Abstract
Phenology is the study of periodic biological events. If we can find easily recognizable events in common plants that precede or coincide with weed emergences, these plants could be used as indicators. Weed seedlings are usually difficult to detect in turf, so the use of phenological indicators may provide an alternative approach to predict the time when a weed appears and consequently guide management decisions. A study was undertaken to determine whether the phenological phases of some plants could serve as reliable indicators of time of weed emergence in turf. The phenology of six shrubs (Crataegus monogyna Jacq., Forsythia viridissima Lindl., Sambucus nigra L., Syringa vulgaris L., Rosa multiflora Thunb., Ziziphus jujuba Miller) and a perennial herbaceous plant [Cynodon dactylon (L.) Pers.] was observed and the emergence dynamics of four annual weed species [Digitaria sanguinalis (L.) Scop., Eleusine indica (L.) Gaertner, Setaria glauca (L.) Beauv., Setaria viridis (L.) Beauv.] were studied from 1999 to 2004 in northern Italy. A correlation between certain events and weed emergence was verified. S. vulgaris and F. viridissima appear to be the best indicators: there is a quite close correspondence between the appearance of D. sanguinalis and lilac flowering and between the beginning of emergence of E. indica and the end of lilac flowering; emergences of S. glauca and S. viridis were predicted well in relation to the end of forsythia flowering. Base temperatures and starting dates required to calculate the heat unit sums to reach and complete the flowering phase of the indicators were calculated using two different methods and the resultant cumulative growing degree days were compared.
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References
Alm DM, McGiffen ME Jr, Hersketh JD (1991) Weed phenology. In: Hodges T (ed) Predicting crop phenology. CRC, Boca Raton, Fla., pp 191–218
Berti A, Dunan C, Sattin M, Zanin G, Westra P (1996) A new approach to determine when to control weeds. Weed Sci 44:496–503
Bradford KJ (2002) Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci 50:248–260
Cantele A (1989) Calchicum autumnale L. Studio dell’accrescimento in ambiente alpino. Agric Ric 94:31–42
Flerchinger GN, Saxton KE (1989a) Simultaneous heat and water model of a freezing snow-residue-soil system. I. Theory and development. Trans ASAE 32:565–571
Flerchinger GN, Saxton KE (1989b) Simultaneous heat and water model of a freezing snow-residue-soil system. II. Field verification. Trans ASAE 32:573–578
Flerchinger GN, Hardegree SP (2004) Modelling near-surface soil temperature and moisture for germination response predictions of post-wildfire seedbeds. J Arid Environ 59:369–385
Forcella F (1998) Real-time assessment of seed dormancy and seedling growth for weed management. Seed Sci Res 8:201–209
Forcella F, Benech-Arnold RL, Sanchez R, Ghersa CM (2000) Modelling seedling emergence. Field Crop Res 67:123–139
Ghersa CM, Holt JS (1995) Using phenology prediction in weed management: a review. Weed Res 35:461–470
Grundy AC (2003) Predicting weed emergence: a review of approaches and future challenges. Weed Res 43:1–11
Hakansson S (2003) Weeds and weed management on arable land. An ecological approach. CABI, Wallingford
Herms DA (1990) Biological clocks: using plant phenology to predict insect activity. Am Nurseryman 172(8):56–63
Herms DA (1998) The flowering sequence of ornamental plants as a tool for predicting the phenology of insect pests. In: Rose MA, Chatfield JA (eds) (1997) Ornamental plants: annual reports and research reviews. Ohio Agricultural Research and Development Center special circular 157. Ohio Agricultural Research and Development Center, Ohio, pp 77–88. http://www.ohioline.osu.edu/sc157/sc157_16.html
Herms DA (1999) Understanding and using degree-days. In: Rose MA, Chatfield JA (eds) (1998) Ornamental plants: Annual reports and research reviews. Ohio Agricultural Research and Development Center special circular 165. Ohio Agricultural Research and Development Center, Ohio, pp 70–76. http://www.ohioline.osu.edu/sc165/sc165_14.html
Herms DA (2000) A biological calendar: using plant phenology to predict insect activity. In: Chatfield JA, Boggs JF, Draper EA, Gao GY (eds) Ornamental plants: annual reports and research reviews 1999. Ohio Agricultural Research and Development Center and Ohio State University Extension special circular 173. Ohio Agricultural Research and Development Center, Ohio State University, Ohio
Johnson BJ, Murphy TR (1994) Herbicide program strategies for controlling annual weed grasses. Ground Maint 4:60–65
Lathrop FH, Dirks CO (1944) Timing the seasonal cycle of insects. J Econ Entomol 37:199–204
Masin R, Zuin MC, Archer DW, Forcella F, Zanin G (2005) Weedturf: a predictive model to aid control of annual weeds in turf. Weed Sci 53:193–201
Mussey GJ, Potter DA (1997) Phenological correlations between flowering plants and activity of urban landscape pests in Kentucky. J Econ Entomol 90:1615–1627
Oriade C, Forcella F (1999) Maximizing efficacy and economics of mechanical weed control in row crops through forecasts of weed emergence. J Crop Prod 2:189–205
Orton DA (1989) Coincide, the Orton system of pest management: timing pest management with ornamental plant development. Plantsmen’s Publications, Flossmoor, Ill.
Orton DA (1996) Using plants to time pest control. Ground Maintenance 1:14–19
Pierson FB, Flerchinger GN, Wright JR (1992) Simulating near surface soil temperature and water on sagebrush rangelands: a comparison of models. Trans ASAE 35:1449–1455
Schwartz MD (2003) Manual of phenological observations. http://www.uwm.edu/~mds/pguide.pdf
Shetlar DJ (2001) Degrees of freedom. Ground Maint 1. http://grounds-mag.com/mag/grounds_maintenance_degrees_freedom
Snyder RL, Spano D, Cesaraccio C, Duce P (1999) Determining degree-day thresholds from field observations. Int J Biometeorol 42:177–182
Spano D, Casareccio C, Duce P, Snyder RL (1999) Phenological stages of natural species and their use as climate indicators. Int J Biometeorol 42:124–133
Throssell C, Weisenberger D (1999) Preemergence Crabgrass Control. http://agry.purdue.edu/turf/report/1999/page33.htm
Wielgolaski FE (1999) Starting dates and basic temperatures in phenological observations of plants. Int J Biometeorol 42:158–168
Yang S, Logan J, Coffey DL (1995) Mathemathical formulae for calculating the base temperature for growing degree days. Agric For Meteorol 74:61–74
Yelverton F (1996) Strategies for turfgrass weed control with preemergence herbicides. http://www.turffiles.ncsu.edu/pubs/weeds/ln&lnd.html
Acknowledgements
This research was supported by the Italian Ministry of Agricultural and Forestry Policies in the special project Inerbimenti e Tappeti Erbosi per la Valorizzazione Agricola, Ricreativa e Sportiva del Territorio (paper no. 165) and, in part, by the Italian National Research Council (CNR) within the activities of the Institute of Agro-Environmental and Forest Biology (IBAF), Weed Science Division of Legnaro (Padova). We thank an anonymous reviewer for comments and suggestions to improve the paper.
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Masin, R., Zuin, M.C. & Zanin, G. Phenological observations on shrubs to predict weed emergence in turf. Int J Biometeorol 50, 23–32 (2005). https://doi.org/10.1007/s00484-005-0266-2
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DOI: https://doi.org/10.1007/s00484-005-0266-2