Relative to MBr-C, there were no significant differences in cucumber stand among halosul‐ furon alone, or combinations containing clomazone, fomesafen, *S*-metolachlor, halosulfuron, and the nontreated control (data not shown). There were no differences among any treatment in the spring experiment for cucumber vine growth rate (*b*), ranging from 0.073 to 0.104 cm GDD−1 (Table 7, Figure 7). In contrast, there was variability in the rate of cucumber vine growth in the autumn experiment as all three herbicide treatments had significantly less growth as compared to MBr-C (Table 8, Figure 8). Previous research indicated that cucumber exhibited biomass variability with respect to injury in response to halosulfuron PRE applied in a greenhouse experiment [54]. Halosulfuron is registered for use in cucumber grown with LDPE mulch in Georgia, but injury can occur if proper precautions are not followed during use [21].

and clomazone are all registered for use with LDPE mulch in Georgia [21].

**5.2. Purple nutsedge control in bell pepper**

pepper growers is needed.

**5.3. Cucumber**

experiment was conducted.

80 Herbicides, Agronomic Crops and Weed Biology

**5.1. Bell pepper**

The complexity and difficulty of managing nutsedge species in vegetable crops have increased with the elimination of methyl bromide. Successful management of nutsedge will require diligent control programs utilizing LDPE mulches along with residual herbicides prior to crop planting, during the cropping season, and between crops (spring and autumn), in order to extend the use of LDPE mulches and reduce costs. This research indicated that combining multiple herbicides could provide control of purple nutsedge in bell pepper and cucumber LDPE mulch production. But variability in purple nutsedge control was observed, which indicates the need for further development as growers incorporate this strategy. Spring and autumn soil-applied residual herbicide treatments prior to LDPE mulch lying did not reduce bell pepper growth. Bell pepper was tolerant of herbicide combinations not previously considered as options for nutsedge control. However, cucumber injury to *S*-metolachlor was unacceptable. Other registered herbicide options should be considered when cucumber is to be grown. Future research should be conducted with the currently evaluated herbicides for other solanaceous and cucurbit crops. Purple nutsedge control was attainable with herbicide applications, but variability was an issue in this research. This should be considered as an area for future research efforts in vegetable production using LDPE mulches.

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for general linear model (GLM) was used for mean separation with 95% asymptotic confidence interval (CI) in SAS 9.2.

b Rates of bell pepper growth (*b*)were calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, bell pepper rate of growth; NS, not significant.

**Table 3.** Rate of bell pepper growth (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in spring 2011 as compared to time in growing degree days (GDD).

Spring

**Figure 3.** Pepper height growth response as affected by herbicide treatment when applied to soil surface as low-densi‐ ty polyethylene mulch was laid in spring 2011. The line represents the linear regression equation with adjusted *R*2 . Da‐ ta points are the means of replications: Clomazone + fomesafen; *y* =6.13 + 0.062*x*; *R*2 = 0.88 ; *P* = 0.975 *S*metolachlor + fomesafen; *y* =7.35 + 0.056*x*; *R*2 = 0.73 ; *P* < 0.0001 *S*-metolachlor + fomesafen + clomazone; *y* =6.48 + 0.062*x*; *R2* = 0.93 ; *P* = 0.0635 Methyl bromide; *y* =6.30 + 0.060*x*; *R*2 = 0.93; ; *P* = 0.527 Nontreated; *y* =6.48 + 0.062*x*; *R*2 = 0.93; ; *P* = 0.0635

Evaluation of Non-fumigant Pesticides as Methyl Bromide Alternatives for Managing Weeds in Vegetables http://dx.doi.org/10.5772/61635 83

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rates of bell pepper growth (*b*) were calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, bell pepper rate of growth; NS, not significant.

**Table 4.** Rate of bell pepper growth (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD).

Autumn

. Da‐

= 0.93; ; *P* = 0.527 Nontreated;

**Rate of bell pepper growthb**

**Treatment** *y0c* **SE** *b* **SE**

Clomazone + fomesafen 6.13 NSa ±1.24 0.062 NS ±0.0038 *S*-metolachlor + fomesafen 7.35 NS ±1.83 0.056 NS ±0.0057 *S*-metolachlor + fomesafen + clomazone 6.48 NS ±0.67 0.062 NS ±0.0021 Methyl bromide + chloropicrin 6.30 NS ±0.63 0.060 NS ±0.0019 Nontreated 6.48 NS ±0.67 0.062 NS ±0.0021

For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for general linear model (GLM) was

Rates of bell pepper growth (*b*)were calculated by linear regression of the herbicide treatments with respect to time in

**Table 3.** Rate of bell pepper growth (*b*) as a response to herbicide used in combination with low-density polyethylene

**Figure 3.** Pepper height growth response as affected by herbicide treatment when applied to soil surface as low-densi‐ ty polyethylene mulch was laid in spring 2011. The line represents the linear regression equation with adjusted *R*2

ta points are the means of replications: Clomazone + fomesafen; *y* =6.13 + 0.062*x*; *R*2 = 0.88 ; *P* = 0.975 *S*-

= 0.93 ; *P* = 0.0635 Methyl bromide; *y* =6.30 + 0.060*x*; *R*2

= 0.73 ; *P* < 0.0001 *S*-metolachlor + fomesafen + clomazone;

used for mean separation with 95% asymptotic confidence interval (CI) in SAS 9.2.

82 Herbicides, Agronomic Crops and Weed Biology

mulch in spring 2011 as compared to time in growing degree days (GDD).

Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, bell pepper rate of growth; NS, not significant.

a

b

GDD. c

Spring

*y* =6.48 + 0.062*x*; *R2*

*y* =6.48 + 0.062*x*; *R*2

metolachlor + fomesafen; *y* =7.35 + 0.056*x*; *R*2

= 0.93; ; *P* = 0.0635

**Figure 4.** Pepper height growth response as affected by herbicide treatment when applied to soil surface as the lowdensity polyethylene mulch was laid in autumn 2011. The line represents the linear regression equation with adjusted *R*2 . Data points are the means of replications: Clomazone + fomesafen; *y* =4.82 + 0.073*x*; *R*2 = 0.55 ; *P* = 0.147 *S*-me‐ tolachlor + fomesafen; *y* =5.04 + 0.074*x*; *R*2 = 0.87 ; *P* = 0.619 *S*-metolachlor + fomesafen + clomazone; *y* =5.35 + 0.071*x*; *R*2 = 0.81 ; *P* = 0.0073 Methyl bromide; *y* =4.48 + 0.072*x*; *R*2 = 0.78 ; *P* = 0.846 Nontreated; *y* =5.20 + 0.072*x*; *R*2 = 0.75 ; *P* = 0.233

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of purple nutsedge growth (*b*) was calculated by linear regression of the herbicide treatments with respect to time, GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

**Table 5.** Purple nutsedge population (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in spring 2011 as compared to time in growing degree days (GDD) in bell pepper.

Spring

**Figure 5.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in spring 2011 with bell pepper as a crop. The line represents the linear regression equation with adjusted *R*2 . Data points are the means of replications: Clomazone + fomesafen; *y* =6.61 + 0.037*x*; *R*2 = 0.38 ; *P* < 0.0001 *S*-metolachlor + fomesafen; ; *y* =5.73 + 0.032*x*; *R*2 = 0.28; *P* < 0.0001 *S*-metolachlor + fomesafen + clomazone; *y* =3.89 + 0.033*x*; *R*2 = 0.26; *P* < 0.0001 Methyl bromide; *y* =0.00 + 0.004*x*; *R*2 = 0.22 ; *P* = 0.0002 Non‐ treated; *y* =11.0 + 0.056*x*; *R*2 = 0.40 ; *P* < 0.0001

Evaluation of Non-fumigant Pesticides as Methyl Bromide Alternatives for Managing Weeds in Vegetables http://dx.doi.org/10.5772/61635 85

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of purple nutsedge growth (*b*) was calculated by linear regression of the herbicide treatments with respect to time, GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

**Table 6.** Purple nutsedge population (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD) in bell pepper.

Autumn

**Purple nutsedge populationb**

**Treatment** *y0c* **SE** *b* **SE**

Clomazone + fomesafen 6.61 *b*a ±1.33 0.037 *b* ±0.0049 *S*-metolachlor + fomesafen 5.73 *b* ±1.43 0.032 *b* ±0.0062 *S*-metolachlor + fomesafen + clomazone 3.89 *b* ±1.28 0.033 *b* ±0.0042 Methyl bromide + chloropicrin 0.0 *a* ±1.88 0.004 *a* ±0.0069 Nontreated 11.0 *b* ±1.88 0.056 *b* ±0.0069

For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation

Rate of purple nutsedge growth (*b*) was calculated by linear regression of the herbicide treatments with respect to

**Table 5.** Purple nutsedge population (*b*) as a response to herbicide used in combination with low-density polyethylene

**Figure 5.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in spring 2011 with bell pepper as a crop. The line represents the linear regression

clomazone; *y* =3.89 + 0.033*x*; *R*2 = 0.26; *P* < 0.0001 Methyl bromide; *y* =0.00 + 0.004*x*; *R*2 = 0.22 ; *P* = 0.0002 Non‐

. Data points are the means of replications: Clomazone + fomesafen; *y* =6.61 + 0.037*x*; *R*2

= 0.28; *P* < 0.0001 *S*-metolachlor + fomesafen +

Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

mulch in spring 2011 as compared to time in growing degree days (GDD) in bell pepper.

a

b

time, GDD. c

Spring

equation with adjusted *R*2

treated; *y* =11.0 + 0.056*x*; *R*2

= 0.38 ; *P* < 0.0001 *S*-metolachlor + fomesafen; ; *y* =5.73 + 0.032*x*; *R*2

= 0.40 ; *P* < 0.0001

with 95% asymptotic CI in SAS 9.2.

84 Herbicides, Agronomic Crops and Weed Biology

**Figure 6.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in autumn 2011 with bell pepper as a crop. The line represents the linear regression equation with adjusted *R*2 . Data points are the means of replications: Clomazone + fomesafen; *y* = −0.68 + 0.016*x*; *R*2 = 0.29; *P* < 0.0001 *S*-metolachlor + fomesafen; *y* = −0.71 + 0.020*x*; *R*2 = 0.20; *P* = 0.0002 *S*-metolachlor + fomesafen + clomazone; *y* = −0.48 + 0.008*x*; *R*2 = 0.24; *P* < 0.0001 Methyl bromide; *y* = −0.39 + 0.006*x*; *R*2 = 0.15; *P* = 0.0195 Nontreated; *y* = −0.88 + 0.017*x*; *R*2 = 0.14; *P* = 0.0232

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of cucumber vine growth (*b*) was calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, cucumber vine rate of growth; NS, not significant.

**Table 7.** Rate of cucumber vine growth (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in spring 2011 as compared to time in growing degree days (GDD).

Spring

**Figure 7.** Cucumber vine length growth response as affected by herbicide treatment when applied to soil as the lowdensity polyethylene mulch was being laid in spring 2011. The line represents the linear regression equation with ad‐ justed *R*2 . Data points are the means of replications: Halosulfuron; *y* =2.12 + 0.094*x*; *R*2 = 0.83; *P* = 0.116 *S*metolachlor + clomazone + halosulfuron; *y* =1.85 + 0.073*x*; *R*2 = 0.77; *P* = 0.0004 *S*-metolachlor + clomazone + fomesafen; *y* =2.44 + 0.081*x*; *R*2 = 0.80; *P* = 0.831 Methyl bromide; *y* =2.40 + 0.081*x*; *R*2 = 0.84; *P* = 0.720 Non‐ treated; *y* =0.79 + 0.104*x*; *R*2 = 0.72; *P* = 0.013

Evaluation of Non-fumigant Pesticides as Methyl Bromide Alternatives for Managing Weeds in Vegetables http://dx.doi.org/10.5772/61635 87

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of cucumber vine growth (*b*) was calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, cucumber vine rate of growth; NS, not significant.

**Table 8.** Rate of cucumber vine growth (*b*) as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD).

Autumn

**Rate of cucumber vine growthb**

**Treatment** *y0c* **SE** *b* **SE**

Halosulfuron 2.12 NSa ±0.88 0.094 NS ±0.0071 *S*-metolachlor + clomazone + halosulfuron 1.85 NS ±0.85 0.073 NS ±0.0068 *S*-metolachlor + clomazone + fomesafen 2.44 NS ±0.83 0.081 NS ±0.0067 Methyl bromide + chloropicrin 2.40 NS ±1.05 0.081 NS ±0.0084 Nontreated 0.79 NS ±1.91 0.104 NS ±0.015

For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation

Rate of cucumber vine growth (*b*) was calculated by linear regression of the herbicide treatments with respect to time

**Figure 7.** Cucumber vine length growth response as affected by herbicide treatment when applied to soil as the lowdensity polyethylene mulch was being laid in spring 2011. The line represents the linear regression equation with ad‐

= 0.83; *P* = 0.116 *S*-

= 0.77; *P* = 0.0004 *S*-metolachlor + clomazone +

= 0.80; *P* = 0.831 Methyl bromide; *y* =2.40 + 0.081*x*; *R*2 = 0.84; *P* = 0.720 Non‐

. Data points are the means of replications: Halosulfuron; *y* =2.12 + 0.094*x*; *R*2

metolachlor + clomazone + halosulfuron; *y* =1.85 + 0.073*x*; *R*2

= 0.72; *P* = 0.013

Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, cucumber vine rate of growth; NS, not significant.

polyethylene mulch in spring 2011 as compared to time in growing degree days (GDD).

**Table 7.** Rate of cucumber vine growth (*b*) as a response to herbicide used in combination with low-density

a

b

c

in GDD.

Spring

justed *R*2

fomesafen; *y* =2.44 + 0.081*x*; *R*2

treated; *y* =0.79 + 0.104*x*; *R*2

with 95% asymptotic CI in SAS 9.2.

86 Herbicides, Agronomic Crops and Weed Biology

**Figure 8.** Cucumber vine length growth response as affected by herbicide treatment when applied to soil as the lowdensity polyethylene mulch was being laid in autumn 2011. The line represents the linear regression equation with adjusted *R*2 . Data points are the means of replications: Halosulfuron; *y* =2.49 + 0.072*x*; *R*2 = 0.79; *P* = 0.216 *S*-metola‐ chlor + clomazone + halosulfuron; *y* =3.77 + 0.050*x*; *R*2 = 0.60; *P* < 0.0001 *S*-metolachlor + clomazone + fomesafen; *y* =3.70 + 0.066*x*; *R*2 = 0.68 ; *P* < 0.0001 Methyl bromide; *y* =3.24 + 0.104*x*; *R*2 = 0.60; *P* = 0.557 Nontreated; *y* =3.76 + 0.118*x*; *R*2 = 0.75; *P* < 0.0001

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of purple nutsedge growth (*b*) calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

**Table 9.** Purple nutsedge population (*b*) growth as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD) in cucumber.

Spring

**Figure 9.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in spring 2011 with cucumber as a crop. The line represents the linear regression equation with adjusted *R*2 . Data points are the means of replications: Halosulfuron; *y* =0.21 + 0.016*x*; *R*2 = 0.16; *P* < 0.0001 *S*-metotachlor + clomazone + halosulfuron; *y* =0.00 + 0.009*x*; *R*2 = 0.41; *P* < 0.0001 *S*-merolachlor + clomazone + fomesafen; *y* = −0.33 + 0.009*x*; *R*2 = 0.47; *P* < 0.0001 Methyl bromide; *y* = −0.11 + 0.004*x*; *R*2 = 0.10; *P* < 0.0001 Nontreated; *y* =0.09 + 0.017*x*; *R*2 = 0.46; *P* = 0.0305

Evaluation of Non-fumigant Pesticides as Methyl Bromide Alternatives for Managing Weeds in Vegetables http://dx.doi.org/10.5772/61635 89

a For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation with 95% asymptotic CI in SAS 9.2.

b Rate of purple nutsedge growth (*b*) calculated by linear regression of the herbicide treatments with respect to time in GDD.

c Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

**Table 10.** Purple nutsedge population (*b*) growth as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD) in cucumber.

Autumn

**Rate of purple nutsedge growthb**

0.33 *b* ±0.55 0.009 *b* ±0.0018

0.11 *a* ±0.77 0.004 *a* ±0.0026

**Treatment** *y0c* **SE** *b* **SE**

Halosulfuron 0.21 *b*a ±0.55 0.016 *b* ±0.0018 *S*-metolachlor + clomazone + halosulfuron 0.00 *b* ±0.55 0.009 *b* ±0.0018

Nontreated 0.09 *b* ±0.77 0.017 *b* ±0.0026

For each herbicide for parameter estimate in each column followed by the same letter are not significantly different (*P*≤0.05) as compared to methyl bromide plus chloropicrin. The REG procedure for GLM was used for mean separation

Rate of purple nutsedge growth (*b*) calculated by linear regression of the herbicide treatments with respect to time in

**Table 9.** Purple nutsedge population (*b*) growth as a response to herbicide used in combination with low-density polyethylene mulch in autumn 2011 as compared to time in growing degree days (GDD) in cucumber.

**Figure 9.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in spring 2011 with cucumber as a crop. The line represents the linear regression

0.0001 *S*-metotachlor + clomazone + halosulfuron; *y* =0.00 + 0.009*x*; *R*2

= 0.46; *P* = 0.0305

. Data points are the means of replications: Halosulfuron; *y* =0.21 + 0.016*x*; *R*2 = 0.16; *P* <

= 0.47; *P* < 0.0001 Methyl bromide; *y* = −0.11 + 0.004*x*; *R*2

= 0.41; *P* < 0.0001 *S*-merolachlor + clomazone

= 0.10; *P* < 0.0001

Abbreviations: *y*0, *y*-intercept; SE, standard error; *b*, purple nutsedge rate of growth.

*S*-metolachlor + clomazone + fomesafen −

88 Herbicides, Agronomic Crops and Weed Biology

Methyl bromide + chloropicrin −

with 95% asymptotic CI in SAS 9.2.

a

b

GDD. c

Spring

equation with adjusted *R*2

+ fomesafen; *y* = −0.33 + 0.009*x*; *R*2

Nontreated; *y* =0.09 + 0.017*x*; *R*2

**Figure 10.** Purple nutsedge stand response as affected by herbicide treatment when applied to soil as the low-density polyethylene mulch was being laid in autumn 2011 with cucumber as a crop. The line represents the linear regression equation with adjusted R2 . Data points are the means of replications: Halosulfuron; *y* = −0.92 + 0.022*x*; R2 = 0.43; P = 0.0002 S-metolachlor + clomazone + halosulfuron; *y* = 0.015 + 0.037*x*; R2 = 0.23; P = 0.0084 S-metolachlor + cloma‐ zone + fomesafen; *y* = 2.94 + 0.034*x*; R2 = 0.22; P = 0.0224 Methyl bromide; *y* = −0.23 + 0.018*x*; R2 = 0.38; P = 0.0006 Nontreated; *y* = −0.57 + 0.037*x*; R2 = 0.42; P = 0.0003

### **Author details**

Timothy Grey1\* and Theodore Webster2

### **References**

[11] Gilreath J.P., Motis T.N., Santos B.M. (2005) *Cyperus* spp. control with reduced meth‐ yl bromide plus chloropicrin doses under virtually impermeable film in pepper. *Crop Protection* 24:285-287.

**Author details**

**References**

Timothy Grey1\* and Theodore Webster2

90 Herbicides, Agronomic Crops and Weed Biology

ham, AL. pp 282-293.

*Weed Science* 46:575-580.

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\*Address all correspondence to<EMAIL_ADDRESS>
1 Crop and Soil Sciences Department, University of Georgia, USA

2 Crop Protection and Management Research Unit, USDA-ARS, Tifton, Georgia, USA

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[36] Miller M.R., Dittmar P.J. (2014) Effect of PRE and POST-directed herbicide for sea‐

[37] Boyd N.S. (2015) Evaluation of preemergence herbicide for purple nutsedge control

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son-long nutsedge control in bell pepper. *Weed Technology* 28:518-526.

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rotational vegetables and sunflower. *Weed Technology* 7:573–577.

*Science Society*. Greensboro, NC, 211 p.

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meturon in soil. *Weed Science* 30:629-632.

55:638-643.

92 Herbicides, Agronomic Crops and Weed Biology

### **Peanut Performance and Weed Management in a Highresidue Cover Crop System**

Jessica A. Kelton, Andrew J. Price, Kip S. Balkcom, Wilson H. Faircloth and Lina Sarunaite

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/61650

### **Abstract**

[54] Webster T.M., Culpepper A.S., Johnson, III W.C. (2003) Response of squash and cu‐

[55] Pillai P., Davis D.E., Truelove B. (1979) Effects of metolachlor on germination,

[56] Sloan M.E., Camper N.D. (1986) Effects of alachlor and metolachlor on cucumber

[57] MacRae A.W., Culpepper A.S., Batts R.B., Lewis K.L. (2008) Seeded watermelon and weed response to halosulfuron applied preemergence and postemergence. *Weed*

[58] Norsworthy J.H., Schroeder J., Thomas S.H., Murray L.W. (2007) Purple nutsedge management in direct-seeded chile pepper using halsosulfuron and cultivation. *Weed*

[59] Silvey B.D., Mitchem W.E., MacRae A.W., Monks D.W. (2006) Snap bean tolerance to halosulfuron PRE, POST, or PRE followed by POST. *Weed Technology* 20:873-876. [60] Dittmar P.J., Monks D.W., Jennings K.M. (2012) Effect of drip-applied herbicides on

[61] Johnson III, W.C., Mullinix, Jr. B.G. (2002) Weed management in watermelon and cantaloupe transplanted on polyethylene-covered seedbeds. *Weed Technology*

[62] Holt J.S. Orcutt D.R. (1996) Temperature thresholds for bud sprouting in perennial

[63] Morales-Payan J.P., Santos B.M., Stall W.M., Bewick T.A. (1997) Effects of purple nut‐ sedge on tomato and bell pepper vegetative growth and fruit yield. *Weed Technology*

growth, leucine uptake, and protein synthesis. *Weed Science* 27:634-637.

cumber cultivars to halosulfuron. *Weed Technology* 17:173-176.

seedlings. *Environmental and Experimental Botany* 26:1-7.

yellow nutsedge in plasticulture. *Weed Technology* 26:243-247.

weeds and seed germination in cotton. *Weed Science* 44:523–533.

*Technology* 22:86-90.

94 Herbicides, Agronomic Crops and Weed Biology

*Technology* 21:636-641

16:806-866.

11:672-676.

Previous research has indicated that conservation tillage is a viable option for suc‐ cessful peanut production; however, interactions between cover crop residues and peanut growth are not fully understood. Additional information is needed about the effects of varying levels of cover crop biomass on peanut growth and develop‐ ment. Level of cover crop residue may also affect the preemergence herbicide activi‐ ty through interception and efficacy of weed suppression. The objectives of this peanut research were to determine if varying amounts of cover crop biomass would affect peanut growth, herbicide interception, or weed control. This research also aimed to determine if cover crop management practices (rolling or standing cover) would affect herbicide interception rates. The study consisted of a rye (*Secale cereale* L.) cover crop planted at three different dates as well as a fallow treatment at two locations: Dawson, GA, and Headland, AL. Pendimethalin was applied PRE at 1 kg ai/ha across the entire area just prior to planting of the Georgia 03-L peanut variety. Soil samples were collected at three different dates after planting for high-pressure liquid chromatography (HPLC) analysis to determine pendimethalin levels. Peanut yields differed only between location regardless of cover crop residue level with the Headland, Alabama, site averaging 4,272 kg/ha and the Dawson, Georgia, site aver‐ aging 2,247 kg/ha. Pendimethalin extraction from soil samples indicated no differ‐ ence in herbicide recovery between winter fallow systems compared to treatments with cover crops. Weed control ratings taken at 21 and 45 days after planting (DAP) showed greater weed suppression for cover crop systems for an extended period of time when higher levels of cover crop biomass are present. Results of this experi‐ ment indicate the inclusion of cover crops in a conservation-tilled peanut system can be a successful alternative to winter fallow systems without reducing peanut yield or herbicide efficacy.

**Keywords:** Conservation tillage, high-residue cover crops, peanut production

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

### **1. Introduction**

Peanut offers significant value to agricultural producers in the southeastern United States each year with approximately 530,000 ha harvested in the United States in 2014 [1]. In recent years, time and money savings offered by conservation systems through reduced labor and tillage practices have led to an increase in peanut production under these systems [2–6]. Govern‐ mental incentives offered to producers meeting certain criteria pertaining to the practice of conservation tillage have also aided in increasing adoption rates of these practices [7].

In addition to reduced production costs, other benefits of conservation tillage are well recognized throughout agricultural literature, including reduced soil and water loss, increased soil organic matter, improved soil structure, higher-quality stand establishment, and less incidence of disease [8–12]. Cover crop integration into conservation tillage systems further enhances benefits achieved through reduced tillage practices when compared to winter fallow systems [13–16]. Despite the advantages and growing interest, peanut production under conservation tillage systems still lags behind conventional production methods owing to producer concern over yield reduction either through digging losses or through reduced pegging due to cover crop residue impediment [17–19]. Furthermore, the use of cover crops with high biomass may reduce the efficacy of preemergent herbicides and increase producer reliance on postemergent formulations [20–22].

Since the introduction of dinitroaniline herbicides, such as pendimethalin, peanut producers have been integrating this soil-applied, preemergent herbicide into the herbicide regime in order to achieve weed suppression of small seeded annuals [23]. The use of these soil-applied herbicide treatments provides residual activity for several problematic weed species and can reduce the dependency on postemergent herbicide formulations. The growing interest in conservation tillage systems, specifically strip-tillage, in peanut has created an even greater demand for successful herbicide treatment plans due to the loss of weed control from weed seed burial through tillage [24,25].

Pendimethalin is frequently used in reduced-tillage systems due to its high water solubility and low volatility in comparison with other dinitroaniline herbicides [26]. However, there is uncertainty as to whether an acceptable level of weed control can be achieved in peanut systems that include a high level of cover crop biomass due to a physical barrier of residue impeding the movement of the herbicide to the soil surface. Efficacy of pendimethalin, which is tightly sorbed to plant residue, can subsequently be reduced if substantial amounts of the herbicide are intercepted by the cover crop biomass [27,28].

Further questions also remain in regard to cover crop management practices and their role in reducing cover crop interaction with soil-applied herbicides in reduced-till peanut systems. Typical termination practices for cover crops include treating the cover with a nonselective herbicide (glyphosate or paraquat) 2–4 weeks prior to the primary crop plant date and leaving standing residue as a cover [29]. Standing residue will reduce soil and water loss but can hinder planting operations by clogging the planter between the row cover [30]. Mechanically rolling or crimping plant residue, used in conjunction with termination herbicides, is another option for effectively managing cover crops prior to planting [29]. This management system, although less frequently used, increases cover crop termination efficacy with the inclusion of an herbicide while effectively creating a dense layer of residue. This layer of cover crop biomass can reduce soil moisture evaporation, subsequently reducing soil strength in comparison with standing residue, and reduce weed seedling emergence [31,32]. While there are many benefits to rolling cover crop residue, concerns exist in regard to increased interception of preemergent herbicides by a dense horizontal layer of plant matter covering the soil surface.

The objectives of this study were to determine the impact of differing levels of biomass residue on peanut production systems in terms of yield and weed control. Moreover, we hope to determine how herbicide interception is affected in different levels of biomass as well as under different termination management strategies to include standing residue and mechanically rolled residue practices.

### **2. Materials and methods**

**1. Introduction**

96 Herbicides, Agronomic Crops and Weed Biology

reliance on postemergent formulations [20–22].

herbicide are intercepted by the cover crop biomass [27,28].

seed burial through tillage [24,25].

Peanut offers significant value to agricultural producers in the southeastern United States each year with approximately 530,000 ha harvested in the United States in 2014 [1]. In recent years, time and money savings offered by conservation systems through reduced labor and tillage practices have led to an increase in peanut production under these systems [2–6]. Govern‐ mental incentives offered to producers meeting certain criteria pertaining to the practice of conservation tillage have also aided in increasing adoption rates of these practices [7].

In addition to reduced production costs, other benefits of conservation tillage are well recognized throughout agricultural literature, including reduced soil and water loss, increased soil organic matter, improved soil structure, higher-quality stand establishment, and less incidence of disease [8–12]. Cover crop integration into conservation tillage systems further enhances benefits achieved through reduced tillage practices when compared to winter fallow systems [13–16]. Despite the advantages and growing interest, peanut production under conservation tillage systems still lags behind conventional production methods owing to producer concern over yield reduction either through digging losses or through reduced pegging due to cover crop residue impediment [17–19]. Furthermore, the use of cover crops with high biomass may reduce the efficacy of preemergent herbicides and increase producer

Since the introduction of dinitroaniline herbicides, such as pendimethalin, peanut producers have been integrating this soil-applied, preemergent herbicide into the herbicide regime in order to achieve weed suppression of small seeded annuals [23]. The use of these soil-applied herbicide treatments provides residual activity for several problematic weed species and can reduce the dependency on postemergent herbicide formulations. The growing interest in conservation tillage systems, specifically strip-tillage, in peanut has created an even greater demand for successful herbicide treatment plans due to the loss of weed control from weed

Pendimethalin is frequently used in reduced-tillage systems due to its high water solubility and low volatility in comparison with other dinitroaniline herbicides [26]. However, there is uncertainty as to whether an acceptable level of weed control can be achieved in peanut systems that include a high level of cover crop biomass due to a physical barrier of residue impeding the movement of the herbicide to the soil surface. Efficacy of pendimethalin, which is tightly sorbed to plant residue, can subsequently be reduced if substantial amounts of the

Further questions also remain in regard to cover crop management practices and their role in reducing cover crop interaction with soil-applied herbicides in reduced-till peanut systems. Typical termination practices for cover crops include treating the cover with a nonselective herbicide (glyphosate or paraquat) 2–4 weeks prior to the primary crop plant date and leaving standing residue as a cover [29]. Standing residue will reduce soil and water loss but can hinder planting operations by clogging the planter between the row cover [30]. Mechanically rolling or crimping plant residue, used in conjunction with termination herbicides, is another option

Field experiments were conducted from the fall of 2006 to the fall of 2008 at the Hooks Hanner Environmental Resource Center in Dawson, GA, and the Alabama Agricultural Experiment Station's Wiregrass Research and Extension Center (WREC) in Headland, AL. Soil types were mostly a Greenville sandy clay loam (fine, kaolinitic, thermic Rhodic Kandiudults) at the Georgia site and a Dothan fine sandy loam (fine-loamy, siliceous, thermic Plinthic Paleudults) at the Alabama site. Experimental layout was a randomized complete block split-plot restric‐ tion design with three replications at each site. The main effect of cover crop residue levels (low, medium, high, or fallow) was determined by planting date. Subplots consisted of cover crop termination practice (herbicide and herbicide plus rolling) and herbicide selection (paraquat and glyphosate).

Three fall planting dates of rye (*Secale cereale* L.) spaced approximately 30 days apart were conducted from October through December at each location for both years. Seeding rates were 100 kg/ha at the Headland and Dawson sites. Cover crops were planted using a Great Plains No-Till1 drill. Termination of rye and fallow plots was conducted in early May, 3 weeks prior to peanut planting (except at the Dawson site where planting was delayed until June for both years) with either glyphosate at 1.7 kg ai/ha or paraquat at 0.84 kg ai/ha. Aboveground ¼ m2 biomass samples were randomly taken from all plots just before termination and dried at 60°C to determine the dry weight. Cover crop residue was then either left standing or mechanically rolled prior to planting.

Peanut (cv Georgia 03-L) was planted into a strip-tilled system each spring at a rate of 18 seed/ m. Strip-tillage, the predominant choice of conservation systems for peanut farmers, was performed using KMC2 ripper to prepare a 30- cm-wide seedbed area. Plot size was four 10 m rows on a 91-cm spacing for the Headland location and six 10-m rows on a 91-cm spacing for the Dawson site. Pendimethalin was applied as a preemergence treatment across the experiment at a rate of 1 kg ai/ha each year.

Soil samples were collected from each experiment at 7-, 14-, and 21-day increments after pendimethalin application (except at WREC in 2007 due to an oversight). Four random subsamples were collected and combined for each of the sampled plots. Collection of soil was done with a stainless steel flat scoop to include the upper 2 cm of the soil surface. Samples were wrapped in foil before being placed in plastic bags to reduce herbicide adsorption to the plastic and subsequently stored in a cooler for storage until processing. Prior to storage, gravimetric water content of the soil was determined with a 20-g portion of each sample.

Preparation of soil samples for HPLC analysis was conducted based on procedures described by Potter et al. [26]. Samples (50 g each) were processed through a 2-mm sieve and placed in 250-mL glass bottles for extraction with three repetitions using 50 mL of methanol. After extraction, samples were vacuum-filtered and the extract was reduced using a rotary evapo‐ rator system to 5 mL. The extract was then reconstituted to a 10-mL volume with 1 g of the extract subsequently being placed into an auto sampler vial along with 10 µg of 0.5-mg/ml 2 chlorolepedine (an internal standard added by the laboratory prior to analysis). In addition, spray targets (70-mm Whatman cellulose filter paper3 ) collected at the time of pendimethalin application were extracted in 25 mL of methanol and then diluted to a 1:10 ratio. A 1-g sample was then prepared for analysis in the same manner as soil sample extracts. High-pressure liquid chromatography (HPLC) was then conducted by the USDA-ARS Southeast Watershed Research Laboratory in Tifton, GA.

In addition, visual weed control ratings on a 0–100% scale with 0 being no control were conducted at 21 and 45 DAP. Peanut yield was calculated with the middle two rows after digging and harvesting at each site. During the experiment, additional management practices (including insect control and nutrient management) followed the respective state's recom‐ mendations for peanut growing practices.

Data analysis was conducted using the GLIMMIX procedure in SAS4 to compare treatment effects on yield as well as weed control rating comparisons at *α* = 0.05. Non-transformed data were used for yield comparison; however, arc sine transformation was used to improve variance in weed control data.

### **3. Results and discussion**

### **3.1. Yield**

Main effect differences were only noted between locations (*P* < 0.0001) with Headland having greater yields in both years of the experiment with 4,432 kg/ha and 4,112 kg/ha for 2007 and 2008 compared with Dawson yield over treatments at 1,775 kg/ha and 2,718 kg/ha (Table 1). Historically, Georgia's average yield is more than the expected yield for Alabama producers with recent 2014 yields for Georgia (4,600 kg/ha) and Alabama (3,600 kg/ha) reflecting this slight difference [1]. The disparity between annual averages and experimental peanut yields could potentially be attributed to the general trend toward irrigation for peanut production in Georgia as opposed to dryland production in Alabama (172,000 ha and 56,000 ha, respectively, in 2014) [1]. For this experiment, neither site was under an irrigation system for the duration of the growing seasons.

a Yield differences are significant between locations (*P* < 0.0001).

subsamples were collected and combined for each of the sampled plots. Collection of soil was done with a stainless steel flat scoop to include the upper 2 cm of the soil surface. Samples were wrapped in foil before being placed in plastic bags to reduce herbicide adsorption to the plastic and subsequently stored in a cooler for storage until processing. Prior to storage, gravimetric water content of the soil was determined with a 20-g portion of each sample.

Preparation of soil samples for HPLC analysis was conducted based on procedures described by Potter et al. [26]. Samples (50 g each) were processed through a 2-mm sieve and placed in 250-mL glass bottles for extraction with three repetitions using 50 mL of methanol. After extraction, samples were vacuum-filtered and the extract was reduced using a rotary evapo‐ rator system to 5 mL. The extract was then reconstituted to a 10-mL volume with 1 g of the extract subsequently being placed into an auto sampler vial along with 10 µg of 0.5-mg/ml 2 chlorolepedine (an internal standard added by the laboratory prior to analysis). In addition,

application were extracted in 25 mL of methanol and then diluted to a 1:10 ratio. A 1-g sample was then prepared for analysis in the same manner as soil sample extracts. High-pressure liquid chromatography (HPLC) was then conducted by the USDA-ARS Southeast Watershed

In addition, visual weed control ratings on a 0–100% scale with 0 being no control were conducted at 21 and 45 DAP. Peanut yield was calculated with the middle two rows after digging and harvesting at each site. During the experiment, additional management practices (including insect control and nutrient management) followed the respective state's recom‐

Data analysis was conducted using the GLIMMIX procedure in SAS4 to compare treatment effects on yield as well as weed control rating comparisons at *α* = 0.05. Non-transformed data were used for yield comparison; however, arc sine transformation was used to improve

Main effect differences were only noted between locations (*P* < 0.0001) with Headland having greater yields in both years of the experiment with 4,432 kg/ha and 4,112 kg/ha for 2007 and 2008 compared with Dawson yield over treatments at 1,775 kg/ha and 2,718 kg/ha (Table 1). Historically, Georgia's average yield is more than the expected yield for Alabama producers with recent 2014 yields for Georgia (4,600 kg/ha) and Alabama (3,600 kg/ha) reflecting this slight difference [1]. The disparity between annual averages and experimental peanut yields could potentially be attributed to the general trend toward irrigation for peanut production in Georgia as opposed to dryland production in Alabama (172,000 ha and 56,000 ha, respectively, in 2014) [1]. For this experiment, neither site was under an irrigation system for the duration

) collected at the time of pendimethalin

spray targets (70-mm Whatman cellulose filter paper3

Research Laboratory in Tifton, GA.

98 Herbicides, Agronomic Crops and Weed Biology

mendations for peanut growing practices.

variance in weed control data.

**3. Results and discussion**

of the growing seasons.

**3.1. Yield**

b Yield differences are significant between years within location (*P* = 0.0143).

c Yield differences are significant between high and fallow residue levels within location for each year (*P* = 0.0054).

**Table 1.** Yield for 2007 and 2008 for the Headland and Dawson experimental sites.

\* Values followed by same letter in same year are not significant at *α* = 0.05.

**Table 2.** Pendimethalin residue recovered through soil extraction process for Headland. \*

\*Values followed by same letter in same year are not significant at *α* = 0.05.

**Table 3.** residue recovered through soil extraction process for Dawson. \*

The location and year of interaction were significant (*P* = 0.0047) with 2008 yields being higher than 2007 for Dawson and yields for Headland being higher in 2007 (Table 1). With low rainfall amounts in comparison to historical averages (Figure 1), reduced 2007 peanut yield for Dawson would be expected due to inadequate rainfall [31]. In 2008, yearly rainfall surpassed average annual rain totals with substantial rainfall occurring in the summer prior to harvest at the Dawson location. Headland rainfall was below average for both 2007 and 2008 (Figure 2), but monthly rainfall totals during the growing season were sufficient for above-average yield (Table 1). Overall, Headland peanut yield for both years of the study, regardless of rain total amounts, was considerably greater than average peanut yields across Alabama.

Yield comparison between fallow treatments and rye cover crop treatments within each location indicated a difference in yield between high-residue treatments and fallow treatments at the Dawson site with high-residue treatments having increased peanut yield by 260 kg/ha in 2007 and 1,010 kg/ha in 2008 (Table 1). The increase in peanut yield under high-residue treatments occurred at the Dawson site both years, although no significant increase in biomass residue was noted for 2007 (Table 1; Figure 3). Headland did have differences between residue levels for both years (Figure 3), but no yield differences were noted for the Headland site (Table 1).

**Year**

**–––––––––––––––μg/g–––––––––––––––**

14 0.3280C 0.2166a 21 0.3150CD 0.1722a

14 0.4453B 0.2976b 21 0.3645BC 0.1601a

14 0.4111B 0.1760a 21 0.2558D 0.1457ac

14 0.3983B 0.1332ac 21 0.2783CD 0.0890c

The location and year of interaction were significant (*P* = 0.0047) with 2008 yields being higher than 2007 for Dawson and yields for Headland being higher in 2007 (Table 1). With low rainfall amounts in comparison to historical averages (Figure 1), reduced 2007 peanut yield for Dawson would be expected due to inadequate rainfall [31]. In 2008, yearly rainfall surpassed average annual rain totals with substantial rainfall occurring in the summer prior to harvest at the Dawson location. Headland rainfall was below average for both 2007 and 2008 (Figure 2), but monthly rainfall totals during the growing season were sufficient for above-average yield (Table 1). Overall, Headland peanut yield for both years of the study, regardless of rain total

Yield comparison between fallow treatments and rye cover crop treatments within each location indicated a difference in yield between high-residue treatments and fallow treatments at the Dawson site with high-residue treatments having increased peanut yield by 260 kg/ha in 2007 and 1,010 kg/ha in 2008 (Table 1). The increase in peanut yield under high-residue treatments occurred at the Dawson site both years, although no significant increase in biomass residue was noted for 2007 (Table 1; Figure 3). Headland did have differences between residue levels for both years (Figure 3), but no yield differences were

amounts, was considerably greater than average peanut yields across Alabama.

**Residue Level Time (d) 2007 2008**

100 Herbicides, Agronomic Crops and Weed Biology

Fallow 7 0.5471A 0.1809a

Low 7 0.4576B 0.3600b

Medium 7 0.4550B 0.3140b

High 7 0.4075B 0.3201b

\*Values followed by same letter in same year are not significant at *α* = 0.05.

**Table 3.** residue recovered through soil extraction process for Dawson. \*

noted for the Headland site (Table 1).

**Figure 1.** Annual rainfall totals for 2006, 2007, and 2008 along with an historical average over the past 30 years for Dawson, GA.

**Figure 2.** Annual rainfall totals for 2006, 2007, and 2008 along with an historical average over the past 30 years for Headland, AL.

**Figure 3.** Biomass yield in kg/ha for 2007 and 2008 for the Headland and Dawson experimental sites. Values followed by same letter in same sampling time are not significant at *α* = 0.05.

### **3.2. HPLC analysis**

Analysis of soil extraction samples detected both pendimethalin and its metabolite, pendime‐ thalin alcohol, 4-[(1-ethylpropyl)amino]-2-methyl-3,5-dinitrobenyzl alcohol. The metabolite data are not presented in this study due to trace amounts detected uniformly throughout the samples (<0.05 µg/mL). Recovered pendimethalin is presented by location and year (Figure 4) due to differences detected between these main effects. The general trend in recovery rate indicated the Dawson site, regardless of year, had higher pendimethalin recovery throughout the 21-day sampling period (Figure 4). No difference in pendimethalin recovery was noted between standing and rolled cover crop treatments.

**Figure 4.** Average pendimethalin residue recovered through soil extraction process by year and location. Values fol‐ lowed by same letter in same sampling time are not significant at *α* = 0.05.

Within location and year, pendimethalin recovery was generally higher for 7-day samples than later sampling dates from expected rapid initial dissipation due to volatilization, photodegra‐ dation, microbial metabolism enhanced by warm soil temperatures and soil moisture, and chemical decomposition [21,27,33]. Increases in pendimethalin recovery amount were noted for winter fallow treatments in comparison to cover crop treatments for only the Dawson site in 2007 (Tables 2 and 3). Previous research has reported increased dissipation of preemergenceapplied herbicides in cover cropping systems compared to systems with no cover crop [21,34]. In our study, only one site had increased biomass yield for cover crop treatments in compari‐ son to fallow treatments (Figure 5); the limited differences between biomass residues in this study at the Dawson site could potentially mask any effect increased cover crop residue may have on herbicide movement to the soil; however, pendimethalin recovery was not greater for fallow treatments at the Headland site where biomass yields were higher in heavy-residue treatments.

**Figure 3.** Biomass yield in kg/ha for 2007 and 2008 for the Headland and Dawson experimental sites. Values followed

Analysis of soil extraction samples detected both pendimethalin and its metabolite, pendime‐ thalin alcohol, 4-[(1-ethylpropyl)amino]-2-methyl-3,5-dinitrobenyzl alcohol. The metabolite data are not presented in this study due to trace amounts detected uniformly throughout the samples (<0.05 µg/mL). Recovered pendimethalin is presented by location and year (Figure 4) due to differences detected between these main effects. The general trend in recovery rate indicated the Dawson site, regardless of year, had higher pendimethalin recovery throughout the 21-day sampling period (Figure 4). No difference in pendimethalin recovery was noted

**Figure 4.** Average pendimethalin residue recovered through soil extraction process by year and location. Values fol‐

by same letter in same sampling time are not significant at *α* = 0.05.

between standing and rolled cover crop treatments.

lowed by same letter in same sampling time are not significant at *α* = 0.05.

**3.2. HPLC analysis**

102 Herbicides, Agronomic Crops and Weed Biology

**(a) Fallow (b) Low**

**Figure 5. Percent pendimethalin recovered from Dawson during the 2007 growing season at three collection times during a 21‐day period after herbicide application. Figure 5.** Percent pendimethalin recovered from Dawson during the 2007 growing season at three collection times dur‐ ing a 21-day period after herbicide application.

Although no difference between pendimethalin recovery amounts under different cover treatments was indicated by the results, the amount of pendimethalin extracted from the soil, when viewed as percentages recovered (Figures 5–8), was never greater than 50% of total herbicide applied at the 7-day sampling date. Previous publications investigating pendime‐ thalin dissipation under varied environments have reported half-lives from 10 to 30 days or longer [21,33,36]. These low recovery percentages would suggest herbicide interception, to a degree, in all cover treatments. However, without a comparative pendimethalin dissipation rate under no residue with similar environmental conditions, it is difficult to determine between what proportion of unrecovered pendimethalin was intercepted and sorbed to plant residue and how much was lost through dissipation and degradation.

**(b) Medium (d) High**

**Figure 6. Percent pendimethalin recovered from Dawson during the 2008 growing season at three collection times during a 21‐day period after herbicide application. Figure 6.** Percent pendimethalin recovered from Dawson during the 2008 growing season at three collection times dur‐ ing a 21-day period after herbicide application.

**Figure 7. Percent pendimethalin recovered from Headland during the 2007 growing season at two collection times during a 21‐day period after herbicide application. Figure 7.** Percent pendimethalin recovered from Headland during the 2007 growing season at two collection times during a 21-day period after herbicide application.

### **3.3. Weed control**

Although no difference between pendimethalin recovery amounts under different cover treatments was indicated by the results, the amount of pendimethalin extracted from the soil, when viewed as percentages recovered (Figures 5–8), was never greater than 50% of total herbicide applied at the 7-day sampling date. Previous publications investigating pendime‐ thalin dissipation under varied environments have reported half-lives from 10 to 30 days or longer [21,33,36]. These low recovery percentages would suggest herbicide interception, to a degree, in all cover treatments. However, without a comparative pendimethalin dissipation rate under no residue with similar environmental conditions, it is difficult to determine between what proportion of unrecovered pendimethalin was intercepted and sorbed to plant

**(a) Fallow (b) Low**

**(b) Medium (d) High**

**three collection times during a 21‐day period after herbicide application. Figure 6.** Percent pendimethalin recovered from Dawson during the 2008 growing season at three collection times dur‐

ing a 21-day period after herbicide application.

**Figure 6. Percent pendimethalin recovered from Dawson during the 2008 growing season at**

residue and how much was lost through dissipation and degradation.

104 Herbicides, Agronomic Crops and Weed Biology

Dominant weed species at the Headland experiment site were nutsedge (*Cyperus* sp.) and smallflower morning glory [*Jaquemontia tamnifolia* (L.) Griseb.]. Weed species present at the Dawson site included Palmer amaranth (*Amaranthus palmeri* S. Watson) and smallflower morning glory. Weed analysis is presented by species at 21 and 45 days after planting (DAP) and averaged over the duration of the experiment due to no difference between years. Residue level was a significant main effect; however, cover crop termination method had no effect on weed control. No interactions were significant for either time period of weed ratings. At 21 DAP, control of smallflower morning glory in Headland was 90% or greater for all residue levels; however, medium- and high-residue treatments had slightly better control at 94%

**Figure 8. Percent pendimethalin recovered from Headland during the 2008 growing season at three collection times during a 21‐day period after herbicide application. Figure 8.** Percent pendimethalin recovered from Headland during the 2008 growing season at three collection times during a 21-day period after herbicide application.

(Table 4). Weed control 2 weeks later indicated suppression of smallflower morning glory by greater than 70% for all treatments, but all cover crop treatments had greater suppression regardless of residue level (Table 4). Nutsedge, like smallflower morning glory, was controlled by 90% or greater at 21 DAP in all residue treatments at Headland, but all cover crop treatments had slightly greater control than fallow treatments (Table 5). At 45 DAP, control of nutsedge was similar to that of smallflower morning glory in that suppression was greater than 70% for all treatments, but greatest weed control was achieved in medium- and high-residue treat‐ ments (Table 5).

At the Dawson site, Palmer amaranth control at 21 DAP was greater in all cover crop treatments compared to fallow treatments (Table 6). Control ratings 2 weeks later indicated greater control of this species by high-residue treatments only (Table 6). Smallflower morning glory followed

**Table 4.** Weed control in Headland of smallflower morning glory by residue treatment in comparison with fallow treatment 21 and 45 days after planting (DAP).

**Table 5.** Weed control in Headland of nutsedge by residue treatment in comparison with fallow treatment at 21 and 45 days after planting (DAP).

a similar trend for both the 21 and 45 DAP control ratings as Palmer amaranth. The first rating revealed greater suppression by all cover crop treatments and the subsequent control rating indicated higher suppression for medium- and high-level cover crop systems (Table 7).

**Table 6.** Weed control in Dawson of Palmer amaranth by residue treatment in comparison with fallow treatment at 21 and 45 days after planting (DAP).

(Table 4). Weed control 2 weeks later indicated suppression of smallflower morning glory by greater than 70% for all treatments, but all cover crop treatments had greater suppression regardless of residue level (Table 4). Nutsedge, like smallflower morning glory, was controlled by 90% or greater at 21 DAP in all residue treatments at Headland, but all cover crop treatments had slightly greater control than fallow treatments (Table 5). At 45 DAP, control of nutsedge was similar to that of smallflower morning glory in that suppression was greater than 70% for all treatments, but greatest weed control was achieved in medium- and high-residue treat‐

**three collection times during a 21‐day period after herbicide application. Figure 8.** Percent pendimethalin recovered from Headland during the 2008 growing season at three collection times

**(b) Medium (d) High**

**Figure 8. Percent pendimethalin recovered from Headland during the 2008 growing season at**

**(a) Fallow (b) Low**

At the Dawson site, Palmer amaranth control at 21 DAP was greater in all cover crop treatments compared to fallow treatments (Table 6). Control ratings 2 weeks later indicated greater control of this species by high-residue treatments only (Table 6). Smallflower morning glory followed

ments (Table 5).

during a 21-day period after herbicide application.

106 Herbicides, Agronomic Crops and Weed Biology

**Table 7.** Weed control in Dawson of smallflower morning glory by residue treatment in comparison with fallow treatment at 21 and 45 days after planting (DAP).

Previous research has suggested that the use of cover residue could potentially decrease the efficacy of preemergent herbicides and, subsequently, reduce crop yield under high-residue cover cropping systems [21,27]; while other researches have indicated that cover crops used in conjunction with PRE herbicide applications achieve similar weed control as peanut systems that utilize both PRE and POST herbicides [37]. The results of this experiment suggest that the use of cover crops, at any level of residue, can be viewed as a feasible alternative to fallow systems without increased herbicide sorption or reduced peanut yield. Moreover, the use of these cover crops when higher levels of residue are achieved may even offer greater weed suppression for a longer period of the growing season, providing producers with a costeffective means to combat weed infestations without an overdependence on early postemer‐ gent herbicide applications.

### **4. Sources of materials**

1 Great Plains No-Till drill, Great Plains Mfg., Inc., 1525 East North Street, Salina, KS 67401.

2 KMC ripper, Kelly Manufacturing Company, 80 Vernon Drive, Tifton, GA 31793.

3 Whatman cellulose filter paper, Whatman Inc., 800 Centennial Avenue, Piscataway, NJ 08854.

4 SAS software, version 9.1, 2002–2003, Statistical Analysis Systems Institute Inc. Cary, NC 27513.

### **Author details**

Jessica A. Kelton1\*, Andrew J. Price2 , Kip S. Balkcom2 , Wilson H. Faircloth3 and Lina Sarunaite4

\*Address all correspondence to<EMAIL_ADDRESS>
1 Crop, Soil, and Environmental Sciences, Auburn University, Auburn, Alabama, US

2 United States Department of Agriculture, Agricultural Research Service, National Soil Dynamics Laboratory, Auburn, Alabama, US

3 Syngenta, Leesburg, Georgia, US

4 Lithuanian Research Centre for Agriculture and Forestry, Lithuania

### **References**

[1] United States Department of Agriculture (USDA), National Agricultural Statistics Service. 2015. Website: http://www.nass.usda.gov/Statistics\_by\_Subject/result.php? A74ABF45-F909-3BBE-94CF- E3BBB9E8FD28&sector=CROPS&group=FIELD %20CROPS&comm=PEANUTS. Accessed 16 February, 2015.

[2] Jordan, D.L., J.S. Barnes, C.R. Bogle, G.C. Naderman, G.T. Roberson, and P.D. John‐ son. 2001. Peanut response to tillage and fertilization. Agronomy Journal 93: 1125– 1130.

cover cropping systems [21,27]; while other researches have indicated that cover crops used in conjunction with PRE herbicide applications achieve similar weed control as peanut systems that utilize both PRE and POST herbicides [37]. The results of this experiment suggest that the use of cover crops, at any level of residue, can be viewed as a feasible alternative to fallow systems without increased herbicide sorption or reduced peanut yield. Moreover, the use of these cover crops when higher levels of residue are achieved may even offer greater weed suppression for a longer period of the growing season, providing producers with a costeffective means to combat weed infestations without an overdependence on early postemer‐

Great Plains No-Till drill, Great Plains Mfg., Inc., 1525 East North Street, Salina, KS 67401.

Whatman cellulose filter paper, Whatman Inc., 800 Centennial Avenue, Piscataway, NJ 08854.

SAS software, version 9.1, 2002–2003, Statistical Analysis Systems Institute Inc. Cary, NC

, Kip S. Balkcom2

1 Crop, Soil, and Environmental Sciences, Auburn University, Auburn, Alabama, US

4 Lithuanian Research Centre for Agriculture and Forestry, Lithuania

2 United States Department of Agriculture, Agricultural Research Service, National Soil

[1] United States Department of Agriculture (USDA), National Agricultural Statistics Service. 2015. Website: http://www.nass.usda.gov/Statistics\_by\_Subject/result.php?

, Wilson H. Faircloth3

and

KMC ripper, Kelly Manufacturing Company, 80 Vernon Drive, Tifton, GA 31793.

gent herbicide applications.

108 Herbicides, Agronomic Crops and Weed Biology

**4. Sources of materials**

1

2

3

4

27513.

**Author details**

Lina Sarunaite4

**References**

Jessica A. Kelton1\*, Andrew J. Price2

3 Syngenta, Leesburg, Georgia, US

\*Address all correspondence to<EMAIL_ADDRESS>
Dynamics Laboratory, Auburn, Alabama, US

assess the benefits and challenges of glyphosate- resistant cropping systems for weed management in U.S. corn, cotton, and soybean. Weed Technology. 23: 134–149.

[26] Grey, T.L., T.M. Webster, and A.S. Culpepper. 2008. Weed control as affected by pen‐ dimethalin timing and application method in conservation tillage cotton (*Gossypium hirsutum* L.). Journal of Cotton Science 12: 318– 324.

[13] Hall, J.C., L.L. Van Eerd, S.D. Miller, M.D.K. Owen, T.S. Prather, D.L. Shaner, M. Singh, K.C. Vaughn, and S.C. Weller. 2000. Future research directions for Weed Sci‐

[14] Schwab, E.B., D.W. Reeves, C.H. Burmester, and R.L. Raper. 2002. Conservation till‐ age systems for cotton in the Tennessee Valley. Soil Science Society of America Jour‐

[15] Price, A.J., M.E. Stoll, J.S. Bergtold, F.J. Arriaga, K.S. Balkcom, T.S. Kornecki, and R.L. Raper. 2008. Effect of cover crop extracts on cotton and radish radicle elongation.

[16] Veenstra, J.J., W.R. Horwath, and J.P. Mitchell. 2007. Tillage and cover cropping ef‐ fects on aggregate-protected carbon in cotton and tomato. Soil Science Society of

[17] Williams, E.J., S. Wilton, M.C. Lamb, and J.I. Davidson. 1998. Effects of selected prac‐ tices for reduced tillage peanut yield, disease, grade, and net revenue. Proceedings of

[18] Monfort, W.S., A.K. Culbreath, K.L. Stevenson, T.B. Brenneman, D.W. Gorbet, and S.C. Phatak. 2004. Effects of reduced tillage, resistant cultivars, and reduced fungi‐ cide inputs on progress of early leaf spot of peanut (*Arachis hypogaea*). Plant Disease

[19] Rowland, D.L., W.H. Faircloth, and C.L. Butts. 2007. Effects of irrigation method and tillage regime on peanut (*Arachis hypogaea* L.) reproductive processes. Peanut Science

[20] Teasdale, J.R., D.R. Shelton, A.M. Sadeghi, and A.R. Isensee. 2003. Influence of hairy vetch residue on atrazine and metolachlor soil solution concentration and weed

[21] Locke, M.A., R.M. Zablotowicz, P.J. Bauer, R.W. Steinriede, and L.A. Gaston. 2005. Conservation cotton production in the southern United States: herbicide dissipation

[22] Blackshaw, R.E. and L.J. Molnar. 2008. Integration of conservation tillage and herbi‐ cides for sustainable dry bean production. Weed Technology 22: 168–176.

[23] Grey, T.L., and G.R. Wehtje. 2005. Residual herbicide weed control systems in pea‐

[24] Lègére, A. and N. Samson. 2004. Tillage and weed management effects on weeds in

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barley-red clover cropping systems. Weed Science 52: 881–885.

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110 Herbicides, Agronomic Crops and Weed Biology

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## **Herbicide Use and Increased Scourge of** *Parthenium hysterophorus* **in Vegetable Production in Trinidad and Tobago**

Puran Bridgemohan, Wendy-Ann P. Isaac, Raymond Macoon and Cherrianne Johny

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/61732

### **Abstract**

This chapter highlights a survey of vegetable-producing areas to determine the occur‐ rence, distribution and importance of *Parthenium hysterophorus* in Trinidad. The weed can significantly reduce crop yields and quality due to its aggressive growth habit, competi‐ tiveness and allelopathic interference. Due to its invasive capacity and allelopathic prop‐ erties, *Parthenium hysterophorus* has the potential to disrupt the natural ecosystem and threaten the biodiversity. It is a difficult weed to manage, and a wide variety of methods, starting with prevention and containment, is necessary to reduce the incidence and spread of this weed. An integrated approach using cultural, physical, chemical and bio‐ logical techniques is necessary to be successful. Focus is made on specific herbicides cur‐ rently being used to manage this weed in vegetables. Despite the negative impact of this weed on the biodiversity, this chapter also explores the potential of the beneficial proper‐ ties of *Parthenium hysterophorous* as a mechanism of management.

**Keywords:** Vegetable production, *Parthenium hysterophorus*, herbicide use, integrated ap‐ proach

### **1. Introduction**

*Parthenium hysterophorus* L., commonly called barley flower [1] and white-head or white-top [2] in the Caribbean, is considered a noxious weed. The plant exhibits wide ecological ampli‐ tude, and invades and competes with all types of crops, especially vegetables, with substantial losses in yield [3]. The weed has become problematic in early orchard establishment, and

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ornamental and greenhouse production, and also invades industrial areas including airport lay-bys.

The weed displays characteristics of profuse seeding ability, photo and thermal insensitivity, non-dormancy, high germination and growth rate and low photorespiratory rate, enormous seed bank, rapid spread and colonization and extreme adaptability in a range of habitats [4] and has spread within the last two decades to all Commonwealth Caribbean countries [2]. It is among the top ten worst weeds of the world and has been listed in the global invasive species [5]. It is now considered one of the worst weeds because of its invasiveness, potential for rapid spread, economic and environmental impacts, its high adaptability to almost any type of environmental conditions and high losses in crop yield and its direct contact with plant or plant parts [5]. As a C3 weed, *Parthenium* uses one of the two types of photosynthetic pathways, which responds to higher levels of CO2 [6]. This enables it to grow more rapidly and become more competitive through increased leaf size, seed size and production, plant toxicity and pollen production [6].

The weed is predominant in the major vegetable-growing areas of Trinidad and has been shown to be effectively controlled by dinitroanilines, e.g. butralin (4- (1, 1-Dimethylethyl)-N- (1-methylpropyl)-2, 6-dinitro-benzenamine) in eggplant (*Solanum melongena* L.), and by the amide herbicide, diphenamid (N, N-Dimethyl-2, 2-diphenyl-acetamide) in cabbage (*Brassica oleracea* var*. capitata* L.) [7]. In pot studies, glufosinate ammonium was shown to give good levels of control [6, 68]. The weed has shown resistance to bipyridylium herbicides in Trinidad and other Caribbean territories and has become dominant on lands where these chemicals are used intensively [2; 6]. The plant has the ability to survive carbohydrate depletion approach to control with rapid regrowth soon after mechanical control [7, 8, 9].

*P. hysterophorous* is deemed a noxious weed in Australia [10] and India [3], where it causes severe skin allergies [11], fever and asthma, and often death among the population [12]. Although no cases of allergies or death have been reported in Trinidad [7], many farmers have, however, reported increased asthma attacks.

In the major vegetable production areas of Trinidad and Tobago, the weed was identified as early as 1956. However, it was not of any significance until the 1960s when the use of paraquat (1, 1'-dimethyl-4-4'-bipyridinium ion) and diquat (6, 7-dihydrodipyrido (1, 2- a: 2, 1-c) pyrazinedium ion) became widespread.

### **2. Biology and ecology**

The genus *Parthenium* comprises 15 species, all of which are native to North and South America. *P. hysterophorus* L. has a native range in the neo-tropics from Mexico to Argentina. It is thought that the species originated in the region surrounding the Gulf of Mexico or in central South America, but is now widespread in North and South America and throughout the entire Caribbean [6].

*P. hysterophorus* L. (family *Asteraceae*) is an aggressive and noxious annual herbaceous weed that has spread from tropical America to various tropical and subtropical parts of the world. It is included in the International Union for Conservation of Nature (IUCN) Global Invasive Species database and is rated one of the most serious weeds of the 20th century. This may be attributed mainly due to its vigorous growth and high fecundity in habitats varying from hot and arid, semi-arid to humid and from low- to middle- to high-altitude regions.

ornamental and greenhouse production, and also invades industrial areas including airport

The weed displays characteristics of profuse seeding ability, photo and thermal insensitivity, non-dormancy, high germination and growth rate and low photorespiratory rate, enormous seed bank, rapid spread and colonization and extreme adaptability in a range of habitats [4] and has spread within the last two decades to all Commonwealth Caribbean countries [2]. It is among the top ten worst weeds of the world and has been listed in the global invasive species [5]. It is now considered one of the worst weeds because of its invasiveness, potential for rapid spread, economic and environmental impacts, its high adaptability to almost any type of environmental conditions and high losses in crop yield and its direct contact with plant or plant parts [5]. As a C3 weed, *Parthenium* uses one of the two types of photosynthetic pathways, which responds to higher levels of CO2 [6]. This enables it to grow more rapidly and become more competitive through increased leaf size, seed size and production, plant toxicity and

The weed is predominant in the major vegetable-growing areas of Trinidad and has been shown to be effectively controlled by dinitroanilines, e.g. butralin (4- (1, 1-Dimethylethyl)-N- (1-methylpropyl)-2, 6-dinitro-benzenamine) in eggplant (*Solanum melongena* L.), and by the amide herbicide, diphenamid (N, N-Dimethyl-2, 2-diphenyl-acetamide) in cabbage (*Brassica oleracea* var*. capitata* L.) [7]. In pot studies, glufosinate ammonium was shown to give good levels of control [6, 68]. The weed has shown resistance to bipyridylium herbicides in Trinidad and other Caribbean territories and has become dominant on lands where these chemicals are used intensively [2; 6]. The plant has the ability to survive carbohydrate depletion approach

*P. hysterophorous* is deemed a noxious weed in Australia [10] and India [3], where it causes severe skin allergies [11], fever and asthma, and often death among the population [12]. Although no cases of allergies or death have been reported in Trinidad [7], many farmers have,

In the major vegetable production areas of Trinidad and Tobago, the weed was identified as early as 1956. However, it was not of any significance until the 1960s when the use of paraquat (1, 1'-dimethyl-4-4'-bipyridinium ion) and diquat (6, 7-dihydrodipyrido (1, 2- a: 2, 1-c)

The genus *Parthenium* comprises 15 species, all of which are native to North and South America. *P. hysterophorus* L. has a native range in the neo-tropics from Mexico to Argentina. It is thought that the species originated in the region surrounding the Gulf of Mexico or in central South America, but is now widespread in North and South America and throughout the entire

to control with rapid regrowth soon after mechanical control [7, 8, 9].

however, reported increased asthma attacks.

pyrazinedium ion) became widespread.

**2. Biology and ecology**

Caribbean [6].

lay-bys.

114 Herbicides, Agronomic Crops and Weed Biology

pollen production [6].

*P. hysterophorus* is an annual herb with a tendency to be perennial, growing erect up to 2 m in height. It has a deeply penetrating root system with a stem that is branched and covered with hairy structures or trichomes, bearing dissected pale green leaves that are lobed and hairy. Leaves vary from 6 to 55 per plant and are irregularly dissected and bipinnate, having small hairs on both sides. Trichomes are considered storehouses for one of the toxic chemicals found in the weed known as parthenin [14].

Flower heads are creamy white, about 4 mm across, arising from the leaf fork and forming a capitula. Flowering usually occurs one month after germination with each flower containing five seeds, which are small (2 mm), wedge-shaped, brown to black in colour and bear two thin white scales. Pollen grains are produced in clusters and are pollinated by wind. A single plant can produce around 15,000 seeds or even up to 100,000 seeds. Seeds are mainly dispersed through water currents, animals and the movement of vehicles, machinery, livestock and stock feed, and to a lesser extent by wind. Seeds can remain viable for long periods and are capable of germinating as long as moisture is available [10].

The ideal conditions for growth are high moisture content, high humidity and a temperature of around 25°C. However, it can grow under a wide range of environmental conditions with soil moisture being the only limiting factor for germination and growth. It can grow under a wide range of soil pH (2.5 to 10.0) [15]. Additionally, it grows well in areas where annual rainfall is higher than 500 mm. In Trinidad, this weed grows on abandoned lands, along highways and roadsides, in drains, gardens, plantations and vegetable crop plots. It colonizes disturbed sites very aggressively, possesses allelopathic properties and has no documented natural enemies like insects or diseases.

### **3. Phytochemical analysis of** *P. hysterophorus*

Phytochemical analysis of *P. hysterophorus* has revealed that plant parts such as leaves, trichomes, inflorescence and pollens contain toxins such as sesquiterpene lactones (SQL), kaempferol, p-coumaric acid and caffeic acid [16; 17]. These phytochemicals are highly concentrated in the leaves. The SQLs, namely parthenin and coronopilin as well as hymenin and ambrosin, are present in the trichomes of the leaves and stems and are responsible for causing various allergies such as dermatitis, hay fever, asthma and bronchitis. It is also responsible for the inhibition of pasture germination and growth. The allelopathic effect is due to allelochemicals such as phenolic acids and SQLs [18; 19]. Other phytotoxic compounds or allelochemcials are hysterin, flavonoids, such as quercelagetin 3,7-dimethylether, 6-hydroxyl kaempferol 3-0 arabinoglucoside, fumaric acid, p-hydroxy benzoin and vanillic acid, anisic acid, p-anisic acid, chlorogenic acid, ferulic acid, sitosterol and other alcohols [17; 20].

### **4. Incidence of** *P. hysterophorus* **in vegetable crops**

Weed surveys in the main vegetable production areas were conducted in both dry and wet season using seven quantitative measures [21–24] *viz.* visual estimates (VE), abundance (Ap), density (Dp), percentage frequency (Fp), relative dominance (RDi), relative density (RDp) and relative frequency (RFp), which were used to compute the Importance Value Index (IVI) of *P. hysterophorus*.

$$\text{IVI} = \text{RDi} + \text{RDp} + \text{RFp}$$

The IVI allowed for comparisons between seasons and years and among crops. However, it does not necessarily represent losses in crop production caused by the weed as crops vary in their competitive ability. The level of losses due to the presence of the weed in various vegetable crops was assessed and the economic importance of the weed determined. Irrespective of the visual estimate (VE) of *P. hysterophorus* infestations in the wet season (Table 1) and dry season (Table 2), the frequency (Fp) in both seasons was greater than 50%.

2 hand weedings and no herbicide1 ; 1 hand weeding and 1 herbicide application2 ; 2 hand weedings and 1 herbicide application3 ; 3 hand weedings and no herbicides4 ; 2 hand weedings and no herbicide5 ; 2 hand weedings6 ; 1 hand weed‐ ing7 . (VE – visual estimate; Fp – frequency; IVI – Importance Value Index)

**Table 1.** Incidence of *P. hysterophorus* in various vegetables during the wet seasons.

Herbicide Use and Increased Scourge of *Parthenium hysterophorus* in Vegetable Production in Trinidad and Tobago http://dx.doi.org/10.5772/61732 117

**Table 2.** Incidence of *P. hysterophorus* in various vegetables during the dry seasons.

kaempferol 3-0 arabinoglucoside, fumaric acid, p-hydroxy benzoin and vanillic acid, anisic

Weed surveys in the main vegetable production areas were conducted in both dry and wet season using seven quantitative measures [21–24] *viz.* visual estimates (VE), abundance (Ap), density (Dp), percentage frequency (Fp), relative dominance (RDi), relative density (RDp) and relative frequency (RFp), which were used to compute the Importance Value Index (IVI) of *P.*

IVI = RDi + RDp + RFp

The IVI allowed for comparisons between seasons and years and among crops. However, it does not necessarily represent losses in crop production caused by the weed as crops vary in their competitive ability. The level of losses due to the presence of the weed in various vegetable crops was assessed and the economic importance of the weed determined. Irrespective of the visual estimate (VE) of *P. hysterophorus* infestations in the wet season (Table 1) and dry season

**Crop VE Fp IVI**

; 1 hand weeding and 1 herbicide application2

; 2 hand weedings and no herbicide5

; 2 hand weedings and 1 herbicide

; 1 hand weed‐

; 2 hand weedings6

Cauliflower1 50 90 417.1 Cauliflower2 10 70 262.5 Tomato3 25 100 274.1 Tomato4 50 90 430.0 Tomato5 75 100 562.5 Cabbage6 40 100 379.9 Cabbage7 50 100 974.7 Patchoi 40 100 382.2 Sweet Pepper 25 50 265.4 Hot Pepper 25 50 273.5 Spinach 30 90 358.0 Okra 100 100 880.0 Fallow Field 100 100 910.0 Mean 48 87.5 489.9 S.E. (+/−) 7.85 5.2 72.17

acid, p-anisic acid, chlorogenic acid, ferulic acid, sitosterol and other alcohols [17; 20].

**4. Incidence of** *P. hysterophorus* **in vegetable crops**

(Table 2), the frequency (Fp) in both seasons was greater than 50%.

*hysterophorus*.

116 Herbicides, Agronomic Crops and Weed Biology

2 hand weedings and no herbicide1

; 3 hand weedings and no herbicides4

. (VE – visual estimate; Fp – frequency; IVI – Importance Value Index)

**Table 1.** Incidence of *P. hysterophorus* in various vegetables during the wet seasons.

application3

ing7

There was no significant difference in the mean Importance Value Index (IVI) of *P. hystero‐ phorus* for the wet (489.9) and dry (443.4) seasons. Also, variations between seasons were minimal under c = similar levels of weed management; cabbage in the wet season had an IVI of 379.9 and in the dry season 360.0; cauliflower 262.5 (wet) and 215.8 (dry) and spinach 358.0 (wet) and 365.6 (dry).

In the wet season (Table 1), there were variations within the same crops due to different levels of weed management, e.g. cauliflower with two hand weedings and no herbicides had a higher IVI (417.1) than a crop of similar age with treatments of one hand weeding and pre-emergence herbicide (262.5); similar trends for tomato and cabbage were observed at the same growth stage, but under different levels of weed management. The application of pre-emergence herbicides reduced the IVI for *P. hysterophorus* by 40 to 50% over the treatment of two hand weedings and no pre-emergent herbicide.

Crops with shrub-type architecture, e.g. hot and sweet peppers, had no competitive plant height advantage over leafy vegetable crops under similar levels of weed management. Both types of crops had an IVI below the mean value recorded for the wet season.

In both the wet and dry seasons, the IVI of leafy vegetable crops was lower than the mean IVI. This is due mainly to the close spacing used at planting and the intensity and thoroughness of the hand-weeding operations practised by the farmers.

A field prepared for planting, but subsequently abandoned, showed an IVI of 910.0 (wet season) and gave an indication of the weed's dominance. The high IVI (880.0) for okra in the wet season was due to the wide spacing as well as the absence of any weed management operations. The *P. hysterophorus* seedlings were the same height as the crop (15–20 cm).

In the fields surveyed, adequate irrigation facilities were available to all farmers during the dry season. Adequate water supply was the main factor determining the lack of shift in *Parthenium* populations between seasons.

### **4.1. Incidence of** *P. hysterophorus* **during different seasons**

There was no significant difference between visual estimates (VE) for *Parthenium* in the wet and dry seasons in the Aranguez district (Table 3) or for the major vegetable-growing areas of Trinidad (Table 4). Visual estimates in the range of 25 to 60% can be considered as moderate infestations [23].

There were no changes in abundance (Ap) between seasons. *Cyperus rotundus* (L.) #CYPRO, 'the world's worst weed' [22], is a serious weed in vegetable crops in India with an abundance of 2.7–9.6 [23]. The Ap for *P. hysterophorus* fell well within this range in both seasons.

Wet season density (Dp) in Aranguez (5.24) did not differ significantly from that of other vegetable-growing areas (5.6). The Dp for *Parthenium* emphasizes predominance of this weed in both seasons. Frequency (Fp) was over 80% in both seasons. Weeds occurring in the frequency levels 75–100 are serious weeds that require some level of control [23].

The IVI indicated that there were no shifts in the *P. hysterophorus* population between seasons (Table 3). Also, there was no significant difference between IVIs for wet season in the major vegetable-growing areas of Trinidad (Table 4). These findings indicate that *P. hysterophorus* is a serious problem in all the major vegetable-growing areas in Trinidad, especially where the IVI is even greater for the dry season.

### **5. Crop loss assessment**

*Parthenium* has caused significant losses to the vegetable production in both seasons in almost all Caribbean islands. Most farmers reported that the weed had no effect on the yield of solanaceous crops, if it was effectively controlled while the crop was in the early vegetative stage or prior to flower initiation. However, if weed control was poor, they observed yield reductions of 25 to 30% for the wet season and 20 to 25% for the dry season.

Farmers found that the presence of the weed within or around the field can result in a reduction of the market yield of cabbage and cauliflower. It was observed that damage to marketable curds of cauliflower caused by the larvae of *Plutella xylostella* (L.) (Lepidoptera: Yponomenti‐ dae) varied between 75 and 100%. Apparently, the adult pest found *P. hysterophorus* to be a suitable 'resting site'. On nursery beds, failure to remove *P. hysterophorus* seedlings at 3- to 5 day intervals on a regular schedule resulted in a 75 to 100% loss of healthy and vigorous vegetable transplants.

Herbicide Use and Increased Scourge of *Parthenium hysterophorus* in Vegetable Production in Trinidad and Tobago http://dx.doi.org/10.5772/61732 119

(VE – visual estimate; Ap – abundance; Dp – density; Fp – frequency; RDi – relative dominance; RDp – relative density; F4RFp – relative frequency; IVI – Importance Value Index)

**Table 3.** Incidence of *P. hysterophorous* during wet and dry seasons for Aranguez, Trinidad.

**4.1. Incidence of** *P. hysterophorus* **during different seasons**

infestations [23].

118 Herbicides, Agronomic Crops and Weed Biology

IVI is even greater for the dry season.

**5. Crop loss assessment**

vegetable transplants.

**Parameter**

There was no significant difference between visual estimates (VE) for *Parthenium* in the wet and dry seasons in the Aranguez district (Table 3) or for the major vegetable-growing areas of Trinidad (Table 4). Visual estimates in the range of 25 to 60% can be considered as moderate

There were no changes in abundance (Ap) between seasons. *Cyperus rotundus* (L.) #CYPRO, 'the world's worst weed' [22], is a serious weed in vegetable crops in India with an abundance

Wet season density (Dp) in Aranguez (5.24) did not differ significantly from that of other vegetable-growing areas (5.6). The Dp for *Parthenium* emphasizes predominance of this weed in both seasons. Frequency (Fp) was over 80% in both seasons. Weeds occurring in the

The IVI indicated that there were no shifts in the *P. hysterophorus* population between seasons (Table 3). Also, there was no significant difference between IVIs for wet season in the major vegetable-growing areas of Trinidad (Table 4). These findings indicate that *P. hysterophorus* is a serious problem in all the major vegetable-growing areas in Trinidad, especially where the

*Parthenium* has caused significant losses to the vegetable production in both seasons in almost all Caribbean islands. Most farmers reported that the weed had no effect on the yield of solanaceous crops, if it was effectively controlled while the crop was in the early vegetative stage or prior to flower initiation. However, if weed control was poor, they observed yield

Farmers found that the presence of the weed within or around the field can result in a reduction of the market yield of cabbage and cauliflower. It was observed that damage to marketable curds of cauliflower caused by the larvae of *Plutella xylostella* (L.) (Lepidoptera: Yponomenti‐ dae) varied between 75 and 100%. Apparently, the adult pest found *P. hysterophorus* to be a suitable 'resting site'. On nursery beds, failure to remove *P. hysterophorus* seedlings at 3- to 5 day intervals on a regular schedule resulted in a 75 to 100% loss of healthy and vigorous

> VE 47.69 36.66 Ap 5.77 5.25

**Season Wet (October–November) Dry (February–April)**

reductions of 25 to 30% for the wet season and 20 to 25% for the dry season.

of 2.7–9.6 [23]. The Ap for *P. hysterophorus* fell well within this range in both seasons.

frequency levels 75–100 are serious weeds that require some level of control [23].

(VE – visual estimate; Ap – abundance; Dp – density; Fp – frequency; RDi – relative dominance; RDp – relative density; F4RFp – relative frequency; IVI – Importance Value Index)

**Table 4.** Incidence of *P. hysterophorous* during wet and dry seasons for the major vegetable-growing areas of Trinidad

### **6. Competitive effect of** *Parthenium* **on selected crops**

A high density of *P. hysterophorus* resulted in the total loss of one tomato crop (cv. Calypso), where failure to remove the weed before flower initiation stage or weed had a V.E. of 100% and IVI *>* 800. *P. hysterophorus* was the only weed present in the field at the time of the survey and was 75 to 100 cm tall and flowering profusely. The farmer had applied paraquat at the pre-plant stage of the crop.

Failure to plant lettuce and celery on *weed*-free plots can result in a 50 to 60% mortality of the transplants. When early hand weeding at 10- to 14-day intervals was not done, mortality in excess of 75% was observed.

No significant reduction in yield was reported by farmers for vining crops, e.g. pumpkin, squash, or cucumber and staked bodibean which withstood the weed competition. However, early hand weeding was essential for bush-type cowpea bodi to prevent yield reductions by 25 to 50%.

Studies conducted on soil amended with unburnt and burnt residues of *P. hysterophorous* revealed phytotoxic effects on test crops, which was attributed to the presence of phenolics [17]. Parthenin has also been reported as a germination and radicle growth inhibitor in several plant varieties and it enters the soil through decomposing leaf litter [17; 19].

The reduction in crop yield and quality is probably due to the competitive ability and allelopath‐ ic potential of *Parthenium*. It is noted that although the weed is a C3 plant, low carbon dioxide compensation concentration and photorespiratory rate were observed [24]. This was attribut‐ ed to the activity of PEP carboxylase. The weed is described as having a lush growth and a high survival potential. It has been reported that *P. hysterophorous* produced allelopathic com‐ pounds that influenced pollen germination and tube growth in solanaceous and bean crops, where yield reductions of 27 to 73% were observed [25; 26].

### **7. Weed economic assessment**

An economic analysis was performed on *P. hysterophorous* involving a cost–benefit analysis, where several variables were inputted onto a toolkit developed by Landcare Research, New Zealand [27]. The toolkit was developed in an attempt to assign monetary values, where possible, to specific variables in order to conduct cost–benefit analyses on different management options for the control of the weed using four management options *viz.* 'Do Nothing' (DN), 'Current Management' (CM), 'Integrated Management Approach' (IMA) and 'Exploitation of Benefits' (EB). The outcome of the toolkit ranked the management options in terms of Net Present Value (NPV), Benefit-Cost Ratio (BCR) and Cost-Effectiveness (CE). The analysis was done on four proposed management options in order to determine the best suitable one for the control of this invasive weed (Table 5).

Over time, the DN option had the most rapid increase in population, followed by the EB and then by CM. The IMA displayed the slowest increase in the invasive population during that time.

Quantifying the benefits for each management option proposed for the control of *P. hystero‐ phorous* (white-top) took into consideration the value per unit for several categories for benefits and costs of each management option. Benefits are described as the monetary or non-monetary gain received because of an action taken or a decision made. The benefits included agricultural and research crops, human health and biodiversity. The human health variable accounts for visits to the doctor for conditions related to the effect of *Parthenium* such as skin inflammation, eczema, asthma, allergic rhinitis, allergic bronchitis and burning and blistering of the eyes (Table 6).

**Table 5.** Description of the proposed management options for the control of *Parthenium hysterophorus*.

Failure to plant lettuce and celery on *weed*-free plots can result in a 50 to 60% mortality of the transplants. When early hand weeding at 10- to 14-day intervals was not done, mortality in

No significant reduction in yield was reported by farmers for vining crops, e.g. pumpkin, squash, or cucumber and staked bodibean which withstood the weed competition. However, early hand weeding was essential for bush-type cowpea bodi to prevent yield reductions by 25 to 50%. Studies conducted on soil amended with unburnt and burnt residues of *P. hysterophorous* revealed phytotoxic effects on test crops, which was attributed to the presence of phenolics [17]. Parthenin has also been reported as a germination and radicle growth inhibitor in several plant

The reduction in crop yield and quality is probably due to the competitive ability and allelopath‐ ic potential of *Parthenium*. It is noted that although the weed is a C3 plant, low carbon dioxide compensation concentration and photorespiratory rate were observed [24]. This was attribut‐ ed to the activity of PEP carboxylase. The weed is described as having a lush growth and a high survival potential. It has been reported that *P. hysterophorous* produced allelopathic com‐ pounds that influenced pollen germination and tube growth in solanaceous and bean crops,

An economic analysis was performed on *P. hysterophorous* involving a cost–benefit analysis, where several variables were inputted onto a toolkit developed by Landcare Research, New Zealand [27]. The toolkit was developed in an attempt to assign monetary values, where possible, to specific variables in order to conduct cost–benefit analyses on different management options for the control of the weed using four management options *viz.* 'Do Nothing' (DN), 'Current Management' (CM), 'Integrated Management Approach' (IMA) and 'Exploitation of Benefits' (EB). The outcome of the toolkit ranked the management options in terms of Net Present Value (NPV), Benefit-Cost Ratio (BCR) and Cost-Effectiveness (CE). The analysis was done on four proposed management options in order to determine the best suitable one for the control of this

Over time, the DN option had the most rapid increase in population, followed by the EB and then by CM. The IMA displayed the slowest increase in the invasive population during that

Quantifying the benefits for each management option proposed for the control of *P. hystero‐ phorous* (white-top) took into consideration the value per unit for several categories for benefits and costs of each management option. Benefits are described as the monetary or non-monetary gain received because of an action taken or a decision made. The benefits included agricultural and research crops, human health and biodiversity. The human health variable accounts for visits to the doctor for conditions related to the effect of *Parthenium* such as skin inflammation, eczema, asthma, allergic rhinitis, allergic bronchitis and burning and blistering of the eyes

varieties and it enters the soil through decomposing leaf litter [17; 19].

where yield reductions of 27 to 73% were observed [25; 26].

**7. Weed economic assessment**

invasive weed (Table 5).

time.

(Table 6).

excess of 75% was observed.

120 Herbicides, Agronomic Crops and Weed Biology

**Figure 1.** The trend of the invasive population for each management option.

The costs associated were different for each management option and included labour and capital costs (tool, safety gear and machinery). Herbicide cost included the purchase of chemicals, based on market prices, and machine service cost included the servicing of the whacker on a per-service basis (Table 6).

The Net Present Value (NPV) represents the overall net benefit of a project to society. The Benefit Cost Ratio (BCR) is the ratio of the NPV of benefits associated with an activity, relative to the NPV of the costs of the same activity. The discounted future costs and benefits to present value used a discount rate of 5% and the project length is assumed to be 10 years. Cost-effective (CE) analysis is an approach often used to rank intervention options when monetary benefits cannot be derived from key categories in a given project. CE is the NPV of the monetized costs of the intervention divided by the effectiveness of the project option measured in physical units. The smaller the CE ratio, the greater is the cost-effectiveness of an intervention.

**Table 6.** Costs and benefits for each management option.

**Figure 2.** Percentage of Waterloo Research Centre (WRC) staff affected by the impact of *Parthenium* (white-top).

The Net Present Value (NPV) represents the overall net benefit of a project to society. The Benefit Cost Ratio (BCR) is the ratio of the NPV of benefits associated with an activity, relative to the NPV of the costs of the same activity. The discounted future costs and benefits to present value used a discount rate of 5% and the project length is assumed to be 10 years. Cost-effective (CE) analysis is an approach Herbicide Use and Increased Scourge of *Parthenium hysterophorus* in Vegetable Production in Trinidad and Tobago http://dx.doi.org/10.5772/61732 123

The costs associated were different for each management option and included labour and capital costs (tool, safety gear and machinery). Herbicide cost included the purchase of chemicals, based on market prices, and machine service cost included the servicing of the

often used to rank intervention options when monetary benefits cannot be derived from key categories in a given project. CE is the NPV of the monetized costs of the intervention divided by the effectiveness of the project option measured in physical units. The smaller the

**Figure 3.** Net Present Value for the management options for the control of *Parthenium*.

Figure 3: Net Present Value for the management options for the control of *Parthenium*.

whacker on a per-service basis (Table 6).

CE ratio, the greater is the cost-effectiveness of an intervention.

(CE) analysis is an approach often used to rank intervention options when monetary benefits cannot be derived from key categories in a given project. CE is the NPV of the monetized costs of the intervention divided by the effectiveness of the project option measured in physical

**Units For Initial Period**

**Integrated Mgmt Approach**

**Exploitation of Benefits**

**Current Management**

units. The smaller the CE ratio, the greater is the cost-effectiveness of an intervention.

**Unit Value (\$/units)**

**Do Nothing**

Agricultural Crops \$/kg 10.00 335 335 335 335 Research Crops \$/kg 25 8,087 8,087 8,087 8,087 Human Health \$/report 200 24 24 24 24 Biodiversity \$/m3 50 5,280 5,280 5,280 5,280

Labour \$/day 200 0 36 72 270 Initial Capital Cost \$/unit 1 0 1,775 8,670 9,000 Herbicides \$/litre 20 0 16 16 0 Machine Service \$/service 200 0 0 3 0 Research \$/hour 30 0 0 0 600

**Figure 2.** Percentage of Waterloo Research Centre (WRC) staff affected by the impact of *Parthenium* (white-top).

**Category Units**

122 Herbicides, Agronomic Crops and Weed Biology

**Table 6.** Costs and benefits for each management option.

**Benefits**

**Costs**

**Table 7.** Summary of the Net Present Value, Cost Benefit Ratio and Cost-Effectiveness rankings for the four management options for the control of *Parthenium*.

The cost–benefit analysis for the four different management options disclosed that the CM option yielded the greatest benefit for each dollar of costs and thus was most efficient on funds (Figure 3). The CM option also ranked first in cost-effectiveness being the option with the least cost per physical unit of benefit (Table 6 and 7). The 'Integrated Management Approach' (IMA) ranked first in NPV. Therefore, this option yielded the most benefit to society in terms of managing the spread of *P. hysterophorous*, without considering the costs associated. Both approaches appear to be better than the DN option. The EB option, however, proved to require the largest investment, to yield the least benefits per dollar spent and be the least cost-effective management option compared to the other options.

### **8. Management of** *Parthenium hysterophorus*

Because of its negative impact on the natural and agroecosystem, it is necessary to manage *P. hysterophorus* before it sets seed and continues to spread. There are several methods docu‐ mented for managing this weed. These include preventative, mechanical, cultural, chemical and biological control methods and even includes potential management by proper utilization of the positive attributes of *P. hysterophorus*. However, effective management of *P. hysteropho‐ rus* requires an integrated approach. The following outlines some of the successful and potential best management practices used throughout the Caribbean and the rest of the world.

### **8.1. Prevention and containment**

The best methods of weed management is prevention and containment. *P. hysterophorus* usually completes its life cycle in 4 weeks; so, it is important to manage the weed before the plant flowers or sets seed and when infestations are small – do not allow the weed to be established. The seeds of *P. hysterophorus* can be spread through flowing water or can be blown by the wind, which further makes prevention of spread difficult. The seed can also stay for years in the soil seed bank and the continuous removal of the weed is required until the seed bank is depleted.

Difficulties in the preventive method could be further exacerbated through the easy spread of seeds through vehicles, machinery, the trading and transport of goods, animals grazing on infested fields and the transportation of sand, soil and compost from infested areas to unin‐ fested areas. These are potential risks for further spread and hence should be controlled through an adoption of quarantine measures involving the adoption of inspection and washdown procedures.

### **8.2. Mechanical control**

Manual removal of *P. hysterophorus* by hand weeding before flowering and seed setting is the most effective method, but it is not necessarily practical or economical particularly where there are large infestations. This method, however, may pose a health hazard from allergic reactions and a danger that mature seeds will drop and increase the area of infestation.

Other mechanical treatments, such as grading, mowing, slashing and ploughing, are also considered inappropriate since they may also promote seed spread as well as rapid regener‐ ation from lateral shoots close to the ground [28; 29]. Ploughing the weed before the plants reach the flowering stage may be effective. Although burning is not promoted as a control strategy, it has been used to control the first flush of emergent weeds at the beginning of the rains in Australia but is only considered a short-term control measure [30]. Burning has been shown to create open niches in the landscape, into which larger number of *Parthenium* seeds are able to germinate in the absence of vegetation.

### **8.3. Cultural control**

This is considered one of the most cost-effective methods, but it is practical only on small farms or where it is part of an integrated weed management strategy. Farmers have used almost every conceivable practice to reduce the infestation on their holding such as hand weeding, brush cutting and even digging out the weed. In all cases, there is a rapid regrowth from both stumps or re-emergence from the existing seed banks.

Mulching using plant stubble is often used for general weed control, but this is on a limited scale. However, this has not proven to be effective in areas where the seed bank is predomi‐ nantly *P. hysterophorous* and the soil is moist. This condition stimulates germination and growth through the layer of mulch. Black plastic sheets may also encourage weed germination as the heat produced and the moisture conserved by plastic mulches favour weed seeds germination. And, as a result, weed control is more effective in the solarized plot than in the non-solarized plot. Mulch can not only control weeds but can also affect seedling growth adversely as in the case of onions [31]. Grass clipping mulch has been found to boost the growth of the other broadleaf weeds.

The use of pre-emergence herbicides (pendimethalin, oxyfluorfen or alachlor) and a postemergence herbicide (propaquizafop) in combination with cultural practices such as hand weeding or black polythene mulch has been shown to be effective. The pre-emergent appli‐ cation of oxyfluorfen followed by soil covering with black polythene mulch recorded the least weed count, dry weight of weeds, higher weed control efficiency and favoured the head initiation, early yield, fresh weight and dry weight of heads and highest economic yield, which was at par with treatment with pendimethalin followed by black polythene mulch [30].

On farms where the soil seed bank was dominated by *P. hysterophorus,* it was observed that mulching coupled with manual weeding during land preparation or ploughing would suppress growth and development of weeds including *P. hysterophorus* and enhance yield of tomato [31].

Other cultural methods include the use of competitive cover crops (*Mucuna pruriens, Arachis pintoi* and *Desmodium hysterophorus*), self-perpetuating competitive plants such as *Cornus sericea, Tagetus erecta* (marigold) or smother crops (*Vigna unguiculata*).

### **8.4. Chemical control**

mented for managing this weed. These include preventative, mechanical, cultural, chemical and biological control methods and even includes potential management by proper utilization of the positive attributes of *P. hysterophorus*. However, effective management of *P. hysteropho‐ rus* requires an integrated approach. The following outlines some of the successful and potential best management practices used throughout the Caribbean and the rest of the world.

The best methods of weed management is prevention and containment. *P. hysterophorus* usually completes its life cycle in 4 weeks; so, it is important to manage the weed before the plant flowers or sets seed and when infestations are small – do not allow the weed to be established. The seeds of *P. hysterophorus* can be spread through flowing water or can be blown by the wind, which further makes prevention of spread difficult. The seed can also stay for years in the soil seed bank and the continuous removal of the weed is required until the seed

Difficulties in the preventive method could be further exacerbated through the easy spread of seeds through vehicles, machinery, the trading and transport of goods, animals grazing on infested fields and the transportation of sand, soil and compost from infested areas to unin‐ fested areas. These are potential risks for further spread and hence should be controlled through an adoption of quarantine measures involving the adoption of inspection and wash-

Manual removal of *P. hysterophorus* by hand weeding before flowering and seed setting is the most effective method, but it is not necessarily practical or economical particularly where there are large infestations. This method, however, may pose a health hazard from allergic reactions

Other mechanical treatments, such as grading, mowing, slashing and ploughing, are also considered inappropriate since they may also promote seed spread as well as rapid regener‐ ation from lateral shoots close to the ground [28; 29]. Ploughing the weed before the plants reach the flowering stage may be effective. Although burning is not promoted as a control strategy, it has been used to control the first flush of emergent weeds at the beginning of the rains in Australia but is only considered a short-term control measure [30]. Burning has been shown to create open niches in the landscape, into which larger number of *Parthenium* seeds

This is considered one of the most cost-effective methods, but it is practical only on small farms or where it is part of an integrated weed management strategy. Farmers have used almost every conceivable practice to reduce the infestation on their holding such as hand weeding, brush cutting and even digging out the weed. In all cases, there is a rapid regrowth from both

and a danger that mature seeds will drop and increase the area of infestation.

are able to germinate in the absence of vegetation.

stumps or re-emergence from the existing seed banks.

**8.1. Prevention and containment**

124 Herbicides, Agronomic Crops and Weed Biology

bank is depleted.

down procedures.

**8.2. Mechanical control**

**8.3. Cultural control**

It is important that *P. hysterophorous* be sprayed early before flowering and seed set. Farmers should scout their fields regularly to check for escaped or untreated isolated infestation. Vegetable farmers prefer a rapid knock-down of weeds before they plant or do cultural control and work towards weed-free plots. Repeated spraying may be required even within a single growing season to prevent further seed production. In this regard, their approach is to use a single herbicide with a broad-spectrum application with the intention to rid the field of grasses, broadleaves and sedges. The most commonly used herbicide over the last 70 years in the Caribbean has been paraquat and diquat. These herbicides work very well and usually give very quick control of most weeds, but sometimes cause severe drift damage. It has been accepted that the overuse of this chemical over the years, in addition to the *P. hysterophorous* metabolic pathways [4; 5; 6], has developed resistance to paraquat and has established the predominance of the weed.

Several herbicides (Table 8) have been used by farmers for control of *P. hysterophorous* based on research by the University of the West Indies, Trinidad and the Ministry of Agriculture, Trinidad [5; 6]. The two most promising herbicides bromoxynil and glufosinate ammonium were applied post-emergence in solanaceous vegetable crops. Both butralin and diphenamid gave good control in the seedling stages as pre-emergence, but these are not very popular amongst farmers. There has been very good control of weeds and *P. hysterophorous* particularly in direct-seeded onions, when oxydiazon and Ioxynil + 2,4-D ester were applied pre-emer‐ gence, with no phytotoxicity.

Agricultural Extension Workers have reported for several years the inability of both glypho‐ sate and gramoxone to control *P. hysterophorous*. This apparent resistance, coupled with the high reproductive capacity of the weed and its wide-ecological amplitude, has given rise to the increased scourge of *P. hysterophorous* in vegetable crops in the Caribbean. In other parts of the world, a similar response is obtained with respect to the resistance by both herbicides [Table 9].

(Post-Em – post-emergent; Pre-Em – pre-emergent)

**Table 8.** Herbicides used by farmers for the control of *Parthenium hysterophorous* in vegetable crops.

Herbicide Use and Increased Scourge of *Parthenium hysterophorus* in Vegetable Production in Trinidad and Tobago http://dx.doi.org/10.5772/61732 127

**Table 9.** Commonly used herbicides in the control of *Parthenium* in vegetable production in other regions.

### **8.5. Biological control**

gave good control in the seedling stages as pre-emergence, but these are not very popular amongst farmers. There has been very good control of weeds and *P. hysterophorous* particularly in direct-seeded onions, when oxydiazon and Ioxynil + 2,4-D ester were applied pre-emer‐

Agricultural Extension Workers have reported for several years the inability of both glypho‐ sate and gramoxone to control *P. hysterophorous*. This apparent resistance, coupled with the high reproductive capacity of the weed and its wide-ecological amplitude, has given rise to the increased scourge of *P. hysterophorous* in vegetable crops in the Caribbean. In other parts of the world, a similar response is obtained with respect to the resistance by both herbicides

> **Weed Control Efficiency Rating**

**Weed Control Efficiency Rating**

**Reference**

[35]

**Herbicide Trade Name Time of Application**

**Table 8.** Herbicides used by farmers for the control of *Parthenium hysterophorous* in vegetable crops.

**Herbicide Time of Application**

Atrazine + Pendimethalin Pre-Em 4

Metsulfuron methyl Pre-Em 4

Chwastox + Buctril Post-Em 4

Imazapyr 6.86 Post-Em 3

Oxyfluorfen + Quizalofop ethyl Pre-Em 4 [32]

Pendimethalin fb 2,4-D sodium salt Pre-Em 4 [33]

Oxyfluorfen Pre-Em **3** [34] Glyphosate + Isoproturon Post-Em 5 [35]

Bromoxynil Buctril Post-Em 5 Glufosinate ammonium Basta Post-Em 5 Oxadiazon Ronstar Pre-Em 4 Ioxynil + 2,4-D ester Actril D Pre-Em 4 Paraquat Gramoxone Post-Em 0 Glyphosate Round-up Post-Em 0 Alachlor Pilarzo Post-Em 5 Dinitroaniline Butralin Post-Em 5 Diphenamid Enide Pre-Em 4

gence, with no phytotoxicity.

126 Herbicides, Agronomic Crops and Weed Biology

(Post-Em – post-emergent; Pre-Em – pre-emergent)

[Table 9].

There are no current biocontrol strategies for the management of *P. hysterophorus* reported in the Caribbean. Biocontrol of *P. hysterophorus* is reported as the most cost-effective, environ‐ mentally friendly and ecologically viable method of control. While several organisms exist locally, there is no observable damage to either seedlings or mature plants. The major fungi and insects, which are reported as potential candidates for biological control of this weed, include leaf rust fungus *Puccinia xanthii* Schwein. var. *parthenii-hysterophorae* Seier, H.C. Evans & Á. Romero (Pucciniaceae), leaf-feeding beetle *Zygogramma bicolorata* Pallister (Coleoptera: Chrysomelidae) and stem-boring weevil *Listronotus setosipennis* Hustache (Coleoptera: Curculionidae) [36].

Other biocontrol agents, which have been reported to show some level of control in Ethiopia, are the stem-galling moth *Epiblema strenuana* (Walker) (Lepidoptera: Tortricidae) and the seedfeeding weevil *Smicronyx lutulentus* Dietz (Coleoptera: Curculionidae) [36; 37]. These have not yet positively been identified but experience elsewhere has demonstrated that a suite of agents is required to achieve effective biological control of *Parthenium* under different environmental conditions and in different regions.

Pathogens such as *Fusarium pallidoroseum, Puccinia melampodii* and *Oidium parthenii* have also been reported as showing good potential as biocontrol agents [38; 39]. *Alternaria alternate, Puccinia abrupt* var. partheniicola (parthenium rust), *P. xanthii* and other rusts are currently being evaluated as potential mycoherbicides for the control of *Parthenium*.

The weed is not grazed by animals or other wild life.

### **9. Allelopathic plant species with potential in controlling** *P. hysterophorus*

There are several studies reporting the use of crude extracts, plant residues and purified compounds of allelopathic plants (crops, grasses, broadleaf weeds and trees) for controlling the germination, growth and physiology of *P. hysterophorus* [40–56]. Table 10 outlines the reported plants.

Herbicide Use and Increased Scourge of *Parthenium hysterophorus* in Vegetable Production in Trinidad and Tobago http://dx.doi.org/10.5772/61732 129

**Table 10.** Phytotoxic effects of allelopathic plants on *Parthenium*.

& Á. Romero (Pucciniaceae), leaf-feeding beetle *Zygogramma bicolorata* Pallister (Coleoptera: Chrysomelidae) and stem-boring weevil *Listronotus setosipennis* Hustache (Coleoptera:

Other biocontrol agents, which have been reported to show some level of control in Ethiopia, are the stem-galling moth *Epiblema strenuana* (Walker) (Lepidoptera: Tortricidae) and the seedfeeding weevil *Smicronyx lutulentus* Dietz (Coleoptera: Curculionidae) [36; 37]. These have not yet positively been identified but experience elsewhere has demonstrated that a suite of agents is required to achieve effective biological control of *Parthenium* under different environmental

Pathogens such as *Fusarium pallidoroseum, Puccinia melampodii* and *Oidium parthenii* have also been reported as showing good potential as biocontrol agents [38; 39]. *Alternaria alternate, Puccinia abrupt* var. partheniicola (parthenium rust), *P. xanthii* and other rusts are currently

**9. Allelopathic plant species with potential in controlling** *P. hysterophorus*

There are several studies reporting the use of crude extracts, plant residues and purified compounds of allelopathic plants (crops, grasses, broadleaf weeds and trees) for controlling the germination, growth and physiology of *P. hysterophorus* [40–56]. Table 10 outlines the

> phenolic acids, 5,7,4' trihydroxy-3',5" dimethoxyflavone and 3-isoprophyl-5-acetoxy cyclohexene-2-one-1

benzoic, vanillic, mcoumaric, p-coumaric, gallic, caffeic, ferulic and chlorogenic acids

terpenoides

**Suppression/Inhibitory**

Reduced germination and root/shoot growth

Reduced germination and root/shoot growth

Reduced germination and root growth

**References**

[40–42]

[40; 41]

[40; 43; 44]

**Effect(s)**

**Present**

being evaluated as potential mycoherbicides for the control of *Parthenium*.

The weed is not grazed by animals or other wild life.

**Name of Plant Plant Part Studied Allelochemicals**

*Oryza sativa* Root and shoot Momilactones A and B,

*Sorghum bicolor* Root and shoot Benzoic, p-hydroxy

*Helianthus annuus* Root and leaves Phenols and

Curculionidae) [36].

reported plants.

**A. Crop plants**

conditions and in different regions.

128 Herbicides, Agronomic Crops and Weed Biology

### **10. Potential for management by utilization**

There are reports of innovative uses of *P. hysterophorus.* It is documented as having insecticidal, nematicidal, fungicidal and bioherbicidal (biopesticide) and growth regulator properties [17; 58]. Furthermore, studies have shown that pre- and post-emergent applica‐ tions of *P. hysterophorous* extracts at high concentrations were effective in significantly decreasing the seed germination and the growth of *Eragrostis* sp. [59]. The plant is also a rich source of nitrogen, phosphorus, potassium, calcium, magnesium and chlorophyll, which makes it suitable for composting. Reports indicate that it aids in moisture conserva‐ tion, which is good for enhanced root penetration and crop growth [57; 60]. It is also used as a green manure for maize and mung bean [61].

More recently, it has been found to confer many health benefits such as a remedy for skin inflammation, rheumatic pain, diarrhoea, urinary tract infections, dysentery, malaria and neuralgia [17]. Extracts from the flowers have shown significant antitumor activity [62; 63]. It has been used as a remedy for inflammation, eczema, skin rashes, herpes, rheumatic pain, cold, heart problems and gynaecological ailments [17]. It has prospects in nanomedicine to be used in applications of eco-friendly nanoparticles in bactericidal, wound healing and other medical and electronic applications [17]. It has the potential to remove heavy metals such as nickel, cadmium, cresol and dyes from the environment, eradication of aquatic weeds such as salvinia (*Salivinia molesta* Mitchell), water lettuce (*Pistia stratiotes*) and water hyacinth (*Eichhornia crassipes*) and seed germination of lovegrass (Eragrostis) [17]. It can also be used as a substrate for commercial enzyme production [64], as additives in cattle manure for biogas production [65], as a flea repellent for dogs and as a source of potash, oxalic acids and high-quality protein (HQP) in animal feed [66; 67].

### **11. Conclusion**

Due to its invasive capacity and allelopathicproperties, *P. hysterophorous* has the potential to disrupt the natural ecosystem and threaten the biodiversity. From an earlier survey, the authors concluded that under systems of intensive vegetable production and where the use of paraquat and glyphosate are widespread, the weed has shown the ability to survive herbicide treatments, except at the seedling stage, regardless of the season and crop or management practices [68]. In addition, biological and cultural control were insignificant in reducing *Parthenium* populations. The weed can significantly reduce crop yield and quality due to its aggressive growth habit, competitiveness and allelopathic interference. It is a difficult weed to manage, and a wide variety of methods, starting with prevention and containment, are necessary to reduce the incidence and spread of this weed. An integrat‐ ed approach using cultural, physical, chemical and biological approaches are necessary for the successful management of this weed. Integrated approaches following different methods coupled with proper land management and best management practices can effectively control this weed. Despite the negative impact of this weed on the biodiversity, there is potential in exploring its beneficial properties as a mechanism of management.

### **Author details**

**10. Potential for management by utilization**

130 Herbicides, Agronomic Crops and Weed Biology

as a green manure for maize and mung bean [61].

**11. Conclusion**

oxalic acids and high-quality protein (HQP) in animal feed [66; 67].