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

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

Rapid spatial growth Biology- vegetative growth 45 DAP 14 DAP

Purple nutsedge “patches”

High infestation level

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

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

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

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%

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 Individual plants were grown for 60 days One tuber was buried Field study 2008

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

Leaf cover area measurements- using image data

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 7:0012:0019:00

Thermal model (degree-days) L - leaf cover area L 0 - initial leaf cover area a - growth rate

Photo-thermal model (Effective-degree-day) L - leaf cover area L 0 - initial lead cover area a - growth rate EDD- effective-degree-days

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

Environmental growth factors

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

18-21°C28-33°C Planting date Final leaf cover area (m 2 ) Final leaf cover area (SED=0.0874)

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

Predictive growth models

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

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

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

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 Final conclusions

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

Summary The thermal model does not provide satisfying results for purple nutsedge spatial growth prediction The photo-thermal-model successfully integrates different and diverse environmental conditions Integration improves accuracy of purple nutsedge spatial growth prediction The photo-thermal-model provides an accurate annual prediction of purple nutsedge spatial growth, under varying temperatures and PAR conditions

Tuber sprouting Rhizomes elongation Basal bulbs formation Shoot emergence Biology- vegetative growth

l=Ax+Be, e ~ {0,  0 2 P  1 } l- observation vector A- coefficient matrix B- conditions matrix X- vector of unknowns Gauss-Helmets model Least-squares criterion Best linear uniformly unbiased parameters estimator e- observational noise P- weight matrix  variance component

Temperature- weeds were planted at 5 planting dates: Jun. 08, Jul. 08, Aug. 08, Oct. 08 and Jul. 09 PAR- weeds grown under 4 shading levels: 0%, 20%, 45% and 60% Field study

Bermuda grass (Cynodon dactylon) Guglielmini and Satorre, 2002, 2004; Abelleyra et al., 2008 Yellow nutsedge (Cyperus esculentus ) Ranson et al. 2009