Developing a temperature-light based spatial growth model for purple nutsedge

1. Developing a temperature-light based spatial growth model for purple nutsedge • Ran lati1,2,Hanan Eizenberg2, and Sagi Filin1 • 1Mapping and Geo-Information, Technion - Israel Institute of Technology, 2Newe Ya’ar Research Center, ARO The 2nd International Conference on: Novel and Sustainable Weed Management in Arid and Semi-Arid Agro-Ecosystems

2. Purple nutsedge (Cyperusrotundus) • Among world's most troublesome weeds • High photo-synthetically efficiency (C4 plant) • Rapid growth during the summer in irrigated crops

3. Biology- vegetative growth 45 DAP 14 DAP Rapid spatial growth

4. Purple nutsedge “patches”

5. High infestation level

6. Vegetative spatial-growth model (Webster, Weed Science, 2005)

7. Purple nutsedge spatial-growth gaps of knowledge • Modeling and prediction purple nutsedge spatial growth • Quantification the impact of growth factors • Interaction between growth factors

8. Objectives Developing a spatial-growth predictive model for purple nutsedge Temperature-radiation based model Understanding the relative contribution of temperature and radiation on its growth

9. Field studies 2008 • Weeds grown under diverse environmental condition • Wide range of temperature and radiation • Temperature- weeds were planted at 4 planting dates: Jun. 08, Jul. 08, Aug. 08, Oct. 08 • Radiation- weeds grown under 4 shading levels: • 0%, 20%, 45% and 60%

10. Field study 2008 Individual plants were grown for 60 days One tuber was buried Actual environmental measurements Temperature and radiation were continuously logged Leaf cover area was measured 5 times Using image data methods Weed-growth models Based on temperature and radiation

11. Environmental measurements Temperatures Data logger [C°] Tbase- minimal growth temperature (10°C) Tmean- mean daily temperature Photosynthetic active radiation PAR Pyranometer [µmol m-2 s-1] CPAR-daily cumulative PAR

12. Leaf cover area measurements- using image data

13. Weed-growth models- assumptions • Annual model is composed of seasonal sub-models • Plant's growth is exponentially related to time under optimal and constant conditions • Under varying conditions- plant growth is better described by physiological-time 19:00 7:00 12:00

14. Thermal model (degree-days) L -leaf cover area L0 -initial leaf cover area a -growth rate

15. Photo-thermal model (Effective-degree-day) L -leaf cover area L0 -initial lead cover area a -growth rate EDD- effective-degree-days

16. Effective-degree-day (EDD) The conductance concept: f- PAR coefficient (Aikman and Scaife, Annals of Botany 1993)

17. Environmental growth factors

18. Optimal temperatures for purple nutsedge growth are 25-35°C Naamat et al., current conference

19. Final leaf cover area (SED=0.0874) 28-33°C 18-21°C Final leaf cover area (m2) Planting date

20. Summary • Under optimal temperature, purple nutsedge growth is linearly related to PAR • Below optimal temperature range, PAR level does not affect purple nutsedge growth

21. Predictive growth models

22. Seasonal growth-models Thermal Photo-thermal (Growth season: August-September)

23. Annual growth-model Photo-thermal Growth season: June-December

24. Final conclusions • Temperature • Major growth factor required for purple nutsedge • Insufficient for purple nutsedge spatial growth prediction • PAR • Determines purple nutsedge growth under optimal temperatures conditions • Does not affect purple nutsedge growth below optimal temperature range

25. Final conclusions • The photo-thermal model • Successfully integrates temperature and PAR measurements • Integration of temperature and PAR improves the prediction ability of the model • Enables annual prediction of purple nutsedge spatial growth • Accurate under varying temperature and PAR conditions

26. Thanks • EWRS - for the generous scholarship • Advisors- Hanan and Sagi • Tal L., Gay and Evgeny • Members in the Dept. of Weed Research in NeweYaar • Fellow students- Tal N., Daliya, Shalev , Rim, Fadi and Amit