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Season-long weed control with sequential herbicide programs in California tree nut crops

Published online by Cambridge University Press:  30 June 2020

Caio A. C. G. Brunharo
Affiliation:
Assistant Professor, Department of Crop and Soil Science, Oregon State University, Corvallis, OR, USA
Seth Watkins
Affiliation:
Staff Research Associate, Department of Plant Sciences, University of California, Davis, CA, USA
Bradley D. Hanson*
Affiliation:
UCCE Weed Science Specialist, Department of Plant Sciences, University of California–Davis, Davis, CA, USA.
*
Author for correspondence: Bradley D. Hanson, Department of Plant Sciences, MS-4, University of California–Davis, One Shields Avenue, Davis, CA95616. Email: [email protected]
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Abstract

Weed control in tree nut orchards is a year-round challenge for growers that is particularly intense during winter through summer as a result of competition and interference with management and harvest operations. A common weed control program consists of an application of a winter PRE and POST herbicide mixture, followed by a desiccation treatment in early spring and before harvest. Because most spring and summer treatments depend on a limited number of foliar-applied herbicides, summer-germinating species and/or herbicide-resistant biotypes become troublesome. Previous research has established effective PRE herbicide programs targeting winter glyphosate-resistant weeds. However, more recently, growers have reported difficulties in controlling several summer-germinating grass weeds with documented or suspected resistance to the spring and summer POST herbicide programs. In this context, research was conducted to evaluate a sequential PRE approach to control winter- and summer-germinating orchard weeds. Eight field experiments were conducted in tree nut orchards to evaluate the efficacy of common winter herbicide programs and a sequential herbicide program for control of a key summer grass weed species. In the sequential-application strategy, three foundational herbicide programs applied in the winter were either mixed with pendimethalin, followed with pendimethalin in March, or applied as a split application of pendimethalin in both winter and spring. Results indicate that the addition of pendimethalin enhanced summer grass weed control throughout the crop growing season by up to 31%. Applying all or part of the pendimethalin in the spring improved control of the summer grass weed junglerice by up to 49%. The lower rate of pendimethalin applied in the spring performed as well as the high rate in the winter, suggesting opportunities for reducing herbicide inputs. Tailoring sequential herbicide programs to address specific weed challenges can be a viable strategy for improving orchard weed control without increasing herbicide use in some situations.

Type
Research Article
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 in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of Weed Science Society of America

Introduction

Orchard crops are grown on over 1.3 million hectares in California, with the tree nuts almond [Prunus dulcis (Mill.) D.A. Webb], walnut (Juglans regia L.), pistachio (Pistacia vera L.), and pecan [Carya illinoinensis (Wangenh.) K. Koch] accounting for nearly half of this hectarage and a 2017 farm gate value of $8 billion (CDFA 2018). Tree nuts are primarily produced in the 700-km-long Central Valley of California, where average annual rainfall ranges from 960 mm yr–1 in the north to 180 mm yr–1 in the south (CIMIS 2020). Because of the Mediterranean climate, most of this precipitation occurs outside the summer growing season, and significant irrigation inputs are required to maintain crop quality and productivity.

Weeds are controlled in these intensely managed cropping systems to reduce direct competition with the crop for water and other inputs, both during orchard establishment and throughout the duration of the several-decade lifespan of the orchard. Poorly controlled orchard weeds can interfere with cultural practices, operation of irrigation equipment, or the accurate placement of water, fertilizers, and other pesticides (Belding et al. Reference Belding, Majek, Lokaj, Hammerstedt and Ayen2004). In some early-flowering tree crops, understory vegetation management is also important for reducing risk of frost damage during critical periods in the spring, as solar radiation energy stored in the soil during the day is reradiated at night. Almonds, walnuts, and pecans are mechanically shaken from the tree, swept into windrows, and picked up from the orchard floor after several days of drying; in these crops, a weed-free and smooth orchard floor is critical to the efficiency of these harvest operations (Company and Gradziel Reference Company and Gradziel2017; Micke Reference Micke1996).

In the mild climate of this region, characterized by winter rainfall and summer irrigation, weed control is a year-round management concern. Because of operational efficiencies, labor costs, and impacts of dust on crop performance and air quality, weed control in most California tree nut orchards utilizes some combination of PRE and POST herbicides. A common chemical weed control program in tree nuts begins with a PRE herbicide applied ahead of the onset of winter rains for incorporation, and this application is often made in “strips” centered on the tree row and may cover around 30% to 50% of the orchard floor (Hanson et al. Reference Hanson, Wright, Sosnoskie, Fischer, Jasieniuk, Roncoroni, Hembree, Orloff, Shreshta and Al-Khatib2014). In spring, the strips are commonly retreated with a POST herbicide program if needed, whereas the area between the sprayed strips is managed with several mowing operations. In summer, shortly before harvest, the entire orchard floor is commonly treated with a POST herbicide program and also closely mowed to minimize plants and debris that can interfere with harvest operations.

Glyphosate is a key component of many orchard herbicide programs. Intense selection pressure led to reports of glyphosate resistance in several key weeds during the late 1990s and 2000s. Such weeds as Italian ryegrass [Lolium perenne L. spp. multiflorum (Lam.) Husnot; (Jasieniuk et al. Reference Jasieniuk, Ahmad, Sherwood, Firestone, Perez-Jones, Lanini, Mallory-Smith and Stednick2008; Simarmata et al. Reference Simarmata, Kaufmann and Penner2003)], horseweed [Erigeron canadensis L. (Hanson et al. Reference Hanson, Shrestha and Shaner2009)], and hairy fleabane [Erigeron bonariensis L. (Moretti et al. Reference Moretti, Sosnoskie, Shrestha, Wright, Hembree, Jasieniuk and Hanson2016; Shrestha et al. Reference Shrestha, Hembree and Va2007)] showed glyphosate resistance. Evaluation of existing and newly registered herbicide programs for control of these glyphosate-resistant (GR) fall- and winter-germinating weeds largely focused on rates, mixtures, and application timing of PRE herbicides (Brunharo and Hanson Reference Brunharo and Hanson2016; Shrestha et al. Reference Shrestha, Hembree and Va2007), or supplementation with other POST mechanisms of action (Moretti et al. Reference Moretti, Mejorado, Watkins, Doll and Hanson2013, Reference Moretti, Shrestha, Hembree and Hanson2015). Based on university and private-sector research and grower experience, several herbicide programs are now commonly used in the tree nut system to provide acceptable control of these winter species.

The extended duration of required weed control remains a challenge in this cropping system. PRE herbicide programs for control of Italian ryegrass, hairy fleabane, and horseweed are most effective when applied relatively early in winter. However, these compounds often do not have sufficient residual activity to last through harvest because of the length of the season, soil temperature, and moisture conditions during the hot, irrigated portion of the spring and summer season. In an effort to extend residual weed control into the spring, many growers use high labeled rates and complex mixtures in their winter programs; such practices are costly and can occasionally lead to crop safety problems. However, even the most effective winter PRE programs usually must be supplemented with applications of glyphosate or other POST herbicides in spring plus the pre-harvest orchard floor treatment to achieve satisfactory control of summer-germinating species.

The first example of a GR summer weed in California orchards was junglerice, identified in the northern Central Valley (Alarcón-Reverte et al. Reference Alarcón-Reverte, García, Urzúa and Fischer2013). Several GR junglerice biotypes were subsequently identified from multiple orchard production regions of the state (Alarcon-Reverte et al. Reference Alarcon-Reverte, Garcia, Watson, Abdallah, Sabate, Hernandez, Dayan and Fischer2015; Morran et al. Reference Morran, Moretti, Brunharo, Fischer and Hanson2018). Other summer grass weed species are also occasionally reported as creating problems in the tree nut production system in the Central Valley of California. Common examples are feather fingergrass (Chloris virgata Sw.), witchgrass (Panicum capillare L.), bearded sprangletop [Leptochloa fusca (L.) P. Beauv. ex Roem. & Schult. spp. fascicularis (Lam.) P. M. Peterson & N. Snow], and threespike goosegrass [Eleusine tristachya (Lam.) Lam.]. Junglerice and the other summer grasses germinate (or in some cases resume growing) when the soil temperatures start to rise in the spring, develop during the summer, and complete their life cycle in the fall. With this life cycle, summer grass weed species reach their maximum biomass accumulation in late summer through early fall—coincidentally when harvest operations are taking place—if previous weed management approaches were insufficient.

To address both winter- and summer-germinating GR weeds, several winter PRE mixture programs were evaluated to achieve sufficient duration of control, and typically the highest label rates were used. Integrated pest management approaches often stress the importance of understanding pest biology and designing control strategies accordingly (Norris et al. Reference Norris, Caswell-Chen and Kogan2003). Shifting a portion of the PRE herbicide program from winter to spring may provide a simple yet viable approach for extended control of summer weed species. In this sequential approach, a second PRE herbicide application is made as part of the spring POST program prior to germination of the summer species rather than trying to achieve summer weed control with high rates of PRE herbicides applied in the winter. This approach specifically targets summer-emerging species and may, at the same time, improve crop safety and provide economic and environmental benefits by reducing overtreatment.

The overall objective of this research was to evaluate herbicide programs that included PRE herbicide application mixtures with pendimethalin in the winter, followed by various sequential-application programs. Management strategies were designed to target summer grass weed species and to achieve season-long weed control as well as to reduce the overall herbicide application amounts during the growing season.

Materials and Methods

During the period 2012 to 2015, several field experiments were conducted in grower almond orchards to compare performance of winter herbicide mixtures to a split-treatment program. Figure 1 depicts field experiment locations across the Central Valley of California (Khale and Wickham Reference Khale and Wickham2013). In 2017–2018, two field experiments were conducted in grower walnut orchards to address the sequential program more thoroughly at a location dominated by GR junglerice.

Figure 1. California map with field experiment locations. Data points are slightly shifted to avoid stacking for clarity of presentation.

Winter PRE Herbicide Mixtures

Two sets of experiments were conducted to evaluate winter PRE herbicide programs that are commonly adopted by nut growers in California (herbicide sources are listed in Table 1). For clarity, the first set of experiments will be denominated as large-plot experiments, and the second set as small-plot experiments. The large-plot experiments comprised four field trials focused on mixtures of oxyfluorfen + oryzalin, pendimethalin + flumioxazin, pendimethalin + rimsulfuron, and pre-mixes of oxyfluorfen/penoxsulam, as well as pendimethalin, flumioxazin, indaziflam, and isoxaben applied alone (Table 2). Sequential applications of pendimethalin and of oxyfluorfen/penoxsulam followed by (fb) pendimethalin were also included in these experiments. The soil mapped to the Delhi series sand at the Delhi-large site (37.43°N, 120.71°W), as an Arbuckle series sandy loam at the Arbuckle site (38.96°N, 122.06°W), and as a Garces series silt loam at the Wasco-large site (35.65°N, 119.43°W). The experiment at the Wasco-large site was conducted twice (Wasco-13-large in 2013 and Wasco-14-large in 2014). The small-plot experiments included two field trials that were focused on different rates and application timings of rimsulfuron, indaziflam, and the pre-mix penoxsulam/oxyfluorfen (Table 3). The small-plot experiments were conducted in different blocks of the same orchards used for the Delhi-large and Wasco-13-large experiments, and were named Delhi-small and Wasco-small, respectively, and had similar soil characterization.

Table 1. Sources of herbicides used in the orchard weed control experiments.

Table 2. Winter herbicide programs for Erigeron bonariensis (ERIBO) and Echinochloa colona (ECHCO) control in California almond orchard large-plot experiments.

a Evaluation dates differed among experimental sites and weed species. Delhi-large in April 2013; Arbuckle in April 2013; Wasco-13-large in April 2013 for ERIBO; Wasco-13-large in May for ECHCO; Wasco-14-large in March 2014 for ERIBO; and Wasco-14-large in May for ECHCO.

b Indaziflam rates were 73 and 51 g ai ha–1 in 2013 and 2014, respectively.

c Abbreviation: fb, followed by.

Table 3. Winter herbicide programs for Erigeron bonariensis (ERIBO) and Echinochloa colona (ECHCO) control in California almond orchards small-plot experiments at multiple locations and years.

a Evaluation dates differed among experimental sites and weed species: Delhi-small in March 2013; Wasco-13-small in April 2013 for ERIBO; and Wasco-13-small in May for ECHCO.

b Indaziflam rates were 73 and 51 g ai ha–1 in 2013 and 2014, respectively (see text for justification).

c Abbreviation: fb, followed by.

In the large-plot experiments, winter and spring herbicide applications were performed as follows: the Delhi-large site was treated on January 14 and March 25, 2013; the Arbuckle site on November 27, 2012 and March 27, 2013; the Wasco-13-large site on February 6 and March 12, 2013; and the Wasco-14-large site on January 16 and March 18, 2014. For the small-plot experiments, the winter and spring treatments were performed as follows: the Delhi-small site was treated on February 1 and March 25, 2013; and the Wasco-13-small site was treated on February 6 and March 12, 2013. A CO2-pressurized backpack sprayer was used to perform the treatments, calibrated to deliver 187 L ha–1 through three 8002 flat-fan extended-range nozzles spaced 0.5 m apart, treating 1.5 m on each side of the trees. The large-plot experiments involved three replications of plots 168 m in length and an effective plot size of 252 m2, whereas the small-plot experiments had four replications of plots 10 m in length and an effective plot size of 30 m2. A randomized complete block design was adopted for all experiments. Weed control was assessed visually, approximately 30, 60, and 90 d after the winter treatment, on a scale that ranged from 0 to 100%, where 0 represented absence of control, and 100% represented complete weed control. Unless precluded by the grower’s preharvest preparations, an evaluation was also conducted 120 d after the winter treatment (see Tables 2 and 3 for evaluation dates). The predominant weed species varied among locations but generally consisted of common orchard species such as little mallow (Malva parviflora L.), common groundsel (Senecio vulgaris L.), shepherd’s-purse [Capsella bursa-pastoris (L.) Medik], Italian ryegrass, and hairy fleabane during the February, March, and April evaluations, and junglerice, yellow nutsedge (Cyperus esculentus L.), threespike goosegrass, common lambsquarters (Chenopodium album L.), and field bindweed (Convolvulus arvensis L.) at the May evaluations.

Weed control data were subjected to the Levene’s homogeneity test of variance to compare the variance among treatments. Generalized linear models using template model builder from the R package glmTMB (Brooks et al. Reference Brooks, Kristensen, Benthem, Magnusson, Berg, Nielsen, Skaug, Mächler and Bolker2017) and a beta distribution with ilink function were fit for each evaluation date for each site (Oliveira et al. Reference Oliveira, Jhala, Gaines, Irmak, Amundsen, Scott and Knezevic2017), where weed control was the response variable, herbicide treatment as fixed effects, and block as random effects. Estimated marginal means for weed control were produced and treatments compared with the R package emmeans (Lenth et al. Reference Lenth, Singmann, Love, Buerkner and Herve2020), including control for overall experiment-wise Type I error rate considering 11 treatments using the Bonferroni correction and α = 0.05.

Sequential Herbicide Management Strategy

Two field experiments (referred to as “Tulare 1” and “Tulare 2”) were conducted in Tulare County near Visalia, CA (Tulare 1: 36.18°N, 119.16°W; Tulare 2: 36.20°N, 119.15°W), from December 2017 to August 2018, to test the sequential herbicide application strategy for season-long weed control. Soil at both sites mapped to a Flamen series loam; Tulare 1 had 0.65% organic matter and pH = 7.3, and Tulare 2 had 1.18% organic matter and pH = 6.92.

The treatments consisted of an application of one of three common PRE herbicides for nut tree crops (indaziflam, penoxsulam/oxyfluorfen, or flumioxazin) as the foundation winter chemical weed management program. Pendimethalin was the herbicide used to evaluate the potential of sequential herbicide programs to target summer grass weed species (Bhowmik and Bingham Reference Bhowmik and Bingham1990). Pendimethalin was applied either as a mixture with the foundation winter PRE herbicide, or as a sequential treatment in spring (Table 4). At both application timings, glyphosate + glufosinate were added to the treatments to ensure that all subsequent evaluations were of new weeds and not from regrowth. Junglerice was the predominant summer weed species at both sites, and its control was evaluated monthly, with aboveground biomass collected in August before trial termination near walnut harvest. Plots were 3 m by 20 m and were arranged in a randomized complete block design with four replications.

Table 4. Sequential treatments, rates, and application timing in walnut orchards in Tulare County, CA.

a Glufosinate at 1,680 g ai ha–1, glyphosate at 1,260 g ae ha–1, ammonium sulfate at 1%, and non-ionic surfactant at 0.25% were added to all treatments.

b Abbreviations: +, mixture; fb, followed by sequential treatment.

Weed control and biomass data were subjected to the Levene’s homogeneity test of variance before model fitting. Experimental site (Tulare 1 and Tulare 2) and block as random effects, and response variable (either weed control or biomass) as fixed effects were included in the linear model using the R package lme4 (Bates et al. Reference Bates, Mächler, Bolker and Walker2015). Interaction between experimental site and treatments were observed for biomass data; therefore, mean separation was performed separately for each site. In addition, lack of normality of residuals was observed for the biomass data from both experimental sites, and a Box-Cox transformation was performed (Box and Cox Reference Box and Cox1964; Brunharo and Hanson Reference Brunharo and Hanson2018) based on a log-likelihood function, with λ = 0.3 and λ = 0.2 for Tulare 1 and Tulare 2, respectively. Mean separation was performed as previously described in the “Winter PRE herbicide mixture” section, and the effects of the treatments on the response variables weed control and biomass (detransformed) are presented.

A contrast analysis was performed to answer the following specific questions: (a) Does the addition of pendimethalin enhance overall weed control?; (b) Can a sequential application of pendimethalin at 2,130 g ai ha–1 in the winter followed by pendimethalin at 2,130 g ha–1 in the spring perform as well as a single pendimethalin application with the higher rate (4,260 g ha–1) in the winter?; and (c) Can the lower pendimethalin rate (2,130 g ha–1) in the spring perform as well as the higher pendimethalin rate (4,260 g ha–1) in the winter for control of summer-emerging grasses? To answer these questions, vectors of contrast values were created with linear combinations of factor levels of interest that summed to zero. The residual mean squared error used to estimate the mean differences, and 95% confidence intervals were derived from the mixed-effects model from the previous analysis. A customized script was created to obtain the mean difference between treatment groups and 95% confidence intervals (available at https://github.com/caiobrunharo/sequential_herbicide_programs) in R (R Core Team 2020). Because the contrasts of interest were not orthogonal, a Sidak correction was applied (Aho Reference Aho2013).

Results and Discussion

Season-long chemical weed management is highly desired by growers, particularly when hard-to-control species and/or weed populations that have evolved herbicide resistance are present in the fields. This research indicates that the winter herbicide programs provide effective winter weed control, including GR hairy fleabane (ERIBO; Tables 2 and 3). However, the overall weed control was less consistent for summer weeds, like junglerice, in the May evaluations for some of the treatments and experimental sites (ECHCO; Tables 2 and 3). For instance, rimsulfuron applied in February provided only 47% junglerice control as observed in May, probably because of the brief residual activity of this molecule (Ashburn-Poppell et al. Reference Ashburn-Poppell, Hayes and Mueller2002). Spring-germinating species, such as junglerice, threespike goosegrass, and field bindweed, become harder to control with POST herbicides as they reach more advanced developmental stages (Soltani et al. Reference Soltani, Nurse and Sikkema2016); therefore, their early control is crucial.

The sequential herbicide application strategy yielded similar results at both sites, and the visual data are presented as a compiled dataset, whereas the biomass data are presented separately for each experimental site. Control of junglerice in August 2018, 8 mo after winter treatments and 5 mo after spring sequential treatments, are shown in Figure 2. The general trend observed is that the addition of pendimethalin enhanced junglerice control throughout the crop growing season. Not surprisingly, junglerice visual control was best with all three winter foundation PRE herbicides followed by a pendimethalin treatment in the spring (treatments 5, 6, 10, 11, 15, and 16; Figure 2). Treatments with the foundation winter PRE treatments alone provided reduced junglerice control levels (treatments 2, 7, and 12; Figure 2).

Figure 2. Junglerice control 8 mo after winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 1 and Tulare 2. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130, (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

Biomass data supported the visual control ratings for junglerice for Tulare 1 (Figure 3) and Tulare 2 (Figure 4). The foundation winter treatments alone resulted in junglerice biomass similar to the untreated plots (treatments 2, 7, and 12). Sequential applications of the higher rate of pendimethalin (4,260 g ha–1) in the spring (treatments 5, 10, and 15; Figures 3 and 4) reduced junglerice biomass to levels close to zero, regardless of the foundation winter PRE program. Tank-mixing pendimethalin (4,260 g ha–1) with the winter foundation program (treatments 3, 8, and 13; Figures 3 and 4) did not provide enhanced junglerice control compared to the foundation winter treatments alone (treatments 2, 7, and 12; Figures 3 and 4). Superior junglerice control was observed with spring applications of pendimethalin. Junglerice control was generally better with most treatments at the Tulare 2 site, where weed pressure was lower (data not shown) compared to Tulare 1. At the lower weed pressure site, the sequential application of the lower rate of pendimethalin (2,130 g ha–1) resulted in similar control levels compared to the higher pendimethalin rate (4,260 g ha–1), which underscores the value of field scouting and tailored herbicide programs.

Figure 3. Junglerice biomass 8 mo after the winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 1. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) Nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130; (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

Figure 4. Junglerice biomass 8 mo after winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 2. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130; (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

The contrast analysis summarized the overall trends observed in the previous analysis (Table 5). We observed that the addition of pendimethalin to the system (either in winter or spring) enhanced junglerice control, improving weed control by up to 31% and reducing the average biomass by up to 159 g m–2 (Table 5, contrast 1). From contrast 2, we observed that a sequential application of lower rates of pendimethalin (2,130 g ha–1 in the winter followed by 2,130 g ha–1 in the spring) provided better control of junglerice than a single application of the higher rate of pendimethalin (4,260 g ha–1) in the winter. The sequential application enhanced weed control by up to 49% and reduced biomass by up to 154 g m–2 (Table 5, contrast 2). Finally, from contrast 3 we observed that the lower rate of pendimethalin (2,130 g ha–1) applied in the spring outperformed the higher rate of pendimethalin (4,260 g ha–1) applied in the winter, where weed control improved by up to 32% and biomass was reduced by up 126 g m–2 (Table 5, contrast 3). These results suggest that a strategic management of the pendimethalin application timing may be more important than the total herbicide load in the system for summer grass control.

Table 5. Contrast analysis of treatment groups.

a MD, Mean difference.

b Confidence interval [lower; upper]. Raw data used to create the contrasts is available at https://github.com/caiobrunharo/sequential_herbicide_programs.

c P < 0.001.

When considering only the summer annual grass species, the lower rates of pendimethalin (2,130 g ha–1) in the spring generally outperformed the higher rate of pendimethalin (4,260 g ha–1) applied in the winter but was not always comparable to the sequential treatments. Biologically significant levels of pendimethalin in soils can be found between 135 d (Hatzinikolaou et al. Reference Hatzinikolaou, Eleftherohorinos and Vasilakoglou2004) and 200 d (Zimdahl et al. Reference Zimdahl, Pietro and Ann1984) after application, with limited mobility in soils (Shaner Reference Shaner2012), which enhances its residual activity compared to other winter PRE herbicides. Because the higher rate of pendimethalin in spring provided excellent control and the lower did not, this is not likely due simply to early-germinating junglerice. Instead, under heavy weed pressure, the spring treatment with the lower rate may not provide sufficient control without the winter component.

The experiments conducted in this research focused primarily on the control of summer grass weed species, and the weed community present in specific fields will determine the adequate herbicide treatment to be adopted. In areas where summer weed species are the major issue, shifting some or all of the pendimethalin component of the herbicide program may significantly improve performance relative to the winter-only PRE approach. However, in areas where winter grass weed species [e.g., annual bluegrass (Poa annua L.), Italian ryegrass] are also troublesome, more attention will need to be given to the winter treatments that could be complemented by pendimethalin addition to target these species in a sequential approach. Pendimethalin is a semi-volatile herbicide that requires incorporation, either by irrigation/rainfall or by mechanical techniques; therefore, the sequential application in the spring will require that growers have the means to uniformly incorporate the herbicide in a timely manner. Although this is feasible in sprinkler- and micro sprinkler–irrigated sites, growers whose orchards are irrigated with single- or double-line drip irrigation systems may need to shift the pendimethalin application date early enough to ensure that it is followed by a spring rain event for incorporation.

Results from this research project suggest that, in some instances, it is possible to improve or maintain weed control outcomes in tree nut orchards using less herbicide by carefully considering the biology of the weed, weed control goals, and the weed management tools available. Chemical weed management that emphasizes the winter PRE herbicide application are well established for hard-to-control weed species such as hairy fleabane, but these programs do not always reliably control key summer-annual weed species. Sequential herbicide applications may be a viable option to provide season-long weed control, particularly with the addition of pendimethalin to the management program to target summer annual grass species.

Acknowledgments

This research was supported, in part, by funding from the Almond Board of California, the California Dried Plum Board, the California Walnut Board, and Bayer Crop Science. No conflicts of interest have been declared.

Footnotes

Associate Editor: Drew Lyon, Washington State University

References

Aho, K (2013) Foundational and Applied Statistics for Biologists Using R. Boca Raton, FL: CRC Press. 618 p Google Scholar
Alarcón-Reverte, R, García, A, Urzúa, J, Fischer, AJ (2013) Resistance to glyphosate in junglerice (Echinochloa colona) from California. Weed Sci 61:4854 CrossRefGoogle Scholar
Alarcon-Reverte, R, Garcia, A, Watson, SB, Abdallah, I, Sabate, S, Hernandez, MJ, Dayan, FE, Fischer, AJ (2015) Concerted action of target-site mutations and high EPSPS activity in glyphosate-resistant junglerice (Echinochloa colona) from California. Pest Manag Sci 71:9961007 CrossRefGoogle ScholarPubMed
Ashburn-Poppell, C, Hayes, RM, Mueller, TC (2002) Dissipation of nicosulfuron and rimsulfuron in surface soil. J Agric Food Chem 50:45814585 CrossRefGoogle Scholar
Bates, D, Mächler, M, Bolker, B, Walker, S (2015) Fitting linear mixed-effects models using lme4. J StatSoftw 67:148 Google Scholar
Belding, RD, Majek, BA, Lokaj, GRW, Hammerstedt, J, Ayen, AO (2004) Orchard floor management influence on summer annual weeds and young peach tree performance. Weed Technol 18:215222 CrossRefGoogle Scholar
Bhowmik, PC, Bingham, SW (1990) Preemergence activity of dinitroaniline herbicides used for weed control in cool-season turfgrasses. Weed Technol 4:387393 CrossRefGoogle Scholar
Box, GEP, Cox, DR (1964) An analysis of transformations. J R Stat Soc B 26:211252 Google Scholar
Brooks, ME, Kristensen, K, Benthem, KJv, Magnusson, A, Berg, CW, Nielsen, A, Skaug, HJ, Mächler, M, Bolker, BM (2017) glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J 9:378400 Google Scholar
Brunharo, CA, Hanson, BD (2016) Performance of mesotrione tankmixes in orchards. Page 22 in Rauch T, ed, Proceedings of the Western Society of Weed Science, Vol 69. Albuquerque, NM: WSWS Research Progress ReportGoogle Scholar
Brunharo, CACG, Hanson, BD (2018) Multiple herbicide–resistant Italian ryegrass [Lolium perenne L. spp. multiflorum (Lam.) Husnot] in California perennial crops: characterization, mechanism of resistance, and chemical management. Weed Sci 66:696701 CrossRefGoogle Scholar
California Department of Food and Agriculture [CDFA] (2018) 2018 Agricultural Statistics Review. Page 76. https://www.cdfa.ca.gov/statistics/PDFs/2017-18AgReport.pdf. Accessed: May 27, 2020Google Scholar
California Irrigation Management Information System [CIMIS] (2020). CIMIS overview. https://cimis.water.ca.gov/. Accessed: March 30, 2020Google Scholar
Company, RSI, Gradziel, TM (2017) Almonds: botany, production and uses. Boston, MA: CABI. 510 p CrossRefGoogle Scholar
Hanson, BD, Shrestha, A, Shaner, DL (2009) Distribution of glyphosate-resistant horseweed (Conyza canadensis) and relationship to cropping systems in the Central Valley of California. Weed Sci 57:4853 CrossRefGoogle Scholar
Hanson, BD, Wright, SD, Sosnoskie, LM, Fischer, A, Jasieniuk, M, Roncoroni, JA, Hembree, KJ, Orloff, SB, Shreshta, A, Al-Khatib, K (2014) Herbicide-resistant weeds challenge some signature cropping systems. California Agriculture 68:142152 CrossRefGoogle Scholar
Hatzinikolaou, AS, Eleftherohorinos, IG, Vasilakoglou, IB (2004) Influence of formulation on the activity and persistence of pendimethalin. Weed Technol 18:397403 CrossRefGoogle Scholar
Jasieniuk, M, Ahmad, R, Sherwood, AM, Firestone, JL, Perez-Jones, A, Lanini, T, Mallory-Smith, CA, Stednick, Z (2008) Glyphosate-resistant Italian ryegrass (Lolium multiflorum) in California: distribution, response to glyphosate, and molecular evidence for an altered enzyme. Weed Sci 56:496502 CrossRefGoogle Scholar
Khale, D, Wickham, H (2013) ggmap: spatial visualization with ggplot2. R J 5:144161 CrossRefGoogle Scholar
Lenth, R, Singmann, H, Love, J, Buerkner, P, Herve, M (2020) Estimated marginal means, aka least-squares means. https://github.com/rvlenth/emmeans. Accessed: February 10, 2020Google Scholar
Micke, W, ed (1996) Almond Production Manual. Oakland, CA: University of California Agriculture and Natural Resources. 277 p Google Scholar
Moretti, ML, Mejorado, R, Watkins, S, Doll, D, Hanson, BD (2013) Post-emergence weed control options in tree nut orchards. Pages 41–47 in Proceedings of the 65th California Weed Science Society annual meeting. Sacramento, CA: California Weed Science SocietyGoogle Scholar
Moretti, ML, Shrestha, A, Hembree, KJ, Hanson, BD (2015) Postemergence control of glyphosate/paraquat-resistant hairy fleabane (Conyza bonariensis) in tree nut orchards in the Central Valley of California. Weed Technol 29:501508 CrossRefGoogle Scholar
Moretti, ML, Sosnoskie, LM, Shrestha, A, Wright, SD, Hembree, KJ, Jasieniuk, M, Hanson, BD (2016) Distribution of Conyza sp. in orchards of California and response to glyphosate and paraquat. Weed Sci 64:339347 CrossRefGoogle Scholar
Morran, S, Moretti, ML, Brunharo, CA, Fischer, AJ, Hanson, BD (2018) Multiple target site resistance to glyphosate in junglerice (Echinochloa colona) lines from California orchards. Pest Manag Sci 74:27472753 CrossRefGoogle ScholarPubMed
Norris, RF, Caswell-Chen, EP, Kogan, M, eds (2003) Concepts in Integrated Pest Management. Upper Saddle River, NJ: Prentice Hall. 586 p Google Scholar
Oliveira, MC, Jhala, AJ, Gaines, T, Irmak, S, Amundsen, K, Scott, JE, Knezevic, SZ (2017) Confirmation and control of HPPD-inhibiting herbicide–resistant waterhemp (Amaranthus tuberculatus) in Nebraska. Weed Technol 31:6779 CrossRefGoogle Scholar
R Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org. Vienna, AustriaGoogle Scholar
Shaner, DL (2012) Field dissipation of sulfentrazone and pendimethalin in Colorado. Weed Technol 26:633637 CrossRefGoogle Scholar
Shrestha, A, Hembree, KJ, Va, N (2007) Growth stage influences level of resistance in glyphosate-resistant horseweed. California Agriculture 61:6770 Google Scholar
Simarmata, M, Kaufmann, JE, Penner, D (2003) Potential basis of glyphosate resistance in California rigid ryegrass (Lolium rigidum) . Weed Sci 51:678682 CrossRefGoogle Scholar
Soltani, N, Nurse, RE, Sikkema, PH (2016) Biologically effective dose of glyphosate as influenced by weed size in corn. Can J Plant Sci 96:455460 Google Scholar
Zimdahl, RL, Pietro, C, Ann, CB (1984) Degradation of pendimethalin in soil. Weed Sci 32:408412 Google Scholar
Figure 0

Figure 1. California map with field experiment locations. Data points are slightly shifted to avoid stacking for clarity of presentation.

Figure 1

Table 1. Sources of herbicides used in the orchard weed control experiments.

Figure 2

Table 2. Winter herbicide programs for Erigeron bonariensis (ERIBO) and Echinochloa colona (ECHCO) control in California almond orchard large-plot experiments.

Figure 3

Table 3. Winter herbicide programs for Erigeron bonariensis (ERIBO) and Echinochloa colona (ECHCO) control in California almond orchards small-plot experiments at multiple locations and years.

Figure 4

Table 4. Sequential treatments, rates, and application timing in walnut orchards in Tulare County, CA.

Figure 5

Figure 2. Junglerice control 8 mo after winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 1 and Tulare 2. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130, (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

Figure 6

Figure 3. Junglerice biomass 8 mo after the winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 1. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) Nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130; (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

Figure 7

Figure 4. Junglerice biomass 8 mo after winter herbicide treatments and 5 mo after the spring sequential pendimethalin treatments at Tulare 2. Gray bars represent untreated or winter-only treatments, and yellow bars represent sequential programs. Means followed by same letter are not statistically different. Treatments (in g ai ha–1): (1) nontreated; (2) indaziflam 51; (3) indaziflam 51 + pendimethalin 4,260; (4) indaziflam 51 followed by (fb) pendimethalin 2,130; (5) indaziflam 51 fb pendimethalin 4,260; (6) indaziflam 51 + pendimethalin 2,130 fb pendimethalin 2,130; (7) penoxsulam/oxyfluorfen 17/826; (8) penoxsulam/oxyfluorfen 17/826 + pendimethalin 4,260; (9) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 2,130; (10) penoxsulam/oxyfluorfen 17/826 fb pendimethalin 4,260; (11) penoxsulam/oxyfluorfen 17/826 + pendimethalin 2,130 fb pendimethalin 2,130; (12) flumioxazin 357; (13) flumioxazin 357 + pendimethalin 4,260; (14) flumioxazin 357 fb pendimethalin 2,130; (15) flumioxazin 357 fb pendimethalin 4,260; (16) flumioxazin 357 + pendimethalin 2,130 fb pendimethalin 2,130.

Figure 8

Table 5. Contrast analysis of treatment groups.