1. Spatial and multi-temporal weed mapping at early stage of cotton crop using GIS Kalivas D.P., G. Economou and Vlachos C.E. Athens 2009 AGRICULTURAL UNIVERSITY OF ATHENS

2. General Scope Spatial mapping of weeds in one of the most important cotton cultivation area in Greece Creation of a Geographical database Influence of abiotic factors and cultivation techniques on weed appearance

3. Questions ? Is there a weed problem Which weeds are the most prevalent during the crucial stages of the crop Are there any new weeds Is pre- emergence control effective Would a geographical database be helpful in taking decision

4.  Estimation of the weed densities  Mapping the weed distribution  Climatic impact on the weed appearence  Correlations between weeds and soil properties  Impact of irrigation system on weeds Objectives

5.  Study area: Karditsa’s prefecture  Crop area: 40000 hectares  Cotton crop is the most important crop  Cotton crop monoculture is using intense cultivation techniques and chemical applications Materials and Methods -1

6. Materials and Methods - 2 Pre- emergence herbicides applied - Karditsa’s prefecture farmers common practices- Active ingredientDose (c.c./ha)% Cultivated area 1Fluometuron + trifluralin3000 - 3300 + 2500 25 2Prometryn + trifluralin3000 + 250015 3Fluometuron330015 4trifluralin250015 5Fluometuron + ethalfluralin3000 + 350010 6ethalfluralin400010 The above herbicides are applied in more than the 90% of the total cultivated area

7. Materials and methods -3  Time of sampling: 2 cultivation periods (2007, 2008) (Before the first mechanical weed control)  Crop stage: Pre- anthesis stage  Grid sapmling scheme: cell size 2,6*2,6km  183 cells were designed only above the cultivated area (lowland)  1 sampling per cell  Final number of samplings: 101 (2007), 80 (2008)

8. Materials and methods -4 Grid applied over the hole prefecture Cell size: 2,6 km x 2,6 km Spatial distribution of the sampling sites Karditsa

9. Materials and methods -5  In each sampling site we sampled 5 different points (each point was 5 m 2 )  Samplings took place between rows  The distance between the points was 3 meters.  Coordinates were recorded from the central point of each area

10. Geographical Database (Using the software GIS ArcMap v. 9.3) Weed density per species Total number of weeds per m 2 Irrigation system (sprinkler and drip) Soil properties (texture, calcium carbonates) Climatic data, 2 meteorological stations (precipitation, temperature ) Coordinates Information input were based on descriptive data Materials and methods -6 Transformed in GIS layers Data collected per sampling site

11. Methods of analysis  Non spatial: Univariate analysis: mean, standard deviation, standard error of mean Bivariate analysis: - correlation coefficient (Pearson correlation coefficient), - comparisons of means (Τ-test) and - analysis of variance (one -way)  Spatial: Examination of the weed spatial distribution and creation of weed appearance interpolated maps (using Inverse Distance Weighting method) Materials and methods -7

12. 2007 Meteorological Data Results- climatic Karditsa station  Mean air temperature 17,5 ο C  Total rainfall 530 mm Dafnospilia station  Mean air temperature 16,4 ο C  Total rainfall 646 mm

13. Results- climatic 2008 Meteorological Data Karditsa station  Mean air temperature 17,5 ο C  Total rainfall 563,3 mm Dafnospilia station  Mean air temperature 16,6 ο C  Total rainfall 273,6 mm The sampling sites were separated in two groups depending on the closest distance from the two meteorological stations No statistically significant differences were found in weed densities between the two groups (T-test)

14. Results- density Cyperus rotundus is the most important weed for both years Total number of weedsCyperus rotundus Weed density appearance in 5 classes (using graduated symbols) yearTotal number (weeds/m 2 ) Cyperus rotundus (weeds/m 2 ) 20074,23,03 20084,033,01

15. Results- density 20072008 Scientific names Mean of weeds ( per m 2 ) Scientific names Mean of weeds ( per m 2 ) 1Cyperus rotundus 3,036 1 Cyperus rotundus 3,016 2Convolvulus arvensis 0,349 2 Portulaca oleracea 0,257 3Portulaca oleracea 0,190 3 Convolvulus arvensis 0,203 4Cynodon dactylon 0,181 4 Cynodon dactylon 0,183 5Sorghum halepense 0,103 5 6 7 8 9 10 11 12 13 14 15 16 17 Solanum nigrum Echinochloa crus-galli Digitaria sanguinalis Sorghum halepense Chrozophora tinctoria Amaranthus retroflexus Amaranthus blitoides Abutilon theophrasti Hibiscus trionum Xanthium strumarium Solanum eleagnifolium Datura stramonium Setaria viridis <0,1 6 7 8 9 10 11 12 13 14 Xanthium strumarium Solanum nigrum Amaranthus retroflexus Chrozophora tinctoria Datura stramonium Echinochloa crus-galli Hibiscus trionum Amaranthus blitoides Abutilon theophrasti < 0,1 Ranking of the weeds based on density (2007,2008)

16. WeedFrequency appearance (%) 1Cyperus rotundus85,1 2Convolvulus arvensis48,5 3Cynodon dactylon39,6 4Solanum nigrum36,6 5Portulaca oleracea24,8 6Xanthium strumarium21,8 7Sorghum halepense16,8 8Chrozophora tinctoria15,8 9Amaranthus retroflexus12,9 10Abutilon theophrasti11,9 1Datura stramonium9,9 1212Amaranthus blitoides8,9 1313Hibiscus trionum7,9 1414Echinochloa crus-galli6,9 Results- frequency Weed Frequency appearance for all 101 sampling points- 2007 Solanum nigrum appears higher in frequency ranking than it does in density ranking

17. Results- frequency Weed Frequency appearance for all 80 sampling points- 2008 WeedFrequency appearance (%) 1Cyperus rotundus 82,5 2Convolvulus arvensis 43,8 3Cynodon dactylon 31,3 4Solanum nigrum 22,5 5Portulaca oleracea 20,0 6Sorghum halepense 12,5 7Chrozophora tinctoria 11,3 8Xanthium strumarium 10,0 9Amaranthus blitoides 8,8 10Datura stramonium 6,3 1Abutilon theophrasti 6,3 1212Amaranthus retroflexus 5,0 1313Hibiscus trionum 3,8 1414Digitaria sanguinalis 3,8 15Echinochloa crus-galli 3,8 16Setaria viridis 1,3 17Solanum eleagnifolium 1,3 The first five weeds appear in the same position for both years

18. Results- spatial distribution In both years the highest values, appear on the southwestern part of the area In 2008 the spatial distribution of the high values are more uniform Total number of weeds (Map of continuous distribution using inverse distance weighing method) 20072008

19. Results- spatial distribution Spatial distribution of Cyperus rotundus in both years is almost the same 20072008

20. Results- spatial distribution Spatial distribution of Convolvulus arvensis’ densities 20072008 C. arvensis’ lower densities values appear in the center of the study area

21. Results- spatial distribution Cyperus rotundus and Convolvulus arvensis are characterized by negative spatial correlation

22. Relative abundance of weeds in Karditsa’s prefecture in 1994-95 Relative abundance % Economou G. et al. Weed Flora Distribution in Greek Fields and Its Possible Influence by Herbicides. Phytoparasitica 33(4): 406-419.

23. 2007 Sprinkler irr.- Mean: 4,64 weeds/ m 2 (74 irrigated sampling sites) Drip irr.- Mean: 2,99 weeds/ m 2 (27 irrigated sampling points) Results- irrigation 2008 Sprinkler irr.- Mean: 4,5 weeds/ m 2 (51 irrigated sampling sites) Drip irr.- Mean: 3,19 weeds/ m 2 (29 irrigated sampling points)

24. Irrigation effect on the density of the most common weeds Statistically significant differences, for 2007: Cyperus rotundus 3,32 plants/ m 2 (sprinkler irrig.) – 2,23 plants/ m 2 (drip irrig.) Convolvulus arvensis 0,42 plants/ m 2 (sprinkler irrig.) – 0,14 plants/ m 2 (drip irrig.) Results- irrigation Statistically significant differences, for 2008: Cyperus rotundus 3,58 plants/ m 2 (sprinkler irrig.) – 2 plants/ m 2 (drip irrig.) Convolvulus arvensis 0,25 plants/ m 2 (sprinkler irrig.) – 0,11 plants/ m 2 (drip irrig.)

25. Soil properties effect on the weed densities Texture ClassSampling points Mean of weeds Si, SiL, FSL, L42 0,1986 SCL, CL, SiCL37 0,1881 SC, SiC, C22 0,9 Total101 0,348 Results- soil properties Reaction with HCL Sampling points Mean of weeds no reaction throughout the surface profile 38 0,249 some reaction occurs deeper than 25 cm 32 0,018 indicates slight reaction in the surface layer (0-25cm) 15 0,693 strong reaction in the surface layer (0-25cm) 16 0,6 Total101 0,348 Mean of C. arvensis plants per m 2, for each class of soil texture Mean of C. arvensis plants per m 2, for each class of CaCO 3 content All differences are statistically significant (p=0,05)

26. Correlations between weed species and between weed species and soil properties Results- correlations 20072008 C.Cp- valueC.Cp- value Cyperus rotundusConvolvulus arvensis -0,270,006-0,190,08 Convolvulus arvensisSoil texture (% clay) 0,330,0010,150,19 >>Carbonates content 0,2170,0290,170,12 Cyperus rotundusTotal density of weeds 0,9210,0000,9250,000 Cynodon dactylonCyperus rotundus -0,2110,034-0,150,18 c.c. Correlation coefficient Cyperus rotundus is negatively correlated with Convolvulus arvensis Convolvulus arvensis is positively correlated with both soil properties Cyperus rotundus is positively correlated with the total density of weeds Cynodon dactylon is negatively correlated with Cyperus rotundus

27. Conclusions 1. Development of a database regarding the appearance of the weeds and the soil parameters in Karditsa’s prefecture cultivation zone using GIS 2. Mapping the most important weeds (Cyperus rotundus) 3. The most important perennial weeds of the area are Cyperus rotundus, Convolvulus arvensis, Cynodon dactylon 4. The most important annual weed was Portulaca oleracea 5. Drip irrigation constitutes a method of side weed control

28. 6. Convolvulus arvensis responses in high carbonate content and in high clay content 7. The two major perennial weeds (Cyperus rotundus and Convolvulus arvensis) of the area, seem to appear in different places, proving a negative spatial relationship 8. Perennial weeds are difficult to control 9. Comparing the results to the respective ones taken in 1994 we observe that the annual weeds are no longer a serious problem for the farmers. Control of annual weeds proves to be effective Conclusions

29. 10. Comparing our results with the previous ones of 1994-95, no new species were recorded 11. 2007 results were very similar to 2008 results regarding the spatial distribution of the main weeds, the density and frequency of the main weeds, and the overall density Conclusions

30. Finally with the developed Geographical database It is easier to:  Monitor the weed appearance in regards to abiotic factors and change of land use  Map the problematic areas (Appearance of new weed species- Development of Resistance)