides; increasing costs to develop new herbicides and price competition from existing products suggest that the downward trend in new herbicide development will continue. In contrast, automated weed removal equipment continues to improve and become more effective.

The performance of the Robovator (F. Poulsen Engineering ApS, Hvals⊘, Denmark), a commercial robotic intrarow cultivator, was evaluated in direct-seeded broccoli and transplanted lettuce during 2014 and 2015 in Salinas, CA, and Yuma, AZ. The main objective was to evaluate the crop stand after cultivation, crop yield, and weed control efficacy of the Robovator compared with a standard cultivator. A second objective was to compare hand weeding time after cultivation within a complete integrated weed management (IWM) system. Herbicides were included as a component of the IWM system. The Robovator did not reduce crop stand or marketable yield compared with the standard cultivator. The Robovator removed 18 to 41% more weeds at moderate to high weed densities and reduced hand-weeding times by 20 to 45% compared with the standard cultivator. At low weed densities there was little difference between the cultivators in terms of weed control and hand-weeding times. The lower-hand weeding time with the Robovator treatments suggest that robotic intrarow cultivators can reduce dependency on hand weeding compared with standard cultivators. Technological advancements and price reductions of these types of machines will likely improve their weed removal efficacy and the long-term viability of IWM programs that will use them.