Open Access Research Article

Creating a Multivariate-Multifunctional Database for Weed Control to Support Organic Mixed Vegetable Production

Yaqeen Salatneh Ashqer1*, Chyi Lyi (Kathleen) Liang2 and Marwan Bikdash1

1Department of Computational Science and Engineering, North Carolina A&T State University, USA

2Center for Environmental Farming System, North Carolina A&T State University 1601 E Market St, Greensboro, NC 27401

Corresponding Author

Received Date: March 26, 2020;  Published Date: April 17, 2020


The organic sector has become one of the fastest-growing agricultural movements in the United States. Weed management is one of the most significant challenges for organic vegetable growers since weed interference reduces crop yield and quality. This paper aims to share an innovative method to design, develop, and implement a multivariate- multifunctional database to help small-scale organic mixed vegetable farms to prevent the spread of weeds from the seeding stage of production. We monitored different types of vegetables in spring 2019 that were produced on a 0.5- acre plot in a small urban farm in Guilford County, North Carolina. We documented the environmental and climatic factors for all vegetables. The database we collected incorporates numbers of records, description of conditions, and photo images of vegetable and weed growth. The expected contribution of this study is to determine or calculate.

• The correlation between vegetable growth, weed growth, and circumstantial factors while taking into consideration human decisions and climate variations.

• The average and optimized vegetable plant growth rates corresponding to natural and human factors.

• The survival ratio between vegetables and weeds under a well-monitored environment.

Keywords: Critical period; Monitoring; Organic farming; Gather images

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