<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJSS</journal-id><journal-title-group><journal-title>Open Journal of Soil Science</journal-title></journal-title-group><issn pub-type="epub">2162-5360</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojss.2021.115015</article-id><article-id pub-id-type="publisher-id">OJSS-109597</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth&amp;Environmental Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Effect of Rye and Mix Cover Crops on Soil Water and Cotton Yield in a Humid Environment
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>José</surname><given-names>O. Payero</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Michael</surname><given-names>W. Marshall</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Rebecca</surname><given-names>H. Davis</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Joe</surname><given-names>Bible</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Nathaniel</surname><given-names>Nemire</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Edisto Research and Education Center, Clemson University, Blackville, SC, USA</addr-line></aff><aff id="aff2"><addr-line>School of Mathematical and Statistical Sciences, Clemson University, SMSS, Clemson, South Carolina, USA</addr-line></aff><pub-date pub-type="epub"><day>31</day><month>05</month><year>2021</year></pub-date><volume>11</volume><issue>05</issue><fpage>271</fpage><lpage>284</lpage><history><date date-type="received"><day>27,</day>	<month>April</month>	<year>2021</year></date><date date-type="rev-recd"><day>28,</day>	<month>May</month>	<year>2021</year>	</date><date date-type="accepted"><day>31,</day>	<month>May</month>	<year>2021</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  In recent years, the use of cover crops is becoming a popular technology among growers in many regions of the United States, which is expected to deliver various benefits such as improving soil health, increasing soil organic matter, controlling weeds, and helping conserve soil water and nutrients. Although expecting these benefits seems reasonable, it is challenging to know how much of these benefits to expect under specific situations. The potential effect of cover crops on soil water conservation is especially significant because of the documented impact of soil water on crop yield, especially for dryland cropping systems. Some researchers have found that planting a cover crop tended to increase soil water, while others have reported the opposite effect. Information on the impact of cover crops on soil water in cotton (
  <em>Gossypium hirsutum</em> L.) production systems in South Carolina is currently lacking. Therefore, the objective of this study was to quantify the effect of cover crops on soil water and cotton yield. A field experiment was conducted in South Carolina during winter, spring, and summer of 2015, with three cover crop treatments. The treatments included: 1) rye (
  <em>Secale cereale </em>L.), planted alone; 2) a mix of six cover crop species; and 3) a control treatment with no-cover. The cover crop was established in the winter, terminated in the spring, and cotton was grown during the summer. Soil water was measured at different depths using capacitance probes and a neutron probe. Our results showed no significant differences in soil water and cotton yield among the cover crop treatments. These results suggest that under the humid conditions of this study, any short-term effect of the cover crop on soil water was masked by timely rain.
 
</p></abstract><kwd-group><kwd>Soil Moisture</kwd><kwd> Soil Water</kwd><kwd> Cover Crop</kwd><kwd> Cotton</kwd><kwd> Sensors</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Planting a cover crop rather than leaving the land fallow during the winter is an agronomic practice that has long been promoted since it offers several potential benefits to the soil and the cash crop. Some of these potential benefits include the effect of cover crop on increasing soil organic carbon and carbohydrates [<xref ref-type="bibr" rid="scirp.109597-ref1">1</xref>], supplying soil Nitrogen [<xref ref-type="bibr" rid="scirp.109597-ref2">2</xref>], stabilizing soil temperature [<xref ref-type="bibr" rid="scirp.109597-ref3">3</xref>], suppressing weeds [<xref ref-type="bibr" rid="scirp.109597-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref5">5</xref>], increasing crop yield [<xref ref-type="bibr" rid="scirp.109597-ref6">6</xref>], conserving soil moisture [<xref ref-type="bibr" rid="scirp.109597-ref7">7</xref>], reducing runoff and soil erosion [<xref ref-type="bibr" rid="scirp.109597-ref8">8</xref>], and increasing water use efficiency [<xref ref-type="bibr" rid="scirp.109597-ref9">9</xref>], among other potential benefits. Because of its direct impact on crop yield, one of the most economically significant potential benefits of planting a cover crop is its effect on conserving soil water. However, there is disagreement in the literature about the impact of cover crops on soil water conservation. Some researchers have reported a net gain in soil water due to planting a cover crop, while others have found the opposite.</p><p>Examples of researchers who have found that cover crops tended to increase soil water include Karukua et al. [<xref ref-type="bibr" rid="scirp.109597-ref10">10</xref>], who compared the effect of cover crop residue in soil moisture in tomato production. They found that the cover crop increased moisture storage, leading to increased tomato yields and water use efficiency. Similarly, Wells et al. [<xref ref-type="bibr" rid="scirp.109597-ref5">5</xref>] evaluated the effect of rye cover crop on soil moisture in soybean production. They found that soil moisture was higher in cereal rye mulch treatments compared to a control treatment. Acharya et al. [<xref ref-type="bibr" rid="scirp.109597-ref11">11</xref>] reported that cover crops increased soil moisture in the top 30 cm soil depth by 3% to 5% compared to control plots. Stipešević and Kladivko [<xref ref-type="bibr" rid="scirp.109597-ref3">3</xref>], evaluating the effect of winter wheat cover crop in corn production, found that the cover crop increased soil moisture due to its mulching effect. Clark et al. [<xref ref-type="bibr" rid="scirp.109597-ref12">12</xref>] also found that soil moisture in the 20 cm soil depth when growing a cover crop was greater than or equal to the no-cover controls throughout the spring and the summer. Daigh et al. [<xref ref-type="bibr" rid="scirp.109597-ref13">13</xref>] observed that during the 2012 drought in Iowa and Indiana, planting a rye cover crop either had no impact or significantly increased soil water.</p><p>On the other hand, Mitchell et al. [<xref ref-type="bibr" rid="scirp.109597-ref7">7</xref>] reported that cover crops tended to decrease soil water. They found that cover crop biomass production may come at the cost of soil water depletion in a semiarid, drought-prone region of California. Similarly, Liebl et al. [<xref ref-type="bibr" rid="scirp.109597-ref4">4</xref>], in a four-year study with rye cover crop in Illinois, found that soil water content was the lowest in June under the late-killed rye (killed at planting) during dry periods due to water depletion caused by the growing rye. McGuire et al. [<xref ref-type="bibr" rid="scirp.109597-ref14">14</xref>], comparing winter legume cover crop vs. fallow for wheat production, showed that more soil water depletion occurred with the cover crop than in fallow. They also found that heavy rains eliminated any detrimental effect on the following wheat crop during the winter. Kahimba et al. [<xref ref-type="bibr" rid="scirp.109597-ref15">15</xref>] found that a cover crop treatment significantly reduced soil moisture during the growing season. Krueger et al. [<xref ref-type="bibr" rid="scirp.109597-ref16">16</xref>] found that the soil moisture after rye killed three to four weeks before planting corn was similar to a control treatment, but soil moisture after rye harvested two days before corn planting was 16% lower than the control.</p><p>Similarly, Ruiz-Colmenero et al. [<xref ref-type="bibr" rid="scirp.109597-ref8">8</xref>] showed that the cover crop treatment reduced soil moisture during a vineyard’s vegetative period compared to soils with traditional tillage. They found that although the transpiration through the permanent cover crop was offset by increased infiltration, the cover crop competed actively for water and resulted, on average, in 40% lower grape yields. Meyer et al. [<xref ref-type="bibr" rid="scirp.109597-ref17">17</xref>] used long-term simulation modeling to compare cover crops to a bare-soil control. They found that cover crops could significantly reduce soil water content (0 - 120 cm deep) for the following cash crop by a mean of 20 - 50 mm, and up to 80 mm in dry spring conditions. Still, early termination of the cover crop could decrease this negative impact. Thus, they suggested destroying cover crops in late autumn and retaining the residues as mulch to take advantage of the multiple services the cover crops provide during the fallow period while avoiding the negative impact on soil water availability for the following cash crop. In South Carolina, information on the effect of cover crops on soil water in cotton cropping systems is currently lacking. Therefore, the objective of this study was to quantify the impact of winter cover crops on soil water and cotton yield.</p></sec><sec id="s2"><title>2. Methods</title><sec id="s2_1"><title>2.1. Field Experiment and Data Collection</title><p>The field experiment for this study was conducted in 2015 at the Clemson University Edisto Research and Education Center (EREC) near Blackville, SC. The experimental field was 130 m &#215; 110 m and had a Barnwell loamy sand (DaB) soil [<xref ref-type="bibr" rid="scirp.109597-ref18">18</xref>]. The typical soil profile for the Barnwell loamy sand soil has a loamy sand layer in the top 0 - 20 cm depth and a sandy clay loam layer in the 20 - 200 cm depth. The research site was located in the humid southeast USA region with average annual precipitation of 1198 mm, and maximum and minimum air temperatures of 25.6˚C and 11.7˚C, respectively [<xref ref-type="bibr" rid="scirp.109597-ref19">19</xref>].</p><p>The field experiment compared three cover crop treatments using a completely randomized design with four replications. The treatments included: 1) rye planted alone; 2) a mix of six cover crop species; and 3) a control treatment with no-cover. These treatments will be referred to as “Rye,” “Mix,” and “None,” respectively. The Mix treatment included rye (56.7%), oats (14.1%), turnip (3.45%), vetch (7%), radish (3.45%), and crimson clover (14.1%). The cover crop was planted in the winter (1/16/2015) and was terminated in the spring using herbicides and the residue was rolled using a tractor-mounted roller (Landoll Company, Marysville, KS). Cotton was planted on 5/17/2015 in the field during the summer following the cover crop.</p><p>Soil volumetric water content (VWC) during the cover crop and cotton growth periods were measured at different depths using capacitance soil moisture sensors and a neutron probe. ECH<sub>2</sub>OEC-5 capacitance moisture sensors (METER Environment, Pullman, WA) were installed at 15, 30, 45, and 60 cm soil depths at the center of each experimental plot. The ECH<sub>2</sub>O EC-5 sensors determine VWC by measuring the dielectric constant of the media using capacitance/frequency domain technology. Em50R wireless radio data loggers (METER Environment, Pullman, WA) were used to automatically read the sensors and store the VWC data every hour. Neutron probe tubes were also installed in each plot to measure VWC using the neutron scattering method [<xref ref-type="bibr" rid="scirp.109597-ref20">20</xref>]. The neutron probe VWC was measured weekly using a CPN Hydroprobe<sup>TM</sup> (CNP, Raleigh, NC) from five soil depths (15, 30, 45, 60, and 76 cm).</p><p>Plant samples were collected from each plot on 4/23/15 to determine the dry biomass production from the planted cover crops and the weeds that grew in the control treatment. For the Mix treatment, the plant samples were also divided to determine the biomass production for each of the six cover crop species included in the cover crop mix (rye, oats, turnip, vetch, radish, and crimson clover). Yield from the cotton plots was also measured using a cotton picker equipped with a yield monitor. <xref ref-type="fig" rid="fig1">Figure 1</xref>(a) shows the established cover crop and control plots, and <xref ref-type="fig" rid="fig1">Figure 1</xref>(b) shows the same plots just before cover crop termination in the spring. <xref ref-type="fig" rid="fig1">Figure 1</xref>(b) also illustrates the significant amount of weed pressure in the control plots. <xref ref-type="fig" rid="fig2">Figure 2</xref>(a) shows one of the soil moisture measurement setups, including the ECH<sub>2</sub>O EC-5 sensors connected to an Em50R data logger in one of the plots. <xref ref-type="fig" rid="fig2">Figure 2</xref>(b) shows the cotton planted after the cover crop was</p><p>terminated, showing the plant residue mulch remaining from the cover crop. Daily weather data for 2015 was obtained from an electronic weather station operated by NOAA, which is located within the EREC research farm.</p></sec><sec id="s2_2"><title>2.2. Statistical Analyses</title><sec id="s2_2_1"><title>2.2.1. Analysis of ECH<sub>2</sub>O EC-5 Sensors VWC Data</title><p>The statistical analysis of the VWC data from the ECH<sub>2</sub>O EC-5 sensors focused on the average soil moisture (ASM), which was calculated as the arithmetic average of the four depths’ daily VWC. Two types of analyses were conducted for ASM from the ECH<sub>2</sub>O EC-5 sensors, focusing on mean daily soil moisture loss (EC5_ASMLoss), which was the difference between the current ASM and the ASM measured the day before. In the first analysis, the mean daily moisture loss was modeled, stratifying by season (cover crop season vs. cotton season) and controlling for new daily infiltration. In the second analysis, the daily moisture loss was modeled, stratifying by month and controlling for new daily infiltration. Data from January and May were excluded from analysis since these months represented transitional periods in crop establishment and soil moisture data collection. Both types of analyses employed a repeated-measures conditional-means model (controlling for daily new infiltration) where the mean square for error was taken from the observed between-plot variation. All analyses were conducted in R 3.6.2 [<xref ref-type="bibr" rid="scirp.109597-ref21">21</xref>] on a Windows 10 platform (the code for conducting analyses is available upon request). In both sets of analyses, the fitted models were of the form,</p><p>E C 5 _ A S M L o s s i j k = μ + T r e a t i + I n f i l t r a t i o n i j k &#215; β + D a y i j k + P l o t k (1)</p><p>where, D a y i j k ~ N ( 0 , σ d 2 ) , P l o t k ~ N ( 0 , σ ϵ 2 ) , and μ correspond to the average soil moisture loss across all days and plots, and β is a correction factor to accommodate the effect of new daily infiltration on moisture loss. The quantities T r e a t i , I n f i l t r a t i o n i j k , D a y i j k , and P l o t k , represent the treatment effect, observed daily infiltration, treatment/day/plot specific effect, and plot-specific variation, respectively. In each analysis, the data were subset according to records belonging to the desired growing season or months, and individual models were fitted to the data belonging to each stratum.</p></sec><sec id="s2_2_2"><title>2.2.2. Analysis of Neutron Probe VWC Data</title><p>The neutron probe daily soil moisture loss (NP_ASMLoss) data were analyzed using the average soil volumetric water content (VWC) calculated as the arithmetic average of four depths. Because of the frequency of data collection with the neutron probe, we could not conduct the analysis on the average daily moisture loss. Instead, the data analysis focused on mean VWC stratifying by month and growing season (cover crop season or cotton season). In both analyses, the data were stratified according to whichever month/season was of interest, and the following model was fitted:</p><p>N P _ A S M L o s s i j k = μ + T r e a t i + D a y i j k + P l o t k (2)</p><p>where, D a y i j k ~ N ( 0 , σ d 2 ) , P l o t k ~ N ( 0 , σ ϵ 2 ) . All error calculations were made using the between-plot variation i.e. σ ϵ 2 .</p></sec><sec id="s2_2_3"><title>2.2.3. Analysis of Cotton Yield and Cover Crop Biomass Data</title><p>The analyses of the cotton yield and cover crop biomass were conducted using the following models:</p><p>C o t t o n Y i e l d = μ + T r e a t i + P l o t k (3)</p><p>C o v e r C r o p B i o m a s s = μ + T r e a t i + P l o t k (4)</p><p>where, T r e a t i represents the cover crop treatment effect, and P l o t k ~ N ( 0 , σ ϵ 2 ) , the plot-specific variation. A Tukey’s comparison was conducted to compare means amongst the three treatments.</p></sec></sec></sec><sec id="s3"><title>3. Results and Discussion</title><sec id="s3_1"><title>3.1. ECH<sub>2</sub>O EC-5 Sensors Data</title><p>The hourly VWC data are presented in <xref ref-type="fig" rid="fig3">Figure 3</xref>. They were collected from four soil depths using the ECH<sub>2</sub>O EC-5 sensors installed in one of the control plots (plot CC105). <xref ref-type="fig" rid="fig4">Figure 4</xref> illustrates the data included for ASM analyses. The top, middle, and bottom panels panel correspond to the daily ASM values for the plots in the Mixed, None (no cover), and Rye treatments, respectively.</p><p>The results of the by-season and by-month analyses of ASM are presented in <xref ref-type="fig" rid="fig5">Figure 5</xref> and <xref ref-type="table" rid="table1">Table 1</xref>. Due to the scale of the day-over-day differences in ASM, all values were presented as percentages rather than on the original ratio scale. Results of the by-Season Analysis, including the fitted means and associated confidence intervals, are shown in the top panel of <xref ref-type="fig" rid="fig5">Figure 5</xref> and the first block of rows in <xref ref-type="table" rid="table1">Table 1</xref>. We observed that treatment did not significantly impact the mean moisture loss after controlling for daily infiltration. The furthest left point at the top-left panel of <xref ref-type="fig" rid="fig5">Figure 5</xref> indicates that the mean percent ASM loss for the mixed cover crop plots during the cover crop season was −0.25 with a 95% confidence interval of −0.28 to −0.22. These results mean that we expected the</p><p>percent ASM loss to decrease daily for Mix cover crops by −0.25 with the corresponding confidence interval.</p><p>Similarly, the furthest right point (in the top panel) indicates that the mean ASM loss for the rye cover crop during the cotton season was −0.52 with a 95% confidence interval of −0.66 to −0.39. It is worth noting that none of the treatments differed significantly within seasons with respect to the mean percent ASM loss. While the confidence interval for the Mix crop did not overlap with the confidence intervals for the rye and None treatments during the cover crop season, the discrepancy between the mean percent ASM loss can hardly be considered significant from a practical standpoint.</p><p>For the by-month analyses, we observed similar results that are summarized graphically in the bottom panel of <xref ref-type="fig" rid="fig5">Figure 5</xref> and the lower block of rows in <xref ref-type="table" rid="table1">Table 1</xref>. The bottom panel of <xref ref-type="fig" rid="fig5">Figure 5</xref> shows that the furthest-right point corresponds to the mean percent ASM loss for the rye cover crop group during August with a value of −1.23 and a corresponding 95% confidence interval (CI) of −1.58 to</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Estimated mean percent ASM loss. Results are presented for each cover crop type and stratified by cover crop season (Cover Crop vs. Cotton) and month (excluding January and March)</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="5"  >Mean Percent Average Soil Moisture Loss</th></tr></thead><tr><td align="center" valign="middle"  colspan="5"  >By Season</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Season</td><td align="center" valign="middle" >Mix</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Rye</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Cover Crop</td><td align="center" valign="middle" >−0.25 (−0.28, −0.22)</td><td align="center" valign="middle" >−0.18 (−0.21, −0.15)</td><td align="center" valign="middle" >−0.18 (−0.21, −0.15)</td></tr><tr><td align="center" valign="middle"  colspan="2"  >Cotton</td><td align="center" valign="middle" >−0.48 (−0.61, −0.34)</td><td align="center" valign="middle" >−0.52 (−0.66, −0.39)</td><td align="center" valign="middle" >−0.52 (−0.66, −0.39)</td></tr><tr><td align="center" valign="middle"  colspan="5"  >By Month</td></tr><tr><td align="center" valign="middle" >Month</td><td align="center" valign="middle"  colspan="2"  >Mix</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Rye</td></tr><tr><td align="center" valign="middle" >Feb.</td><td align="center" valign="middle"  colspan="2"  >−0.11 (*)</td><td align="center" valign="middle" >−0.15 (*)</td><td align="center" valign="middle" >−0.26 (*)</td></tr><tr><td align="center" valign="middle" >Mar.</td><td align="center" valign="middle"  colspan="2"  >−0.43 (−0.55, −0.32)</td><td align="center" valign="middle" >−0.31 (−0.43, −0.20)</td><td align="center" valign="middle" >−0.38 (−0.5, −0.27)</td></tr><tr><td align="center" valign="middle" >Apr.</td><td align="center" valign="middle"  colspan="2"  >−0.32 (−0.39, −0.26)</td><td align="center" valign="middle" >−0.23 (−0.30, −0.17)</td><td align="center" valign="middle" >−0.31 (−0.38, −0.24)</td></tr><tr><td align="center" valign="middle" >Jun.</td><td align="center" valign="middle"  colspan="2"  >−0.38 (*)</td><td align="center" valign="middle" >−0.35 (*)</td><td align="center" valign="middle" >−0.30 (*)</td></tr><tr><td align="center" valign="middle" >Jul.</td><td align="center" valign="middle"  colspan="2"  >−0.39 (−0.48, −0.29)</td><td align="center" valign="middle" >−0.43 (−0.52, −0.33)</td><td align="center" valign="middle" >−0.54 (−0.63, −0.45)</td></tr><tr><td align="center" valign="middle" >Aug.</td><td align="center" valign="middle"  colspan="2"  >−0.23 (−0.31, −0.15)</td><td align="center" valign="middle" >−0.38 (−0.46, −0.31)</td><td align="center" valign="middle" >−0.40 (−0.48, −0.33)</td></tr><tr><td align="center" valign="middle" >Sep.</td><td align="center" valign="middle"  colspan="2"  >−0.20 (−0.40, 0.00)</td><td align="center" valign="middle" >−0.35 (−0.55, −0.15)</td><td align="center" valign="middle" >−0.39 (−0.59, −0.19)</td></tr><tr><td align="center" valign="middle" >Oct.</td><td align="center" valign="middle"  colspan="2"  >−0.73 (−0.88, −0.59)</td><td align="center" valign="middle" >−0.63 (−0.78, −0.48)</td><td align="center" valign="middle" >−0.82 (−0.97, −0.68)</td></tr><tr><td align="center" valign="middle" >Nov.</td><td align="center" valign="middle"  colspan="2"  >−1.17 (−1.52, −0.82)</td><td align="center" valign="middle" >−1.19 (−1.54, −0.84)</td><td align="center" valign="middle" >−1.23 (−1.58, −0.88)</td></tr><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap><p>−0.88. It is worth noting that, like in the by-season analyses, the Mix cover crop had marginally non-overlapping interval with the other two cover crop types (−0.31 to −0.15 vs. −0.46, −0.31 and −0.48, −0.33 for None and rye cover crop, respectively). However, this was only observed during August and, as such, should not be over-interpreted. In all, we observed no consistent differences in moisture retention when stratifying by-season or by-month.</p></sec><sec id="s3_2"><title>3.2. Neutron Probe Data</title><p>The results from the neutron probe ASM data analyses, both by-season and by-month, are shown in <xref ref-type="table" rid="table2">Table 2</xref> and <xref ref-type="fig" rid="fig6">Figure 6</xref>. The by-month results in <xref ref-type="table" rid="table1">Table 1</xref> show that in February, the mean soil moisture for the Mix cover crop plots was 0.28 with a corresponding confidence interval (0.26, 0.31). The related point in <xref ref-type="fig" rid="fig6">Figure 6</xref> can be found in the bottom panel (black circle and associated line segment illustrating the 95% CI) furthest point to the left. It shows that the rye cover crop had almost consistently (excepting September) the highest average soil moisture. However, when considered in contrast to the expected margins of error, the observed soil moistures offer only marginal evidence that the rye cover crop may increase average soil moisture.</p></sec><sec id="s3_3"><title>3.3. Cover Crop Biomass and Cotton Yield Production</title><sec id="s3_3_1"><title>3.3.1. Cover Crop Biomass Production</title><p>The average biomass production for the Mix, Rye, and None treatments was 4138, 4941, and 1791 kg/ha, respectively. <xref ref-type="fig" rid="fig7">Figure 7</xref>(a) showed no significant difference in biomass production between the Mix and Rye cover crop treatments,</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Mean average soil moisture (95% CI) as measured by neutron probe. Means are presented stratifying by month and cover crop season (note that May was excluded due to cotton crop planting, and there were no neutron probe measurements in June). * denotes that there was not enough between plot variation to estimate the error accurately</title></caption><table><tbody><thead><tr><th align="center" valign="middle"  colspan="4"  >Mean Average Soil Moisture by Neutron Probe</th></tr></thead><tr><td align="center" valign="middle"  colspan="4"  >By Season</td></tr><tr><td align="center" valign="middle" >Season</td><td align="center" valign="middle" >Mix</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Rye</td></tr><tr><td align="center" valign="middle" >Cover Crop</td><td align="center" valign="middle" >0.28 (0.26, 0.31)</td><td align="center" valign="middle" >0.30 (0.27, 0.32)</td><td align="center" valign="middle" >0.32 (0.30, 0.34)</td></tr><tr><td align="center" valign="middle" >Cotton</td><td align="center" valign="middle" >0.21 (0.20, 0.23)</td><td align="center" valign="middle" >0.23 (0.21, 0.24)</td><td align="center" valign="middle" >0.24 (0.22, 0.26)</td></tr><tr><td align="center" valign="middle"  colspan="4"  >By Month</td></tr><tr><td align="center" valign="middle" >Month</td><td align="center" valign="middle" >Mix</td><td align="center" valign="middle" >None</td><td align="center" valign="middle" >Rye</td></tr><tr><td align="center" valign="middle" >Feb.</td><td align="center" valign="middle" >0.28 (0.26, 0.31)</td><td align="center" valign="middle" >0.29 (0.27, 0.32)</td><td align="center" valign="middle" >0.32 (0.29, 0.34)</td></tr><tr><td align="center" valign="middle" >Mar.</td><td align="center" valign="middle" >0.29 (0.27, 0.31)</td><td align="center" valign="middle" >0.31 (0.28, 0.33)</td><td align="center" valign="middle" >0.33 (0.31, 0.35)</td></tr><tr><td align="center" valign="middle" >Apr.</td><td align="center" valign="middle" >0.28 (0.26, 0.30)</td><td align="center" valign="middle" >0.29 (0.27, 0.31)</td><td align="center" valign="middle" >0.31 (0.29, 0.34)</td></tr><tr><td align="center" valign="middle" >Jul.</td><td align="center" valign="middle" >0.21 (0.19, 0.23)</td><td align="center" valign="middle" >0.22 (0.20, 0.23)</td><td align="center" valign="middle" >0.25 (0.23, 0.27)</td></tr><tr><td align="center" valign="middle" >Aug.</td><td align="center" valign="middle" >0.21 (0.19, 0.22)</td><td align="center" valign="middle" >0.23 (0.21, 0.24)</td><td align="center" valign="middle" >0.23 (0.21, 0.24)</td></tr><tr><td align="center" valign="middle" >Sep.</td><td align="center" valign="middle" >0.19 (*)</td><td align="center" valign="middle" >0.21 (*)</td><td align="center" valign="middle" >0.20 (*)</td></tr></tbody></table></table-wrap><p>but the control treatment produced significantly less biomass than the other two treatments. Still, the control treatment without cover crop (None) produced a considerable amount of biomass from weeds. The production of weeds is a problem for farmers since they must be controlled before crop planting. The amount of biomass produced by the Mix and Rye cover crops provides mulch for the cash crop. The mulch could have potential benefits to the soils and cash crop, such as increasing soil organic carbon and carbohydrates, supplying soil Nitrogen, stabilizing soil temperature, suppressing weeds, reducing runoff and soil erosion, among other benefits [<xref ref-type="bibr" rid="scirp.109597-ref2">2</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref4">4</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.109597-ref11">11</xref>]. <xref ref-type="fig" rid="fig7">Figure 7</xref>(b) shows the different species’ biomass in the Mix treatment, which indicates that the rye species predominated. There were insignificant amounts of biomass produced by all the other species. These results suggest that the percentage of rye seeds in the seed mixture should be reduced considerably to allow the other cover crop species in the mixture to grow.</p></sec><sec id="s3_3_2"><title>3.3.2. Cotton Yield Production</title><p>The mean yield was 1259 kg/ha (95% CI 836, 1682) for the Mix cover crop treatment, 1066 kg/ha (95% CI 700, 1433) for the no cover crop (None) treatment, and 1132 kg/ha (95% CI 766, 1499) for the Rye cover crop treatment. The cotton yield analysis showed no significant differences between the mean yields among the three cover crop treatments (<xref ref-type="fig" rid="fig8">Figure 8</xref>).</p></sec></sec><sec id="s3_4"><title>3.4. Impact of Rainfall on Cover Crop Treatment Effect</title><p>The daily and cumulative rain during 2015 at the study site are shown in <xref ref-type="fig" rid="fig9">Figure 9</xref>, and the monthly rainfall totals are shown in <xref ref-type="table" rid="table3">Table 3</xref>. <xref ref-type="fig" rid="fig9">Figure 9</xref> showed frequent rain during 2015, totaling 1315 mm, which was greater than the long-term average for the site (1198 mm per year). Rainfall during the cover crop growing period (January to April) averaged 112 mm/month. Also, there was significant rain (118 mm) in April, which replenished the soil profile just before the cover crop was terminated. Therefore, the soil profile was relatively saturated during the cover crop period, negating the cover crop potential effect on soil water. Although there was little rain in May (10 mm), there was significant rain in early June (95 mm), after the cotton crop was planted, which refilled the soil profile and counteracted any potential carry-over effect of the cover crop on soil water.</p><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Monthly rain (mm) during 2015 in Blackville, SC</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Jan</th><th align="center" valign="middle" >Feb</th><th align="center" valign="middle" >Mar</th><th align="center" valign="middle" >Apr</th><th align="center" valign="middle" >May</th><th align="center" valign="middle" >Jun</th><th align="center" valign="middle" >Jul</th><th align="center" valign="middle" >Aug</th><th align="center" valign="middle" >Sept</th><th align="center" valign="middle" >Oct</th><th align="center" valign="middle" >Nov</th><th align="center" valign="middle" >Dec</th><th align="center" valign="middle" >Total</th></tr></thead><tr><td align="center" valign="middle" >113</td><td align="center" valign="middle" >115</td><td align="center" valign="middle" >102</td><td align="center" valign="middle" >118</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >95</td><td align="center" valign="middle" >62</td><td align="center" valign="middle" >103</td><td align="center" valign="middle" >129</td><td align="center" valign="middle" >205</td><td align="center" valign="middle" >173</td><td align="center" valign="middle" >89</td><td align="center" valign="middle" >1315</td></tr></tbody></table></table-wrap><p>Several rain events in early July also contributed to replenish the soil profile during the early portion of the cotton-growing season. The impact of these rainfall events on soil VWC can be observed in <xref ref-type="fig" rid="fig4">Figure 4</xref>. These timely rainfall events offer some explanation as to why there was no significant effect of the cover crop treatments on soil water, neither during the cover crop season nor during the cotton season. It also demonstrates why there was no treatment effect on cotton yield.</p></sec></sec><sec id="s4"><title>4. Conclusion</title><p>In this experiment, Rye, Mix, and control (None) cover crop treatments were compared to evaluate their effects on soil water during both the cover crop growing season and the cotton-growing season. We also assessed the impact of the cover crop treatments on cover crop biomass production and cotton yield. Time series data of VWC were collected hourly using automatic capacitance soil moisture probes installed at four soil depths. Also, less frequent measurements were taken using a neutron probe. Our results showed that under the conditions of this study, the cover crop treatments had no significant effect on soil water. Also, the cover crop treatments did not affect cotton yield. However, the two cover crop treatments (Mix and Rye) provided a significant amount of biomass compared to the control, potentially offering additional benefits to the soil and the cash crop. The timely and abundant rain observed in this study masked any potential effect of the cover crop on soil water during the study. In this study, the cover crop had no detrimental impact on reducing soil water for the cash crop; however, there are many other beneficial aspects that the cover crop provides for the cash crop including weed suppression and nutrient recycling.</p></sec><sec id="s5"><title>Acknowledgements</title><p>Technical Contribution No. 6980 of the Clemson University Experiment Station. This material is based upon work supported by NIFA/USDA, under project SC-1700593 and SC-170539. Additional funding provided by USDA-NRCS Project number 69-3A75-17-274. Names of commercial products are solely provided as information to the reader and do not imply an endorsement or recommendation by the authors or their organizations.</p></sec><sec id="s6"><title>Conflicts of Interest</title><p>The authors declare no conflicts of interest regarding the publication of this paper.</p></sec><sec id="s7"><title>Cite this paper</title><p>Payero, J.O., Marshall, M.W., Davis, R.H., Bible, J. and Nemire, N. (2021) Effect of Rye and Mix Cover Crops on Soil Water and Cotton Yield in a Humid Environment. Open Journal of Soil Science, 11, 271-284. https://doi.org/10.4236/ojss.2021.115015</p></sec></body><back><ref-list><title>References</title><ref id="scirp.109597-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">R Core Team (2020) R: A Language and Environment for Statistical Computing. 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