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Title: Evaluating phenological indicators for predicting giant foxtail (Setaria faberi) emergence

Author
item CARDINA, JOHN - THE OHIO STATE UNIV.
item HERMS, CATHERINE - THE OHIO STATE UNIV.
item HERMS, DANIEL - THE OHIO STATE UNIV.
item Forcella, Frank

Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/17/2007
Publication Date: 8/28/2007
Citation: Cardina, J., Herms, C.P., Herms, D.A., Forcella, F. 2007. Evaluating Phenological Indicators for Predicting Giant Foxtail (Setaria Faberi) Emergence. Weed Science. 55:455-464.

Interpretive Summary: Ornamental plants commonly growing in and near farm sites across the Corn Belt possibly can be used as tools to predict when important weeds germinate and emerge in the spring. Emergence of giant foxtail was monitored for five years in agricultural fields, as were the dates of first flowering and full bloom of 23 ornamental plants. This allowed the creation of a "biological calendar." Growing degree days also were recorded for each year. The biological calendar was associated more closely with foxtail emergence than either calendar days or growing degree days. In addition to being generally more accurate, the biological calendar approach also offers the advantage of providing information on the order of biological events. This allows a greater degree of anticipation of the progress of weed emergence, and it thereby permits farmers to better plan and implement weed management strategies. For example, initial flowering of common lilac precedes 25% emergence of giant foxtail by about 10 days, and full bloom of lilac occurs simultaneously with 25% foxtail emergence. Thus, farmers can recognize at initial lilac flowering that a preemergence herbicide will have to be applied to fields within one week to affect high levels of foxtail control. Farmers, crop consultants, and herbicide applicators will benefit from these results through the enhanced ability to apply herbicides at times that maximize their effectiveness.

Technical Abstract: We evaluated the use of ornamental plants as phenological indicators for predicting giant foxtail emergence, and compared their performance with predictions based upon calendar date, cumulative growing degree-days (GDD) and the WeedCast program. From 1997 to 2001, we monitored giant foxtail emergence in a field experiment with and without fall and spring tillage to estimate the dates of 25, 50 and 80% emergence; we also recorded dates of first and full bloom of 23 ornamental plant species. Dates of weed emergence and ornamental blooming were compiled to create a biological calendar of 54 phenological events for each year. The events were ordered by average (1997 – 2000) cumulative GDD (January 1 start date, 50 deg F base temperature), and the bloom events occurring just before the foxtail emergence events were chosen as the phenological indicators for 2001. The calendar date method used the average (1997 – 2000) dates of foxtail emergence to predict 2001 emergence. The GDD model was chosen by determining the start date and base temperature combination that provided the lowest coefficient of variation for the 1997 – 2000 data (October 1 start date, 0 deg C base temperature). The WeedCast prediction was generated using local soil and environmental data from 2001. The rank order of phenological events in 2001 showed little deviation from the 4-year (1997 – 2000) average rank order. The deviation in sequence for giant foxtail emergence was at most 3 d for 25% emergence and 2 to 10 d for 50 and 80% emergence, depending on tillage treatment. The biological calendar indicated that, on average, 80% of giant foxtail seedlings had emerged when multiflora rose was in full bloom. We compared the biological calendar predictions for 25, 50 and 80% emergence with those based on calendar date, cumulative GDD, and WeedCast. The average deviation in predictions ranged from 4.4 d for the biological calendar to 11.4 d for GDD. In addition to being generally more accurate, the biological calendar approach also offers the advantage of providing information on the order of events, thus helping to anticipate the progress of emergence, and to plan and implement management strategies.