22835_07_Salonen.indd 189 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. © Agricultural and Food Science Manuscript received December 2004 Weed flora and weed management of field peas in Finland Jukka Salonen, Terho Hyvönen and Heikki Jalli MTT Agrifood Research Finland, Plant Production Research, FI-31600 Jokioinen, Finland e-mail: jukka.salonen@mtt.fi The composition of the weed flora of dry pea (Pisum sativum L.) fields and cropping practices were inves- tigated in southwestern Finland. Surveys were done in 2002–2003 in 119 conventionally cropped fields and 64 fields under organic cropping. Herbicides were applied to 92% of conventionally cropped fields where they provided relatively good control but were costly. Weeds were controlled mechanically only in five fields under organic production. A total of 76 weed species were recorded, of which 29 exceeded the 10% frequency level of occurrence. The average number of weed species per field was 10 under conventional cropping and 18 under organic cropping. The most frequent weed species in both cropping practices were Chenopodium album, Stellaria media and Viola arvensis. Elymus repens was the most frequent grass spe- cies. The difference in species composition under conventional and organic cropping was detected with Redundancy Analysis. Under conventional cropping, features of crop stand and weed control explained 38.7% and 37.6% of the variation respectively. Under organic cropping the age of crop stand and field loca- tion (y co-ordinate) respectively explained best the variation. Weeds could be efficiently managed with herbicides under conventional cropping, but they represented a significant problem for organic production. Mixed cultivation of pea with cereals is recommended, particularly for organic cropping, as it favours crop competition against weeds. Key words: biodiversity, bentazone, herbicides, metribuzin, organic farming, Pisum sativum, Redundancy Analysis, variation partitioning, weeds, weed control Introduction Pea (Pisum sativum L.) is a minor field crop grown only on about 5 000 hectares corresponding rough- ly to 0.25% of the cultivated field area in Finland (Ministry of Agriculture and Forestry 2004). About 34% of that dry pea area was under certified or- ganic production in 2002–2003. Combine-harvest- ed field pea is grown for human consumption, ani- mal feed or seed for sowing. Peas are often grown in a rotation with cereals and also mixed with cere- 22835_07_Salonen.indd 189 12.10.2005 14:10:46 190 A G R I C U L T U R A L A N D F O O D S C I E N C E Salonen, J. et al. Weed flora and weed management of field peas als, particularly with oats (Avena sativa L.) and typically on organic farms. Cereal-dominated crop rotation is typical of conventional farms in south- western Finland, whereas organic crop production aims at more diverse crop sequences. Dry pea pro- duction would provide conventional farms in par- ticular with an excellent alternative crop, but the uncertainty of harvest under rainy conditions in August and high production costs (seed, crop pro- tection, drying) limit expansion of pea cultivation. A research programme, “Pea as a source for domestic protein”, was launched in 2002 in Fin- land to improve crop reliability and economics of pea production through better management. A sub- project of the research programme, a survey of dis- eases, pests and weeds in pea fields, was carried out in 2002–2003. The objective was to establish the major targets for crop protection in order to de- fine control recommendations, particularly in the case of possible marked expansion in pea produc- tion. In addition, the current crop management and crop protection practices for pea cultivation were investigated by interviewing farmers. Published information on diseases, insect pests and weeds of pea fields in Finland is sparse. Re- cent weed research activities have been directed at herbicide testing in field pea (Ruuttunen 1999). On the other hand, there are detailed descriptions of the weed flora in spring cereals from the late 1990s (Salonen et al. 2001a, b). Earlier, an inventory of weeds in organically cultivated cereal fields was carried out on 40–48 farms visited annually in 1984–1986 (Mela 1988). This paper focuses on the results of a weed sur- vey with two specific aims. First, we aimed to study the general patterns of weed community spe- cies composition in relation to crop management in all fields examined. Secondly, we analysed weed communities in conventionally and organically cropped fields separately, aiming to explore the relative importance of different cropping measures as well as other factors explaining the variation in weed species composition. We expected that the application of herbicides with various active ingre- dients would be of central importance in conven- tionally cropped fields, while in organically cropped fields the variation would be explained with various cropping measures of more equal im- portance. Material and methods Study regions, farms and fields The weed survey was carried out in southwestern Finland in 2002–2003 (Fig. 1). The survey regions and farms were randomly selected using national statistics on pea cultivation from previous years provided by the Information Centre of the Minis- try of Agriculture and Forestry. Regions of inten- sive and less intensive pea cultivation were includ- ed. The majority of organic farms studied had con- verted from conventional to organic cropping in the mid-1990s and had carried out organic crop- ping on average for seven years. The number of pea fields examined was 93 in 2002 and 90 in 2003. In both years 32 fields were under organic production. Pea was typically grown in pure stands, but 28% of fields were mixed stands, predominantly (87%) pea with oats. Ac- cording to EU regulations, the proportion of cere- als may not exceed 15% of the weight of sown seed in a mixture. Altogether 11 pea varieties were grown, of which a Swedish variety Karita (55%), a Danish variety Stok (19%) and a Finnish variety Tiina (14%), were the most common varieties, present in almost 90% of survey fields. In most cases there were 1–3 pea fields per farm. The previous crop in pea fields was predom- inantly spring cereal (Table 1). Grassland had been included in crop rotation during the previous five years in 22% of conventional fields studied and in 82% of organic fields. Manure was applied to about 15% of the fields studied and manure was used both in conventional and organic cropping. Weed samples The occurrence of weeds was assessed from five 1.0 m2 (1.0 m × 1.0 m) sample quadrats randomly 22835_07_Salonen.indd 190 12.10.2005 14:10:46 191 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. Fig. 1. Location of surveyed pea fields in southwestern Finland. Table 1. Background information on the cropping practices of studied fields. Number of fields (nominal variables) or median, minimum and maximum (continuous variables) of explanatory variables used in Redundancy Analysis (RDA). Variable (scale or unit) Comment All data (n = 171) Conventional (n = 109) Organic (n = 57) Conventional/organic Farm type 109/62 – – Crop/dairy Cropping practice 117/54 – – Weed control (yes/no) Chemical or mechanical weed control applied 107/64 – – SPATIAL Field size (ha) Size of the field 3.8 (0.1–13) 5 (0.5–12) 3 (0.1–13.3) X co-ordinate X co-ordinate of the field midpoint 3287738 (3197235– 3395928) 3285319 (3197235– 3395928) 3309969 (3211991– 3367192) Y co-ordinate Y co-ordinate of the field midpoint 6737983 (6665859– 6830757) 6737983 (6665859– 6830148) 6735754 (6683866– 6830757) CROP STAND Age of stand (days) Difference between sowing date and sampling date 52 (21–86) 52 (23–75) 51 (21–86) Cover of pea (%) Cover of pea and other crop (data pooled over five sample quadrats) 260 (5–485) 302 (48–485) 180 (5–440) Height of pea (cm) Height of pea in sample quadrat 40 (4–90) 45 (5–90) 25 (4–60) Mixed (yes/no) Pea cropped in the mixture with other crop 48/123 11/98 34/23 22835_07_Salonen.indd 191 12.10.2005 14:10:47 192 A G R I C U L T U R A L A N D F O O D S C I E N C E Salonen, J. et al. Weed flora and weed management of field peas Table 1. Continued Variable (scale or unit) Comment All data (n = 171) Conventional (n = 109) Organic (n = 57) WEED CONTROL Chemical weed control No weed control – 9 – Herb1: Bentazone or bentazone+MCPA Weak effect against POLAV, VIOAR, POAAN and SENVU – 34 – Herb2: Aclonifen or Aclonifen+bentazone or Aclonifen+bentazone+MCPA Weak effect against VIOAR, POAAN and SENVU – 16 – Herb3: Metributzin+bentazone or Metribuzin+bentazone+MCPA or Metribuzin + aclonifen Effective against most broad- leaved species – 8 – Herb4: Metribuzin or Metribuzin+MCPA Weak effect against GALSP – 42 – Non-chemical weed control (yes/no) Mechanical weed control applied – – 5/52 Years in organic production (years) – – 7 (2–25) CROP ROTATION Pre crop Spring cereal 101 71 28 Winter cereal 26 15 10 Grassland 11 1 9 Pea 12 7 4 Sugar beet 9 9 – Other 12 6 6 Grass (yes/no) Grassland in crop rotation 75/96 24/85 47/10 SOIL Soil type Coarse 14 5 8 Clay 151 102 45 Organic 6 2 4 TILLAGE Autumn ploughing 121 81 40 Spring ploughing 15 6 8 Minimum tillage 35 22 9 FERTILIZATION Manure (yes/no) Manure applied as fertilizer 25/146 13/96 12/45 N (kg ha-1) Amount of nitrogen in mineral fertilization and manure 32 (0–100) 44 (0–100) 0 (0–39) P (kg ha-1) Amount of phosphorus in mineral fertilization and manure 6 (0–42) 11 (0–28) 0 (0–32) located in each field. The term frequency refers to the proportion of fields where the species was found in quadrats. In addition, visible patches of the common and troublesome perennial weeds Cirsium arvense, Elymus repens and Sonchus ar- vensis were recorded separately over the whole field. Weed cover was visually assessed and re- corded using a scale of 0–3 (0 = not present, 1 = less than 5% cover, 2 = 5–25% cover and 3 = more than 25% cover) by species. The weed cover data 22835_07_Salonen.indd 192 12.10.2005 14:10:47 193 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. from five sample quadrats were pooled and the sum was used as a measure of weed abundance in the data analyses. The plant species nomenclature follows that of Hämet-Ahti et al. (1998). The full scientific names with attribution are given in Table 2. Bayer codes for weed species (Bayer 1992) are used in the presentation of results. Statistical analyses Conventional and organic production are charac- terised by different crop management practices, including fertiliser application method and amount. Herbicide application in conventional cropping clearly creates a significant selection pressure in weed communities (Hald 1999, Hyvönen and Sa- lonen 2002, Poggio et al. 2004) that is absent in organic cropping. Several factors associated with crop rotation, crop management and diverse envi- ronmental variables, should be taken into account (see e.g. Haas and Streibig 1982, Rydberg and Milberg 2000). Therefore, the application of mul- tivariate methods was considered appropriate for analysing these complex data (see e.g. Salonen 1993, Hallgren et al. 1999, Lepŝ and Šmilauer 2003). The complete data set derived from 183 fields that were used in frequency calculations (Table 2). In the ordination analyses some fields were ex- cluded due to missing data of explanatory varia- bles (see Table 1 for the number of fields in each analysis). Data on factors involved in each field were collected through observation, measurement or by interviewing the farmer. The statistical anal- yses were performed either using SAS procedures (version 8.2., SAS Institute Inc. 1999) or with CANOCO 4 software (ter Braak and Šmilauer 1998). The preliminary analysis of the data was con- ducted using Detrended Correspondence Analysis (DCA) to measure the lengths of gradients. Since the lengths of gradients for the first and the second DCA axes were short (2.4 and 2.5, respectively), an analysis with the linear response model (i.e. Re- dundancy Analysis, RDA) was considered more appropriate than analysis with the unimodal re- sponse model (i.e. Canonical Correspondence Analysis, CCA) (see Lepŝ and Šmilauer 2003). The default options of CANOCO were applied. All the species for which there was a single observa- tion (13 species in all data, 15 species in organi- cally cropped fields and 18 in conventionally cropped fields) were given a zero weight in the analyses (i.e. they did not affect the analyses). In the first series of analyses of complete data, all explanatory variables (see Table 3) were in- cluded in the forward selection procedure of CANOCO. The statistical significance of the terms was tested using the unrestricted Monte Carlo per- mutation test (999 permutations). Explanatory variables with a P-value > 0.05 were excluded from further analyses (Table 3). For the explora- tion of general patterns in species composition of the weed community, and the relationship between the species composition and explanatory variables, RDA was conducted on the species matrix con- strained by statistically significant explanatory variables (Fig. 2). The significance of the first RDA axes and the overall significance of the RDA mod- els were evaluated using Monte Carlo permutation tests with trace as a test statistic and 999 permuta- tions. In the second series of analyses, weed commu- nities of conventionally and organically cropped fields were analysed separately (data on 109 and 57 fields, respectively). The relative importance of various factors was studied using variation parti- tioning (Borcard et al. 1992). For variation parti- tioning, the explanatory variables were classified into seven groups (Table 1). The variables includ- ed in the groups of weed control and fertilization differed between cropping practices (see Table 3). All groups of explanatory variables were submit- ted to the forward-selection procedure, and the fol- lowing series of analyses were conducted with statistically significant explanatory variables: 1) RDA of the species matrix constrained by the ma- trix of each group of significant explanatory vari- ables one at a time and 2) partial RDA of the spe- cies matrix constrained by the matrix of each group of significant explanatory variables one at a time and using one of the other matrices as a covariate. Variation partitioning was conducted by applying 22835_07_Salonen.indd 193 12.10.2005 14:10:47 194 A G R I C U L T U R A L A N D F O O D S C I E N C E Salonen, J. et al. Weed flora and weed management of field peas the variation explained by the explanatory varia- bles, i.e., the sum of all canonical eigenvalues in RDA analysis where all significant explanatory variables and no covariables were included in the analysis, as a measure of the total variation (Øk- land and Eilertsen 1994, Økland 1999). Results Weed species composition and weed cover A total of 76 weed species were recorded in sam- ple quadrats. The 29 most frequent weed species were found in more than 10% of surveyed fields (Table 2). The average number of weed species per field was 10 (min 3, max 21) under conventional cropping and 18 (min 8, max 31) under organic cropping. The most frequent weed species in both crop- ping systems were Chenopodium album, Stellaria media and Viola arvensis (Table 2). Of the total 76 recorded weed species 59 species occurred in con- ventionally cropped fields and 68 species in or- ganically cropped fields. There were 17 weed spe- cies that were found only in organically cropped fields (e.g. Achillea millefolium L., Barbarea vul- garis R.Br., Rumex longifolius DC. and Sonchus asper (L.) Hill). On the other hand, 8 weed species (e.g. Atriplex patula L., Avena fatua L., Solanum nigrum L.) were found occasionally in some con- ventionally cropped fields. In some fields volun- teer crop plants including Avena sativa L., Hor- deum vulgare L., Linum usitatissimum L. and Phleum pratense L. occurred as weeds. To supplement information on the most com- mon perennial weed species in our random sample quadrats, comprehensive observation of weed patches increased the number of fields infested with Cirsium arvense (frequency 33% vs. 43%). This suggested that growth of C. arvense was more patchy, or the patches were higher and more visi- ble than those of Elymus repens and Sonchus ar- vensis in early July. In all, these three perennial species were more frequently found in organic fields than in conventional fields (Table 2). The observed weed cover of individual species was usually less than 5%, corresponding to the rank value 1 on the scale for visual observation. The crop cover, pea alone or pea with cereal, was on average 60% under conventional cropping and 40% under organic cropping in early July. On some organic farms pea stands completely failed follow- ing poor crop emergence and/or vigorous weed growth. In the analysis of the comprehensive data (all 171 fields) using RDA, only eight variables proved to be statistically significant in the forward selec- tion procedure (Table 3). The first RDA axis cap- tured 13.5% of the variation in the species compo- sition and 67.1% of the variation in the species- environment relation; the second RDA axes cap- tured only a minor portion of the variation (2.2 and 11.1%, respectively). A Monte Carlo permutation test showed both the first and all RDA axes togeth- er to be statistically significant (P < 0.01). The main gradient in the variation in species composition along the first ordination axis was the difference between conventionally and organically cropped fields (Fig. 2). In addition to cropping practices, the first axis was related to weed control and grassland-dominated crop rotations. The most dominant species included herbicide-susceptible Spergula arvensis and Erysimum cheiranthoides as well as species typical of grassland-dominated crop rotations, e.g. Elymus repens, Ranunculus re- pens and Plantago major. The second axis was related to properties of the crop stand (cover and age) as well as soil type and tillage. The most dom- inant species included herbicide tolerant Galium spurium and Fumaria officinalis. Cropping practices Chemical weed control was practised on 92% of conventionally cropped fields. Bentazone and metribuzin were the most frequently applied active ingredients. Other compounds applied were aclon- ifen or MCPA mixed with bentazone. In addition 22835_07_Salonen.indd 194 12.10.2005 14:10:47 195 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. Table 2. Frequencies of occurrence (%) of 32 most frequent weed species in pea fields. Species/Taxon Bayer code Production type Total Conventional Organic Unsprayed Sprayed All Achillea millefolium L. ACHMI 0 0 0 8* 3 Brassica rapa L. ssp. oleifera (DC.) METZG. BRSRO 22 10 11 25* 16 Capsella bursa-pastoris (L.) MEDIK. CAPBP 22 17 18 47* 28 Chenopodium album L. CHEAL 89 68 70 97* 79 Cirsium arvense (L.) SCOP. CIRAR 22 21 21 56* 33 Elymus repens (L.) GOULD AGRRE 67 56 57 75* 63 Equisetum arvense L. EQUAR 22 12 13 22 16 Erysimum cheiranthoides L. ERYCH 78 38 41 81* 55 Fallopia convolvulus (L.) À.LÖVE POLCO 44 55 55 75* 62 Fumaria officinalis L. FUMOF 67 55 56 72 62 Galeopsis L. spp. GAESS 78 55 57 97* 71 Galium spurium L. a GALSP 33 65 63 59 62 Gnaphalium uliginosum L. GNAUL 11 2 3 13* 6 Lamium L. spp. LAMSS 11 43 40 56* 46 Lapsana communis L. LAPCO 56 40 41 70* 51 Matricaria matricarioides (LESS.) PORT. MATMT 11 10 10 30* 17 Myosotis arvensis (L.) HILL MYOAR 56 16 19 47* 32 Persicaria lapathifolia (L.) GRAY POLLA 33 12 13 59* 30 Plantago major L. PLAMA 11 7 8 20* 12 Poa annua L. POAAN 22 12 13 17 14 Polygonum aviculare L. POLAV 44 44 44 47 45 Ranunculus repens L. RANRE 11 4 4 22* 10 Sonchus arvensis L. SONAR 67 44 45 80* 57 Spergula arvensis L. SPRAR 56 15 18 70* 36 Stellaria media (L.) VILL. STEME 67 68 68 92* 77 Taraxacum officinale WEBER in WIGGERS TAROF 0 11 10 17 13 Thlaspi arvense L. THLAR 22 12 13 47* 25 Trifolium L. spp. TRFSS 67 21 24 63* 38 Tripleurospermum inodorum (L.) SCH.BIP. MATIN 33 40 39 73* 51 Tussilago farfara L. TUSFA 0 3 3 16* 7 Vicia cracca L. VICCR 11 7 8 27* 14 Viola arvensis MURRAY b VIOAR 100 79 81 81 81 Number of fields 9 110 119 64 183 a = incl. G. aparine, b = incl. V. tricolor * Significant difference in frequencies between “Conventional All” and “Organic” (Fisher’s Exact Test, P < 0.05) to the relatively effective control of broad-leaved weeds, grass weeds, Elymus repens in particular, were controlled separately with selective gramini- cides, including fluazifop-P-butyl, propaquizafop and quizalofop-P-ethyl. However, selective grass weed control was not a common practice and was carried out only on seven of 119 conventionally cropped fields. In organically cropped fields, me- chanical weed control, namely harrowing, was carried out only in five fields (i.e. 9%). More than 80% of survey fields were ploughed, mainly in au- tumn, but in some cases in the spring. In conventionally cropped fields, the RDA analysis showed that the characteristics of crop stand – the height of pea, the age of crop stand and the mixed crop stand – were the most important 22835_07_Salonen.indd 195 12.10.2005 14:10:48 196 A G R I C U L T U R A L A N D F O O D S C I E N C E Salonen, J. et al. Weed flora and weed management of field peas Table 3. Explanatory variables included in the forward selection procedure of Redundancy Analysis (RDA), their conditional variances and statistical significance. Statistical significance of variables was determined by forward selection in RDA with the unrestricted Monte Carlo (n = 999) permutation test. Variable Code All data Conventional Organic Conditional variance1 P-value Conditional variance1 P-value Conditional variance1 P-value Conventional/organicORGANIC 0.12 0.001* – – – – Crop/dairy CROP 0.01 0.101 – – – – Weed control WCTRL 0.02 0.001* – – – – SPATIAL Field size AREA 0 0.424 0.01 0.539 0.02 0.154 X co-ordinate X 0.01 0.086 0.01 0.122 0.03 0.185 Y co-ordinate Y 0.01 0.048* 0.02 0.040* 0.03 0.020* CROP STAND Age of stand AGE 0.01 0.001* 0.03 0.002* 0.03 0.036* Cover of pea COVER 0.01 0.003* 0.01 0.241 0.02 0.140 Height of pea HEIGHT 0.01 0.205 0.03 0.001* 0.02 0.516 Mixed/Non-mixed MIXED 0 0.329 0.02 0.022* 0.02 0.442 WEED CONTROL Chemical None NHERB – – 0.02 0.003* – – Herb1 HERB1 – – 0.04 0.001* – – Herb2 HERB2 – – 0.02 0.135 – – Herb3 HERB3 – – 0.02 – – – Herb4 HERB4 – – 0.03 0.008* – – Non-chemical NONCHE – – – – 0.01 0.794 Years in organic production OYEARS – – – – 0.02 0.625 CROP ROTATION Pre crop Spring cereal SPRINGC 0 0.736 0.01 0.417 0.02 0.114 Winter cereal WINTERC 0 0.271 <0.01 0.732 0.01 0.955 Grassland GRASS 0.01 0.760 0.02 0.085 0.01 0.613 Pea PEA † † 0.01 0.286 0.01 † Sugar beet SUGAR 0 0.111 <0.01 † † † Other OCROP 0.01 0.347 0.01 0.400 0.03 0.258 Grass/No grass GROT 0.01 0.014* 0.02 0.009* 0.01 0.723 SOIL Soil type Coarse COARSE 0.01 0.073 0.01 0.192 0.02 0.201 Clay CLAY 0.02 0.001* 0.01 0.391 0.03 0.055 Organic ORG † † 0.01 † 0.03 0.072 TILLAGE Autumn ploughing APLOUGH 0.01 0.116 0.01 0.344 0.02 0.354 Spring ploughing SPLOUGH 0.01 † 0.01 † 0.02 0.161 Minimum tillage MTILLAGE 0.01 0.028* 0.01 0.076 0.02 † FERTILIZATION Manure MANURE 0 0.818 <0.01 0.936 0.02 0.651 N N 0.01 0.905 0.01 0.538 – – P P 0.01 0.430 0.01 0.509 – – 1 The share of variance explained by each variable at the time it was included in the model. *Included in the further analyses. †No value received in the RDA analysis. 22835_07_Salonen.indd 196 12.10.2005 14:10:48 197 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. -3 0 3 -6 0 6 Organic Conventional -1 0 1 -0,4 0,0 0,4 B) A) WCTRL AGE CLAY COVER Y GROT MTILLAGE ORGANIC CIRAR POLCO FUMOF CHEAL STEME BRSRO GALSP LAMSS VIOAR TRFSS POLAV GAESSVICCR MATIN SONAR THLAR EQUAR CAPBP ERYCH LAPCOGNAUL MYOARMATMT TAROF TUSFA POLLAPOAAN ACHMI PLAMA SPRARAGRRE RANRE Fig. 2. Redundancy Analysis (RDA) of weed species and all statistically significant explanatory variables. Plot of species (only 32 most frequent species are shown) and ex- planatory variables (A) and of fields (B). Eigenvalues for axes 1 and 2 are 0.135 and 0.022, respectively. See Table 3 for abbreviations of explanatory variables and Table 2 for abbreviations of species’ names. factors (with 38.7% share) explaining variation in the species composition (Table 4). In general, con- ventional pea stands were higher and denser than those of organic pea (Table 1). Application of her- bicides was the second most important group of factors explaining variation (with 37.6% share) in species composition. Within the weed control group, the application of bentazone alone or benta- zone with MCPA, and application of pure metribuz- in or metribuzin with MCPA, were the most im- portant explanatory variables. In the RDA analysis of organic fields, the two significant variables – y co-ordinate and age of crop stand – explained almost equal shares of the variation, 51.7% and 48.3%, respectively. The variables for weed management were not statisti- Table 4. Partitioning of variation among the groups of variables for conventionally cropped fields. Variation explained (%) by Variable X Covariable Y Variable X Joint of X and Y Covariable Y Other Weed control All variables 37.6 7.6 54.8 0 Crop stand 41.4 3.8 40.3 14.5 Crop rotation 43.0 2.2 9.7 45.1 Spatial 42.5 2.7 6.5 48.3 Crop stand All variables 38.7 5.4 55.9 0 Crop rotation 41.9 2.1 9.7 46.3 Spatial 44.6 –0.5 9.7 46.2 Crop rotation All variables 8.1 3.7 88.2 0 Spatial 10.8 1.1 8.1 80 Spatial All variables 5.9 3.2 90.9 0 22835_07_Salonen.indd 197 12.10.2005 14:10:49 198 A G R I C U L T U R A L A N D F O O D S C I E N C E Salonen, J. et al. Weed flora and weed management of field peas cally significant in the forward selection procedure (Table 3). Discussion The total number of weed species (76) recorded in pea fields illustrates the species richness of arable fields. It was, however, lower than the number of species (188) recorded in a survey of spring cere- als (Salonen et al. 2001a). An obvious reason for this is that a smaller number of fields were sur- veyed in a more restricted geographical area. Con- sequently, our data set consisted mainly of samples from clay soils, which are predominant in south- western Finland. In comparison with earlier stud- ies in organically cultivated cereals fields, in the mid-1980s Mela (1988) found 103 weed species or taxa (221 fields studied) and Salonen et al. (2001b) in the late 1990s found 126 species or taxa (165 fields studied). In all surveys the most frequently occurring species were the same, but they ranked slightly differently. Similarities in weed flora of pea fields were recorded at the European level (Uludag et al. 2003). The composition of weed flora is a result of long-term cropping histories, management practic- es and environmental conditions (see e.g. Håkans- son 2003). As a consequence of such selection pressure within weed flora Chenopodium album, Galeopsis spp. and Stellaria media are characteris- tic of cereal-dominated rotations in Finland and have been among the most common species in all weed surveys of spring cereals (Mukula et al. 1969, Erviö and Salonen 1987, Mela 1988, Salonen et al. 2001a) as well as e.g. in organic spring cereals in Sweden (Rydberg and Milberg 2000). Clearly, the same weed species emerging from an established seed bank dominated our survey fields where pea was a component of cereal-based crop sequences. Moreover, the three mentioned species seem to be particularly typical of organic pea production as they exceeded the frequency level of 90%. As expected, most variation in the species composition was established between organic and conventional cropping practices. The difference between cropping measures was related to weed control and the inclusion of grassland in the crop rotation. Both of these factors were also important in the separate analysis of conventionally cropped fields. The importance of weed control was not surprising since application of herbicides was shown to be an important factor previously (Hald 1999, Hyvönen and Salonen 2002, Hyvönen et al. 2003). In contrast, the effect of crop rotation has often been shown to be weak (Bàrberi et al. 1997, Andersson and Milberg 1998, Doucet et al. 1999), unless grasslands are included in the rotation (Paatela and Erviö 1971, Sjursen 2001). Evidently, organically cropped fields had more diverse crop rotation histories than conventionally cropped fields. The inclusion of grassland in a crop rotation increased the abundance of some perennial species (e.g. Ranunculus repens and Achillea millefolium) that are adapted to grasslands (Raatikainen and Raatikainen 1975). In both cropping practices, the characteristics of crop stand explained a large share of the varia- tion in the species composition. Age of crop stand, i.e. the difference between sowing and sampling dates, was an important variable among the crop stand characteristics. Apparently, competitive abil- ity of crop stand is an important factor for reducing weed problems, especially under organic cropping where application of herbicides is avoided (Bond and Lennartson 1999). Pea breeding programmes in Finland have been successful in increasing the protein content of peas and developing high-yield- ing semileafless afila-type varieties (Hovinen 1988). However, such varieties are poor competi- tors against weeds. Competitive ability of pea stands should be taken into account when breeding new cultivars. Meanwhile, effective direct weed control is a prerequisite for a high pea yield. Lawson (1983) showed that even though high- density pea stands suppress weeds very effectively, densely sown pea is no less vulnerable to yield loss than those at lower density are. In Finland the rec- ommended crop density for semileafless pea is 110–120 plants m-2 (Laine and Kontturi 2002). The plant density was not recorded in our survey fields but the cover assessments indicate that in many 22835_07_Salonen.indd 198 12.10.2005 14:10:49 199 A G R I C U L T U R A L A N D F O O D S C I E N C E Vol. 14 (2005): 189–201. cases the crop stand was not dense enough to com- pete against the weeds effectively. Intercropping of pea with cereals would evidently improve weed growth suppression (Hauggaard-Nielsen et al. 2001, Poggio 2005). Weed management did not explain the varia- tion in the species composition in organically cropped fields. Organic crop production aims at maintenance of weeds at a manageable level by cultural means (Bond and Lennartsson 1999). Weed management strategies should include di- verse applications of crop rotation, cultivations, crop density, cultivar selection and mechanical control (Stopes and Millington 1991). Unfortu- nately, only a few of the survey farms carried out mechanical weed control even though it might have provided at least moderate control at an ac- ceptable risk of crop damage (Larsen and An- dreasen 2004). Organic farming appears to be ben- eficial for biodiversity since the number of weed species is often higher than in conventional farm- ing (e.g. Hald 1999, Salonen et al. 2001a). This is in agreement with our results from pea fields. The efficacy of chemical control was relatively good in most of the survey fields. For conventional cropping, the selection of herbicides available seems to be satisfactory for adequate weed control, but control costs are high. Mixtures of different ac- tive ingredients were commonly applied to broad- en the control spectrum since e.g. Galium spurium was clearly a problem weed that remained in fields treated with metribuzin alone. Likewise, Fallopia convolvulus, Polygonum aviculare or Viola arven- sis were not properly controlled with some other herbicides applied alone. However, even sensitive species like Chenopodium album and Stellaria me- dia having a long period of emergence (Erviö 1981) were frequent in conventional fields, al- though much less abundant than in organic fields. The cost of herbicides applied at the recom- mended rates varied between € 29–95 ha-1 in Fin- land in 2004. In Finnish field experiments the yield increase achieved with chemical weed control has reached 500 kg ha-1 (Pessala and Erviö 1979, Ruut- tunen 1999). However, as mentioned by Knott (1994), it is questionable to recommend chemical weed control as being always economic at the cur- rent price level of food peas, € 200–250 per 1 000 kg (Ministry of Agriculture and Forestry 2004). Nevertheless, herbicide use is advisable as it repre- sents a long-term strategy to keep the weed pres- sure at a low level. In conclusion, the weed flora of pea fields was similar to that recorded in earlier surveys of spring cereal fields. Weeds can be efficiently managed with herbicides under conventional cropping but represent a great problem under organic cropping in which implementation of mechanical weed con- trol methods is advisable in order to reduce yield losses. Mixed cultivation of pea with cereals is recommended, particularly under organic crop- ping, as it favours crop competition against weeds. Weeds can not be regarded as a particular dis- incentive to planned expansion in pea production although they are expensive to control under con- ventional cropping and challenging to manage un- der organic cropping. Acknowledgements. The weed survey was part of the re- search programme “Pea as a source of domestic protein“, coordinated by Professor Pirjo Peltonen-Sainio. We thank farmers who allowed us to visit their fields and provided us with information about farming practices. The authors acknowledge the efforts of Dr. Erja Huusela-Veistola in the arrangement of farm visits and preparatory steps of data handling. Both Erja and Mr. Pentti Ruuttunen gave valuable comments on the manuscript. The survey was fi- nanced by MTT Agrifood Research Finland and the Min- istry of Agriculture and Forestry. References Andersson, T.N. & Milberg, P. 1998. Weed flora and the rela- tive importance of site, crop, crop rotation, and nitro- gen. Weed Science 46: 30–38. 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SELOSTUS Hernepeltojen rikkakasvit ja niiden torjunta Suomessa Jukka Salonen, Terho Hyvönen ja Heikki Jalli MTT (Maa- ja elintarviketalouden tutkimuskeskus) MTT:n tutkimushankkeeseen ”Kotimaista valkuaista herneestä” sisältyi vuosina 2002–2003 hernepeltojen rik- kakasvikartoitus Varsinais-Suomessa, Hämeessä, Sata- kunnassa ja Uudellamaalla. Tutkimustilat valittiin satun- naisesti käyttäen apuna tilastotietoa (MMM/TIKE) her- neen viljelyn laajuudesta vuosina 1997–2001. Otantaan sisältyi ruokaherne-, rehuherne- ja seoskasvustoja alueil- ta, joilla herneen viljelyn yleisyys vaihtelee. Rikkakasvit kartoitettiin, jotta voitaisiin todeta, mitkä rikkakasvilajit ovat yleisimpiä ja runsaimpia herneviljelyksillä, mitkä tekijät vaikuttavat rikkakasvien esiintymiseen ja miten hyvin rikkakasvien torjunta onnistuu kemiallisesti. Vuonna 2002 kartoitettiin 93 peltoa ja vuonna 2003 90 peltoa. Kartoitukseen sisältyi 64 luonnonmukaisesti ja 119 tavanomaisesti viljeltyä peltoa, joiden rikkakasvit määritettiin heinäkuun alussa. Rikkakasvien esiintymi- nen havainnoitiin viideltä 1 m2 näytealalta käyttäen luo- kittelevaa peittävyysasteikkoa (0–3). Lajiston koostu- muksen vaihtelua ja sitä selittäviä tekijöitä tutkittiin redundanssianalyysin (RDA) avulla. Hernepelloilta tavattiin yhteensä 76 rikkakasvilajia. Yleisimpiä rikkakasveja olivat jauhosavikka, pillikkeet, pihatähtimö ja pelto-orvokki. Yleisin kestorikkakasvi oli juolavehnä, jota tavattiin 57 %:lla tavanomaisesti viljel- lyistä ja 75 %:lla luonnonmukaisesti viljellyistä pellois- ta. Leveälehtisistä kestorikkakasveista peltovalvatti oli yleisempi kuin pelto-ohdake. Hernepeltojen rikkakasvi- lajisto oli paljolti samanlaista kuin aiemmissa kartoituk- sissa havaittu kevätviljapeltojen lajisto. Tuotantomuoto vaikutti rikkakasvilajistoon. Tavan- omaisesti viljellyillä pelloilla kasvoi keskimäärin 10 lajia ja luomupelloilla 18 lajia. Luomupeltojen rikkakasvilli- suus koostui pitkälti samoista lajeista, sillä peräti 12 lajia tavattiin yli 70 %:lla tutkituista luomupelloista. Tavan- omaisesti viljellyillä hernepelloilla lajisto sen sijaan vaih- teli lähinnä sen mukaan, mitä torjunta-ainetta oli käytetty. Rikkakasvien torjunta-aineista kolme selvästi eniten käytettyä olivat Senkor (metributsiini), Basagran SG (bentatsoni) ja Basagran MCPA (bentatsoni + MCPA). Valmisteiden teho oli yleensä hyvä, mutta herneen rik- kakasvien kemiallinen torjunta on kallista esim. viljan- viljelyyn verrattuna. Valikoivia juolavehnän torjunta-ai- neita ruiskutettiin vain seitsemällä pellolla. Mekaanises- ti rikkakasveja torjuttiin viidellä luomupellolla. Suurin vaihtelu lajiston koostumuksessa oli luon- nonmukaisesti ja tavanomaisesti viljeltyjen lohkojen välillä. Torjunta-aineiden käyttö ja nurmen esiintyminen viljelykierrossa selittivät myös vaihtelua. Tavanomai- sesti viljellyillä pelloilla hernekasvuston ominaisuudet ja torjunta-aineiden käyttö selittivät 38,7 ja 37,6 % lajis- ton koostumuksen vaihtelusta. Luomupelloilla herne- kasvuston ikä (kylvö- ja näytteenottopäivän välinen ero- tus) ja pellon sijainti (y-koordinaatti) selittivät 51,7 ja 48,3 % lajiston koostumuksen vaihtelusta. Hernepeltojen rikkakasveja voidaan torjua tehok- kaasti torjunta-aineilla, mutta luomuviljelyssä rikkakas- vit ovat ongelma, jonka voisi osittain ratkaista lisäämäl- lä rikkakasvien mekaanista torjuntaa. Seoskasvustojen, esim. herne/kaura, käyttöä suositellaan erityisesti luo- muviljelyssä, koska se tehostaa viljelykasvin kilpailua rikkakasveja vastaan. Rikkakasvit eivät aseta merkittä- viä esteitä herneen viljelyn laajentumiselle, olkoonkin että niiden torjunta on kallista tavanomaisessa viljelyssä ja haasteellista luomuviljelyssä. 22835_07_Salonen.indd 201 12.10.2005 14:10:50 Weed flora and weed management of field peas in Finland Introduction Material and methods Results Discussion References SELOSTUS