Estimation of Bermudagrass Production in Florida
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Permanent Link: http://ufdc.ufl.edu/IR00001507/00001
 Material Information
Title: Estimation of Bermudagrass Production in Florida
Physical Description: Fact Sheet
Creator: Overman, A. R.
Publisher: University of Florida Cooperative Extension Service, Institute of Food and Agriculture Sciences, EDIS
Place of Publication: Gainesville, Fla.
Publication Date: 1997
Acquisition: Collected for University of Florida's Institutional Repository by the UFIR Self-Submittal tool. Submitted by Melanie Mercer.
Publication Status: Published
General Note: "First published May 1991; revised February 1997; reviewed April 2000."
General Note: "Circular 938"
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Source Institution: University of Florida Institutional Repository
Holding Location: University of Florida
Rights Management: All rights reserved by the submitter.
System ID: IR00001507:00001


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CIR938 Estimation of Bermudagrass Production in Florida 1 A. R. Overman, F. M. Rhoads, R. L. Stanley, Jr., and C. G. Chambliss2 1. This document is Circular 938, one of a series of the Department of Agricultural and Biological Engineering, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. First published May 1991; revised February 1997; reviewed April 2000. Please visit the EDIS Web site at http://edis.ifas.ufl.edu. 2. A. R. Overman, Professor, Agricultural and Biological Engineering; F. M. Rhoads, Profeesor, Soil and Water Science; R. L. Stanley, Jr., Associate Professor, Agronomy; and C. G. Chambliss, Associate Professor, Agronomy; Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, 32611. The Institute of Food and Agricultural Sciences is an equal opportunity/affirmative action employer authorized to provide research, educational information and other services only to individuals and institutions that function without regard to race, color, sex, age, handicap, or national origin. For information on obtaining other extension publications, contact your county Cooperative Extension Service office. Florida Cooperative Extension Service/Institute of Food and Agricultural Sciences/University of Florida/Christine Taylor Waddill, Dean. Introduction Bermudagrass is grown extensively in Florida for pasture and hay. Numerous studies have been conducted. Jeffers (1955) compared the response of Coastal bermuda and Pensacola bahia to applied N and water availability. Ruelke and Prine (1971) compared the response of several warm season grasses, including Coastal bertnuda, to applied N. More recently, Rhoads and Stanley (1989) evaluated the response to applied N and S. Mathematical models have been developed to relate dry matter production (Overman et al., 1988; Overman et al., 1990a) and crude protein (Overman and Wilkinson, 1990) to management practices. This publication provides graphical and tabular estimates of production (harvested dry matter and crude protein) in relation to management factors (applied N, harvest interval, and rainfall conditions). Results are drawn from more detailed analysis presented elsewhere (Overman et al., 1990b) and based upon field studies with various soil types (Red Bay sandy loam, Scranton loamy sand, and Dothan loamy sand). The reader is referred to cited articles for more details of the studies and analysis. Results here are given in English units. This article is a companion to one on bahiagrass (Overman et al., 1989). Results A graphical format is used to present the most information in limited space. Figure 1 shows annual dry matter yields (tons/acre) in relation to applied N (lb/acre), harvest interval (weeks) and moisture conditions (optimum season vs. dry season). Figure 2 shows crude protein (%) in relation to applied N and harvest interval. Figure 3 shows cumulative dry matter production over the season for a harvest interval (dt) of 6 weeks, applied N of 100 lb/acre and 200 lb/acre, and optimum and dry seasons. Estimates are also shown in Table 1 for a harvest interval of 6 weeks (a reasonable interval for hay production). Example The graphical procedure is now illustrated. For our example we choose: applied N = 100 lb/acre harvest interval (dt) = 6 weeks


Estimation of Bermudagrass Production in Florida 2 Figure 1 Figure 2 Figure 3 Estimated yields are (Figure 1): optimum season: Yield = 5.0 tons/acre dry season : Yield = 2.5 tons/acre Estimated crude protein (CP) is (Figure 2): CP = 9.0% It should be pointed out that at applied N of 135 lb/acre, dry matter yield is half the maximum potential for that harvest interval and those moisture conditions. Estimated dry matter accumulation over the season is shown in Figure 3. Yields for the dry season are half that for optimum season. Time to accumulate 50% of total dry matter is approximately 27 weeks (July 10). The alternative procedure is to use Table 1. For the harvest interval of 6 weeks and applied N of 100 lb/acre, we read crude protein of 9.2%. Dry matter yield is 5.0 tons/acre (optimum season) and 2.5 tons/acre (dry season). Corresponding N removal is 150 lb/acre and 75 lb/acre, respectively. For average weather conditions, we might average values above to obtain the yield of 3.8 tons/acre and N removal of 110 lb/acre. This latter value suggests removal (110 lb/acre) exceeding application (100 lb./acre). To sustain production, applied N of 150 lb/acre gives 10% crude protein, 4.5 tons/acre and 150 lb/acre N removal for average conditions. Summary This publication has described a graphical procedure for estimating yield and crude protein of bermudagrass in Florida for optimum and dry seasons. While actual yields may vary from year-to-year due to weather conditions, these results show the affect of applied N (lb/acre) and harvest interval (weeks) on production under average conditions. For sustained yields, soil chemistry must be kept in balance by addition of lime, phosphorus, potassium, and micronutrient. Periodic soil tests are recommended for this purpose. References 1. Jeffers, R.L. 1955. Response of warm-season permanent-pasture grasses to high levels of nitrogen. Soil and Crop Science Soc. Fla. Proc. 15: 231-239. 2. Overman, A.R., and S.R. Wilkinson. 1990. Estimation of nitrogen concentration in bermudagrass. Fert. Res. 21: 171-177.


Estimation of Bermudagrass Production in Florida 3 3. Overman, A.R., E.A. Angley, and S.R. Wilkinson. 1988. Empirical model of Coastal bermudagrass production. Trans. Amer. Soc. Agr. Engr. 31: 466-470. 4. Overman, A.R., W.G. Blue and C.G. Chambliss. 1989. Estimation of bahiagrass production in Florida. SS-AGE-918. University of Florida, Gainesville, FL. 5. Overman, A.R., C.R. Neff, S.R. Wilkinson, and F.G. Martin. 1990a. Water, harvest interval and applied nitrogen effects on forage yield of bermudagrass and bahiagrass. Agron. J. 82: 1011-1016. 6. Overman, A.R., F.M. Rhoads, R.L. Stanley, Jr., and O.C. Ruelke. 1990b. Estimation of dry matter production and nitrogen uptake by Coastal bermudagrass in Florida. Florida Agr. Exp. Sta. Tech. Bul. University of Florida, Gainesville, FL. 74 p. (in press). 7. Prine, G.M., and G.W. Burton. 1956. The effect of nitrogen rate and clipping frequency upon the yield, protein content and certain morphological characteristics of coastal bermudagrass (Cynodon dactylon, (L) Pers.). Agron. J. 48: 296-301. 8. Rhoads, F.M., and R.L. Stanley, Jr. 1989. Coastal bermudagrass yield, soil pH, and ammonium sulfatenitrate rates. NFREC, Quincy Research Report 89-9. University of Florida, Gainesville. 11 pp. 9. Ruelke, O.C., and G.M. Prine. 1971. Performance of six hybrid bermudagrass, pangola digitgrass, and Pensacola bahiagrass at three fertility levels in central Florida. Soil and Crop Sci. Soc. Fla. Proc. 31: 67-71.


Table 1. Estimation of Bermudagrass Production in Florida 4 Table 1. Estimates of crude protein and dry matter for bermudagrass harvested every 6 weeks. Optimum season Dry season Applied N, lb/acre Crude Protein, % Dry Matter, tons/acre N removal, lb/acre Dry Matter, tons/acre N Removal, lb/acre 100 9.2 5.0 150 2.5 75 200 11.0 7.0 250 3.5 125 300 12.2 8.8 340 4.4 170 400 13.1 9.8 410 4.9 205 500 13.8 10.4 460 5.2 230