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CROP ECOLOGY, MANAGEMENT & QUALITY

The Influence of Defoliation Timing on Yields and Quality of Two Cotton Cultivars

^a LSU AgCenter, 212-B Macon Ridge Rd., Winnsboro, LA 71295
^b North Carolina State University, P.O. Box 7620, Raleigh, NC 27695
^c North Carolina State University, Department of Crop Science, P.O. Box 7620, Raleigh, NC 27695-7620
^d LSU AgCenter, Dean Lee Research Station, 8305 East Campus Avenue, Alexandria, LA 71302-9306

^* Corresponding author (jfaircloth{at}agcenter.lsu.edu).

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
The timing of certain cotton (Gossypium hirsutum L.) management practices varies according to the yield potential and quality characteristics associated with a variety. A defoliation timing study was performed to (i) determine if certain cultivars respond differently to defoliation timings and (ii) compare the use of the open boll percentage at defoliation (OBPD), nodes above cracked boll (NACB), and micronaire readings at defoliation for their effectiveness in timing defoliation. The study was conducted in 1999, 2000, and 2001. Treatments consisted of two proprietary cultivars (ST 474 and DP 5409), each defoliated on the basis of OBPD measurements. At the time of defoliation, NACB was recorded and lint samples were retained for later high volume instrumentation (HVI) analysis. Neither variety produced consistently higher yields than the other in this study. In 2000, delaying defoliation from 40 to 60 OBPD would have resulted in a significant addition of approximately 75 kg lint ha^–1 for either variety. Stoneville 474 micronaire was highest in all years suggesting that timely defoliation is more critical to ST 474 cotton compared with DP 5409 in years when overall conditions are favorable for high micronaire. DP 5409 fiber length (UHM) values were consistently higher than ST 474 and UHM was unaffected by changes in OBPD values regardless of variety. Stoneville 474 had higher uniformity index (UI) values in all three years and delaying defoliation produced mixed results. The data demonstrate that proper defoliation timing strategies aimed at optimizing quality can vary across varieties. Proper defoliation timing in the two varieties examined in this study varied little with respect to yields. Both NACB and micronaire readings taken at defoliation were more effective for timing defoliation to optimize micronaire readings than OBPD.

Abbreviations: OBPD, open boll percentage at defoliation • NACB, nodes above cracked boll • UHM, staple length • UI, uniformity index

	INTRODUCTION

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THE NECESSITY of defoliating cotton varies annually and is determined by numerous factors including weather patterns, soil type, cotton market value, cultivar, and various input costs. Defoliants are commonly used to terminate cotton development in preparation for harvest. Removal of leaves is necessary because cotton is a perennial plant and leaves have deleterious effects on harvest efficiency and fiber quality. Properly timing defoliation involves balancing the value of potential yield increases and losses with possible alterations in fiber quality and possible discounts. Defoliating cotton to improve grade can negatively affect yield and yield components (Barker et al., 1976). If cotton is defoliated too early, yields can be compromised significantly because boll development is incomplete, whereas delaying defoliation allows immature bolls to develop, potentially enhancing yields (Snipes and Baskin, 1994). However, delaying defoliation increases risks of yield loss to early frosts and inclement weather, both of which are possible in North Carolina during the later boll development period. Defoliation timing also affects various cotton quality characteristics. Later applications of defoliants can result in increased length (UHM), length uniformity (UI) (Laferney et al., 1963), and micronaire (Kelley and Boman 1999, 2000). This situation results in extremely difficult management decisions that indirectly protect against high micronaire readings yet may negatively affect yields and length potential.

Cultivar selection is a critical management tool since both yield and quality characteristics are influenced by genetics (Bradow, 1999). Meredith (1986) reports that cultivar selection accounts for 75% of length variation, whereas 51% micronaire variation is attributed to weather and management with only 25% determined by genetics. Bradow (1999) reports both environmental factors and genotype influence length. Twenty-three years of cotton quality data from the Mississippi River valley delta region indicates that inferior quality (staple length and micronaire) is highly correlated with the introduction of new cultivars (Barnes and Herndon, 1997). Yield and quality responses to defoliation timing vary because of genetic and environmental heterogeneity, regardless of the maturity of the cultivar (Whitwell et al., 1987). Reducing the negative impact of defoliation on yield and quality requires effective decision-making tools.

NACB is a method of timing defoliation where only plants containing a first-position cracked boll are utilized (Kerby et al., 1992). Beginning with the node above the sympodial branch containing the highest first position cracked boll, nodes are counted upward to the node containing the highest harvestable boll. The number of nodes traversed equals the NACB value. Kerby et al. (1992) remarks that using the traditional OBPD measurement as a tool for timing defoliation requires knowledge of flowering period length. If the flowering period is short, the crop will be compact and defoliation could occur before 60 OBPD. If the flowering period is extended, however, the bolls will be distributed throughout the plant and the plant may need more time to develop all bolls fully, thus early defoliation would not be appropriate. Supak et al. (1993) supports the use of NACB as a means of timing defoliation, provided the crop is uniform in emergence and fruiting initiation and retention are normal. Both researchers report no adverse yield or micronaire changes in cotton terminated at NACB 3.

Using OBPD as a predictive model for defoliant timing, Snipes and Baskin (1994) report yield losses and decreases in micronaire resulting from early defoliation and recommend that defoliants be applied after 60% of the bolls are open. Sassenrath-Cole and Hedin (1996) later report boll opening may be more reflective of boll age rather than maturity, thus using OBPD as a benchmark for timing defoliation may result in significant deviations from optimal fiber quality.

The research herein was initiated to examine defoliation-timing effects on reproductive development of two cultivars that differ in micronaire. Additionally, this research compared the use of NACB, OBPD, and micronaire readings taken at defoliation as means of timing defoliation and thus maximizing yields and optimizing micronaire readings at harvest.

	MATERIALS AND METHODS

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The following study was conducted in 1999, 2000, and 2001, on the Central Crops Research Station (CCRS) at Clayton, NC. Treatments consisted of two cultivars, ST 474 (Stoneville Pedigreed Seed, Memphis, TN) and DP 5409 (Delta and Pine Land Company, Scott, Mississippi), defoliated at five maturity stages on the basis of targeted OBPD measurements. ST 474 is an early-maturing cotton cultivar that is high yielding, short staple (length of fiber), and high micronaire (indicator of the fineness or maturity of cotton fiber) relative to other cultivars grown in North Carolina. DP 5409 is an early-maturing cotton cultivar that usually yields less and produces lint with a longer staple and lower micronaire relative to ST 474 (Bowman, 1996). Cotton was planted on 6 May 1999, 9 May 2000, and 11 May 2001, at 44400 seeds ha^–1. Plots contained four rows spaced 1 m apart. In 1999 and 2000, rows were 15.2 m in length and in 2001 rows were 10.7 m in length. A randomized complete block design with a factorial arrangement of treatments replicated four times was used each year. North Carolina Cooperative Extension guidelines were followed regarding insect control, weed control, and fertility (Cotton Information, 2000). All statistical analyses were conducted at the p 0.05 level by SAS software (SAS Inst., 1997).

In September of each year, OBPD measurements were taken several times weekly with target maturity stages at 15, 30, 45, 60, and 85 OBPD. Mean OBPD for each plot was calculated by averaging three random samples of OBPD. Each sample was comprised of bolls from five adjacent plants. In 1999 and 2001, plots were defoliated when OBPD in a treatment averaged across the four replicates approximated the targeted OBPD. The actual percent open recorded at the time of treatment and the amount of rainfall from harvest aid application to harvest is reported in Table 1. Because of field variation in 2000, plots were evaluated and sprayed on an individual basis when the targeted maturity was attained. In all years, mixtures of Finish (ethephon + cyclanilide) at the 1.68 kg ai ha^–1 rate with Dropp (N-phenyl-N, 1, 2, 3-thiadiazol-5-ylurea) at the 0.08 kg ai ha^–1 rate were applied for defoliation while the minimum daily temperature was 13°C. When daily temperatures fell below this point, a mixture of Finish (ethephon + cyclanilide) at the 1.68 kg ai ha^–1 rate, Harvade (2, 3-dihydro-5, 6-dimethyl 1,4 dithiin 1,1,4,4-tetraoxide) at the 0.38 kg ai ha^–1 rate, and Def (S, S, S-tributyl phosphorotrithioate) at the 0.70 kg ai ha^–1 rate was used for defoliation. All defoliation applications were delivered using a CO₂ backpack sprayer with pressure set to 4.22 g cm^–2. The boom sprayed two rows and nozzles were hollow cone TX-6's. The sprayers were calibrated for a 4.8 km h^–1 walking speed before each application and chemicals mixed accordingly.

All data from harvest including lint yield, micronaire, UHM, and UI, were analyzed by a general linear model (GLM), with year, replicate, cultivar, and target OBPD as class variables. Where interactions involving year were significant, GLM was run by year with replicate and cultivar as class variables and OBPD as a continuous variable, fitting linear main effects and cultivar by OBPD interactions. Additionally, GLM was run by year with cultivar as a class variable fitting for OBPD, cultivar, and OBPD within cultivar to generate regression equations relating yield, micronaire readings from lint retained at harvest, UHM, and UI, to OBPD for each cultivar and compare slopes to 0.

In 2000 and 2001, data were taken to compare the use of NACB, micronaire readings taken at defoliation, and OBPD for timing defoliation. Yield was modeled by GLM with year, replicate, cultivar, and the target OBPD as class variables with the method of timing (NACB, micronaire readings taken at defoliation) as a continuous variable. Similar to the previous analyses using OBPD as a continuous variable, GLM was later run by year with cultivar and replicate as class variables and NACB and micronaire readings taken at defoliation as continuous variables, fitting linear main effects and cultivar x method of timing interactions. Again, similar to OBPD analyses, GLM was run by year to generate regression equations relating yield to NACB and micronaire at defoliation for each cultivar and compare slopes to 0. Data from each method of timing defoliation were also used to compare the ability of each method to predict the micronaire values from lint retained at harvest.

	RESULTS

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Yield
The year x cultivar interaction was significant in the model fitting for yield and when models were reanalyzed by year (Table 2). Neither slope was significantly different from 0 in 1999 (Fig. 1). In 2000, the slopes of the regression for each cultivar were different from 0 (Fig. 1) and the OBPD main effect was significant (Table 2). Lastly, in 2001 the slope for ST 474 was not significantly different from 0 while the slope for DP 5409 was significantly different from 0. Thus, delaying defoliation resulted in significant yield improvements for both cultivars in 2000 and only for DP 5409 in 2001. Although yields were not significantly different for either cultivar in 1999 and 2000, yields in ST 474 treatments were significantly higher in 2001 as the cultivar main effect was significant (Table 2). The slopes of DP 5409 treatments in 2000 and 2001 suggest the importance of timely defoliation in DP 5409 with respect to yields.

View larger version (26K): [in this window] [in a new window]   Fig. 1. Relationship between yield and time of defoliation based on various OBPD for two cultivars over 3 yr at Clayton, NC. Each data point represents yield at a particular OBPD measured in an individual plot.

View larger version (20K): [in this window] [in a new window]   Fig. 2. Relationship between micronaire and time of defoliation based on various OBPD's for two cultivars over three years at Clayton, NC. Data are pooled over 3 yr and each data point represents micronaire at a particular OBPD measured in an individual plot.

View larger version (27K): [in this window] [in a new window]   Fig. 3. Relationship between length uniformity (UI) and time of defoliation based on various OBPD for two cultivars over 3 yr at Clayton, NC. Each data point represents UI at a particular OBPD measured in an individual plot.

The ability to evaluate methods of timing defoliation varied on the basis of the predicted parameter (yield or micronaire at harvest). Because of a significant cultivar x micronaire value from lint taken at defoliation interaction, it was impossible to quantitatively conclude that one method of timing defoliation was superior to another with respect to yield (Table 4). Because there was no significant cultivar x method of timing defoliation interaction with respect to micronaire values taken at harvest, values from both cultivars were combined and examined for their relationship with OBPD, NACB, and micronaire values taken at defoliation (Fig. 4). The use of OBPD was the least related to micronaire readings taken at harvests on the basis of R² values. However, all predictors were significant in their ability to predict micronaire at harvest.

View larger version (22K): [in this window] [in a new window]   Fig. 4. Relationship of micronaire values obtained at harvests to 1) micronaire values taken at defoliation, 2) nodes above cracked boll (NACB) taken at defoliation, and 3) the open boll percentage at defoliation (OBPD). Each data point represents micronaire values at harvest resulting from defoliating at a particular micronaire, NACB, or percentage of open boll measurement taken for an individual plot.

	DISCUSSION

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Although total rainfall and heat units [[(daily mean high temperature °C + daily mean low temperature °C)/2]– 16°C] appeared adequate in 1999 (69 cm and 1257), overall yields were lowest in this year (Table 1). This is probably due to damage associated with Hurricane Floyd in September 1999, where 43.18 cm of rainfall accumulated in 26 d. This resulted in flooding and substantial boll rot, confounding yield data in this year. In both 2000 and 2001, rainfall and temperature conditions were adequate (64 cm and 1108 heat units in 2000 and 38 cm and 1072 heat units in 2001) for cotton production in NC. Although not always significantly different from 0, there was a trend associating increasing OBPD with increasing yield. In 2000, predicted yield values demonstrated that delaying defoliation from 40 to 60% would have translated into an additional yield of approximately 75 kg ha^–1. As reported by Bowman (1996), in both 2000 and 2001, ST 474 yields were higher than DP 5409. In 2001, temperatures were abnormally warm during the fall and thus the growing season appeared to have been extended. Consistent with earlier findings, the abnormally warm late season weather may have contributed to high yields in 2001 (Jones and Wells, 1998).

The only micronaire readings that would have resulted in discounts were below the government loan program's acceptable range (3.5–5.0) and most of these readings came from DP 5409 plots. Low micronaire resulting in discounts is uncommon in North Carolina relative to high micronaire discounts. Over the past decade, an average of 2.1% of the cotton harvested in North Carolina has been low micronaire compared to 12.4% high micronaire (Edmisten and Faircloth, 2001). Thus, based on earlier findings concerning the association between environment and micronaire (Meredith, 1986), in years where environmental conditions favor high micronaire, defoliation timing would be more critical when growing ST 474 cotton. Therefore, the cultivar and growing conditions within a particular season should be considered by a producer when making defoliation timing decisions.

Also consistent with cultivar trials performed in North Carolina by Bowman (1996), ST 474 lint was more uniform in length in all three years. On the basis of the government loan program for 2001, most UI values from DP 5409 lint were within the acceptable range (80–82), while many ST 474 UI values were above the acceptable range and could have received a premium for uniformity. As expected, UHM remained unchanged in both cultivars as OBPD values increased. Similar to results in earlier cultivar trials (Bowman, 1996), UHM in DP 5409 plots was consistently higher than ST 474.

With regards to managing for improved micronaire, this study demonstrates the potential use of NACB as an accurate tool for timing defoliation. It appears to be at least as correlated to micronaire values as either OBPD or micronaire values taken at defoliation. Using NACB as an alternative to measuring the OBPD would be more cost-effective as the time required for taking NACB is considerably less. These findings warrant further investigation into the relationship of these techniques to yields in additional locations, environments, and with other cultivars.

Received for publication October 31, 2002.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

• Barker, G.L., C.S. Shaw, K.E. Luckett, and F.T. Cooke, Jr. 1976. Effects of defoliation, plant maturity, and ginning setup on cotton quality and value in the midsouth. United States Department of Agriculture, Agricultural Research Service. ARS-S-120. 27 pp.
• Barnes, M., and C. W. Herndon, Jr. 1997. Causal factors of cotton quality discount and premiums in the mid-south: 1973–1995. 326–330. p. 326–330. In Proceedings of the Beltwide Cotton Conference, New Orleans, LA. 7–10 Jan. 1997. National Cotton Council of America, Memphis, TN.
• Bowman, D.T. 1996. North Carolina measured crop performance soybean and cotton 1996. Official Cultivar Testing, North Carolina State University, Raleigh, NC. Crop Science Research Report No. 163.
• Bradow, J.M. 1999. How genotype and temperature modify yarn properties and dye uptake. p. 510–512. In Proceedings of the Beltwide Cotton Conference, Orlando, FL. 3–7 Jan. 1999. National Cotton Council of America. Memphis, TN.
• Cotton Information. 2000. North Carolina Cooperative Extension Service. North Carolina State University, Raleigh.
• Edmisten, K.L., and J.C. Faircloth. 2001. The 2000 cotton crop. Carolina Cotton Notes 01–3a. http://www.cropsci.ncsu.edu/ccn/2001/ccn-01-1.htm; verified 16 July 2003.
• Jones, M.A., and R. Wells. 1998. Fiber yield and quality of cotton grown at two divergent population densities. Crop Sci. 38:1190–1195.[Abstract/Free Full Text]
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• Laferney, P.E., R.A. Mullikin, and W.E. Chapman. 1963. Effects of defoliation, harvesting, and ginning practices on micronaire reading, fiber properties, manufacturing performance, and product quality of El Paso area cotton, season 1960–1961. United States Department of Agriculture, Agricultural Research Service. Marketing Research Report No. 690.
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• Snipes, C.E., and C.C. Baskin. 1994. Influence of early defoliation on cotton yield, seed quality, and fiber properties. Field Crops Res. 37:137–143.
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This Article Abstract Figures Only Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via ISI Web of Science (1) Citing Articles via Google Scholar Google Scholar Articles by Faircloth, J. C. Articles by Stewart, A. M. Search for Related Content PubMed Articles by Faircloth, J. C. Articles by Stewart, A. M. Agricola Articles by Faircloth, J. C. Articles by Stewart, A. M. Related Collections Cotton Other Fiber Crops Other Oil Crops Production Agriculture