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ARS Home » Southeast Area » Florence, South Carolina » Coastal Plain Soil, Water and Plant Conservation Research » Research » Publications at this Location » Publication #408141

Research Project: Advancing Cotton Genetics and Innovative Cropping Systems for Improved Quality and Production

Location: Coastal Plain Soil, Water and Plant Conservation Research

Title: Data from: Using perennial groundcover crops to suppress weeds and thrips in the Southeast Cotton Belt

item Billman, Eric
item Campbell, Benjamin - Todd
item REAY-JONES, FRANCIS - Clemson University

Submitted to: Dryad Digital Repository
Publication Type: Database / Dataset
Publication Acceptance Date: 9/10/2023
Publication Date: N/A
Citation: N/A

Interpretive Summary: Digital research data corresponding to a published manuscript

Technical Abstract: This is digital research data corresponding to a published manuscript, Using Perennial Groundcover Crops to Suppress Weeds and Thrips in the Southeast Cotton Belt, published in Crop Science. Modern cotton production (Gossypium hirsutum L.) in the United States relies on chemical and physical inputs that increase the environmental and monetary costs of managing the crop. Perennial groundcover crops (PGCC) may reduce inputs by persisting in the interrow spaces of the cotton crop during summer months. A 2-year field study was conducted in Florence, SC, to evaluate growing PGCCs with cotton using a 4 × 4 Latin square consisting of four cover crop treatments: (1) a fallow, unplanted control, (2) annual ryegrass (Lolium multiflorum Lam.) monoculture, (3) a binary red clover (Trifolium pratense L.) and white clover (Trifolium repens L.) mixture, and (4) a trinary mixture of annual ryegrass, red clover, and white clover. Fallow and annual ryegrass treatments were killed with a burndown herbicide application, while treatments containing clovers were mowed. Plots were strip-tilled and planted with cotton in May each year. Interrow biomass, weed and thrips populations, and perennial clover populations were collected from June to October along with annual lint yields from cotton harvest in October. Methods are described in the published manuscript Descriptions on how to interpret each dataset and their corresponding figures are found in the file, and the dataset consists of a Microsoft Excel Spreadsheet with separate tabs containing associated data for each figure found in the published manuscript.