Degree-days for predicting smooth crabgrass emergence in cool-season turfgrasses

被引:45
作者
Fidanza, MA
Dernoeden, PH
Zhang, M
机构
[1] Department of Agronomy, Univ. of Maryland, College Park, MD
关键词
D O I
10.2135/cropsci1996.0011183X0036000400029x
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Successful smooth crabgrass [Digitaria ischaemum (Schreber) Schreber ex Muhlenb.] management in turfgrass with herbicides depends on accurate application timing. Little information exists, however, regarding smooth crabgrass seed germination, and there are no reliable methods for predicting crabgrass emergence. The objective of this study was to utilize degree-day (DD) accumulation as a means of predicting smooth crabgrass seedling emergence in cool-season turfgrasses. Smooth crabgrass seedlings were counted and removed from field plot grids on a weekly basis from 1 Apr. to 31 Aug. 1992 to 1994 in turf maintained at two mowing height treatments (i.e., 3.7 or 6.4 cm). Air and soil temperatures at the thatch surface and 2.5 and 5.0 cm below the soil surface were monitored. Soil temperature at the 2.5-cm depth provided the highest correlation with emergence and was used to quantify DD accumulation with a base temperature of 12 degrees C. The mean soil temperatures during the 7-d period prior to seedling emergence were 15.6, 13.9, and 17.5 degrees C in 1992, 1993, and 1993, respectively. Minimum soil temperatures during the same periods of each gear ranged from 10.4 to 12.5 degrees C. A mean soil temperature >22.8 degrees C was required for the emergence of large numbers of seedlings. Smooth crabgrass first emerged between 42 and 78 DD; however, the major emergence period corresponded to a range of 140 to 230 DD. A cumulative percentage emergence model was developed based on DD accumulation, which was accurately described by a Gompertz distribution (r(2) = 0.96).
引用
收藏
页码:990 / 996
页数:7
相关论文
共 28 条
[11]   WEED MANAGEMENT AND TALL FESCUE QUALITY AS INFLUENCED BY MOWING, NITROGEN, AND HERBICIDES [J].
DERNOEDEN, PH ;
CARROLL, MJ ;
KROUSE, JM .
CROP SCIENCE, 1993, 33 (05) :1055-1061
[12]  
DRAPER NR, 1981, APPLIED REGRESSION A
[13]  
ELMORE CL, 1995, P ANN M NE WEED SCI, V49, P69
[15]  
GIANFAGNA AJ, 1951, P AM SOC HORTIC SCI, V58, P291
[16]  
GILMORE E. C., 1958, AGRON JOUR, V50, P611
[17]   A MATHEMATICAL-MODEL TO UTILIZE THE LOGISTIC FUNCTION IN GERMINATION AND SEEDLING GROWTH [J].
HSU, FH ;
NELSON, CJ ;
CHOW, WS .
JOURNAL OF EXPERIMENTAL BOTANY, 1984, 35 (160) :1629-1640
[18]   PREDICTION OF KENTUCKY BLUEGRASS ROOT-GROWTH USING DEGREE-DAY ACCUMULATION [J].
KOSKI, AJ ;
STREET, JR ;
DANNEBERGER, TK .
CROP SCIENCE, 1988, 28 (05) :848-850
[19]   OPTIMIZATION OF WEED MANAGEMENT-SYSTEMS - THE ROLE OF ECOLOGICAL MODELS OF INTERPLANT COMPETITION [J].
KROPFF, MJ ;
LOTZ, LAP .
WEED TECHNOLOGY, 1992, 6 (02) :462-470
[20]   POPULATION MODELING APPROACH FOR EVALUATING LEAFY SPURGE (EUPHORBIA-ESULA) DEVELOPMENT AND CONTROL [J].
MAXWELL, BD ;
WILSON, MV ;
RADOSEVICH, SR .
WEED TECHNOLOGY, 1988, 2 (02) :132-138