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FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) MANAGEMENT IN THE EVERGLADES AGRICULTURAL AREA (EAA)
By
JOSE VENANCIO FERNANDEZ
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2017
© 2017 Jose Venancio Fernandez
To my family, wife, and friends for all their love, support, and encouragement
4
ACKNOWLEDGMENTS
“The whole art of teaching is only the art of awakening the natural curiosity of
young minds for the purpose of satisfying it afterwards.” – Anatole France
I am not a child but my brain was infantile when I started this journey; today it has
reached adolescence and is more curious than ever. I have to thank all my committee
members and faculty in the Agronomy and Soil and Water Science Departments at the
University of Florida for awakening my curiosity and for providing the means and
resources necessary for me to develop new ways of thinking.
In particular, I wish to thank my graduate advisor, Dr. Dennis C. Odero, for giving
me the opportunity to be part of his research program. There is no way I can express
my gratitude for all that he has done for me. I am extremely grateful for his friendship,
patience, and the knowledge he imparted to me. This work would have not been
possible without his guidance and support.
I would also like to extend my appreciation to the members of my committee:
Drs. Gregory MacDonald, Jason Ferrell, Brent Sellers, and Chris Wilson, in no specific
order, for the advice provided while conducting this project, for encouraging me to be a
better scientist, and for always taking time from their schedules to address all of my
concerns. I would especially like to thank Hunter and Kali Smith, Mike Durham, Sarah
Berger, Raphael Negrisoli, Ann and Garry Hartman, my Zamorano family, and my
Everglades Research and Education Center family for their friendship and support.
Finally, but certainly not least, I owe this achievement to my parents and siblings
and their families for their support and encouragement throughout this long journey. A
special thanks to my wife, Karen, for trusting me with the decisions make our future.
5
TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 7
LIST OF FIGURES .......................................................................................................... 9
ABSTRACT ................................................................................................................... 10
CHAPTER
1 DIFFERENTIAL RESPONSE OF FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) POPULATIONS IN THE SUGARCANE PRODUCTION AREA OF SOUTH FLORIDA TO ASULAM ................................... 12
Material and Methods ............................................................................................. 16
Plant Material ................................................................................................... 16 Greenhouse Asulam Dose-Response Bioassay ............................................... 16
Outside Container Asulam plus Trifloxysulfuron Dose-Response Bioassay ..... 19 Results and Discussion........................................................................................... 20
Greenhouse Asulam Dose-Response Bioassay ............................................... 20 Outside Container Asulam plus Trifloxysulfuron Dose-Response Bioassay ..... 23
2 EARLY-SEASON FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) CONTROL AND SUGARCANE TOLERANCE TO A PREMIX OF ATRAZINE, MESOTRIONE, AND S-METOLACHLOR .............................................................. 36
Materials and Methods............................................................................................ 39
Fall Panicum Control Experiment ..................................................................... 39 Sugarcane Tolerance Experiment .................................................................... 42
Results and Discussion........................................................................................... 44 Fall Panicum Control Experiment ..................................................................... 44
Organic soil ................................................................................................ 44 Mineral soil ................................................................................................. 47
Sugarcane Tolerance Experiment .................................................................... 50
3 FIELD DISSIPATION OF S-METOLACHLOR IN ORGANIC AND MINERAL SOILS IN SOUTH FLORIDA ................................................................................... 60
Materials and Methods............................................................................................ 62
Study Location .................................................................................................. 62 Herbicide Treatment Application and Soil Sampling ......................................... 63
Herbicide Extraction and Analysis .................................................................... 64 Statistical Analysis ............................................................................................ 65
Results and Discussion........................................................................................... 66
6
Organic Soils .................................................................................................... 66 Mineral Soils ..................................................................................................... 67
4 CONCLUSIONS ..................................................................................................... 74
LIST OF REFERENCES ............................................................................................... 76
BIOGRAPHICAL SKETCH ............................................................................................ 83
7
LIST OF TABLES
Table page 1-1 Fall panicum populations, collection location, and history of exposure to
asulam. ............................................................................................................... 28
1-2 ANOVA and analysis of deviance results for fall panicum population aboveground dry weight and regrowth (probability of survival), respectively in response to asulam in the greenhouse. .............................................................. 28
1-3 Log-logistic model parameters and standard errors in parenthesis for fall panicum population aboveground dry weight (Eq 1-1) and regrowth (probability of survival) (Eq 1-2) in response to asulam in the greenhousea. ...... 29
1-4 ANOVA and analysis of deviance results for fall panicum population aboveground dry weight and regrowth (probability of survival), respectively in response to asulam applied alone or in combination with trifloxysulfuron in outside container experiments. ........................................................................... 30
1-5 Log-logistic model parameters and standard errors in parenthesis for fall panicum population aboveground dry weight in response to asulam applied alone or in combination with trifloxysulfuron in outside container experimentsa. ...................................................................................................... 30
1-6 Log-logistic model parameters and standard errors in parenthesis for fall panicum population regrowth (probability of survival) in response to asulam applied alone or in combination with trifloxysulfuron in outside container experimentsa. ...................................................................................................... 31
2-1 Sugarcane varieties, planting and application dates for PRE and early POST herbicide treatments for fall panicum control on organic and mineral soils. ........ 53
2-2 Herbicide treatments, rates, and application timing on organic and mineral soils for fall panicum control and sugarcane tolerance experiments. .................. 54
2-3 Planting and herbicide application dates for sugarcane varietal response to Pre and early POST herbicides on organic and mineral soils. ............................ 54
2-4 Fall panicum control and sugarcane stalk counts in response to PRE and early POST herbicide treatments on organic soils in Belle Glade, FL. ............... 55
2-5 Fall panicum control and sugarcane stalk counts in response to PRE and early POST herbicide treatments on mineral soils near Loxahatchee, FL. ......... 56
2-6 Sugarcane stand (population) in response to PRE and early POST herbicide treatments on mineral soils 4 mo after PRE application (equivalent to 3 mo after early POST application) in Belle Glade, FL in 2015-2016. ......................... 57
8
3-1 Model parameters and standard errors in parenthesis for the linear and exponential decay models (provided in Eq 3-1 and 3-2, respectively) for organic and mineral soils, respectively, half-life and coefficient of determination (R2) for dissipation of S-metolachlor in Florida sugarcane fields. .................................................................................................................. 69
3-2 Weekly average temperature and rainfall for the four locations for the duration of the experiment.a ................................................................................ 69
9
LIST OF FIGURES
Figure page 1-1 Aboveground dry weight of fall panicum populations in response to asulam
28 d after treatment in the greenhouse. The x-axis uses a logarithmic scale. .... 32
1-2 Probability of survival of fall panicum treated with asulam 7 d after aboveground biomass harvesting (equivalent to 35 d after treatment) in the greenhouse. The x-axis uses a logarithmic scale. .............................................. 33
1-3 Aboveground dry weight of fall panicum populations in response to asulam applied alone or in combination with trifloxysulfuron (16 g ha-1) 28 d after treatment in outside container experiments combined over two experimental runs. The x-axis uses a logarithmic scale. .......................................................... 34
1-4 Probability of survival of fall panicum treated with asulam alone or in combination with trifloxysulfuron (16 g ha-1) 7 d after aboveground biomass harvesting (equivalent to 35 d after treatment) in outsider container experiments combined over two experimental runs. The x-axis uses a logarithmic scale. ................................................................................................ 35
2-1 Air temperature and rainfall during the experiment early in the season on organic soil in 2014-2015 and 2015-2016 near Belle Glade, FL (Source: https://rainwise.net/weather/erec133430). .......................................................... 58
2-2 Air temperature and rainfall during the experiment early in the season on mineral soil in 2014-2015 and 2015-2016 near Loxahatchee, FL (Source: https://rainwise.net/weather/erec233430). .......................................................... 59
3-1 Air temperature and rainfall during the experiment in 2013-2014 and 2014-2015 sugarcane growing seasons in Belle Glade, Fl on organic soil (Source: https://rainwise.net/weather/erec133430). .......................................................... 70
3-2 Air temperature and rainfall during the experiment in 2014-2015 and 2015-2016 sugarcane growing seasons near Loxahatchee, Fl on organic soil (Source: https://rainwise.net/weather/erec233430). ........................................... 71
3-3 Field dissipation of S-metolachlor in organic soil in Florida from 2013 to 2015. Data fitted to Eq 3-1. ........................................................................................... 72
3-4 Field dissipation of S-metolachlor in mineral soil in Florida from 2014 to 2016. Data fitted to Eq 3-2. ........................................................................................... 73
10
Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy
FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) MANAGEMENT IN THE
EVERGLADES AGRICULTURAL AREA (EAA)
By
Jose Venancio Fernandez
May 2017
Chair: Dennis C. Odero Cochair: Gregory E. MacDonald Major: Agronomy
Fall panicum (Panicum dichotomiflorum Michx.) is the most prevalent grass weed
associated with sugarcane (Saccharum spp. interspecific hybrids) production in Florida.
Currently, asulam is the only herbicide used to control fall panicum that escapes PRE
and early POST herbicide applications. However, sugarcane growers are reporting
reduced control of fall panicum with asulam. Dose-response bioassays were conducted
to determine the response of four south Florida fall panicum populations and one control
(Mississippi) population to asulam. The south Florida populations were more tolerant to
asulam compared to the control population. Further studies showed adequate
postemergence control of all populations could be achieved by tank-mixing asulam with
trifloxysulfuron.
A commercial premix of atrazine, mesotrione and S-metolachlor was evaluated
as an alternative for fall panicum control. The premix was compared to commercial
herbicide standards used by sugarcane growers on organic and mineral soils. On
organic soils, the premix performed similar to the PRE standard used by the growers;
11
however, it did not provide acceptable fall panicum control when applied early POST.
On mineral soils, the premix provided control similar to the PRE and POST standards
used by growers. The study showed that fall panicum control with the premix varied
depending on soil type, environmental conditions, and weed size.
Dissipation of S-metolachlor on organic and mineral soils of south Florida was
evaluated. Half-life (DT50) of S-metolachlor on organic soil was 19 days in the first year
and 62 days in the second year. On mineral soil, the DT50 of S-metolachlor was 12 and
24 days in the first and second years, respectively. Half-life values ranging from 12 to
24 days have previously been reported in the southern United States.
This research confirms the observations reported by sugarcane growers
regarding reduced fall panicum control with asulam. The results show that tank-mixing
asulam with trifloxysulfuron improves control of fall panicum and the commercial
herbicide premix is viable alternative that can be incorporated in sugarcane weed
management programs that include fall panicum management.
12
CHAPTER 1 DIFFERENTIAL RESPONSE OF FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) POPULATIONS IN THE SUGARCANE PRODUCTION AREA OF SOUTH
FLORIDA TO ASULAM
Sugarcane (Saccharum spp. interspecific hybrids) is an important row crop in
Florida cultivated on approximately 172,000 ha (USDA-NASS 2017a). Sugarcane
production is located in south Florida primarily around the southern edge of Lake
Okeechobee in the Everglades Agricultural Area (EAA). Approximately 78% of the crop
is cultivated on organic or muck soils (Histosols) of the EAA, and the remainder 22% is
on mineral soils adjacent to the EAA (VanWeelden et al. 2016). In Florida, a single
planting of sugarcane is harvested three to five times with the first year’s crop (plant
cane) representing 34% and subsequent regrowth crops (ratoon cane) representing
66% of the crop (VanWeelden et al. 2016). Production decline to unacceptable levels in
the ratoon crop culminates in plowing the crop under after harvest followed by
immediate replanting (referred to as successive planting) or rotation with other crops
prior to replanting. Crops commonly grown in rotation with sugarcane in Florida include
rice (Oryza sativa L.), commercial sod, sweet corn (Zea mays L. var. saccharata),
radish (Raphanus sativus L.), green bean (Phaseolus vulgaris L.), and several leafy
green vegetables. The long sugarcane production cycle in combination with rotating the
crop with grass crops results in heavy weed pressure of mostly annual and perennial
grasses.
Fall panicum (Panicum dichotomiflorum Michx.), a member of the Poaceae family
and native to eastern United States and West Indies (Bryson and DeFelice 2009), is the
most prevalent annual grass weed associated with sugarcane cultivation in Florida
(Odero et al. 2014). Currently, fall panicum is widely distributed throughout most of the
13
continental United States with the exception of Wyoming and North Dakota (USDA-
NRCS 2017b). Fall panicum is a prolific seed producer and a single plant can produce
10,000 to over 100,000 seeds depending on plant size (Fausey and Renner 1997,
Govinthasamy and Cavers 1995). The variation in fall panicum seed quantity is
attributed to seed shattering soon after ripening which makes estimation of seed
number difficult (Govinthasamy and Cavers 1995). Optimal fall panicum germination in
the field occurs at depths of 1.0 to 2.5 cm, although some emergence from as deep as
7.5 cm can occur (Brecke and Duke 1980; Fausey and Renner 1997). In south Florida,
fall panicum germination can occur year round because of the subtropical climate;
however, the highest emergence is normally observed between September and May
which coincides with planting, harvesting, and early season development of sugarcane
(J. V. Fernandez and D. C. Odero, personal observation). The critical timing of fall
panicum removal in sugarcane ranges from 6 to 8 wk after emergence indicating early
season competition, and season-long fall panicum interference can result in up to 60%
sucrose yield reduction (Odero et al. 2016). Interference effects of other grass weeds in
sugarcane have also been shown to result in significant yield reductions. Lencse and
Griffin (1991) reported season-long itchgrass (Rottboellia cochinchinensis (Lour) W.D.
Clayton) interference reduced sugarcane yield by 43%. Millhollon (1995) reported that
sugarcane yields were reduced by 17 and 35% after one and two years of johnsongrass
(Sorghum halepense (L.) Pers.) interference, respectively.
Management programs for fall panicum in Florida sugarcane, regardless of the
soil type, generally consist of multiple herbicide applications in combination with
mechanical cultivation to provide season-long control. Pendimethalin applied PRE in
14
combination with atrazine or metribuzin is used for early season fall panicum control.
However, reduced activity from pendimethalin occurs when applied under dry conditions
with no incorporation (Odero and Shaner 2014a); conditions often associated with
sugarcane planting and harvesting in Florida. Consequently, early POST application of
atrazine or metribuzin in combination with ametryn are used for control of fall panicum
<4 cm in height. Because of the small window of control provided by the triazine
herbicides, asulam applied alone or sometimes in combination with trifloxysulfuron is
used to control fall panicum that escape PRE and early POST herbicide applications
(Odero and Dusky 2014; Odero et al. 2014). The asulam-trifloxysulfuron tank-mix has
also been shown to enhance the efficacy of asulam for johnsongrass control in
sugarcane (Dalley and Richard 2008) and tropical signalgrass (Urochloa subquadripara
(Trin.) R. D. Webster) control in St. Augustinegrass (Stenotaphrum secondatum (Walt.)
Kuntz) (Teuton et al. 2004).
Asulam is a phenylsulfonyl carbamate herbicide thought to inhibit normal mitotic
division and thereby interfere with cell division and expansion (Anderson 1996, Sterret
and Fretz 1975). It has also been reported to inhibit folic acid synthesis from p-
aminobenzoic acid (PABA), resulting in impairment of biological methylations and hence
inhibit protein and nucleic acid synthesis in susceptible plants (Stephen et al. 1980;
Veerasekaran et al. 1981a; Hewertson and Collin 1984). Thus, the mechanism of action
of asulam appears to be similar to that of a carbamate and a sulphanilamide which
inhibit mitosis and folic acid synthesis, respectively (Shaner 2014).
More often, Florida sugarcane growers are reporting reduced control of fall
panicum with asulam. Reduced weed control can be associated with evolution of
15
herbicide resistance or poor management practices. To date no weed resistance to
asulam has been reported (Heap 2017); however, enhanced resistance of barley
(Hordeum vulgare L.) to asulam has been achieved by selecting individual plants that
were able to grow in nutrient medium containing asulam (Giffard et al. 1986). Plant
tolerance to asulam is associated with enhanced folate levels (Veerasekaran et al.
1981b).
Management practices that can potentially affect asulam efficacy are application
timing and carrier volume. The large and concentrated acreage of sugarcane commonly
results in fields that are sprayed later than the optimum timing. Reduced control of
torpedograss (Panicum repens L.) regrowth in sugarcane has been reported when
asulam is not applied at an optimum timing of 60 d after planting (DAP) (Hossain et al.
2001). Asulam applications 20 and 40 DAP allowed new regrowth to appear while
applications 80 DAP did not provide complete control of torpedograss (Hossain et al.
2001). Because asulam is a systemic herbicide, it requires good coverage and spray
retention for efficacious weed control. In Florida to cover large swaths of sugarcane
fields, many growers reduce carrier volume from 187 to 94 L ha-1 and increase spraying
speed from 5 to 16 km hr-1. Asulam applications using <187 L ha-1 carrier volume can
be intercepted by sugarcane foliage thereby resulting in reduced contact with fall
panicum. In contrast, carrier volume >187 L ha-1 can produce bigger droplets that
bounce and wash down to the ground. Richard (1991) reported an optimal spray volume
of 187 L ha-1 for johnsongrass control with asulam for spray volumes ranging from 47 to
561 L ha-1. Veerasekaran et al. (1977) reported that asulam absorption in brackenfern
(Pteridium aquilinum (L.) Kuhn) reduced by 20% at 14 d after treatment (DAT) when
16
temperature decreased from 30 to 20 C suggesting that the efficacy of asulam is
affected by temperature. Based on the aforementioned observations, it is important to
determine if fall panicum in Florida sugarcane is becoming less sensitive or resistant to
asulam, or if reduced control is the result of current management practices. Therefore,
the objectives of this study were to (i) determine sensitivity to asulam of several fall
panicum populations in south Florida using a dose-response bioassay and (ii) determine
the efficacy of asulam plus trifloxysulfuron for improved fall panicum control.
Material and Methods
Plant Material
Seeds from four populations of fall panicum were collected at maturity from two
organic soil locations in the EAA and two mineral soil locations adjacent to the EAA in
2015 (Table 1-1). Collected seeds from each population were stored for four mo in the
dark at 2 C prior to use. A fall panicum population with no known history of exposure to
asulam from Azlin Seed Service (Leland, MS 38756) obtained in 2015 was used as a
comparison.
Greenhouse Asulam Dose-Response Bioassay
The response of all five populations of fall panicum to asulam was evaluated in
greenhouse experiments conducted at the University of Florida, Gainesville, FL in 2015.
Seeds from each population were planted and allowed to germinate in flats (28 cm wide
by 54 cm long by 6.2 cm deep) containing a commercial potting medium (Fafard Mixes
for Professional Use, Conrad Fafard Inc., Agawam, MA 01001). At 18 d after
emergence (DAE), individual plants were transplanted to Cone-tainers™ (SC10 Cone-
tainers, International Greenhouse Company, Danville, IL 61834) 3.8 cm in diameter by
21 cm deep and allowed to grow for 28 d. At transplanting, plants of the same size were
17
selected to obtain uniformity across all plants. Plants were watered as needed and
fertilized with 14-14-14 slow release fertilizer (Osmocote® Smart-Release Plant Food,
Scotts-Sierra Horticultural Products Company, Marysville, OH 43040) to ensure that
moisture and nutrients were not limiting factors. The plants were kept in a greenhouse
maintained at 33/24 C day/night temperatures under natural light.
The experiment was arranged as a completely randomized design with six
replications of each treatment for each population and repeated twice. Treatments
consisted of asulam (Asulox®, United Phosphorus, Inc., King of Prussia, PA 19406)
applied at 230, 470, 940, 1880, 3700, 7400, and 14800 g ha-1 on fall panicum plants
with an average height of 30 cm for all populations at 46 DAE. These rates correspond
to 1/16 to 4x the recommended asulam single application use rate of 3700 g ha-1 on
sugarcane. A nonionic surfactant at 0.25%v/v (Induce®, Helena Chemical Company,
Collierville, TN 38017) was included with all asulam rates. An untreated control for each
population was included for comparison. Asulam was applied using a moving-nozzle
spray chamber (Generation II Spray Booth, Devries Manufacturing Corp., Hollandale,
MN 56045) equipped with a TeeJet 8002E nozzle tip (Spraying Systems Co. ®,
Wheaton, IL 60187) calibrated to deliver 187 L ha-1 at 172 kPa. Treatments were
applied on July 6, 2015 and August 3, 2015 for the first and second experimental runs,
respectively. Plants were returned to the greenhouse following treatment applications
and maintained as previously described. Subirrigation was used after spraying to avoid
washing the herbicide from the plants. To avoid cutting the growing points, aboveground
biomass was harvested 2.5 cm, aboveground at 28 DAT. The harvested biomass was
then dried in an oven set at 60 C for 72 hr to obtain aboveground dry weight. After
18
harvest the plants were kept in the greenhouse for 7 d and allowed to regrow. The
binomial response of presence or absence of fall panicum regrowth was recorded as 1
or 0, respectively from each pot.
Aboveground dry weight data were subjected to ANOVA for each fall panicum
population to determine the effect of asulam rate, experimental run and their
interactions using R (R version 3.3.3, R Core Team 2016). Nonlinear regression
analysis was then performed on aboveground dry weight data using the drc package
(Ritz and Streibig 2005) of R. Data were analyzed using a four-parameter log-logistic
model similar to that described by Seefeldt et al. (1995), but with the lower limit fixed at
0 so that the equation takes the form:
Y = d/(1+exp{b[log(x)-log(ED50)]} (1-1)
where Y is aboveground dry weight, x is the asulam rate, b is the relative slope at the
inflection point, d is the upper limit, and ED50 is the rate required to cause 50% growth
reduction. Fixing the lower limit at the priori chosen value is biologically relevant
because aboveground dry weight <0 g cannot be obtained, i.e. biomass cannot be
negative even at very high asulam rates.
A generalized linear model was used to conduct analysis of deviance on fall
panicum regrowth data using the glm function in R for each population to determine the
effect of asulam rate, experimental run and their interactions on the probability of fall
panicum survival following herbicide treatment. Analysis of deviance, analogous to
ANOVA, is appropriate for binomial data (Venables and Ripley 2002). A two-parameter
log-logistic model was used to analyze regrowth data for each experimental run to
determine the probability of fall panicum survival after asulam treatment. The two-
19
parameter log-logistic model is similar to the four-parameter log logistic model described
by Seefeldt et al. (1995), but with the upper and lower limits fixed at 1 and 0,
respectively because of the binomial response:
Y = 1/(1+exp{b[log(x)-log(ED50)]}) (1-2)
where Y is regrowth (probability of fall panicum surviving asulam application), and x, b,
are the same as in Eq (1-1) and ED50 is the rate required to result in 50% probability of
survival. A lack-of-fit test at the 95% level comparing the regression models (Eq 1-1 and
1-2) to ANOVA was conducted to determine whether the models were appropriate fit to
data (Ritz and Streibig 2005).
Outside Container Asulam plus Trifloxysulfuron Dose-Response Bioassay
An outside container study was conducted at the University of Florida Everglades
Research and Education Center (EREC) in Belle Glade, FL in 2016 to determine
whether trifloxysulfuron enhances asulam for fall panicum control for four populations
from Florida (Table 1-1). Seeds from each population were planted directly into Cone-
tainers™ containing a commercial potting medium (Sungro® for Professional Growing
Mix, Sun Gro Horticulture, Agawam, MA 01001) and placed outside on benches for the
entire duration of the study in order to expose the plants to field environmental
conditions. At 21 DAE, fall panicum was thinned to one plant per Cone-tainer™ to
obtain uniform size across all plants. Plants were watered as needed and fertilized with
14-14-14 slow release fertilizer to ensure that moisture and nutrients were not limiting
factors. Plants were allowed to grow for 56 and 52 days after planting for the first run
and second experimental runs planted on July 26, 2016 and October 1, 2016,
respectively.
20
A factorial arrangement of asulam rates (0, 230, 470, 940, 1880, 3700, and 7400
g ha-1) and trifloxysulfuron (0, 16 g ha-1) (Envoke, Syngenta Crop Protection, LLC.
Greensboro, NC 27409) were applied to each fall panicum population in a manner
similar to the greenhouse experiment. Herbicide treatments were applied on September
20, 2016 and November 22, 2016 for the first and second experimental runs,
respectively. Plants were returned outside following treatment and maintained as
previously described. Aboveground biomass and regrowth data were collected in a
manner similar to the greenhouse experiment. The experiment was a completely
randomized design with a factorial arrangement and four replications of each treatment
for each population.
Aboveground dry weight data was subjected to ANOVA for each fall panicum
population to determine the effect of asulam treatments, trifloxysulfuron, experimental
run and their interactions using R. Aboveground dry weight data was then fit to Eq 1-1.
Analysis of deviance on fall panicum regrowth data using the glm function in R for each
population to determine the effect of asulam treatments, trifloxysulfuron, experimental
run and their interactions on the probability of fall panicum survival was conducted. The
regrowth data was then fit to Eq 1-2.
Results and Discussion
Greenhouse Asulam Dose-Response Bioassay
There were experimental run-by-treatment interactions (P<0.05) for fall panicum
aboveground dry weight 28 DAT in response to asulam for all five populations;
therefore, data were analyzed separately by experimental run for each population
(Table 1-2). There was a significant effect (P<0.05) of asulam on aboveground dry
weight of fall panicum 28 DAT for all populations (Table1-2). The lack-of-fit test at 95%
21
was not significant (P>0.05) for the fitted curves (Figure 1-1, Table 1-3) indicating that
the log-logistic model (Eq 1-1) provided the best fit to estimate the response of fall
panicum aboveground dry weight for all populations to asulam (Ritz and Streibig 2005).
Parameter estimates for the fitted curves are provided in Table 1-3.
Fall panicum aboveground dry weight decreased as asulam rates increased for
all populations (Figure 1-1). However, there were differences in the d parameter, the
theoretical maximum aboveground dry weight of fall panicum based on the log-logistic
model, between experimental runs for all fall panicum populations resulting in an
increase of 56 to 79% aboveground dry weight from the first to the second experimental
run. This difference was probably attributed to differences in growth rate between the
two runs resulting in the observed experimental run effect (P<0.05) (Table 1-2), even
though plants in both runs were grown for the same duration of time. Similarly, the rate
required to result in 50% fall panicum aboveground dry weight reduction (ED50) varied
between experimental runs for all populations. The ED50 values were 332 and 239 g,
856 and 238 g, 674 and 238 g, 325 and 286 g, and 448 and 344 g for the first and
second experimental runs for Azlin, EREC, Okeelanta, PPI, and Tecan populations,
respectively. Potency of herbicides is typically based on the ED50 parameter as long as
it makes biological sense (Ritz et al. 2015). Therefore, these results show that the Azlin
population was most sensitive to asulam based on overall lowest average ED50 value.
The expected aboveground dry weight reduction for asulam at 3,700 g ha-1 (labeled rate
for sugarcane) based on the log-logistic model (Eq 1-1) was 88 and 99%, 91 and 100%,
99 and 100%, 86 and 100%, and 81 and 96% for the first and second experimental runs
for Azlin, EREC, Okeelanta, PPI, and Tecan populations, respectively. This shows that
22
asulam at the labeled rate would generally provide >93% aboveground fall panicum
growth reduction for all populations with the exception of the Tecan population which
averaged 89% across the two experimental runs. These results show that fall panicum
populations in Florida sugarcane have a differential response to asulam.
Although aboveground dry weight data was used for determining specified doses
of asulam required to provide fall panicum growth reduction, this information did not
show whether these doses would ultimately result in plant mortality. Consequently, a
binary response of fall panicum mortality after aboveground biomass harvesting was
collected to determine probability of survival following exposure to asulam. There were
no significant experimental run-by-treatment interactions (P>0.05) for the binomial
response of fall panicum regrowth 7 d after aboveground biomass harvesting
(equivalent to 35 DAT) for all populations (Table 1-2); therefore, data were combined
across experimental runs for analysis for each population. Similar to aboveground dry
weight, asulam had an effect (P<0.05) on the probability of fall panicum survival
following treatment for all populations. A test of the lack-of-fit at the 95% level was not
significant (P>0.05) for all fitted curves (Table 1-3), indicating that the log-logistic model
(Eq 1-2) was appropriate (Ritz and Streibig 2005). Model parameters are provided in
Table 1-3. The probability of fall panicum survival decreased with increasing asulam
rates for all populations (Figure 1-2). Asulam rates that would result in 50% fall panicum
survival (ED50) following application were 547, 1099, 979, 784, and 1468 g ha-1 for
Azlin, EREC, Okeelanta, PPI, and Tecan populations, respectively, indicating
differences in susceptibility to asulam among the populations. Similar to aboveground
dry weight, the Azlin population was more susceptible. Asulam was 1-, 2-, 2-, and 3-fold
23
less potent on PPI, Okeelanta, EREC, and Tecan populations, respectively, compared
to the Azlin population. The Azlin population came from a location that had no known
history of exposure to asulam. The probability of fall panicum surviving following
exposure to asulam at the sugarcane labeled rate of 3,700 g ha-1 for Azlin, EREC,
Okeelanta, PPI, and Tecan populations was estimated to be 0, 2, 1, 0, and 7%,
respectively in a controlled environment.
Currently, there is no information on asulam resistant weeds (Heap 2017). Some
sugarcane growers in Florida use asulam rates <3700 g ha-1, most commonly 2800 g
ha-1, depending fall panicum size. However, it has been reported that resistance can be
achieved in barley by selecting individuals that survive low rates of asulam (Giffard et al.
1986). Neve and Powles (2005) demonstrated the potential for reduced rates of an
ACCase inhibiting herbicide, diclofop-methyl, rapidly selecting for resistance in rigid
ryegrass (Lolium rigidum Gaudin). Similarly, Busi et al. (2011) reported pyroxasulfone (a
very long chain fatty acid inhibitor) resistance in rigid ryegrass obtained by recurrent
exposure to low doses with >30% of plant survival at 2.4-fold the recommended rate
after three generations of recurrent pyroxasulfone selection.
Outside Container Asulam plus Trifloxysulfuron Dose-Response Bioassay
The interactions of asulam, trifloxysulfuron, and experimental run were not
significant for all populations (P>0.05) with the exception of the EREC population
(P=0.006) for fall panicum aboveground dry weight (Table 1-4). However, the main
effects of asulam and trifloxysulfuron were significant (P<0.05); therefore, only these
main effects are discussed. Fall panicum aboveground dry weight was modeled as a
function of asulam applied alone or in combination with trifloxysulfuron using a log-
logistic model (Eq 1-1). A test of lack-of-fit at the 95% level was not significant (P>0.05)
24
(Table 1-5), indicating that the regression model was appropriate for all fitted curves
(Ritz and Streibig 2005). Fall panicum aboveground dry weight decreased as asulam
rate increased when applied alone or in combination with trifloxysulfuron for all
populations 28 DAT (Figure 1-3). Aboveground dry weight reduction was greater when
asulam was applied in combination with trifloxysulfuron for all the populations. The
ratios of the ED50 values for asulam applied alone compared to tank-mixes with
trifloxysulfuron were significantly different from 1 (P<0.05) for all populations, indicating
that addition of trifloxysulfuron to asulam reduced aboveground dry weight for all
populations at 28 DAT. Addition of trifloxysulfuron to asulam increased the potency of
asulam by 27-, 5-, 7-, and 21-fold for the EREC, Okeelanta, PPI, and Tecan
populations, respectively. Enhanced efficacy of asulam and trifloxysulfuron tank mix has
previously been reported on johnsongrass and tropical signalgrass control (Dalley and
Richard 2008; Teuton et al. 2004). Furthermore, the ED50 values for Tecan and
Okeelanta populations for asulam applied alone exceeded the labeled sugarcane rate of
3,700 g ha-1.
The observed response of fall panicum populations from Florida sugarcane to
asulam in an outside environment similar to what occurs in the field was different from
the response observed in a controlled environment (greenhouse), even though plants
for both experiments were grown from the same batch of seeds. Similarly, Teuton et al.
(2004) reported different responses of tropical signalgrass to herbicides in controlled
experiment environment and field experiments. In their study, the size of tropical
signalgrass was different for the greenhouse and the field experiments. In the outside
container experiment, the reduced sensitivity of fall panicum to asulam compared to the
25
greenhouse experiment was probably attributed to temperature. The average daily high
and low temperatures after treatment for the entire duration of experiments were 20.5
and 29.9 C for the first experimental run and 15.5 and 26.3 C for the second
experimental run, respectively (Anonymous 2017a). Veerasekaran et al. (1977) reported
reduced absorption of asulam of 20% when temperatures decreased from 30 to 20 C.
Similarly, Sharma et al. (1978) reported 87 and 40% less asulam foliar penetration 4 hr
after treatment in wild oat (Avena fatua L.) at 10 and 20 C, respectively, compared to 30
C. This suggests that asulam efficacy in Florida sugarcane is probably affected by low
temperatures particularly early in the year (January to April) when minimum and
maximum temperatures (average for the last 15 years) range from 10 to 16 C and 23 to
28 C, respectively (Anonymous 2017a).
Effects of asulam and trifloxysulfuron with respect to fall panicum probability of
survival (regrowth) were significant (P<0.05) for all populations, but three way
interactions with experimental run were not significant (Table 1-4). Therefore, only the
main effects are discussed. The log-logistic model (Eq 1-2) provided the best fit to
estimate the probability of fall panicum survival following treatment with asulam alone or
in combination with trifloxysulfuron. A test of lack-of-fit at the 95% level was not
significant (P>0.05) (Table 1-6), indicating that the regression model was appropriate for
the fitted curves (Ritz and Streibig 2005). The probability of fall panicum survival
decreased as asulam rate increased when applied alone or in combination with
trifloxysulfuron for all populations 7 d after aboveground biomass harvesting (equivalent
to 35 DAT) (Figure 1-4). However, the probability of survival was greater when asulam
was applied alone compared to the combination with trifloxysulfuron for all the
26
populations. Similar to aboveground dry weight, the ratios of the ED50 values for asulam
applied alone compared to tank-mixes with trifloxysulfuron were significantly different
from 1 (P<0.05) for all populations, indicating that combination of trifloxysulfuron with
asulam decreased the probability of fall panicum survival. In the absence of
trifloxysulfuron, fall panicum survival increased 3-, 2-, 2-, and 3-fold for the EREC,
Okeelanta, PPI, and Tecan populations, respectively based on ED50 values. The
probability of fall panicum survival at the sugarcane labeled rate of asulam decreased
from 19, 47, and 28% to 4, 2, and 0% for the EREC, Okeelanta, and PPI populations
when trifloxysulfuron was added to the tank mix. In contrast, the probability of survival of
the Tecan population increased from 2 to 6% at the labeled asulam rate with addition of
trifloxysulfuron even though the ED50 value decreased with the tank mix.
The probability of fall panicum survival of 2 to 47% at the labeled sugarcane rate
based on the outside container experiment confirms observations of reduced fall
panicum control by asulam reported by Florida sugarcane growers. Differential
sensitivity of fall panicum populations to asulam was observed suggesting that fall
panicum control will probably vary in the sugarcane production area of south Florida
depending on the population. Although, both controlled environment and outside
experiments indicated no evolution of asulam resistance in fall panicum populations in
Florida sugarcane, the outside container experiment demonstrated that environmental
factors, particularly temperature may contribute to reduced control observed by
sugarcane growers. The results showed that reduced controlled can be overcome by
tank mixing asulam with trifloxysulfuron. However, further research needs to be
conducted to determine the effects of fall panicum growth stage, temperature, and
27
application practices such as carrier volume and speed on the efficacy of asulam.
Because of the potential for recurrent selection with low rates of asulam that can select
for herbicide resistance (Neve and Powles 2005; Busi et al. 2011), it is important to
educate growers on making more informed management decisions to reduce potential
development of fall panicum resistance to asulam in Florida sugarcane.
28
Table 1-1. Fall panicum populations, collection location, and history of exposure to asulam.
Population Location Soil type Exposure to asulama
EREC Belle Glade, FL (26.66 N, 80.63 W) Organic Nob Okeelanta South Bay, FL (26.58 N, 80.78 W) Organic Yes PPI Loxahatchee, FL (26.76 N, 80.39 W) Mineral Yes Tecan Clewiston, FL (26.63 N, 80.94 W) Mineral Yes Azlin Leland, MS Unknown No
aPopulation exposed to at least one application of asulam (3700 g ha-1) every season for the last 10 years. bEREC population was collected from a field that is not used for sugarcane production but is adjacent to a sugarcane field. Table 1-2. ANOVA and analysis of deviance results for fall panicum population
aboveground dry weight and regrowth (probability of survival), respectively in response to asulam in the greenhouse.
Population
Response
P-value ANOVA Analysis of deviance
Azlin Asulam rate <0.0001 <0.0001 Run <0.0001 0.1551 Asulam rate × Run <0.0001 0.9824
EREC Asulam rate <0.0001 <0.0001 Run <0.0001 0.6622 Asulam rate × Run <0.0001 0.9779
Okeelanta Asulam rate <0.0001 <0.0001 Run 0.0412 0.1707 Asulam rate × Run <0.0001 1.0000
PPI Asulam rate <0.0001 <0.0001 Run 0.0002 0.5304 Asulam rate × Run <0.0001 0.9934
Tecan Asulam rate <0.0001 <0.0001 Run <0.0001 1.0000 Asulam rate × Run <0.0001 0.9690
29
Table 1-3. Log-logistic model parameters and standard errors in parenthesis for fall panicum population aboveground dry weight (Eq 1-1) and regrowth (probability of survival) (Eq 1-2) in response to asulam in the greenhousea.
Population Response Runb Model parameters (±SE) Lack-of-fit testc b d e
Azlin Aboveground dry weight 1 0.83 (0.18) 2.23 (0.16) 331.61 (94.33) 0.4433 2 1.92 (0.42) 9.15 (0.48) 239.01 (28.10) 0.9968
Survival Combined 3.90 (1.07) --- 547.46 (46.00) 1.0000 EREC Aboveground dry weight 1 1.60 (0.44) 1.70 (0.13) 855.54 (168.85) 0.0441
2 4.58 (1.63) 7.93 (0.38) 238.01 (11.27) 0.9999 Survival Combined 3.35 (0.83) --- 1098.64 (144.29) 1.0000
Okeelanta Aboveground dry weight 1 2.52 (1.19) 2.89 (0.25) 673.62 (104.62) 0.0049 2 4.58 (1.63) 6.63 (0.37) 238.01 (11.27) 0.9999
Survival Combined 3.21 (0.78) --- 978.75 (131.30) 1.0000 PPI Aboveground dry weight 1 0.84 (0.24) 2.89 (0.25) 325.46 (110.69) 0.5125
2 2.49 (0.54) 6.63 (0.37) 285.91 (26.03) 0.9772 Survival Combined 5.04 (1.52) --- 784.41 (84.40) 0.3829
Tecan Aboveground dry weight 1 0.67 (0.20) 1.96 (0.22) 447.54 (241.27) 0.3340 2 1.36 (0.25) 7.74 (0.51) 344.44 (62.33) 0.2480
Survival Combined 2.76 (0.62) --- 1467.50 (212.74) 0.9998 a Eq 1-1: Y = 100/(1+exp{b[log(x)-log(ED50)]}), and Eq 1-2: Y = 1/(1+exp{b[log(x)-log(ED50)]}), whereY is the response (i.e., above ground dry weight or probability of survival), x is the asulam rate, b is the relative slope at the inflection point, d is the upper limit, and ED50 is the rate required to cause 50% response. bData analyzed separately for each experimental run for aboveground dry weight and combined over experimental runs for probability of survival (see Table 1-2). cA lack-of-fit test at the 95% level comparing the regression models (Eq 1-1 and 1-2) to ANOVA was conducted to determine whether the models were appropriate fit for the data.
30
Table 1-4. ANOVA and analysis of deviance results for fall panicum population aboveground dry weight and regrowth (probability of survival), respectively in response to asulam applied alone or in combination with trifloxysulfuron in outside container experiments.
Population Responsea P-value ANOVA Analysis of deviance
EREC Asulam <0.0001 <0.0001 Trifloxysulfuron <0.0001 0.0013 Experimental run <0.0001 0.0235 Asul × Trif × Run 0.0060 1.0000
Okeelanta Asulam <0.0001 <0.0001 Trifloxysulfuron 0.0001 0.0008 Experimental run <0.0002 1.0000 Asul × Trif × Run 0.1052 1.0000
PPI Asulam <0.0001 <0.0001 Trifloxysulfuron 0.0168 0.0635 Experimental run <0.0001 0.0010 Asul × Trif × Run 0.5780 1.0000
Tecan Asulam 0.2016 <0.0001 Trifloxysulfuron 0.0871 <0.0001 Experimental run 0.0039 1.0000 Asul × Trif × Run 0.4908 1.0000
aAbbreviations: Asul, asulam; Trif, trifloxysulfuron.
Table 1-5. Log-logistic model parameters and standard errors in parenthesis for fall
panicum population aboveground dry weight in response to asulam applied alone or in combination with trifloxysulfuron in outside container experimentsa.
Population Trifloxysulfuron (g ha-1)
Model parameters (±SE) Lack-of-fit testb b d e
EREC 0 1.58 (0.61) 5.98 (0.60) 1671.71 (488.52) 0.3124 16 0.44 (0.15) 5.10 (0.33) 62.44 (59.14) 0.8906
Okeelanta 0 1.24 (0.55) 4.70 (0.43) 5415.29 (1984.51) 0.8799
16 0.69 (0.18) 4.27 (0.38) 1008.58 (390.88) 0.8474
PPI 0 0.86 (0.26) 5.19 (0.52) 2020.26 (784.73) 0.7509 16 0.61 (0.17) 5.06 (0.40) 303.72 (136.07) 0.7272
Tecan 0 0.90 (0.55) 5.68 (0.96) 3841.12 (2666.93) 0.8865 16 0.51 (0.21) 5.51 (0.55) 186.06 (145.19) 0.9980
a Eq 1-1: Y = 100/(1+exp{b[log(x)-log(ED50)]}) whereY is the response (above ground dry weight), x is the herbicide rate, b is the relative slope at the inflection point, d is the upper limit, and ED50 is the rate required to cause 50% growth reduction. bA lack-of-fit test at the 95% level comparing the regression models (Eq 1-1) to ANOVA was conducted to determine whether the model was appropriate fit for the data.
31
Table 1-6. Log-logistic model parameters and standard errors in parenthesis for fall panicum population regrowth (probability of survival) in response to asulam applied alone or in combination with trifloxysulfuron in outside container experimentsa.
Population Trifloxysulfuron (g ha-1)
Model parameters (±SE) Lack-of-fit testb
P(survival)c b e
EREC 0 1.50 (0.59) 1426.76 (320.96) 0.7351 19.3% 16 1.56 (0.45) 455.19 (94.53) 0.6735 3.7%
Okeelanta 0 3.77 (1.55) 3591.19 (359.89) 0.7958 47.2%
16 4.43 (1.32) 1440.10 (138.01) 0.8589 1.5%
PPI 0 1.53 (0.42) 2021.80 (412.73) 0.7653 28.4% 16 11.30 (30.62) 1098.84 (515.39) 0.4676 0.0%
Tecan 0 7.40 (8.11) 2141.76 (337.54) 0.5911 1.7% 16 1.58 (0.51) 623.24 (135.66) 0.1979 5.6%
aEq 1-2: Y = 1/(1+exp{b[log(x)-log(ED50)]}), whereY is the response (i.e., probability of survival), x is the asulam rate, b is the relative slope at the inflection point, and ED50 is the rate required to result in 50% probability of survival. bA lack-of-fit test at the 95% level comparing the regression models (Eq 1-1) to ANOVA was conducted to determine whether the model was appropriate fit for the data. cProbability of fall panicum survival following exposure to asulam at the labeled rate for sugarcane of 3700 g ha-1.
32
Figure 1-1. Aboveground dry weight of fall panicum populations in response to asulam
28 d after treatment in the greenhouse. The x-axis uses a logarithmic scale.
33
Figure 1-2. Probability of survival of fall panicum treated with asulam 7 d after
aboveground biomass harvesting (equivalent to 35 d after treatment) in the greenhouse. The x-axis uses a logarithmic scale.
34
Figure 1-3. Aboveground dry weight of fall panicum populations in response to asulam
applied alone or in combination with trifloxysulfuron (16 g ha-1) 28 d after treatment in outside container experiments combined over two experimental runs. The x-axis uses a logarithmic scale.
35
Figure 1-4. Probability of survival of fall panicum treated with asulam alone or in
combination with trifloxysulfuron (16 g ha-1) 7 d after aboveground biomass harvesting (equivalent to 35 d after treatment) in outsider container experiments combined over two experimental runs. The x-axis uses a logarithmic scale.
36
CHAPTER 2 EARLY-SEASON FALL PANICUM (PANICUM DICHOTOMIFLORUM MICHX.) CONTROL AND SUGARCANE TOLERANCE TO A PREMIX OF ATRAZINE,
MESOTRIONE, AND S-METOLACHLOR
Florida is a major sugarcane (Saccharum spp. interspecific hybrids) producing
state, accounting for 48% of total production in the United States (USDA-NASS 2017a).
In 2015, sugarcane was cultivated on approximately 172,000 ha in Florida, making it the
most cultivated field crop in the state (USDA-NASS 2017a). Approximately 78% of
commercial sugarcane is cultivated on organic or muck soils (Histosols) in the
Everglades Agricultural Area (EAA) around the southern tip of Lake Okeechobee in
south Florida, and the remainder 22% is on mineral soils adjacent to the EAA
(VanWeelden et al. 2016). Organic soils of the EAA have organic matter content as high
as 80-90% (Snyder et al. 1978) compared to low organic matter (0.5 to 3%) with no
significant silt or clay associated with mineral soils (Spodols and Entisols) used for
sugarcane cultivation (McCray et al. 2014). Weed interference is a major impediment to
sugarcane production in Florida, making weed management a major production cost
associated with the crop. Weed management is generally difficult on organic compared
to mineral soils because of their high organic matter content, high cation exchange
capacity, and large soil microbial populations associated with herbicide adsorption and
metabolism particularly for soil-applied herbicides (Schueneman and Sanchez 1994,
Shea 1989). Despite the occurrence of several annual and perennial weed species
associated with sugarcane in Florida, fall panicum (Panicum dichotomiflorum Michx.) is
the most prevalent (Odero et al. 2014). Fall panicum is an annual grass weed native to
eastern United States and West Indies (Bryson and DeFelice 2009) widely distributed
throughout most of continental United States with the exception of Wyoming and North
37
Dakota (USDA-NRCS 2017b). In Florida, season-long competition of fall panicum with
sugarcane can result in up to 60% sucrose yield reduction when no adequate control
measures are undertaken (Odero et al. 2016).
Fall panicum management programs in Florida sugarcane generally consist of
multiple herbicide applications in combination with mechanical cultivation to provide
season-long control. Pendimethalin applied at sugarcane planting (August to January)
and on ratoon cane following harvest (October to April) has been the foundation for
PRE fall panicum control in Florida sugarcane. Pendimethalin is applied in combination
with atrazine and metribuzin to broaden the spectrum of weed control in sugarcane.
Generally, the tank-mix of pendimethalin with metribuzin provides better grass control
than with atrazine (Millholon 1993). Fall panicum prevalence has been shown to
increase when atrazine is used as a residual herbicide (Triplett and Lytle 1972). The
effectiveness of pendimethalin is increased by incorporation to reduce loss by
photodecomposition (Shaner 2014). However, rapid dissipation of pendimethalin occurs
when surface applied with no incorporation under dry conditions associated with
sugarcane planting and harvesting in Florida (Odero and Shaner 2014a), resulting in
reduced fall panicum control. Early POST atrazine plus metribuzin or atrazine or
metribuzin applied in combination with ametryn are then used to control fall panicum <4
cm in height. Kupatt et al. (1985) reported that atrazine applied at 1.58 kg ha-1 in
combination with tridiphane at the one- to three-leaf stage of fall panicum provided
effective control; however, the same rate applied at four- to six-leaf stage severely
reduced control. However, Thompson (et al. 1971) reported that fall panicum has
intermediate tolerance to atrazine when applied alone. Although, metribuzin can provide
38
acceptable early POST control of fall panicum (J. V. Fernandez personal observation),
its use is limited on mineral soils of Florida because of leaching concerns (Anonymous
2017). As a result, fall panicum that escape PRE and early POST herbicide applications
are controlled with asulam applied alone or in combination with trifloxysulfuron (Odero
and Dusky 2014; Odero et al. 2014). Millholon (1993) also reported control of itchgrass
(Rottboellia cochinchinensis (Lour) W.D. Clayton) that escaped PRE pendimethalin with
asulam in sugarcane. Recently, Florida sugarcane growers have been reporting
reduced control of fall panicum with asulam. Because of limited number of herbicide
options available for fall panicum control in Florida sugarcane, there is need to evaluate
more weed control options to ensure maximization of sugarcane production.
Currently, a three-way premix of atrazine (853 g ha-1), mesotrione (227 g ha-1),
and S-metolachlor (2,271 g ha-1) has been proposed for PRE and early POST use in
sugarcane. Atrazine, a chloro-s-triazine herbicide that inhibits photosystem II, and
mesotrione, a triketone herbicide that inhibits 4-hydroxyphenylpyruvate (HPPD) are
currently registered for PRE and POST use in sugarcane (Shaner 2014; Mitchell et al.
2001). S-metolachlor, a chloroacetamide herbicide for PRE broadleaf weed and grass
control thought to inhibit the very long-chain fatty acid synthesis (Böger et al., 2000;
Shaner, 2014) is not currently registered for use in sugarcane in the United States.
Armel et al. (2003) reported that PRE atrazine and acetochlor, a chloroacetamide
followed by POST mesotrione provided >80% control of giant foxtail (Setaria faberi
Herrm.) in corn (Zea mays L.). Stephenson et al. (2004) reported that mesotrione alone
or in combination with atrazine provided adequate broadleaf weed control but required
addition of S-metolachlor to provide broadleaf signalgrass (Brachiaria platyphylla
39
Griseb.) control in corn. Armel et al. (2003) also reported synergistic effect of
mesotrione plus atrazine on giant foxtail control in corn. Other studies have
demonstrated variable control of grass weeds with the atrazine plus metolachlor tank-
mix in corn (Buhler 1991; Hartzler and Roth 1993; Johnson et al. 1997; Thomas et al.
2004). Variable giant foxtail control has also been reported for the tank mix of atrazine
with mesotrione (Armel et al. 2003).
There are no reported studies on the efficacy of the premix of atrazine,
mesotrione, and S-metolachlor on grass control in any cropping system. Since
sugarcane can take up to 30 d to emerge after planting, and takes at least four mo after
emergence to close canopy, it is important to determine the efficacy of the three-way
premix for fall panicum control in Florida sugarcane. Therefore, the objectives of this
study were to (i) determine PRE and early POST fall panicum control in sugarcane with
the premix of atrazine, mesotrione, and S-metolachlor on organic and mineral soils of
Florida and (ii) determine the response of sugarcane varieties to PRE and early POST
application of the premix on organic and mineral soils of Florida.
Materials and Methods
Fall Panicum Control Experiment
Field studies were conducted in 2014-2015 and 2015-2016 sugarcane growing
seasons on organic soil at the Everglades Research and Education Center (EREC) in
Belle Glade, FL (26.65 N, 80.63 W in 2014-2015 season; 26.66 N, 80.64 W in 2015-
2016 season) and on mineral soil at the PPI Farm near Loxahatchee, FL (26.76 N,
80.39 W in 2014-2015 season; 26.81 N, 80.44 W in 2015-2016 season). The soil in
Belle Glade was a Dania muck with 75% organic matter and pH of 7.3 while the soil in
Loxahatchee was a Holopaw fine sand with 1.6% organic matter and pH of 7.5.
40
Sugarcane was conventionally planted using mature stalks in 15 cm deep furrows
spaced 1.5 m apart. Fertilizer was applied at all experimental locations based on
University of Florida-IFAS soil test recommendations. Sugarcane varieties and planting
dates are listed in Table 2-1.
Herbicide treatments on both organic and mineral soils consisted of PRE and
early POST application of the premix of atrazine + mesotrione + S-metolachlor (Lumax®
EZ, Syngenta Crop Protection, LLC., Greensboro, NC), atrazine (Atrazine 4L, Winfield
Solutions, LLC., St Paul, MN), mesotrione (Callisto®, Syngenta Crop Protection, LLC.,
Greensboro, NC), and S-metolachlor (Dual II Magnum®, Syngenta Crop Protection,
LLC., Greensboro, NC) (Table 2-2). The premix was applied at the proposed use rate
(1X rate) of 853, 227, and 2,271 g ha-1 of atrazine, mesotrione, and S-metolachlor,
respectively, and at the 2X and 4X rates. Atrazine + pendimethalin (Prowl® H2O, BASF
Ag Products, Research Triangle Park, NC) and atrazine + 2,4-D amine (Amine 4 2,4-D
Weed Killer, Loveland Products, Inc., Greeley, CO) + ametryn (Evik® DF, Syngenta
Crop Protection, LLC., Greensboro, NC) were used as PRE and early POST
commercial standards, respectively, for comparison. A nonionic surfactant at 0.25% v/v
(Preference®, Winfield Solutions, LLC., St. Paul, MN) was included with all POST
treatments. A nontreated weedy control was also included. Preemergence treatments
were applied after planting before sugarcane and weed emergence. Early POST
treatments were applied 29 and 20 d after planting when fall panicum was 5 cm and <5
cm in height, in 2014 and 2015, respectively on both organic and mineral soil study
locations. Herbicide application dates and timing for both organic and mineral soil
locations are listed in Table 2-1. Herbicide treatments were applied with a CO2
41
pressurized backpack sprayer calibrated to deliver 187 L ha-1 at 276 kPa using TeeJet
XR11002-VS nozzle tips (Spraying Systems Co., Wheaton, IL). Plots were 3 m wide
(two sugarcane rows, 1.5 m apart) by 9 m long at all locations. The experiment was
arranged in a randomized complete block design with four replications of each
treatment. Fall panicum was the predominant weed species at all locations. Broadleaf
weeds present at the organic soils locations included spiny amaranth (Amaranthus
spinosus L.) and ragweed parthenium (Parthenium hysterophorus L.) for the first and
second year, respectively. Common ragweed (Ambrosia artemisiifolia L.) was the main
broadleaf weed for both years in the mineral soil locations.
Visual evaluation of fall panicum control and sugarcane injury was assessed 65
(equivalent to 35 and 40 d after POST treatment in 2014-2015 and 2015-2016,
respectively) and 100 d after treatment (DAT) for PRE applications (equivalent to 71
and 80 d after POST treatment in 2014-2015 and 2015-2016, respectively) using a
scale of 0 (no control, no crop injury) to 100% (complete control, crop death).
Sugarcane stand counts (population) were taken from each plot 100 d after PRE
applications were made to determine the effect of herbicide treatments on early season
growth of the crop with the exception of the 2014-2015 season for organic soil. Stand
counts on organic soil for 2014-2015 was done after harvesting, whereby the harvesting
level was raised 10 cm above the ground to allow for counting of stalks that were
millable. Delay in taking stand counts was attributed to heavy rains which resulted in
stalks lodging on the ground from very early in the season.
Data were subjected to ANOVA and analyzed separately for each soil type using
R (R version 3.3.3, R Core Team 2016). Because of differences in days after planting
42
prior to early POST application and weed sizes between the two growing seasons, fall
panicum control was analyzed separately by year (growing season) for each soil type.
Sugarcane early season stand counts were also analyzed separately by year because
of different varieties used in the experiments. Also, for the organic soil location, stand
counts taken for the first year reflected season-long sugarcane growth and not the early
season development. Means were separated using Fisher’s Protected LSD test at P ≤
0.05 using the agricolae package of R (de Mendiburu 2016) when herbicide treatment
effects were significant (P ≤ 0.05).
Sugarcane Tolerance Experiment
Field studies were conducted to determine sugarcane tolerance to the premix of
atrazine, mesotrione, and S-metolachlor using four sugarcane varieties predominantly
cultivated on organic soils (‘CP88-1762’, ‘CP89-2143’, ‘CP00-1101’, and ‘CP96-1252’)
and two varieties cultivated on mineral soils (‘CPCL97-2730’ and ‘CPCL00-411’) in
Florida (Rice at al. 2014; VanWeelden et al. 2016). The studies were conducted in
2014-2015 and 2015-2016 sugarcane growing seasons on organic soil at the EREC in
Belle Glade, FL (26.66 N, 80.63 W for 2014-2015 season; 26.66 N, 80.64 W for 2015-
2016 season), and in 2015-2016 on mineral soil at two locations at the PPI Farm near
Loxahatchee, FL (26.81 N, 80.43 W for location 1; 26.80 N, 80.42 W for location 2). The
soil in Belle Glade was a Dania muck with 75% organic matter and pH of 7.3 while the
soil in Loxahatchee was a Holopaw fine sand with 1.6% organic matter and pH of 7.5.
Sugarcane was conventionally planted similar to the weed control experiment and
fertilizer applied in-furrow at planting based on University of Florida-IFAS soil test
recommendations. Planting dates are listed in Table 2-3.
43
Herbicide treatments, application timing, and application method were the same
as for the weed control experiment (Table 2-2). An untreated weed-free control was
included. Preemergence treatments were applied after planting before sugarcane and
weed emergence while early POST treatments were applied 83 and 89 d after planting
on organic and mineral soil locations, respectively when sugarcane was approximately
55 cm in height. Herbicide application date and timings are listed in Table 2-3. The
experiment was a randomized complete block design with a split-plot arrangement and
four replications for both soil types. Main plots consisted of 14 herbicide treatments and
subplots consisted of two or four sugarcane varieties depending on soil type. Each main
plot was 6 m wide (four sugarcane rows, 1.5 m apart) by 9 m long. Each row within
each plot was planted to a different variety. The fields received two POST application of
asulam (Asulox®, United Phosphorus, Inc., King of Prussia, PA) at 3.7 kg ha-1 tank
mixed with trifloxysulfuron (Envoke®, Syngenta Crop Protection, LLC., Greensboro, NC)
at 16 g ha-1 and 2,4-D (Amine 4 2,4-D Weed Killer, Loveland Products, Inc., Greeley,
CO) at 2.1 kg ha-1 to maintain weed-free conditions.
Sugarcane injury was assessed visually 30 DAT for the PRE treatments and 21
DAT for the POST treatments, respectively, using a scale of 0 (no crop injury) to 100%
(crop death). Sugarcane stalk counts were taken for each variety 4 mo after POST
herbicide application to determine the effect of herbicide treatments on early season
development of sugarcane.
Data were analyzed separately for each soil type. All data were subjected to
ANOVA with herbicide treatment, varieties, year (or location for the mineral soil), and
interactions as fixed effects, and blocks as random effects using the R program (R
44
Development Core Team 2016). Data were combined when there were significant
interactions of fixed effects. Means were separated using Fisher’s Protected LSD test at
P ≤ 0.05 using the agricolae package of R (de Mendiburu 2016).
Results and Discussion
Fall Panicum Control Experiment
Organic soil
A total of 7 and 49 mm of precipitation was received 3 d prior to PRE herbicide
application in 2014-2015 and 2015-2016 seasons, respectively (Figure 2-1). This was
followed by 10 and 44 mm of precipitation 14 d after PRE herbicide application in 2014-
2015 and 2015-2016 seasons, respectively. Precipitation total of 87 mm was received
100 d after planting in 2014-2015 compared to 483 mm in 2015-2016. The premix of
atrazine, mesotrione, and S-metolachlor applied PRE or early POST did not injure
sugarcane in either growing season regardless of application rate, indicating that the
sugarcane varieties (CPCL02-0926 and CPCL80-1743) used in the experiments
exhibited tolerance to the premix. Similarly, each of the components of the premix and
commercial standards did not result in sugarcane injury at any application timing. The
herbicide treatments had no effect on sugarcane stand in either growing season
(P>0.05) (Table 2-4).
There were herbicide treatment effects (P<0.05) on fall panicum control at all
evaluation timings in both seasons (Table 2-4). At 65 DAT the PRE 1X rate of the
premix provided 73 and 100% fall panicum control in the first and second seasons,
respectively. Increasing the PRE rates of this premix did not result in a significant
increase in fall panicum control in either season at 65 DAT. Components of the premix,
atrazine and mesotrione applied PRE provided 25 to 65% fall panicum control
45
compared to 63 to 100% control by S-metolachlor at 65 DAT. The commercial PRE
standard of atrazine plus pendimethalin provided 89 and 100% fall panicum control at
65 DAT, which was not significantly different from the 1X rate of the premix. Although,
there were no significant differences in fall panicum control at 65 DAT compared to the
commercial standard (89 and 93% for the first and second year, respectively), the
control provided by the premix in the first year (73%) would most likely be considered
unacceptable by sugarcane growers. Fall panicum control decreased to 60 and 80%
with the 1X rate of the premix in the first and second seasons, respectively compared to
85 and 83% by the commercial PRE standard at 100 DAT. Fall panicum control
provided by PRE S-metolachlor was higher in the second season (85%) compared to
the first season (55%) at 100 DAT. Overall, higher fall panicum control with PRE
application of the premix observed in 2015-2016 season compared to 2014-2015
season was attributed to significant precipitation received prior to and after herbicide
application (Figure 2-1). This suggests that the premix applied PRE will provide
acceptable residual fall panicum control on organic soil when there is adequate
precipitation prior to and after application, and at least twice the proposed use rate of
the premix will be required to achieve acceptable fall panicum control under low
precipitation. Whaley et al (2009) reported that the efficacy of S-metolachlor applied
alone or in combination with atrazine and mesotrione were affected by low rates of
precipitation. Giant foxtail control increased from 25 to 78% when 3.1 cm of rainfall was
received 7 d after PRE application of mesotrione (0.24 kg ha-1) plus atrazine (0.56 kg
ha-1) compared to when no rainfall was received (Armel et al. 2003). Smith et al. (2016)
reported that at least 6.4 mm of irrigation water was required to provide acceptable
46
control of Palmer amaranth (Amaranthus palmeri S. Watson) when using S-metolachlor.
Fall panicum control provided by PRE atrazine and mesotrione applied alone was
unacceptable. Enhanced degradation of atrazine under field conditions has been
reported on organic soils of the EAA (Odero and Shaner 2014b), probably explaining
the level of fall panicum control provided by atrazine ranged between 50 and 23%.
Mesotrione applied PRE has also been shown to provide low giant foxtail control (37%)
in corn (Armel et al. 2003).
Early POST treatments were applied 29 and 20 d after PRE application when fall
panicum was 5 and <5 cm in height in 2014-2015 and 2015-2016. Early POST
application of the premix at the 1X rate provided 68% control of fall panicum 36 DAT
compared to 96% control provided by the commercial standard (atrazine + ametryn +
2,4-D amine) in the first season (Table 2-4). Fall panicum control was higher in the
second season (79%) at 45 DAT even though this was an evaluation done 9 d later.
The observed difference in control was probably attributed to smaller fall panicum size
at early POST treatment application in the second compared to the first season.
However, fall panicum control by early POST 1X rate of the premix was significantly
lower than the commercial standard which provided 96 and 98% fall panicum control in
the first and second seasons at 36 and 45 DAT, respectively. Fall panicum control
decreased by 9 and 18% with 1X rate of the premix 35 d after the initial evaluation in the
first and second seasons, respectively compared to 6 and 20% by the commercial
standard. Higher fall panicum control was achieved by higher rates of the premix (2X
and 4X rates) applied early POST. Based on these results, the efficacy of the premix on
fall panicum at the proposed labeled rate can be achieved when early POST application
47
is made on much smaller fall panicum compared to the sizes treated in this study,
otherwise higher rates than currently proposed will be required to achieve acceptable
control. Overall, components of the premix applied alone provided 33 to 43% fall
panicum control 36 DAT in the first season and 0 to 63% control 45 DAT in the second
season.
Poor control of fall panicum by early POST atrazine and S-metolachlor applied
alone was probably attributed to the ability of species to moderately metabolize atrazine
(Thompson et al. 1971) and the insignificant foliar activity of S-metolachlor (Shaner
2014). Mesotrione at 100 g ha-1 has been reported to provide 69% control of fall
panicum at the 2- to 3-leaf and 5- to 6-leaf stage 14 DAT in a controlled environment
(Soltani et al. 2012) compared to 43 to 60% control by mesotrione at 227 g ha-1 in this
study at 36 and 45 DAT, respectively. De Cauwer et al. (2014) also reported sensitivity
of fall panicum to mesotrione. This study shows that the efficacy of the premix applied
POST on fall panicum may possibly be attributed to the synergy of atrazine and
mesotrione because of limited foliar activity of S-metolachlor which provided no control
in 2015-2016 season.
Mineral soil
On mineral soil locations, precipitation totals for 3 d prior to herbicide application
was 10 and 2 mm in 2014-2015 and 2015-2016, respectively (Figure 2-2). In 2015-
2016, a total of 11 mm of precipitation was received 14 d after PRE application, of which
6 mm was received on the day of herbicide application. Total precipitation of 19 mm
was received 14 d after PRE herbicide application in 2015-2016. Precipitation totals 100
d after planting were 142 and 311 mm in 2014-2015 and in 2015-2016, respectively.
48
Similar to organic soils, there was no injury on sugarcane (‘CPCL97-2730’ and
‘CPCL00-4111’) with the premix of atrazine, mesotrione, and S-metolachlor or each of
the individual components applied PRE or early POST regardless of application rate or
timing. Similarly, the commercial standards did not result in sugarcane injury at either
application timing. The herbicide treatments had an effect on sugarcane stand in 2014-
2015 (P<0.001) and no effect (P = 0.442) in 2015-2016 season (Table 2-5). The lowest
sugarcane stand was observed in early POST atrazine, mesotrione, and the untreated
control. The low stand counts in these early POST treatments was probably attributed to
poor emergence and not treatment effect because early POST S-metolachlor had a
higher stand count even though its level of fall panicum control was not significantly
different from these treatments.
PRE application of the premix at the 1X rate provided 95 and 100% control of fall
panicum at 65 DAT for the first and second seasons, respectively, compared to 100%
control provided by the commercial standard (Table 2-5). Fall panicum control by the
premix (1X rate) decreased to 88% at 100 DAT for the first season, but was not
significantly different from 95% control provided by the commercial standard. S-
metolachlor alone provided >98% control of fall panicum at 100 DAT both seasons.
Atrazine and mesotrione provided <45% fall panicum control in the first season
compared to >98% control in the second season at 100 DAT. High levels of fall panicum
control with atrazine and mesotrione in the second season might be related to more
precipitation after treatment application.
The high levels of PRE fall panicum control provided by the premix on mineral
soil, particularly by the S-metolachlor component, is probably attributed to the ability of
49
the herbicide to adsorb to organic soils than on soils with low organic matter and clay
content (Shaner 2014), resulting in low level of control in organic soil. The atrazine
component of the premix also provided better fall panicum control in mineral compared
to organic soil. Odero and Shaner (2014b) reported enhanced atrazine degradation with
an initial rapid rate of dissipation on organic soils of the EAA, resulting in shorter
residual activity. Kurtz et al. (2010) also reported that enhanced degradation of atrazine
occurs in soils with organic matter content of up to 46% which is lower than the organic
matter content in the present study locations. Lower activity of PRE atrazine on organic
compared to mineral soil was probably attributed to initial rapid loss previously reported
resulting from enhanced degradation on atrazine adapted organic soils of the EAA
(Odero and Shaner 2014b). Adsorption of mesotrione has been shown to be greatest in
high organic matter soils having heavy soil textures (Rouchaud et al. 2001), which may
explain the low level of fall panicum control observed on organic compared to mineral
soils. In addition, although mesotrione is adsorbed on soil organic matter, its low soil
mobility and depth of penetration (Rouchaud et al. 2001) likely accounted for the
residual activity observed on the mineral soils with low organic matter and clay content.
Similar to the organic soil locations, early POST treatments were applied 29 and
20 d after PRE application when fall panicum was 5 and <5 cm in height in 2014-2015
and 2015-2016 seasons, respectively. Early POST application of the 1X rate of the
premix provided 58% fall panicum control at 36 DAT compared to 78% control provided
by the commercial standard in the first season (Table 2-5). In contrast, fall panicum
control of 87 and 89% was provided by the 1X rate of the premix and the commercial
standard, respectively at 45 DAT in the second season even though this was an
50
evaluation done 9 d later compared to the evaluation at 36 DAT for the first season.
Early POST fall panicum control provided by the components of the premix was <38%
with the exception of 93% control provided by mesotrione at 45 DAT in the second
season. Similar to organic soils, higher rates of the premix (≥2X rate) applied early
POST were required to provide acceptable fall panicum control in seasons where the
1X rate of the premix provided unacceptable control. However, the 1X rate of the premix
applied PRE provided much better fall panicum control on mineral soil thereby providing
a potential new tool for efficacious fall panicum management on mineral soil.
Sugarcane Tolerance Experiment
Similar to the weed control experiments, there was no injury on all sugarcane
varieties on organic and mineral soils from PRE or early POST application of the premix
of atrazine, mesotrione, and S-metolachlor at all rates used in the study or from
individual components of the premix. PRE and early POST commercial standards also
caused no injury on sugarcane on both organic and mineral soils. This indicated that
sugarcane exhibited tolerance to herbicides in the premix even at higher rates (up to
4X) than the proposed use rate. Atrazine and mesotrione are widely used for selective
weed control in sugarcane (Anonymous 2009; Jones and Griffin 2009). Although S-
metolachlor is not labeled for use in the United States, it is registered for use in
sugarcane in other countries such as Brazil and Australia (Correia et al. 2012). Current
wide spread use of the herbicides (atrazine, mesotrione, S-metolachlor) in sugarcane
explained the lack of injury to the crop by these herbicides even at very high rates in the
three-way premix on organic and mineral soils used for sugarcane cultivation in Florida.
Sugarcane stand for both soil types was not affected by the interaction between
year (or location) with other main effects (i.e. herbicide treatment, sugarcane variety)
51
(P>0.05); therefore, data were combined over years (or locations). For organic soil,
herbicide treatment effect was not significant (P = 0.397) while sugarcane varietal effect
was significant (P<0.001), however, their interaction was not (P = 1.000). Therefore,
only the main effect of sugarcane variety is discussed for organic soil. There were
differences in sugarcane stand for organic soil between the varieties (P<0.001).
Sugarcane ‘CP96-1252’ had the highest population (72,176 stalks ha-1) followed by
‘CP88-1762’ (70,557 stalks ha-1); however, they were not significantly different.
Similarly, ‘CP00-1101’ with a population of 68,051 plants ha-1 was not significantly
different from ‘CP88-1762’. Sugarcane ‘CP89-2143’ had the lowest sugarcane
population (58,590 plants ha-1). These results show that the premix had no effect on
sugarcane on organic soils, showing that it will be safe on the crop on these soils.
For mineral soil, herbicide treatment effect was significant (P<0.001) while
sugarcane varietal effect (P = 0.112) and their interaction (P = 0.968) were not
significant. Consequently, only the main effect of herbicide treatment is presented
(Table 2-6). Although there was herbicide treatment main effect on sugarcane stand,
injury on the crop was not observed. The differences among the treatments was
probably attributed to variability in crop stand as a result of poor establishment across
the study locations. Overall, the premix at the proposed use rate or higher resulted in
higher sugarcane population.
These results show that when used as a PRE herbicide, fall panicum control with
the premix of atrazine, mesotrione, and S-metolachlor varied depending on soil type
and precipitation received prior to or after application. Overall, PRE application of the
premix provided acceptable residual fall panicum control when there was adequate
52
precipitation prior to and after application, and at least twice the proposed use rate of
the premix was required to achieve acceptable fall panicum control under low
precipitation. As an early POST herbicide, the premix provided variable fall panicum
control and mostly did not provide acceptable control at the proposed use rate,
particularly on organic soil. Acceptable fall panicum control at the proposed labeled rate
can be achieved when early POST applications are made on much smaller fall panicum
compared to the sizes treated in this study, otherwise higher rates than currently
proposed will be required to achieve acceptable control. There was no injury on all
sugarcane varieties on organic and mineral soils from PRE or early POST application of
the premix at all rates used in the study or from individual components of the premix,
indicating that sugarcane exhibited tolerance to herbicides in the premix. Because
herbicide options are limited in sugarcane cultivation, the premix of atrazine,
mesotrione, and S-metolachlor is a welcome addition for use for sugarcane growers.
The premix would also provide growers with the flexibility to use it either as a PRE or
early POST herbicide especially when it cannot be used PRE under dry conditions
associated with sugarcane planting in Florida. Further studies are required to determine
critical timing of application based on fall panicum size with early POST applications
and the effect of tank mixes with other triazines (ametryn and metribuzin) to improve fall
panicum control.
53
Table 2-1. Sugarcane varieties, planting and application dates for PRE and early POST herbicide treatments for fall panicum control on organic and mineral soils.
Herbicide application Location Variety Soil type Season Planting PRE Early POST
Belle Glade, FL CPCL02-0926 Organic 2014-2015 11/14/2014 11/24/2014 12/23/2014 CPCL80-1743 Organic 2015-2016 11/17/2015 11/23/2015 12/13/2015 Loxahatchee, FL CPCL97-2730 Mineral 2014-2015 11/05/2014 11/10/2014 12/09/2014 CPCL00-4111 Mineral 2015-2016 12/05/2015 12/15/2015 01/05/2016
54
Table 2-2. Herbicide treatments, rates, and application timing on organic and mineral soils for fall panicum control and sugarcane tolerance experiments.
Herbicide treatmenta Rate Application timing (g ha-1) Atrazine + mesotrione + S-metolachlor (1×) 853 + 227 + 2,271 PRE Atrazine + mesotrione + S-metolachlor (2×) 1,706 + 454 + 4,543 PRE Atrazine + mesotrione + S-metolachlor (4×) 3,412 + 909 + 9,086 PRE Atrazine 853 PRE Mesotrione 227 PRE S-metolachlor 2,271 PRE Atrazine + pendimethalinb 4,490 + 4,270 PRE Atrazine + mesotrione + S-metolachlor (1×) 853 + 227 + 2,271 Early POST Atrazine + mesotrione + S-metolachlor (2×) 1,706 + 454 + 4,543 Early POST Atrazine + mesotrione + S-metolachlor (4×) 3,412 + 909 + 9,086 Early POST Atrazine 853 Early POST Mesotrione 227 Early POST S-metolachlor 2271 Early POST Atrazine + 2,4-D amine + ametrync 4,490 + 4,260 + 560 Early POST
a1X, 2X, and 3X are atrazine + mesotrione + S-metolachlor at the 1X, 2X, and 4X proposed use
rate for sugarcane; all early POST treatments included a nonionic surfactant at 0.25% v/v. bPRE commercial standard on both organic and mineral soils for Florida sugarcane. cEarly POST commercial standard on both organic and mineral soils for Florida sugarcane.
Table 2-3. Planting and herbicide application dates for sugarcane varietal response to
Pre and early POST herbicides on organic and mineral soils.
Herbicide application
Location Soil type Season Planting PRE Early POST
Belle Glade, FL Organic 2014-2015 11/14/2014 11/17/2014 02/08/2015 Organic 2015-2016 11/20/2015 11/24/2015 02/15/2016 Loxahatchee, FL Mineral 2015-2016 12/03/2015 12/17/2015 02/04/2016 Mineral 2015-2016 12/08/2015 12/17/2015 02/04/2016
55
Table 2-4. Fall panicum control and sugarcane stalk counts in response to PRE and early POST herbicide treatments on organic soils in Belle Glade, FL.
2014-2015 2015-2016
Controlb Controlb
Treatmenta Rate Timing Standc 65 DAT
100 DAT Standd, e
65 DAT
100 DAT
g ha-1 stalks ha-1 %
stalks ha-1 %
Atr + mes + S-met (1X) 853 + 227 + 2,271 PRE 26,820 73 60 136,164 100 80 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 PRE 22,963 85 75 83,241 100 85 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 PRE 24,578 94 86 100,463 100 88 Atrazine 853 PRE 20,093 25 23 113,649 48 50 Mesotrione 227 PRE 23,681 33 23 100,822 65 70 S-metolachlor 2,271 PRE 26,013 63 55 100,194 100 85 Atrazine + pendimethalin 4,490 + 4,270 PRE 25,026 89 85 105,217 93 83 Atr + mes + S-met (1X) 853 + 227 + 2,271 EPOST 25,564 68 50 107,191 79 70 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 EPOST 22,335 89 85 137,240 100 88 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 EPOST 24,129 100 96 88,802 100 90 Atrazine 853 EPOST 21,976 33 20 104,859 63 53 Mesotrione 227 EPOST 20,451 43 28 113,828 60 78 S-metolachlor 2,271 EPOST 20,700 43 15 53,819 0 0 Atrazine + ametryn + 2,4-D 4,490 + 560 + 4,260 EPOST 25,923 96 90 83,151 98 78 Untreated control 19,286 0 0 52,385 0 0 LSD (0.05) NS 23 22 NS 21 16 P-value 0.653 <0.001 <0.001 0.210 <0.001 <0.001
Abbreviations: Atr + mes + S-met is Atrazine + mesotrione + S-metolachlor; DAT, d after treatment; PRE, preemergence; EPOST,
early postemergence. a1X, 2X, and 4X are atrazine + mesotrione + S-metolachlor at the 1X, 2X, and 4X proposed use rate for sugarcane. b65 DAT for PRE herbicides equivalent to 35 and 40 d after POST treatment in 2014-2015 and 2015-2016, respectively; 100 DAT for PRE herbicides equivalent to 71 and 80 d after POST treatment in 2014-2015 and 2015-2016, respectively. cStand of sugarcane ‘CPCL02-0926’ taken 100 d after PRE application. dStand of sugarcane ‘CPCL80-1743’ taken 100 d after PRE application. eStand counts taken after harvesting whereby the harvesting level was raised 10 cm above the ground to allow for counting of stalks that were millable.
56
Table 2-5. Fall panicum control and sugarcane stalk counts in response to PRE and early POST herbicide treatments on mineral soils near Loxahatchee, FL.
2014-2015 2015-2016
Controlb Controlb
Treatmenta Rate Timing Standc 65 DAT
100 DAT Standd,
65 DAT
100 DAT
g ha-1 stalks ha-1
% stalks ha-1
%
Atr + mes + S-met (1X) 853 + 227 + 2,271 PRE 12,289 95 88 15,249 100 100 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 PRE 18,120 98 80 21,169 100 100 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 PRE 25,026 100 100 22,963 100 100 Atrazine 853 PRE 18,210 50 45 17,402 98 98 Mesotrione 227 PRE 19,913 43 28 13,545 98 100 S-metolachlor 2,271 PRE 20,721 98 98 17,671 100 100 Atrazine + pendimethalin 4,490 + 4,270 PRE 24,398 100 95 27,000 100 95 Atr + mes + S-met (1X) 853 + 227 + 2,271 EPOST 27,000 58 45 14,262 87 83 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 EPOST 23,771 85 95 17,850 100 98 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 EPOST 23,950 100 99 19,375 100 98 Atrazine 853 EPOST 9,150 8 0 17,581 38 50 Mesotrione 227 EPOST 6,638 25 23 15,249 93 75 S-metolachlor 2,271 EPOST 20,003 23 33 23,322 30 53 Atrazine + ametryn + 2,4-D 4,490 + 560 + 4,260 EPOST 21,348 78 70 12,658 89 90 Untreated control 5,741 0 0 17,222 0 0 LSD (0.05) 6,494 23 26 NS 20 13 P-value <0.001 <0.001 <0.001 0.442 <0.001 <0.001
Abbreviations: Atr + mes + S-met is Atrazine + mesotrione + S-metolachlor; DAT, d after treatment; PRE, preemergence; EPOST,
early postemergence. a1X, 2X, and 4X are atrazine + mesotrione + S-metolachlor at the 1X, 2X, and 4X proposed use rate for sugarcane. b65 DAT for PRE herbicides equivalent to 35 and 40 d after POST treatment in 2014-2015 and 2015-2016, respectively; 100 DAT for PRE herbicides equivalent to 71 and 80 d after POST treatment in 2014-2015 and 2015-2016, respectively. cStand of sugarcane ‘CPCL97-2730’ taken 100 d after PRE application. dStand of sugarcane ‘CPCL00-4111’ taken 100 d after PRE application.
57
Table 2-6. Sugarcane stand (population) in response to PRE and early POST herbicide treatments on mineral soils 4 mo after PRE application (equivalent to 3 mo after early POST application) in Belle Glade, FL in 2015-2016.
Treatmenta Rate Timing Sugarcane standb
g ha-1 stalks ha-1 Atr + mes + S-met (1X) 853 + 227 + 2,271 PRE 46,808 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 PRE 47,435 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 PRE 50,215 Atrazine 853 PRE 34,568 Mesotrione 227 PRE 39,051 S-metolachlor 2,271 PRE 52,636 Atrazine + pendimethalin 4,490 + 4,270 PRE 42,772 Atr + mes + S-met (1X) 853 + 227 + 2,271 EPOST 50,126 Atr + mes + S-met (2X) 1,706 + 454 + 4,543 EPOST 52,905 Atr + mes + S-met (4X) 3,412 + 909 + 9,086 EPOST 55,057 Atrazine 853 EPOST 48,691 Mesotrione 227 EPOST 52,950 S-metolachlor 2,271 EPOST 47,615 Atrazine + ametryn + 2,4-D 4,490 + 560 + 4,260 EPOST 52,681 Untreated control 41,338 LSD (0.05) 7,168 P-value 0.001
Abbreviations: Atr + mes + S-met is Atrazine + mesotrione + S-metolachlor; DAT, d after treatment; PRE, preemergence; EPOST, early postemergence. a1X, 2X, and 4X are atrazine + mesotrione + S-metolachlor at the 1X, 2X, and 4X proposed use rate for sugarcane. bSugarcane stand counts averaged over two locations and two sugarcane varieties (‘CPCL97-2730’ and ‘CPCL00-411’).
58
Figure 2-1. Air temperature and rainfall during the experiment early in the season on
organic soil in 2014-2015 and 2015-2016 near Belle Glade, FL (Source: https://rainwise.net/weather/erec133430).
59
Figure 2-2. Air temperature and rainfall during the experiment early in the season on
mineral soil in 2014-2015 and 2015-2016 near Loxahatchee, FL (Source: https://rainwise.net/weather/erec233430).
60
CHAPTER 3 FIELD DISSIPATION OF S-METOLACHLOR IN ORGANIC AND MINERAL SOILS IN
SOUTH FLORIDA
Sugarcane is cultivated on approximately 172,000 ha in Florida, making the state
one of the largest producers in the United States (USDA-NASS 2017a). Approximately
78% of sugarcane is cultivated on high organic matter Histosols of the Everglades
Agricultural Area (EAA), and the remainder 22% is primarily on adjacent Spodosols and
Entisols with low organic matter (0.5 to 3%) and no significant silt or clay (VanWeelden
et al. 2016; McCray et al. 2014). Effective weed management is important for profitable
sugarcane production in Florida. Weed interference, primarily from grasses, has the
most negative effect on sugarcane production in Florida. Fall panicum (Panicum
dichotomiflorum Michx.) is the most prevalent and problematic annual grass species
that causes significant yield losses in Florida sugarcane (Odero et al. 2014; Odero et al.
2016). Sugarcane growers in Florida rely on pendimethalin for PRE annual grass
control at sugarcane planting (August to January) and following harvest (October to
April) of the ratoon crop. Sugarcane growers expect residual weed control following
PRE application of pendimethalin. However, dissipation of pendimethalin is rapid on
organic soils when applied under dry conditions with no incorporation associated with
sugarcane planting and harvesting in Florida, resulting in half-lives of as low as 8 d
(Odero and Shaner 2014a). Therefore, there is a need to evaluate more fall panicum
control options in Florida sugarcane because of the limited number of herbicide options
currently available.
A premix of atrazine (853 g ha-1), mesotrione (227 g ha-1), and S-metolachlor
(2,271 g ha-1) has been proposed for broad spectrum PRE and early POST weed
control in Florida sugarcane. Atrazine and mesotrione, are primarily used for broadleaf
61
weed control, are currently registered for PRE and POST use in sugarcane (Shaner
2014). S-metolachlor is not currently labeled for use in the United States even though it
is registered for use in other sugarcane producing countries (Correia et al. 2012). S-
metolachlor is a PRE chloroacetanilide herbicide thought to inhibit very long chain fatty
acid synthesis (Böger et al. 2000; Shaner 2014). It is primarily absorbed by emerging
shoots, especially grass coleoptiles (Shaner 2014). The racemic metolachlor originally
consisted of a pair of S- and R-isomers in a ratio of 50:50. Due to an enantioselective
catalytic process, the ratio of S- and R-isomers was changed to 80:20 with the S-isomer
providing 95% of herbicidal activity (Blaser and Spindler 1997; Blaser et al. 1999). The
S-isomer is also more active at the site of action in susceptible plants and allows for
lower use rates than the racemic metolachlor (Shaner 2014). Higher activity in grass
control using S-metolachlor compared to racemic metolachlor has been reported
(O’Connell et al.1998; Shaner et al. 2006). Although, there is a difference in isomer
ratios of racemic metolachlor and S-metolachlor, their half-lifes have been shown to be
similar (O’Connell et al.1998; Shaner et al. 2006).
S-metolachlor has relatively high water solubility (488 mg L-1) and low Koc (200
mL g-1) (Shaner 2014) which increases its potential for movement in the soil profile. It
also readily adsorbs to organic matter compared to clay. The half-life of S-metolachlor
using bioassay studies range from 17 to 70 d (Zimdahl and Clark 1982; Walker and
Brown 1985) compared to 9 to 42 d under field conditions (Martinez et al. 1997; Mueller
et al. 1999; Shaner and Henry 2007; Wu et al. 2015). In Canada the half-life of S-
metolachlor ranged from 80 to 142 d (Frank et al. 1991).
62
Degradation of S-metolachlor in soil can be affected by biotic and abiotic factors.
Under field conditions S-metolachlor is primarily degraded microbially (Kearney and
Kaufman 1988; Bouchard et al. 1982; Kotoula-Syka et al. 1997; Miller et al. 1997, Rice
et al. 2002; Caracciolo et al. 2004). However, abiotic factors such as temperature and
soil moisture have also been reported to have an effect on S-metolachlor degradation.
S-metolachlor losses as soil moisture increases under constant temperature have been
reported, indicating that it can persist for a longer period under unsaturated conditions
compared to saturated conditions (Zimdahl and Clark 1982; Walker and Brown 1985;
Sahid and Wei 1993; Dinelli et al. 2000; Rice et al. 2002; Gish et al. 2009). Constant
moisture levels and decreasing temperatures also reduce S-metolachlor degradation
(Zimdahl and Clark 1982; Walker and Brown 1985; Braverman et al. 1986).
Currently, no data are available on degradation of S-metolachlor on organic and
mineral soils used for sugarcane cultivation in south Florida. Understanding the
dissipation rate and persistence of S-metolachlor in these soils is important to provide
information for formulating weed management programs particularly fall panicum in
sugarcane. Therefore, the objective of this study was to determine field dissipation of S-
metolachlor on organic and mineral soils used for sugarcane production in south
Florida.
Materials and Methods
Study Location
Field studies were conducted to evaluate dissipation of S-metolachlor on organic
and mineral soils used for sugarcane cultivation in Florida between 2013 and 2016.
Studies on organic soil were conducted in the 2013-2014 and 2014-2015 sugarcane
growing seasons (26.66 N, 80.63 W for 2013-2014 season; 26.65 N, 80.63 W for 2014-
63
2015 season) at the Everglades Research and Education Center in Belle Glade, FL on
Dania muck soil containing 75% organic matter and having a pH of 7.3. Studies on
mineral soil were conducted in 2014-2015 and 2015-2016 sugarcane growing seasons
(26.76 N, 80.39 W for 2014-2015 season; 26.81 N, 80.44 W for 2015-2016 season) at
the PPI Farm near Loxahatchee, FL. The soil was a Holopaw fine sand containing 1.6%
organic matter and having a pH of 7.5 at both mineral soil locations. Both organic and
mineral soil locations were on sugarcane fields not previously treated with S-
metolachlor.
Herbicide Treatment Application and Soil Sampling
A three-way premix of atrazine, mesotrione, and S-metolachlor (Lumax EZ,
Syngenta Crop Protection, LLC, Greensboro, NC 27409) at the proposed use rate for
sugarcane of 853, 227, and 2,271 g ha-1, respectively, was applied PRE after
sugarcane planting at all study locations. Treatments on organic soil were applied on
December 10, 2013 to experimental fields planted to two rows each of sugarcane
‘CP96-1252’ and ‘CP88-1762’, and on November 27, 2014 to fields planted to one row
each of sugarcane ‘CP00-1101’, ‘CP96-1252’, ‘CP88-1762’, and ‘CP89-2143’. For
mineral soil locations, fields planted to sugarcane ‘CPCL97-2730’ and ‘CPCL00-4111’
were treated on November 27, 2014 and December 17, 2015, respectively. Herbicides
were applied using a CO2 pressurized backpack sprayer calibrated to deliver 187 L ha-1
at 276 kPa with Teejet® XR11002-VS nozzle tips (Spraying Systems Co., Wheaton IL
60187). Plots consisted of four and two sugarcane rows 1.5 m apart by 9 m long for the
organic soil locations in the first and second seasons, respectively, and two sugarcane
rows 1.5 m apart by 9 m long for the mineral soil locations. The experiment was set up
in a randomized complete block design with four replications for both soil types at all
64
study locations. Weather information (temperature and rainfall) during the experiments
is presented in Figure 3-1 and Figure 3-2 for organic and mineral soils, respectively.
Soil samples were collected from all locations at 0, 7, 14, 21, 28, 35, 42, 49, 56,
63, 70, 77, and 84 d after treatment (DAT). Three soil cores 3 cm in diam from the top
7.5 cm of soil from the surface were taken randomly for each plot from bare soil
surfaces between sugarcane rows and composited. Samples were then placed in
coolers filled with ice immediately after collection from the field before transportation
and storage within one to two hours at -18 C until analysis.
Herbicide Extraction and Analysis
S-metolachlor was extracted using toluene according to Shaner and Henry
(2007). Soil samples were thawed for four to six hr, composited, and wet sieved prior to
extraction of S-metolachlor. Ten grams of the sieved soil from each sample was placed
into a 50-ml polypropylene tube and 10 ml of distilled water and 10 ml of water-
saturated toluene were added to the soil. The tubes were shaken horizontally for two hr
in a Eberbach shaker (E6010, Eberbach Corporation, Ann Arbor, MI) and then
centrifuged at 1,800 g for 25 min. Two ml of the toluene phase was transferred to a 2-ml
volumetric tube.
The concentration of S-metolachlor in the toluene phase was determined using a
gas chromatograph-mass spectrometer (Shimadzu GCMS QP2010 SE, Shimadzu
Scientific Instruments, Columbia, MD 21046) operated in scan monitoring mode. The
quantifier m/z monitored for S-metolachlor was 162, while m/z 238 and m/z 240 were
used as qualifiers. A Rtx-5MS column, 30 m long, 0.25 µm df, and 0.25 mm internal
diam (Restek Corporation, Bellefonte, PA 16823) was used with helium as the carrier
gas. The injection mode was splitless for one minute with an injector temperature of 240
65
C and an injection volume of 1 µL. The gas chromatograph oven program was as
follows: initial temperature 90 C (hold 1min), ramped at 30 C per min to 240 C (hold 1.5
min), with a total run time of 10 min. The ion source and transfer line temperatures were
held at 250 C. Under these conditions, the retention time for S-metolachlor was 7.07
min. Quantification was done using an external standard of S-metolachlor (S-
metolachlor technical grade, Chem Service, Inc., West Chester, PA, 19381) with six
calibration points. The minimum detection limit was 0.05 ppm (5 µg kg-1). The extraction
efficiency of S-metolachlor was 81 and 94% for organic and mineral soils, respectively.
Statistical Analysis
ANOVA was performed on all data for each soil type using the R program (R
3.3.3, R Core Team 2016) at the 5% level of significance. Data were analyzed
separately by year when there was a significant year effect for each soil type. S-
metolachlor dissipation was fitted to a linear decay model (Eq 3-1) for organic soils and
an exponential decay model (Eq 3-2) for the mineral soils using the drc package of R
(Ritz and Streibig 2005):
Y = a + bt (3-1)
where Y is S-metolachlor amount (µg kg-1) in soil at time t, a is initial S-metolachlor
amount (µg kg-1) in soil at the first sampling time (t = 0), b is first-order rate constant
(d-1) or rate of decay, and t is time in d (DAT).
Y = ae-tb (3-2)
where Y, a, b, and t are the same as in Eq 3-1. Half-life (DT50) values for each soil type
were calculated using Eq 3-3:
DT50 = ln(0.5)/b (3-3).
66
Results and Discussion
Dissipation of S-metolachlor was analyzed separately by soil type due to
differences in chemical and physical properties of the soils. There was a significant year
effect (P<0.05) on dissipation of S-metolachlor for both soil types; therefore, data are
presented by year (or growing season) for each soil type. Difference in precipitation
distribution and amounts could be related for organic (Figure 3-1) and for mineral soils
(Figure 3-2). Bulk density differences between organic and the mineral soils reflect the
difference in initial concentration of S-metolachlor between soils.
Organic Soils
Initial concentrations of S-metolachlor were 3769 and 3793 µg kg-1 in the first and
second seasons, respectively (Table 3-1). S-metolachlor dissipation was linear (Figure
3-3) compared to biphasic rate of dissipation observed for atrazine, metribuzin and
pendimethalin on organic soils (Odero and Shaner 2014a; Odero and Shaner 2014b).
The rate of dissipation was higher in the first season (b = 43) compared to the second
season (b = 28), resulting in a DT50 of 19 and 62 d for the first and second seasons,
respectively. Although S-metolachlor degradation is most often attributed to microbial
degradation (Kearney and Kaufman 1988), enhanced degradation, as reported by
Sanyal and Kulshrestha (1999), for the first season was not likely because S-
metolachlor or metolachlor had not been previously applied in the fields where the
studies were conducted. For both seasons limited precipitation events were observed in
the first four wk after treatment (WAT) application; however, heavy rain events in the
first season were recorded between 5 and 9 WAT (Table 3-2; Figure 3-1), possibly
explaining the higher dissipation rate observed during the first season. Rice et al. (2002)
reported that saturated soils favored dissipation of S-metolachlor. Since the main
67
interest of the study was to determine the dissipation rate of S-metolachlor, no further
studies were conducted to determine the cause of accelerated dissipation observed in
the first season. Although, the physiochemical properties of the organic soil is different
than the soils for the previous metolachlor dissipations studies, the DT50 of 19 d is within
the range reported by Mueller et al. (1999) and Shaner and Henry (2007). The DT50 of
62 d for the second year exceeded what has been previously reported. The slower
dissipation rate in the second season could be related to low soil moisture due to limited
rain events during the whole season (Zimdahl and Clark 1982; Walker and Brown 1985;
Sahid and Wei 1993; Dinelli et al. 2000; Rice et al. 2002; Gish et al. 2009). Furthermore,
lower average temperatures toward the end of the study could have had an effect on
dissipation rate of S-metolachlor (Zimdahl and Clark 1982; Walker and Brown 1985;
Braverman et al. 1986).
Mineral Soils
Initial concentrations of S-metolachlor were 1548 and 1721 µg kg-1 of soil for the
first and second seasons, respectively (Table 3-1). S-metolachlor had a biphasic rate of
dissipation both years (Figure 3-4). There was an initial rapid rate of dissipation within
the first 28 d followed by a slow rate of dissipation both years. The DT50 of S-
metolachlor was 12 and 24 d for the first and second seasons, respectively. Marginal
rainfall events in the first 3 WAT probably resulted in the shorter half-life observed in the
first season (Table 3-2). Smith et al. (2016) reported that Palmer amaranth (Amaranthus
palmeri S. Watson) dry biomass was reduced from 27 to 4 g at 35 DAT on mineral soils
when S-metolachlor was incorporated with 1.6 and 6.4 mm of irrigation, respectively.
Similar to the report by Smith et al. (2016), 1.5 and 7.6 mm of rainfall was received in
the first and second seasons of this study, respectively. Although, dissipation rates both
68
years were different, the DT50 of S-metolachlor both years were similar to previous
reports (Mueller et al. 1999; Shaner and Henry 2007).
It is important to determine how the dissipation rate of S-metolachlor and DT50
values relate to control of fall panicum and other weed species on organic and mineral
soils used for sugarcane cultivation in Florida. Furthermore, it is also important to
determine the bioavailable fraction of S-metolachlor in each type of soil and relate it to
weed control. It is highly probable that the high initial amount of S-metolachlor detected
on the organic soils was adsorbed to organic matter, and would result in lower weed
control. Further studies are required to determine how incorporation mechanically and
by rainfall or irrigation would affect dissipation of S-metolachlor on both soil types.
Understanding how dissipation rates are affected by incorporation will provide growers
with the level of weed control to expect from S-metolachlor.
69
Table 3-1. Model parameters and standard errors in parenthesis for the linear and exponential decay models (provided in Eq 3-1 and 3-2, respectively) for organic and mineral soils, respectively, half-life and coefficient of determination (R2) for dissipation of S-metolachlor in Florida sugarcane fields.
Model parameters (±SE) Soil type Year A b R2 Half-life (DT50)
Organic 2013-2014 3768.91 (357.53) -42.86 (7.19) 0.43 19 2014-2015 3792.58 (451.01) -27.57 (7.11) 0.26 62 Mineral 2014-2015 1548.01 (79.37) 0.06 (0.01) 0.90 12 2015-2016 1721.11 (124.99) 0.03 (0.00) 0.78 24
Table 3-2. Weekly average temperature and rainfall for the four locations for the
duration of the experiment.a
WAT
Organic soils Mineral soils 2013 – 2014 2014 - 2015 2014 - 2015 2015 - 2016
Avg T Rain Avg T Rain Avg T Rain Avg T Rain
- 1 20.2 0.3 23.1 7.4 23.7 3.3 23.7 0.0 1 19.1 0.8 17.5 0.0 18.3 1.5 23.5 7.6 2 18.7 0.5 17.7 2.0 17.0 1.6 21.6 2.3 3 19.3 1.3 13.3 0.3 15.2 0.0 22.5 4.8 4 17.8 5.6 19.4 3.8 21.0 17.8 21.8 10.4 5 16.6 79.2 21.1 11.9 22.0 0.0 22.6 7.4 6 12.0 0.8 21.4 2.0 21.2 0.3 24.0 11.9 7 14.0 0.3 18.5 10.9 20.2 3.8 21.7 19.4 8 19.1 88.4 16.4 0.6 17.6 0.6 18.6 11.4 9 20.5 37.6 15.5 2.8 15.2 1.5 16.5 35.3 10 16.5 13.2 16.0 0.0 17.5 20.6 13.5 38.4 11 20.9 2.0 16.7 29.7 16.3 8.9 18.3 99.3 12 19.3 5.1 14.8 4.3 14.2 4.3 18.2 35.3
a Abbreviation: WAT, weeks after treatment, Avg T, average temperature, Rain, mm of rain. (Source: https://rainwise.net/weather/erec133430; https://rainwise.net/weather/erec233430).
70
Figure 3-1. Air temperature and rainfall during the experiment in 2013-2014 and 2014-
2015 sugarcane growing seasons in Belle Glade, Fl on organic soil (Source: https://rainwise.net/weather/erec133430).
71
Figure 3-2. Air temperature and rainfall during the experiment in 2014-2015 and 2015-
2016 sugarcane growing seasons near Loxahatchee, Fl on organic soil (Source: https://rainwise.net/weather/erec233430).
.
72
Figure 3-3. Field dissipation of S-metolachlor in organic soil in Florida from 2013 to
2015. Data fitted to Eq 3-1.
73
Figure 3-4. Field dissipation of S-metolachlor in mineral soil in Florida from 2014 to
2016. Data fitted to Eq 3-2.
74
CHAPTER 4 CONCLUSIONS
A major challenge in Florida sugarcane production has been effective programs
for control of grass weed species. This problem is compounded by the fact that grass
crops such as sweet corn or rice are typically used in rotation with sugarcane. Due to
limited availability of grass herbicide options, fall panicum has emerged as the most
troublesome weed in Florida sugarcane production. Asulam is currently the best
herbicide available for efficacious fall panicum control in sugarcane, but a decrease in
efficacy on fall panicum has been observed.
A dose-response bioassay conducted under greenhouse conditions found
differences in response to asulam among four Florida fall panicum populations. When
compared to a population of fall panicum that was never exposed to asulam, a decrease
in sensitivity to asulam was observed in all the populations from Florida. Furthermore,
dose-response bioassays using the same Florida populations but conducted outside the
greenhouse reflected even lower levels of susceptibility or sensitivity to asulam. The
probability of fall panicum survival after receiving the labeled rate of asulam (3,700 g ai
ha-1) ranged from 2 to 47%. Addition of trifloxysulfuron at 16 g ai ha-1 reduced fall
panicum survival to between 0 to 4% for three of the fall panicum populations. In
contrast the probability of survival of one of the populations increased from 2 to 6%
when trifloxysulfuron was added to asulam.
A commercial three-way herbicide premix containing atrazine, mesotrione, and
S-metolachlor was evaluated for management of fall panicum. No information is
currently available on the efficacy of the premix on grass control in sugarcane cropping
systems. However, several studies using different combinations of the component
75
herbicides of the premix have shown variable control of grass weeds. When used PRE
on organic soils, the premix was able to provide fall panicum control similar to
commercial standards used by sugarcane growers. However, early POST application of
the premix on organic soils provided significantly lower fall panicum control compared to
the commercial standard used by growers. Application of the premix PRE or early
POST on mineral soils provided acceptable fall panicum control comparable to the
commercial standard. Results from the study showed that adequate soil moisture after
application will be required to ensure efficacious fall panicum control with the premix
when applied PRE. Also, the study showed that application timing of the premix based
on fall panicum size will be critical for efficacious fall panicum control.
Understanding the persistence of S-metolachlor on organic and mineral soils
used for sugarcane production is important for development of weed management
programs. On organic soils, the half-life of S-metolachlor was 19 to 62 days for the first
and second growing seasons, respectively. The half-life of 62 days was probably
attributed to low precipitation and temperatures during the duration of the experiment.
The half- life of S-metolachlor on mineral soils was 12 and 24 days for the first and
second seasons, respectively. Dissipation rates of S-metolachlor for mineral soils was
consistent with what has previously been reported in southern United States.
76
LIST OF REFERENCES
Anderson WP (1996) Weed Science Principles and Applications. 3rd edn. St. Paul, MN: West Publishing Company. 387 p Anonymous (2009) Best Use Guidelines for Sugarcane Grown in Florida: Callisto. Greensboro, NC: Syngenta Crop Protection Anonymous (2017a) Archived SFWMD Station Data. University of Florida/IFAS and the South Florida Water Management District. http://erec.ifas.ufl.edu/WD/Ewdmain.htm . Accessed March, 2017 Anonymous (2017b) Tricor® herbicide. United Phosphorus. http://www.upi-
usa.com/agricultural-products/tricor-herbicide. Accessed March 09, 2017 Armel GR, Wilson HP, Richardson RJ, Hines TE (2003) Mesotrione, acetochlor, and atrazine for weed management in corn (Zea mays). Weed Technol 17:284-290 Blaser H, Buser H, Coers K, Hanreich R, Jalett H, Jelsch E, Pugin B, Schneider H,
Spindler F, Wegmman A (1999) The chiral switch of metolachlor: The development of a large scale enantioselective catalytic process. Chimia 53:275-280
Blaser H, Spindler F (1997) Enantioselective catalysis for agrochemicals: The case
history of the Dual Magnum® herbicide. Chimia 51:297-299 Böger P, Matthes B, Schmalfu J (2000) Towards the primary target of chloroacetamides-new findings pave the way. Pest Manag Sci 56:497-508 Bouchard DC, Lavy TL, Marx DB (1982) Fate of metribuzin, metolachlor, and
fluometuron in soil. Weed Sci 30:629-632 Braverman MP, Lavy TL, Barnes CJ (1986) The degradation and bioactivity of
metolachlor in the soil. Weed Sci 34:479-484 Brecke BJ, Duke WB (1980) Dormancy, germination, and emergence characteristics of fall panicum (Panicum dichotomiflorum) seed. Weed Sci 28:683-685
Bryson CT, DeFelice MS (2009) Weeds of the South. Athens, GA: University of Georgia Press. 395 p Buhler DD (1991) Early preplant atrazine and metolachlor in conservation tillage corn (Zea mays). Weed Technol 5:66-71 Busi R, Gaines TA, Walsh MJ, Powles SB (2011) Understanding the potential for
resistance evolution to the new herbicide pyroxasulfone: field selection at high dose versus recurrent selection at low doses. Weed Res 52:489-499
77
Caracciolo AB, Giuliano G, Grenni P, Guzzella L, Pozzoni F, Bottoni P, Fava L, Crobe
A, Orru M, Funari E (2005) Degradation and leaching of the herbicides metolachlor and diuron: A case study in an área of northern Italy. Environ Pollution 134:525-534
Correia NM, Perussi FJ, Gomes LJP (2012) S-metolachlor efficacy on the control of
Brachiaria decumbens, Digitaria horizontalis, and Panicum maximum in mechanically green harvested sugarcane. Planta Daninha 30:861–870
Dalley CD, Richard EP (2008) Control of rhizome johnsongrass (Sorghum halepense) in sugarcane with trifloxysulfuron and asulam. Weed Technol 22:397-401 De Cauwer DB, Geeroms T, Claerhout S, Bulcke R, Reheul D (2014) Differential
sensitivity of locally naturalized panicum species to HPPD- and ALS-inhibiting herbicides. J Plant Dis Protect 121:32-40
de Mendiburu F (2016) Package Agricolae: Statistical procedures for agricultural
research. Version 1.2-4. Available at https://cran.r-project.org/web/packages/agricolae/agricolae.pdf Accessed March 21, 2017
Dinelli G, AccinelliC, Vicari A, Catizone P (2000) Comparison of persistence of atrazine
and metolachlor under field and laboratory conditions. J Agric Food Chem 48:3037-3043
Fausey JC, Renner KA (1997) Germination, emergence, and growth of giant foxtail
(Setaria faberi) and fall panicum (Panicum dichotomiflorum). Weed Sci 45:423-425
Frank R, Clegg BS, Patni NK (1991) Dissipation of cynazine and metolachlor on a clay
loam soil, Ontario, Canada, 1987-1990. Arch Environ Contam Toxicol 31:253-262
Giffard SC, Collin HA, Putwain PD (1986) Enhancement of asulam resistance in barley. Weed Res 26:389-396 Gish TJ, Prueger JH, Kustas WP, Daughtry CST, McKee LG, Russ A, Hatfield JL (2009)
Soil moisture and metolachlor volatilization observations over three years. J Environ Qual 38:1785-1795
Govinthasamy K, Cavers PB (1995) The effects of smut (Ustilago destruens) on seed
production, dormancy, and viability in fall panicum (Panicum dichotomiflorum). Can J Botany 73:1628-1634
Hartzler RG, Roth GW (1993) Effect of prior year’s weed control on herbicide effectiveness in corn (Zea mays). Weed Technol 7:611-614
78
Heap I. (2017) The International Survey of Herbicide Resistant Weeds. http://www.weedscience.org . Accessed March 20, 2017 Hewertson NA, Collin HA (1984) Mechanism of action of asulam in celery tissue cultures. Weed Res 24:79-83 Hossain MA, Kuramochi H, Ishimine Y, Akamine H (2001) Application timing of asulam
for torpedograss (Panicum repens L.) control in sugarcane in Okinawa island. Weed Bio and Manag 1:108-114
Johnson WG, DeFelice MS, Holman CS (1997) Application Timing affects weed control
with metolachlor plus atrazine in no-till corn (Zea mays) Weed Technol 11:207-211
Jones CA, Griffin JL (2009) Red morningglory (Ipomoea coccinea) control and competition in sugarcane. J Am Soc Sugar Cane Technol 29:25-35
Kearney PC, Kaufman DD (1988) Herbicides: Chemistry, degradation, and mode of
action. 3rd edn. New York, NY: Marcel Dekker, 202 p Kotoula-Syka E, Htzios KK, Berry DF, Wilson HP (1997) Degradation of acetanilide
herbicides in history and nonhistory soils from eastern Virginia. Weed Technol 11:403-409
Krutz LJ, Shaner DL, Weaver MA, Webb RMT, Zablotowicz RM, Reddy KN, Huang Y,
Thomson SJ (2010) Agronomic and environmental implications of enhanced s-triazine degradation. Pest Manag Sci 66:461-481
Kupatt CC, Ilnicki RD, Vitolo DB (1985) Postemergence fall panicum control in corn with DOWCO 356-triazine combinations. Proc North East Weed Sci Soc 44-47 Lencse RJ, Griffin JL (1991) Itchgrass (Rottboellia cochinchinensis) interference in sugarcane (Saccharum sp.). Weed Technol 5:396-399 Martinez L, Lechon Y, Sanchez-Brunete C, Tadeo JL (1997) Persistence of metolachlor,
atrazine and deethylatrazine in soils and its simulation by deterministic models. Toxicol and Environ Chem 54:219-232
McCray JM, Morgan KT, Baucum L, Ji S (2014) Sugarcane yield response to nitrogen
on sand soils. Agron J 106:1461-1469 Miller JL, Wollum AG, Weber JB (1997) Degradation of carbon-14-atrazine and carbon-
14 metolachlor in soil from four depths. J Environ Qual 26:633-638
79
Millhollon RW (1993) Preemergence control of itchgrass (Rottboellia cochinchinensis) and johnsongrass (Sorghum halepense) in sugarcane (Saccharum spp hybrids) with pendimethalin and prodiamine. Weed Sci 41:621-626
Millhollon RW (1995) Growth and yield of sugarcane as affected by johnsongrass (Sorghum halepense) interference. J Am Soc Sugar Cane Technol 15:32-40 Mitchell G, Bartlett DW, Fraser TEM, Hawkes TR, Holt DC, Townson JK, Wichert, RA
(2001) Mesotrione: a new selective herbicide for use in maize. Pest Manag Sci 57:120-128
Mueller TC, Shaw DR, Witt WW (1999) Relative dissipation of acetochlor, metolachlor,
and SAN 582 from three surface soils. Weed Technol 13:341-346 Neve P, Powles S (2005) Recurrent selection with reduced herbicide rates results in the
rapid evolution of herbicide resistance in Lolium rigidum. Theor Appl Genet 110:1154-1166
O’Connell JO, Harms CT, Allen JRF (1998) Metolachlor, S-metolachlor and their role
within sustainable weed management. Crop Protection 17:207-212 Odero DC, Duchrow M, Havranek N (2016) Critical timing of fall panicum (Panicum dichotomiflorum) removal in sugarcane. Weed Technol 30:13-20 Odero DC, Dusky JA (2014) Weed Management in Sugarcane. EDIS Publication SS- AGR-09. http://edis.ifas.ufl.edu/wg04 . Accessed March 20, 2017 Odero DC, Sellers B, Baucum L, Curtis R (2014) Fall Panicum: Biology and Control In
Sugarcane. EDIS Publication SS-AGR-132. http://edis.ifas.ufl.edu/sc079. Accessed March 20, 2017
Odero DC, Shaner DL (2014a) Dissipation of pendimethalin in organic soils in Florida. Weed Technol 28:82-88 Odero DC, Shaner DL (2014b) Field dissipation of atrazine and metribuzin in organic
soils in Florida. Weed Technol 28:578-586 R Core Team (2016) R: A language and environment for statistical
computing. R foundation for statistical computing, Vienna: Austria. ISBN 3-900051-07-9. URL http://www.R-project.org . Accessed March 20, 2017
Rice PJ, Anderson TA, Coats JR (2002) Degradation and persistence of metolachlor in
soil: Effects of concentration, soil moisture, soil depth, and sterilization. Environ Toxicol and Chem 21:2640-2648
80
Rice R, Baucum L, Davidson W (2014) Sugarcane variety census: Florida 2013. Sugar J July, 11-19 Richard EP (1991) Optimizing diluent volume improves Johnsongrass control in sugarcane (Saccharum sp.) with asulam. Weed Technol 5:363-368 Ritz C, Kniss AR, Streibig JC (2015) Research methods in weed science: statistics. Weed Sci 63(Sp 1):166-187 Ritz C, Streibig JC (2005) Bioassay analysis using R. J Stat Sofw 12:1-22 Rouchaud J, Neus O, Eelen H, Bulcke R (2001) Mobility and adsorption o the triketone
herbicide mesotrione in the soil of corn crops. Toxicol Environ Chem 79:211-222 Sahid IB, Wei CC (1993) Degradation of two acetanilide herbicides in a tropical soil. Bull
Environ Contam Toxicol 50:24-28 Sanyal D, Kulshrestha G (1999) Effects of repeated metolachlor applications on its
persistence in field soil and degradation kinetics in mixed microbial cultures. Biol Fertil Soils 30:124-131
Schueneman TJ, Sanchez CA (1994) Vegetable production in the EAA. Pages 238-277
in Bottcher AB and Izuno FT, eds. Everglades Agricultural Area (EAA): Water, Soil, Crop, and Environmental Management. Gainesville, FL: University Press of Florida
Seefeldt SS, Jensen JE, Fuerst EP (1995) Log-logistic analysis of herbicide dose- response relationships. Weed Technol 9:21 Shaner DL, Brunk G, Belles D, Westra P, Niessen S (2006) Soil dissipation and
biological activity of metolachlor and S-metolachlor in five soils. Pest Manag Sci 62:617-623
Shaner DL, Henry B (2007) Field history and dissipation of atrazine and metolachlor in
Colorado J Environ Qual 36:128-134 Shaner DL (2014) Herbicide Handbook. 10th edn. Lawrence, KS: Weed Science Society of America. 513 p Sharma MP, Vandenborn WH, McBeath DK (1978) Spray retention, foliar penetration,
translocation and selectivity of asulam in wild oats and flax. Weed Res 18:169-173
Shea PJ (1989) Role of humified organic matter in herbicide adsorption. Weed Technol 3:190-197
81
Smith HC, Ferrell JA, Webster TM, Fernandez JV, Dittmar PJ, Munoz PR, MacDonald GE (2016) Impact of irrigation volume on PRE herbicide activity. Weed Technol 30:793-800
Snyder GH, Burdine HW, Crockett JR, Gascho GJ, Harrison DS, Kidder G, Mishoe JW
(1978) Water table management for organic soil conservation and crop production in the Florida Everglades (Florida Agricultural Experiment Stations Bulletin 801). Gainesville, FL: University of Florida
Soltani N, Kaastra AC, Swanton CJ, Sikkema PH (2012) Efficacy of topramezone and
mesotrione for the control of annual grasses. Int Res J Agric Sci Soil Sci 2:046-050
Stephen NH, Cook GT, Duncan (1980) A possible mechanism of action of asulam
involving folic acid biosynthesis. Ann Appl Biol 96:227-234 Stephenson DO IV, Bond JA, Walker ER, Bararpour MT, Oliver LR (2004) Evaluation of mesotrione in Mississippi Delta corn production. Weed Technol 18:1111-1116 Sterrett RB, Fretz TA (1975) Asulam-induced mitotic irregularities in onion root-tips. HortScience 10:161-162 Teuton TC, Unruh JB, Brecke BJ, MacDonald GE, Miller GL, Ducar JT (2004) Tropical
signalgrass (Urochloa subquadripara) control with preemergence- and postemergence-applied herbicides. Weed Technol 18:419-425
Thomas WE, Burke IC, Wilcut JW (2004) Weed management in glyphosate-resistant corn with glyphosate, halosulfuron, and mesotrione. 18:826-834 Thompson L, Houghton JM, Slife FW, Butler HS (1971) Metabolism of atrazine by fall panicum and large crabgrass. Weed Sci 4:409-412 Triplett GB, Lytle GD (1972) Control and ecology of weeds in continuous corn grown without tillage. Weed Sci 5:453-457 United States Department of Agriculture-National Agricultural Statistics Service (2017a) Crop Production. https://www.nass.usda.gov/Quick_Stats/Ag_Overview/state
Overview.php?state=FLORIDA. Accessed March 20, 2017 United States Department of Agriculture-Natural Resources Conservation Service (2017b) Plants Profile: Panicum dichotomiflorum Michx. http://plants.usda.gov/co
re/profile?symbol=PADI. Accessed March 20, 2017 VanWeelden M, Rice R, Davidson W, Swanson S (2016) Sugarcane variety census
Florida 2015. Sugar J. July Pp 12-25.
82
Veerasekaran P, Kirkwood RC (1977) Studies on the mode of action of asulam in bracken (Pteridium aquilinum L. Kuhn) I. Absorption and translocation of [14C] asulam. Weed Res 17:33-39
Veerasekaran P, Kirkwood RC, Parnell EW (1981a) Studies of the mechanisms of
asulam in plants. Part I: Antagonistic interaction of asulam and 4-aminobenzoic acid. Pest Manag Sci 12:325-329
Veerasekaran P, Kirkwood RC, Parnell EW (1981b) Studies of the mechanism of action
of asulam in plants. Part II: Effect of asulam on the biosynthesis of folic acid. Pest Manag Sci 12:330-338
Venables WN, Ripley BD (2002) Modern Applied Statistics with S. 4th edn. New York, NY: Springer. 495 p
Walker A, Brown PA (1985) The relative persistence in soil of five acetanilide
herbicides. Bull Environ Contam Toxicol 34:143-149 Whaley CM, Armel GR, Wilson HP, Hines TE (2009) Evaluation of S-metolachlor and S- metolachlor plus atrazine mixtures with mesotrione for broadleaf weed control in corn. Weed Technol 23:193-196 Wu X, Long Y, Li J, Li R, Liu R, Li M (2015) Degradation of metolachlor in tobacco field
soil. Soil and Sediment Contam 24:398-410 Zimdahl RL, Clark SK (1982) Degradation of three acetanilide herbicides in soil. Weed
Sci 30:545-548
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BIOGRAPHICAL SKETCH
Jose V. Fernandez grew up in Tegucigalpa, Francisco Morazan, Honduras. He
attended Escuela Agricola Panamerican, Zamorano, where he obtained a Bachelor of
Science degree in agronomy in 2003. Since then, he worked as a farm manager for two
beef and one dairy operation companies, and as an extension agent in Honduras. In
2011, he was accepted in the graduate weed science program in the Agronomy
Department at the University of Florida. Under the supervision of Dr. Dennis Odero, he
focused on ragweed parthenium management in the Everglades Agricultural Area. He
obtained his Master of Science degree in agronomy at the University of Florida in 2013.
Jose continued his graduate work at the University of Florida pursuing a doctorate
degree in agronomy where he will graduate in May 2017.
