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Data from: Using perennial groundcover crops to suppress weeds and thrips in the southeast cotton belt

Cite this dataset

Billman, Eric; Campbell, Benjamin T.; Reay‐Jones, Francis P. F. (2023). Data from: Using perennial groundcover crops to suppress weeds and thrips in the southeast cotton belt [Dataset]. Dryad. https://doi.org/10.5061/dryad.c866t1gcs

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, in Crop Science, Vol. 63 p. 3037 - 3050.

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.

README: Data from: Using perennial groundcover crops to suppress weeds and thrips in the southeast cotton belt

This dataset was used to generate 7 figures in the publication, "Using Perennial Groundcover Crops to Suppress Weeds and Thrips in the Southeast Cotton Belt". All data was collected in Florence, South Carolina at the Clemson University Pee Dee Research and Education Center during 2021 and 2022.

Description of dataset and file structure

Data is presented in an Microsoft Excel Spreadsheet, with separate tabs for datasets related to each of the 7 figures/subfigures in the published manuscript.

For all data the following treatment abbreviations are used:

Fallow = weedy, unplanted treatment
ARG = annual ryegrass
RC+WC = 50/50 mixture of red and white clover
ARG+RC+WC = 50% annual ryegrass, 25% red clover, and 25% white clover

Tab 1: These data were used to generate Figure 1, featuring mean weather data for the study years, 2021 & 2022, along with 30-year mean weather data for the nearest NOAA weather station (Florence, SC Regional Airport). Units are provided in the column headers.

Tab 2: These data were used to generate Figures 2a and 2b, featuring the amount of summer month interrow biomass during the cotton production season. Biomass in the RC+WC and ARG+RC+WC treatments is a mix of weeds and clovers, while ARG and fallow treatments are entirely comprised of weedy biomass

Tab 3: These data were used to generate Figures 3a and 3b, featuring the weed populations in each treatment for each year of the study.

Tab 4: These data were used to generate Figures 4a and 4b (white clover populations among treatments for each year) and Figures 5a and 5b (red clover populations for each year).

Tab 5: These data were used to generate Figures 6a, 6b, 6c, and 6d, featuring the mature and immature thrip populations from each year of the study.

Tab 6: These data were used to generate Figures 7a and 7b, with the final column (lint yield kg/ha) being calculated from the previous lbs/acre values.

Sharing Access Information

These data were originated from the published manuscript: https://doi.org/10.1002/csc2.21048.

Methods

Methods are detailed in the published manuscript: https://doi.org/10.1002/csc2.21048

Funding

Cotton (United States), Award: 21-113SC

Cotton (United States), Award: 22-113SC