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Potential spring canola yield losses due to weeds in Canada and the United States

Published online by Cambridge University Press:  19 December 2022

Charles M. Geddes*
Affiliation:
Research Scientist, Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, AB, Canada
Breanne D. Tidemann
Affiliation:
Research Scientist, Agriculture and Agri-Food Canada, Lacombe Research and Development Centre, Lacombe, AB, Canada
Joseph T. Ikley
Affiliation:
Assistant Professor, Department of Plant Sciences, North Dakota State University, Fargo, ND, USA
J. Anita Dille
Affiliation:
Professor, Department of Agronomy, Kansas State University, Manhattan, KS, USA
Nader Soltani
Affiliation:
Adjunct Professor, Department of Plant Agriculture, University of Guelph Ridgetown Campus, Ridgetown, ON, Canada
Peter H. Sikkema
Affiliation:
Professor, Department of Plant Agriculture, University of Guelph Ridgetown Campus, Ridgetown, ON, Canada
*
Author for correspondence: Charles M. Geddes, Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, 5403 1st Avenue South, Lethbridge, AB T1J 4B1, Canada Email: [email protected]
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Abstract

Weeds represent one of the most important biotic threats to agricultural plant health, and the potential global impact of weeds on crop yields is similar to that of all other pests (animal pests and pathogens) combined. Canola is the most-grown crop in Canada based on seeded area and generates on average Can$29.9 billion in economic activity each year. The objective of this report, sponsored by the Weed Science Society of America Weed Loss Committee, was to provide an updated estimate of potential yield and monetary losses due to weed interference in spring canola grown in Canada and the United States. Quantitative yield data from field experiments were provided by researchers and weed science professionals in the northern Great Plains region; the major canola-producing area of North America. Overall, 89 yield loss estimates were compiled, covering the 18-yr period from 2003 to 2020. Average canola yield losses due to weed interference in Alberta, Saskatchewan, Manitoba, and North Dakota were 35%, 30%, 18%, and 28%, respectively. Potential yield losses weighted by canola harvested area averaged 30%, 28%, and 30% for Canada, the United States, and both countries combined, respectively. Therefore, unfettered weed interference in spring canola represents a potential monetary loss of Can$2.21 billion, $0.16 billion, and $2.37 billion for farmers in Canada, the United States, and both countries combined. The realization of such losses could manifest through continued selection for herbicide-resistant weeds, indicating the critical need for canola farmers to diversify resistance selection pressures by implementing proactive integrated weed management programs.

Type
Education/Extension
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© His Majesty the King in Right of Canada, 2022 and the Author(s), 2022. Published by Cambridge University Press on behalf of the Weed Science Society of America

Introduction

Canola is the most-grown crop based on seeded area in Canada [considering bread wheat (Triticum aestivum L.) and durum wheat (Triticum durum Desf.) as different crops; see Statistics Canada 2022]. This important oilseed crop is grown on about one quarter of all arable land in Canada each year, making it a sizable factor in the Canadian agricultural economy. The name canola is derived from “Canadian oil” owing to its unique fatty acid profile and solid shell components developed in Canada from rapeseed in the late 1960s to 1970s (Canola Council of Canada 2022a). Canola includes seeds from the Brassica genus [primarily B. napus, but also B. rapa L. and B. juncea (L.) Czern.] that contain <2% erucic acid and <30 µmol g−1 of key glucosinolate compounds in the oil-free seed. Compared with traditional rapeseed, these unique traits improved both the quality of the fatty acid profile for human consumption and the palatability and nutritional quality of the seed meal for livestock feed. Today, the canola value chain in Canada, including growers, seed developers, processors, and exporters, generates Can$29.9 billion in economic activity each year (Canola Council of Canada 2022b).

Canada remains the largest producer of canola worldwide, producing on average (2015 to 2020) about 19.9 billion kg of canola seed on 8.6 million ha each year (Figure 1; Statistics Canada 2022). About 99% of canola production in Canada consists of spring B. napus genotypes (Canadian Grain Commission 2022) grown in the prairie provinces of Alberta, Saskatchewan, and Manitoba (Figure 2; Statistics Canada 2022). Canola is grown to a lesser extent in the United States, producing on average (2015 to 2020) about 1.4 billion kg of seed on 0.7 million ha each year (Figure 1; USDA-NASS 2022); the majority (about 86% to 96%) of which is produced in North Dakota (Figure 3; USDA-NASS 2022). While few resources differentiate between spring and winter canola production in the United States, it is estimated that >90% is spring canola based on regional production practices and recent (2020 to 2022) production statistics (U.S. Canola Association 2022). Spring canola is typically grown in the northern Great Plains, whereas winter canola is grown in the south central/southern Great Plains, and both are grown in the Pacific Northwest.

Figure 1. Spring canola annual (A, B) total production, (C, D) harvested area, and (E, F) average yield in Canada and the United States over the past 50 yr of production (1970 to 2020). Highlighted areas indicate the timeline of yield loss data compiled in the current study. Adapted from Statistics Canada (2022) and USDA-NASS (2022). Note: Production statistics represent both spring and winter canola; however, winter canola represents <1% of overall production in Canada and the United States.

Figure 2. Map depicting the major canola-producing areas in western Canada based on kilograms of canola produced between 2017 and 2019. Image from USDA-FAS (2022). Note: Spring canola cultivars comprise essentially all canola production in western Canada.

Figure 3. Map depicting the major canola producing areas in the United States based on kilograms of canola produced between 2015 and 2019. Image from USDA-FAS (2022). Note: Production metrics are undifferentiated among spring and winter canola cultivars.

Weeds represent one of the most significant biotic threats to agricultural plant health, and the potential global impact of weeds on crop yields is similar to that of all other pests (animal pests and pathogens) combined (Oerke Reference Oerke2006). Recent reports from the Weed Science Society of America (WSSA) Weed Loss Committee have highlighted the potential impact of weed interference on yields of several major field crops grown in North America (Dille et al. Reference Dille, Stahlman, Thompson, Bean, Soltani and Sikkema2020; Flessner et al. Reference Flessner, Burke, Dille, Everman, VanGessel, Tidemann, Manuchehri, Soltani and Sikkema2021; Soltani et al. Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2016, Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2017, Reference Soltani, Dille, Gulden, Sprague, Zollinger, Morishita, Lawrence, Sbatella, Kniss, Jha and Sikkema2018a, Reference Soltani, Dille, Robinson, Sprague, Morishita, Lawrence, Kniss, Jha, Felix, Nurse and Sikkema2018b). Potential yield losses due to weeds in corn (Zea mays L.), soybean [Glycine max (L.) Merr.], spring wheat, winter wheat, dry bean (Phaseolus vulgaris L.), sugar beet (Beta vulgaris L.), and sorghum [Sorghum bicolor (L.) Moench] averaged 50%, 52%, 20%, 23%, 71%, 70%, and 47%, respectively, in their major growing regions of North America. This equates to a potential loss of about US$51.1 billion (∼Can$60.5 billion) per annum in North America if weed control tactics were not implemented in these seven crops.

Understanding the potential yield and monetary losses due to weed interference is critical to quantify the return on investment for the implementation of on-farm weed control practices, and for investment in weed management research. Herbicides continue to represent the primary method of weed management in canola. Herbicide use patterns in canola changed in 1995/1996 with the introduction of herbicide resistance traits into canola cultivars followed by the rapid adoption of these technologies by farmers (Beckie et al. Reference Beckie, Harker, Hall, Warwick, Légère, Sikkema, Clayton, Thomas, Leeson, Séguin-Swartz and Simard2006; Brunharo et al. Reference Brunharo, Gast, Kumar, Mallory-Smith, Tidemann and Beckie2022). In 2020, the majority of canola grown in the prairie region of Canada was glufosinate-resistant (61% of insured canola land base), followed by glyphosate-resistant (28%), imidazolinone-resistant (3%), and other cultivars (<1% including glyphosate- plus glufosinate-resistant, sulfonylurea-resistant, and conventional cultivars; ∼8% of cultivars with traits not specified; see Brunharo et al. Reference Brunharo, Gast, Kumar, Mallory-Smith, Tidemann and Beckie2022 and Canadian Grain Commission 2022). The introduction of herbicide resistance traits in canola resulted in either similar or improved efficacy and decreased cost of weed control, in addition to occasional yield benefits, compared with traditional herbicide regimes (Beckie et al. Reference Beckie, Harker, Hall, Warwick, Légère, Sikkema, Clayton, Thomas, Leeson, Séguin-Swartz and Simard2006; Harker et al. Reference Harker, Blackshaw, Kirkland and Derksen2000; O’Donovan et al. Reference O’Donovan, Harker, Clayton and Blackshaw2006). In 1989, hybrid canola cultivars exhibiting heterosis were introduced into the marketplace. The hybrid vigor of these cultivars manifested as higher seed yield, aboveground biomass, and competitive ability compared with traditional open-pollinated canola (Beckie et al. Reference Beckie, Johnson, Blackshaw and Gan2008b; Harker et al. Reference Harker, Clayton, Blackshaw, O’Donovan and Stevenson2003; Van Deynze et al. Reference Van Deynze, McVetty, Scarth and Rimmer1992; Zand and Beckie Reference Zand and Beckie2002). For example, canola hybrids produced 50% greater aboveground biomass and 24% greater seed yield than open-pollinated canola (Van Deynze et al. Reference Van Deynze, McVetty, Scarth and Rimmer1992), whereas hybrid canola cultivars were twice as competitive as open-pollinated cultivars at high wild oat (Avena fatua L.) densities (Zand and Beckie Reference Zand and Beckie2002). Today, almost all canola cultivars grown in Canada are hybrids (Canadian Grains Commission 2022). While hybrid cultivars dominate spring canola production in the northern Great Plains, both hybrid and open-pollinated winter canola are grown in warmer regions of the United States (Anonymous 2018).

The rapid development of the canola industry over the past half-century represents one of the primary success stories of prairie agriculture in the northern Great Plains region. However, the sustainability of this sector is dependent on the continued efficacy of weed control practices, which is threatened by unrelenting selection for herbicide-resistant weeds in canola-growing regions. A 2014 to 2017 survey of the Canadian prairies found herbicide-resistant weeds in about 16.2 million ha (59%) of annual cropland based on field area (Beckie et al. Reference Beckie, Shirriff, Leeson, Hall, Harker, Dokken-Bouchard and Brenzil2020), representing a large increase from 9.9 million ha (37%) in 2007 to 2009 and 4.4 million ha (16%) in 2001 to 2003. Undoubtedly, the selection for and rapid increase of glyphosate-resistant kochia [Bassia scoparia (L.) A.J. Scott; see Beckie et al. Reference Beckie, Hall, Shirriff, Martin and Leeson2019 and Geddes et al. Reference Geddes, Pittman, Gulden, Jones, Leeson, Sharpe, Shirriff and Beckie2022] was one factor, among others, contributing to the shift in herbicide resistance trait technology from the dominance of glyphosate-resistant to glufosinate-resistant canola cultivars between the 2000s and 2010s/2020s (Beckie et al. Reference Beckie, Harker, Hall, Warwick, Légère, Sikkema, Clayton, Thomas, Leeson, Séguin-Swartz and Simard2006; Brunharo et al. Reference Brunharo, Gast, Kumar, Mallory-Smith, Tidemann and Beckie2022; Canadian Grain Commission 2022). Therefore, it is likely that the evolution of and selection for herbicide-resistant weeds shifted herbicide use patterns in canola, and this impact will continue to grow in the absence of transformative changes to predominant weed management practices implemented by canola farmers.

Estimates of the yield and monetary losses due to weed interference in canola are warranted to inform weed management investment within the canola industry, and to help shape strategies for weed management in canola due to the increased prevalence of herbicide-resistant weeds. A 1991 WSSA Weed Loss Committee survey of expert opinion reported 11% canola yield losses due to weed interference in the Canadian prairies, equating to annual production losses of about 381 million kg of canola seed and monetary losses of Can$79 million (Swanton et al. Reference Swanton, Harker and Anderson1993). However, 2020 canola harvested area, average yield, and total seed production in Canada and the United States were 2.8, 1.7, and 4.9 times larger, respectively, than in 1991 (Figure 1; Statistics Canada 2022; USDA-NASS 2022). The objective of this WSSA Weed Loss Committee report was to provide an updated estimate of potential yield and monetary losses due to weed interference in spring canola grown in Canada and the United States.

Materials and Methods

Weed scientists, professionals, extension specialists, and private research companies conducting research on weed management in canola were contacted and asked to provide canola yield data from experiments that included both weedy and weed-free treatments. Yield data were requested initially for a 15-yr period between 2007 and 2021, but based on data availability the search was expanded to the 18-yr period between 2003 and 2020. Other canola yield data were collected from the published scientific literature. The methods for gathering and analyzing the quantitative yield data followed those implemented previously for other crops in recent WSSA Weed Loss Committee reports (Dille et al. Reference Dille, Stahlman, Thompson, Bean, Soltani and Sikkema2020; Flessner et al. Reference Flessner, Burke, Dille, Everman, VanGessel, Tidemann, Manuchehri, Soltani and Sikkema2021; Soltani et al. Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2016, Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2017, Reference Soltani, Dille, Gulden, Sprague, Zollinger, Morishita, Lawrence, Sbatella, Kniss, Jha and Sikkema2018a, Reference Soltani, Dille, Gulden, Sprague, Zollinger, Morishita, Lawrence, Sbatella, Kniss, Jha and Sikkema2018b).

Mean yield values for season-long weedy and weed-free treatments from the same experiment and environment were required for inclusion in the data set. The weedy treatments must have had weeds controlled prior to crop planting or emergence using either tillage or nonresidual herbicide treatment. Subsequent weeds were allowed to emerge with the crop and remain in the crop for the entire growing season. The weed-free treatments were considered those with >95% visible weed control and absence of visible crop injury. All other agronomic factors were similar among the weedy and weed-free treatments and represented standard best management practices recommended for canola production in the northern Great Plains region.

Potential yield loss (YL%) values were calculated for each experiment and environment combination using Equation 1:

(1) $${\rm{Potential}}\;YL\;\% = \left( {{\rm{weed - free}}\;{\rm{yield}} - {\rm{weedy}}\;{\rm{yield}}} \right)/{\rm{weed - free}}\;{\rm{yield}} \times 100.$$

Yield loss values derived from each experiment were averaged within each year, then yearly yield loss values were averaged across the 18-yr period within each province or state.

Where available, province-wide/state-wide and national average canola harvested area (harvested hectares or acres), seed yield (in kilograms per hectare or bushels per acre), and total seed production (kilograms or bushels) data were compiled for the 50-yr period from 1970 to 2020 (Figure 1) using open-source databases, including Statistics Canada (2022) and USDA-NASS (2022). These data were averaged for the 18-yr period (2003 to 2020) coinciding with the yield loss data set. The average farm-gate price for canola seed (Can$552.31 per 1,000 kg) was calculated using 2013 to 2020 data reported by the Canola Council of Canada (2022c). A 10-yr (2010 to 2020) average exchange rate (1.1937 Canadian to U.S. dollars) was used to convert Canadian and U.S. currencies. Total production and farm-gate price data were used to calculate the total value of canola for each province, state, and country. Then, aggregated potential yield loss values for the corresponding jurisdiction were applied to determine the potential production and monetary losses due to weed interference. National yield and monetary losses were determined using province-wide/state-wide data weighted based on harvested canola area.

Results and Discussion

Overall, 89 yield loss estimates were obtained from Alberta, Saskatchewan, Manitoba, and North Dakota. These provinces and state together represent about 99% and 86% to 96% of canola production by weight in Canada and the United States, respectively (Figures 2 and 3; Statistics Canada 2022; USDA-NASS 2022). All compiled yield loss estimates were for spring B. napus genotypes, the majority of which represented hybrid canola cultivars. An exception included open-pollinated canola data reported by Beckie et al. (Reference Beckie, Johnson, Blackshaw and Gan2008a) for which yield loss values did not differ from those reported for hybrid canola.

Mean potential yield losses of spring canola due to weed interference ranged among provinces/states from 18% to 35% (Table 1). Saskatchewan accounted for about half (48%) of the canola production by harvested area (3.65 million ha) among these locations over the 18-yr period covered in the current study. During this timeframe, an average of 6.44 billion kg of canola seed was produced in Saskatchewan annually, representing an estimated total farm-gate value of Can$3.56 billion per year. With potential canola yield losses of 30% due to weed interference, this equates to a potential loss of 1.94 billion kg of canola seed for Saskatchewan farmers, equivalent to a monetary value of Can$1.08 billion. Alberta accounted for about one-third (29%) of canola production by harvested area (2.23 million ha), totaling 4.69 billion kg of canola seed and an average farm-gate value of Can$2.59 billion each year. Potential canola yield losses due to weed interference were greatest in Alberta (35%) compared with the other provinces/states. Therefore, Alberta farmers risk losing 1.62 billion kg of canola seed or about Can$0.90 billion per annum in the absence of any weed management tactics. Manitoba and North Dakota consisted of 16% (1.22 million ha) and 6% (0.47 million ha) of canola harvested area, respectively, during the study timeframe. Total canola production in Manitoba and North Dakota were 2.41 billion and 0.87 billion kg of seed, respectively, representing a farm-gate value of Can$1.33 billion and $0.48 billion per annum. These two jurisdictions also resulted in the lowest potential canola yield losses due to weed interference among the major canola-producing provinces/states. With potential canola yield losses of 18%, Manitoba farmers risk losing 0.44 billion kg of canola seed or about Can$0.24 billion per year in the absence of effective weed management. Similarly, farmers in North Dakota risk losing 0.24 billion kg of canola seed, equivalent to about Can$0.13 billion per year with potential yield losses due to weed interference of 28%.

Table 1. Spring canola annual harvested area, average yield, total production, and value, with estimated potential yield and monetary losses due to weed interference in the major canola producing provinces and states for the 18-yr period between 2003 and 2020.

a Adapted from Statistics Canada (2022) and USDA-NASS (2022).

b Abbreviations: ac, acres; bu, bushels; Can$, Canadian dollars; ha, hectares; kg, kilograms; M, million.

c Yield loss values were determined using weedy and weed-free plots in experiments conducted within each province or state.

d Cross-provincial data refer to yield loss data available only as means across environments in multiple Canadian prairie provinces. These data were excluded from the tabulation of national metrics.

Based on national yearly average (2003 to 2020) canola production in Canada and the United States (totaling 14.51 billion kg of canola seed and a farm-gate value of about Can$8.02 billion), unfettered weed interference in spring canola risks potential yield losses of 30%, equivalent to an annual loss of about 4.28 billion kg of canola seed or Can$2.37 billion (Table 2). About 94% of canola in the northern Great Plains region was grown in Canada, based on the 2003 to 2020 harvested area in the major canola-producing provinces/states included in the current study. Therefore, canola production in Canada averaged about 13.50 billion kg of canola seed or a farm-gate value of about Can$7.46 billion each year. With a weighted average potential yield loss of 30%, canola farmers in Canada risk losing about 4.00 billion kg of canola seed or Can$2.21 billion each year in the absence of weed management practices. On average, canola farmers in the United States grew 1.01 billion kg of canola seed each year, equivalent to Can$0.56 billion. About 28% of this is at risk of loss due to weed interference, representing a loss of 0.28 billion kg of canola seed or Can$0.16 billion annually for farmers in the United States.

Table 2. Spring canola annual harvested area, average yield, total production, and value, with estimated potential yield and monetary losses due to weed interference in Canada and the United States for the 18-yr period between 2003 and 2020.

a Adapted from Statistics Canada (2022) and USDA-NASS (2022).

b Abbreviations: ac, acres; bu, bushels; Can$, Canadian dollars; ha, hectares; kg, kilograms; M, million.

c Yield loss values were determined using weedy and weed-free plots in experiments conducted within each province or state, then weighted based on province/state-wide production area.

Potential spring canola yield losses due to weed interference reported in the current study (30% on average; Table 2) were higher than those reported recently by the WSSA Weed Loss Committee for spring wheat (20%) and winter wheat (23%; Flessner et al. Reference Flessner, Burke, Dille, Everman, VanGessel, Tidemann, Manuchehri, Soltani and Sikkema2021), but much lower than those reported for corn (50%; Soltani et al. Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2016), soybean (52%; Soltani et al. Reference Soltani, Dille, Burke, Everman, VanGessel, Davis and Sikkema2017), dry bean (71%; Soltani et al. Reference Soltani, Dille, Gulden, Sprague, Zollinger, Morishita, Lawrence, Sbatella, Kniss, Jha and Sikkema2018a), sugar beet (70%; Soltani et al. Reference Soltani, Dille, Robinson, Sprague, Morishita, Lawrence, Kniss, Jha, Felix, Nurse and Sikkema2018b), and sorghum (47%; Dille et al. Reference Dille, Stahlman, Thompson, Bean, Soltani and Sikkema2020). However, based on potential monetary losses for farmers in Canada and the United States, loss of effective weed control in spring canola (about Can$2.37 billion or US$1.98 billion per annum) would have a greater impact than on spring wheat (US$1.39 billion), dry bean (US$0.72 billion), sugar beet (US$1.27 billion), or sorghum (US$0.95 billion), but a lesser impact than on corn (US$26.72 billion), soybean (US$17.21 billion), or winter wheat (US$2.19 billion).

The current study represents an updated assessment of potential yield and monetary losses due to weed interference in spring canola production across its major growing areas of North America. The potential yield losses averaged across the northern Great Plains region (30%; Table 2) were greater than those (20% on average) observed across 10 canola fields in central Alberta between 1995 and 1997 (Harker Reference Harker2001). Similarly, these canola yield losses were greater than those imposed by kochia monoculture (13% yield loss on average with 47 to 105 kochia plants per square meter) among five environments in southern Alberta (Geddes and Sharpe Reference Geddes and Sharpe2022). Previous 1991 estimates of canola yield loss due to weed interference based on expert opinion were 10%, 10%, and 13% in Alberta, Saskatchewan, and Manitoba, respectively; equivalent to monetary losses of Can$23 million, Can$39 million, and Can$18 million, respectively (Swanton et al. Reference Swanton, Harker and Anderson1993). Greater yield loss estimates in the current report were likely due to our assessment using quantitative data for weedy and weed-free field plots, compared with the previous 1991 estimates, which were based on a survey of expert opinion. Weed control experiments are typically located in areas of fields with uniform—and often high—weed density, which undoubtedly results in greater potential yield losses. Thus, while qualitative yield loss estimates are often subject to many assumptions and uncertainties, quantitative estimates summarizing observed yield losses in weed control experiments could conceivably overestimate potential yield losses in fields with low and heterogeneous weed densities. Nevertheless, when the rapid growth of the canola industry (Figure 1) is considered along with inflation since 1991 and higher yield loss estimates, the updated monetary losses reported in the current assessment were not unexpected.

Although spring canola represents the majority of canola production (>99% by weight) in Canada and the United States (Statistics Canada 2022; U.S. Canola Association 2018; USDA-NASS 2022), it should be recognized that potential yield losses due to weed interference may differ between spring canola and winter canola cultivars. Winter cultivars represent <1% the canola grown in Canada and the United States and are grown primarily in the south-central and southern Great Plains regions. All estimates used to derive potential canola yield losses in the current assessment were based on spring canola cultivars. Since winter canola tends to yield 20% to 30% more than spring canola (U.S. Canola Association 2022), it is possible that yield losses due to weed interference in winter canola could differ from the 30% estimated for spring canola in the current study.

The current assessment highlights the critical need for implementation of proactive integrated weed management to mitigate further selection for herbicide-resistant weeds. Strategic rotation of herbicide resistance traits, mixing or layering multiple effective herbicides sites of action where possible, and timely herbicide application are important factors to mitigate weed pressure in canola (Harker et al. Reference Harker, Clayton, O’Donovan, Blackshaw and Stevenson2004, Reference Harker, O’Donovan, Clayton and Mayko2008; Martin et al. Reference Martin, Van Acker and Friesen2001). Perhaps equally as important are nonchemical weed management practices such as growing canola in a crop rotation once in three (or more) years (Cathcart et al. Reference Cathcart, Topinka, Kharbanda, Lange, Yang and Hall2006), and planting competitive cultivars (Beckie et al. Reference Beckie, Johnson, Blackshaw and Gan2008a, Reference Beckie, Johnson, Blackshaw and Gan2008b) at higher seeding rates (Harker et al. Reference Harker, Clayton, Blackshaw, O’Donovan and Stevenson2003; Hosseini et al. Reference Hosseini, Alizadeh and Ahmadi2006; O’Donovan Reference O’Donovan1994) early in the growing season (Bullied et al. Reference Bullied, Van Acker, Marginet and Kenkel2006) with spring fertilization (Blackshaw et al. Reference Blackshaw, Beckie, Molnar, Entz and Moyer2005). Competitive ability differs widely among canola and mustard [B. juncea (L.) Czern. or Sinapis alba L.] cultivars for which, in general, cultivars with rapid emergence, early growth, and tall stature result in greater weed suppression (Beckie et al. Reference Beckie, Johnson, Blackshaw and Gan2008b). Opportunity exists for canola breeders to exploit such diversity in the development of competitive, weed-suppressive cultivars that could become an important component of an integrated weed management system.

Past research identified effective and truly integrated strategies for weed management in canola (Blackshaw et al. Reference Blackshaw, Beckie, Molnar, Entz and Moyer2005; Harker et al. Reference Harker, Clayton, Blackshaw, O’Donovan and Stevenson2003, Reference Harker, O’Donovan, Turkington, Blackshaw, Lupwayi, Smith, Johnson, Pageau, Shirtliffe, Gulden, Rowsell, Hall and Willenborg2016); however, further adoption of these diversified weed management programs is warranted to mitigate the continued threat and growing impact of herbicide-resistant weeds in canola production. The current study identified the potential impact of weeds on canola production and profitability in Canada and the United States. The implementation of any new on-farm weed management practice bares the imperious consideration of return on investment. Understanding the potential impact of weeds in farm fields is the foundation for these decisions. However, weed seedbanks in soil are a collective function of past management, and it is therefore imperative that weed control decisions also consider the compounding return on investment of proactive management strategies.

Acknowledgments

We thank the members of the WSSA Weed Loss Committee for their valuable input. We also thank the dedicated researchers and weed science colleagues who provided canola yield loss data. This research received no specific grant from any funding agency, commercial or not-for-profit sectors. No conflicts of interest have been declared.

Footnotes

Associate Editor: Drew Lyon, Washington State University

References

Anonymous (2018) Great Plains Canola Production Handbook. Manhattan, KS: Kansas State University Research and Extension, 64 pGoogle Scholar
Beckie, HJ, Harker, KN, Hall, LM, Warwick, SI, Légère, A, Sikkema, PH, Clayton, GW, Thomas, AG, Leeson, JY, Séguin-Swartz, G, Simard, M.-J. (2006) A decade of herbicide-resistant crops in Canada. Can J Plant Sci 86:12431264 CrossRefGoogle Scholar
Beckie, HJ, Johnson, EN, Blackshaw, RE, Gan, Y (2008a) Productivity and quality of canola and mustard cultivars under weed competition. Can J Plant Sci 88:367372 CrossRefGoogle Scholar
Beckie, HJ, Johnson, EN, Blackshaw, RE, Gan, Y (2008b) Weed suppression by canola and mustard cultivars. Weed Technol 22:182185 CrossRefGoogle Scholar
Beckie, HJ, Hall, LM, Shirriff, SW, Martin, E, Leeson, JY (2019) Triple-resistant kochia [Kochia scoparia (L.) Schrad.] in Alberta. Can J Plant Sci 99:281285 CrossRefGoogle Scholar
Beckie, HJ, Shirriff, SW, Leeson, JY, Hall, LM, Harker, KN, Dokken-Bouchard, F, Brenzil, CA (2020) Herbicide-resistant weeds in the Canadian prairies: 2012 to 2017. Weed Technol 34:461474 CrossRefGoogle Scholar
Blackshaw, RE, Beckie, HJ, Molnar, LJ, Entz, T, Moyer, JR (2005) Combining agronomic practices and herbicides improves weed management in wheat–canola rotations within zero-tillage production systems. Weed Sci 53:528535 CrossRefGoogle Scholar
Brunharo, CA, Gast, R, Kumar, V, Mallory-Smith, CA, Tidemann, BD, Beckie, HJ (2022) Western United States and Canada perspective: are herbicide-resistant crops the solution to herbicide-resistant weeds? Weed Sci 70:272286 CrossRefGoogle Scholar
Bullied, WJ, Van Acker, RC, Marginet, AM, Kenkel, NC (2006) Agronomic and environmental factors influence weed composition and canola competitiveness in southern Manitoba. Can J Plant Sci 86:591599 CrossRefGoogle Scholar
Canadian Grain Commission (2022) Grain varieties by acreage insured. https://www.grainscanada.gc.ca/en/grain-research/statistics/varieties-by-acreage/ Accessed: September 2, 2022Google Scholar
Canola Council of Canada (2022a) History of canola seed development. https://www.canolacouncil.org/canola-encyclopedia/history-of-canola-seed-development/ Accessed: July 17, 2022Google Scholar
Canola Council of Canada (2022b) Industry overview. https://www.canolacouncil.org/about-canola/industry/ Accessed: July 17, 2022Google Scholar
Canola Council of Canada (2022c) Exports. https://www.canolacouncil.org/markets-stats/exports/#export-values Accessed: September 2, 2022Google Scholar
Cathcart, RJ, Topinka, AK, Kharbanda, P, Lange, R, Yang, R-C, Hall, LM (2006) Rotation length, canola variety and herbicide resistance system affect weed populations and yield. Weed Sci 54:726734 CrossRefGoogle Scholar
Dille, JA, Stahlman, PW, Thompson, CR, Bean, BW, Soltani, N, Sikkema, PH (2020) Potential yield loss in grain sorghum (Sorghum bicolor) with weed interference in the United States. Weed Technol 34:624629 CrossRefGoogle Scholar
Flessner, ML, Burke, IC, Dille, JA, Everman, WJ, VanGessel, MJ, Tidemann, B, Manuchehri, MR, Soltani, N, Sikkema, PH (2021) Potential wheat yield loss due to weeds in the United States and Canada. Weed Technol 35:916923 CrossRefGoogle Scholar
Geddes, CM, Sharpe, SM (2022) Crop yield losses due to kochia (Bassia scoparia) interference. Crop Prot 157:105981 CrossRefGoogle Scholar
Geddes, CM, Pittman, MM, Gulden, RH, Jones, T, Leeson, JY, Sharpe, SM, Shirriff, SW, Beckie, HJ (2022) Rapid increase in glyphosate resistance and confirmation of dicamba-resistant kochia (Bassia scoparia) in Manitoba. Can J Plant Sci 102:459464 CrossRefGoogle Scholar
Harker, KN (2001) Survey of yield losses due to weeds in central Alberta. Can J Plant Sci 81:339342 CrossRefGoogle Scholar
Harker, KN, Blackshaw, RE, Kirkland, KJ, Derksen, DA, Wall (2000) Herbicide-tolerant canola: weed control and yield comparisons in western Canada. Can J Plant Sci 80:647654 CrossRefGoogle Scholar
Harker, KG, Clayton, GW, Blackshaw, RE, O’Donovan, JT, Stevenson, FC (2003) Seeding rate, herbicide timing and competitive hybrids contribute to integrated weed management in canola (Brassica napus). Can J Plant Sci 83:433440 CrossRefGoogle Scholar
Harker, KN, Clayton, GW, O’Donovan, JT, Blackshaw, RE, Stevenson, FC (2004) Herbicide timing and rate effects on weed management in three herbicide-resistant canola systems. Weed Technol 18:10061012 CrossRefGoogle Scholar
Harker, KN, O’Donovan, JT, Clayton, GW, Mayko, J (2008) Field-scale time of weed removal in canola. Weed Technol 22:747749 CrossRefGoogle Scholar
Harker, KN, O’Donovan, JT, Turkington, TK, Blackshaw, RE, Lupwayi, NZ, Smith, EG, Johnson, EN, Pageau, D, Shirtliffe, SJ, Gulden, RH, Rowsell, J, Hall, LM, Willenborg, CJ (2016) Diverse rotations and optimal cultural practices control wild oat (Avena fatua). Weed Sci 64:170180 CrossRefGoogle Scholar
Hosseini, NM, Alizadeh, HM, Ahmadi, HM (2006) Effects of plant density and nitrogen rates on the competitive ability of canola (Brassica napus L.) against weeds. J Agric Sci Technol 8:281291 Google Scholar
Martin, SG, Van Acker, RC, Friesen, LF (2001) Critical period of weed control in spring canola. Weed Sci 49:326333 CrossRefGoogle Scholar
O’Donovan, JT (1994) Canola (Brassica rapa) plant density influences tartary buckwheat (Fagopyrum tataricum) interference, biomass, and seed yield. Weed Sci 42:385389 CrossRefGoogle Scholar
O’Donovan, JT, Harker, KN, Clayton, GW, Blackshaw, RE (2006) Comparison of a glyphosate-resistant canola (Brassica napus L.) system with traditional herbicide regimes. Weed Technol 20:494501 CrossRefGoogle Scholar
Oerke, EC (2006) Centenary Review – Crop losses to pests. J Agr Sci 144:3143 CrossRefGoogle Scholar
Soltani, N, Dille, JA, Burke, IC, Everman, WJ, VanGessel, MJ, Davis, VM, Sikkema, PH (2016) Potential corn yield losses from weeds in North America. Weed Technol 30:979984 CrossRefGoogle Scholar
Soltani, N, Dille, JA, Burke, IC, Everman, WJ, VanGessel, MJ, Davis, VM, Sikkema, PH (2017) Perspectives on potential soybean yield losses from weeds in North America. Weed Technol 31:148154 CrossRefGoogle Scholar
Soltani, N, Dille, JA, Gulden, RH, Sprague, CL, Zollinger, RK, Morishita, DW, Lawrence, NC, Sbatella, GM, Kniss, AR, Jha, P, Sikkema, PH (2018a) Potential yield loss in dry bean crops due to weeds in the United States and Canada. Weed Technol 32:342346 CrossRefGoogle Scholar
Soltani, N, Dille, JA, Robinson, DE, Sprague, CL, Morishita, DW, Lawrence, NC, Kniss, AR, Jha, P, Felix, J, Nurse, RE, Sikkema, PH (2018b) Potential yield loss in sugar beet due to weed interference in the United States and Canada. Weed Technol 32:749753 CrossRefGoogle Scholar
Statistics Canada (2022) Estimated areas, yield, production, average farm price and total farm value of principal field crops in metric and imperial units. https://www150.statcan.gc.ca/t1/tbl1/en/cv.action?pid=3210035901 Accessed: September 6, 2022Google Scholar
Swanton, CJ, Harker, KN, Anderson, RL (1993) Crop losses due to weeds in Canada. Weed Technol 7:537542 CrossRefGoogle Scholar
U.S. Canola Association (2022) U.S. Canola Production. https://www.uscanola.com/crop-production/spring-and-winter-canola/ Accessed: September 17, 2022Google Scholar
[USDA-NASS] U.S. Department of Agriculture–National Agricultural Statistics Service (2022) Quick Stats. https://quickstats.nass.usda.gov/ Accessed: September 2, 2022Google Scholar
[USDA-FAS] U.S Department of Agriculture–Foreign Agricultural Service (2022) Crop Production Maps. https://ipad.fas.usda.gov/ogamaps/cropproductionmaps.aspx Accessed: September 8, 2022Google Scholar
Van Deynze, AE, McVetty, PBE, Scarth, R, Rimmer, SE (1992) Effect of varying seeding rates on hybrid and conventional summer rape performance in Manitoba. Can J Plant Sci 72:635641 CrossRefGoogle Scholar
Zand, E, Beckie, HJ (2002) Competitive ability of hybrid and open-pollinated canola (Brassica napus) with wild oat (Avena fatua). Can J Plant Sci 82:473480 CrossRefGoogle Scholar
Figure 0

Figure 1. Spring canola annual (A, B) total production, (C, D) harvested area, and (E, F) average yield in Canada and the United States over the past 50 yr of production (1970 to 2020). Highlighted areas indicate the timeline of yield loss data compiled in the current study. Adapted from Statistics Canada (2022) and USDA-NASS (2022). Note: Production statistics represent both spring and winter canola; however, winter canola represents <1% of overall production in Canada and the United States.

Figure 1

Figure 2. Map depicting the major canola-producing areas in western Canada based on kilograms of canola produced between 2017 and 2019. Image from USDA-FAS (2022). Note: Spring canola cultivars comprise essentially all canola production in western Canada.

Figure 2

Figure 3. Map depicting the major canola producing areas in the United States based on kilograms of canola produced between 2015 and 2019. Image from USDA-FAS (2022). Note: Production metrics are undifferentiated among spring and winter canola cultivars.

Figure 3

Table 1. Spring canola annual harvested area, average yield, total production, and value, with estimated potential yield and monetary losses due to weed interference in the major canola producing provinces and states for the 18-yr period between 2003 and 2020.

Figure 4

Table 2. Spring canola annual harvested area, average yield, total production, and value, with estimated potential yield and monetary losses due to weed interference in Canada and the United States for the 18-yr period between 2003 and 2020.