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Technology for Automation of Weed Control in Specialty Crops

Published online by Cambridge University Press:  23 February 2017

Steven A. Fennimore ,
David C. Slaughter ,
Mark C. Siemens ,
Ramon G. Leon  and
Mazin N. Saber
Steven A. Fennimore*
Affiliation:
Department of Plant Sciences, University of California, Davis, Salinas, CA 93905
David C. Slaughter
Affiliation:
Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA 95616
Mark C. Siemens
Affiliation:
Department of Agricultural and Biosystems Engineering, University of Arizona, Tucson, AZ 85721
Ramon G. Leon
Affiliation:
West Florida Research and Education Center and Agronomy Department, University of Florida, Jay, FL 32565
Mazin N. Saber
Affiliation:
University of Arizona, Yuma Agricultural Center, AZ 85364
*
Corresponding author's E-mail: safennimore@ucdavis.edu
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Abstract

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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.

Los cultivos hortícolas de alto valor tales como flores, hierbas, y vegetales generalmente no tienen un espectro adecuado de químicos herbicidas para el control de malezas y han sido dependientes de la deshierba manual para alcanzar un control de malezas comercialmente aceptable. Sin embargo, la escasez de mano de obra ha provocado el incremento en los costos de la deshierba manual. Si se pretende contener los costos de producción, existe una necesidad de desarrollar tecnologías alternativas a la mano de obra para el control de malezas en cultivos hortícolas de alto valor. La tecnología de máquinas de visión, combinada con procesadores de datos, ha sido desarrollada para hacer posible que máquinas comerciales puedan reconocer los patrones de siembra en hileras del cultivo y a la vez controlar equipos automatizados que pueden desempeñar labores tales como la remoción de malezas en la hilera de siembra, o ralear la densidad de siembra del cultivo. Los sistemas de máquinas de visión comerciales dependen de la diferencia entre el tamaño del cultivo y el de las malezas y/o de la regularidad del patrón de distribución del cultivo para que el sistema pueda reconocer las plantas del cultivo y las malezas a su alrededor. Sin embargo, donde las malezas son grandes o la población de malezas es muy densa, los sistemas de máquinas de visión actuales no pueden diferenciar efectivamente entre las malezas y los cultivos. Los equipos automatizados de deshierba disponibles comercialmente hoy en día dependen de cultivadores o aspersores dirigidos para controlar malezas. Los equipos de acción para el control de malezas en modelos futuros podrían usar abrasión con aspersión de arena con aire a presión o calor con equipos con llamas de fuego para matar las malezas. Las estrategias de control de malezas en el futuro probablemente requerirán la adaptación de los cultivos al equipo automatizado de remoción de malezas. Un ejemplo de esto sería el cambio de patrones de siembra y distancias entre hileras del cultivo para facilitar la labranza en dos direcciones. La consolidación de compañías químicas continúa reduciendo el número de compañías que están buscando nuevos herbicidas. Además, el incremento en los costos de desarrollar nuevos herbicidas y el precio de la competencia a partir de productos existentes sugiere que la tendencia decreciente en el desarrollo de nuevos herbicidas continuará. En contraste, equipos automatizados de remoción de malezas continúan mejorando y haciéndose más efectivos.

Keywords

Automationintegrated weed managementintelligent cultivatorintrarow weed controlmechanizationrobotic weedingvegetable crops
Type
Research Article
Information
Weed Technology , Volume 30 , Issue 4 , December 2016 , pp. 823 - 837
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Weed Science Society of America

Footnotes

Associate editor for this paper: Robert Nurse, Agriculture and Agri-Food Canada.

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