The water flowed by way of gravity into a 125 mL beaker, leaving debris behind. Filter papers were changed periodically as needed. Then, 50 mL were allocated from the filtered sample and placed in storage at -20° C until analysis. A standard for pendimethalin, ACS-grade hexane and MS-grade acetonitrile were obtained from Fisher Scientific. Liquid-liquid extraction methods were modified from USEPA . High pressure liquid chromatography tandem mass spectrometry was employed to analyze for residue in water samples. Fifteen mL samples were extracted three times with 3 mL of hexane and placed on a rotary platform shaker for 5 minutes, then set aside for 15 minutes. Hexane extracts were pooled and 3 mL were then dried under a nitrogen gas stream. Then, volumes of 500 µL acetonitrile were added to the dried sample and vortexed. Volumes of 500 µL 0.4% formic acid was then added and vortexed for a final concentration factor of 15. A Shimadzu LCMS-8040 triple quadrupole mass spectrometer was used equipped with electrospray ionization on positive mode. The desolvation line temperature and heat block temperature were 250° and 400° C, respectively. Nebulizing gas and drying gas were set at a flow of 3 L min-1 and 15 L min-1 , respectively. The mobile phase flow rate was 0.4 mL min-1 and an injection volume of 10 µL. The C18 column was Phenomenex Kinetex polar, 100 by 3.0 mm and 2.6 µm particle size. The multiple reaction monitoring ion transitions for the quantifier ionwere 282.0 > 212.1 m/z in a dwell time of 10 ms and for the qualifier ions were 282.2 > 43.1 m/z and 282.2 > 194 m/z in a dwell time of 5 ms. The limit of detection was 0.006 µg L-1 and the limit of quantification was 0.008 µg L-1. Multiple calibration curves were implemented for the low concentration range and for the high concentration range using Shimadzu LabSolutions and MacCoss Skyline software for small molecules. Method recovery was performed by spiking five non-treated collected water samples with 0.20 µg L-1 of pendimethalin before extraction . A low concentration of pendimethalin below 0.05 µg L-1 was present in the collected non-treated samples, therefore, cannabis dryingn racks the peak areas of the control samples without standard spiking were subtracted from the spiked samples.

The recovery in water samples was on average 79%.A significant increase in sweet potato [Ipomoea batatas Lam.] production area in the southeastern United States has occurred in the past decade, increasing from 33,548 ha in 2007 to 51,800 ha in 2017 . Sweetpotato has proven to be a valuable crop with a national farm gate value of $705.7 million in 2016, up from $298.4 million in 2006 . North Carolina is the largest sweetpotato-producing state, accounting for 54% of U.S. production . North Carolina, California, Mississippi, and Louisiana account for 94% of sweetpotato production in the United States . Unfortunately, due to its prostrate growth habit and relatively slow growth, sweetpotato does not compete well with problematic weeds, resulting in reduced yields . Palmer amaranth and large crabgrass [Digitaria sanguinalis Scop.] are among the top five most common weeds in North Carolina sweetpotato, with A. palmeri being identified as the most troublesome weed . Amaranthus palmeri has been reported to be taller, to have a faster growth rate and greater leaf area, and to produce more overall biomass when compared with other Amaranthus species . Season-long A. palmeri interference is seen in vegetable crops, with reduced yield of 94% in bell pepper , 67% in tomato , 36% to 81% in sweetpotato , with the greater yield losses associated with higher A. palmeri densities. Limited herbicide options exist for use in sweetpotato . Growers rely on PRE herbicides, which do not always provide efficacious weed control and require rainfall for activation. POST herbicide options for A. palmeri control in sweetpotato are limited to between-row applications of carfentrazone or glyphosate . The lack of POST herbicides forces growers to use tillage for control of weeds until row closure, at which time growers have no additional control options for dicotyledonous weeds other than mowing weeds above the cropcanopy and hand weeding, which is a costly control measure . Digitaria sanguinalis is commonly found in fruit and vegetable crops but has not been highly ranked as a problematic weed due to efficacious POST herbicides such as clethodim, fluazifop, or sethoxydim . Although these graminicides can be effective, grasses escaping herbicide application or sprayed after substantial establishment may continue to compete with the crop and reduce yields.

Furthermore, herbicide resistance management for D. sanguinalis should be considered, as resistance to acetyl-CoA carboxylase herbicides, including those registered for use in sweetpotato has been reported . While its impact on sweetpotato has not been reported, season-long, D. sanguinalis reduced yield in bell pepper by 46% , snap bean by 47% to 50% , and watermelon [Citrullus lanatus Matsum. & Nakai] by 82% . A better understanding of the interactions of A. palmeri and D. sanguinalis with sweetpotato would allow for better decision making regarding their control. Thus, the objectives of this study were to determine the effect of five densities of A. palmeri and D. sanguinalis on sweetpotato biomass and storage root yield and quality, the intraspecific response of A. palmeri and D. sanguinalis across five densities with and without sweetpotato, and the effect of sweetpotato on growth of A. palmeri and D. sanguinalis.Field studies were conducted with ‘Covington’ sweetpotato at the Horticultural Crops Research Station near Clinton, NC on a Norfolk loamy sand with humic matter 0.31% and pH 5.9 in 2016 and an Orangeburg loamy sand with humic matter 0.47% and pH 5.9 in 2017. Nonrooted ‘Covington’ sweetpotato 20- to 30-cm-long cuttings were mechanically planted approximately 7.6-cm deep into ridged rows 1 m apart in the entire study at an in-row spacing of approximately 30 cm on June 9, 2016, and June 12, 2017. At 1 d after transplanting, sweetpotato plants were removed by hand in the no-sweetpotato treatments. On the same day, treatment rows assigned A. palmeri or D. sanguinalis were broadcast seeded on the soil surface and lightly raked to a depth of approximately 1.0 cm. After weed seeding, the entire study was irrigated with 1.3 cm of water using overhead irrigation to aid in weed seed establishment. No additional irrigation was applied, in either year, after the initial irrigation event. Treatments consisted of a single weed species at five weed densities grown with and without sweetpotato arranged in a randomized complete block design with three replications . Amaranthus palmeri and D. sanguinalis were hand thinned to treatment densities of 0 , 1, 2, 4, and 8 and 0 , 1, 2, 4, and 16 plants m−1 of row, respectively, when A. palmeri was approximately 8 cm tall, and D. sanguinalis had two expanded leaves. At the time of weed thinning, sweetpotato averaged one to two newly expanded leaves on each plant. Densities of A. palmeri and D. sanguinalis were based on those used in previous research . Plots consisted of two bedded rows, each 1-m wide by 5-m long, with the first row being a weed-free buffer row planted to sweetpotato and the second row a treatment row. Treatment rows were maintained at specific weed treatment densities, and border rows were maintained free of weeds season-long by weekly removal by hand. Season-long rainfall and growing degree day data are presented in Table 1. Two days before sweetpotato harvest, 5 sweetpotato plants and 5 plants of each weed species were randomly harvested at the soil level from each plot to determine aboveground biomass. Samples were placed in 2-ply paper yard waste bags measuring 40 by 30 by 89 cm and fresh biomass was recorded. Samples were then placed in a propane-heated, forced-air drier for 96 h at 80 C. Once dry, samples were removed and weighed immediately to determine dry biomass. To determine fresh and dry sweetpotato and weed biomass on a per plant basis, total sweetpotato or weed biomass within a treatment and replication was divided by the number of plants harvested. To determine dry biomass per meter of row, individual weed biomass was multiplied by sweetpotato plant and/or weed number in 1 m of row, respectively.

Sweetpotato storage roots were harvested at 113 d after transplanting in 2016 and at 107 DAT in 2017. In both years storage roots were harvested with a tractor-mounted two-row chain digger and hand sorted into jumbo , no. 1 , and canner grades and weighed. Total marketable yield was calculated as the sum of jumbo and no. 1 grades. Data for crop biomass, vertical growing weed individual weed biomass, weed biomass per meter of row, yield, and quality were subjected to ANOVA using PROC MIXED in SAS . Treatment, year, and treatment by year were considered fixed effects, while replication within year was treated as a random effect. Year was treated as a fixed effect to further evaluate components of the year by treatment interaction, such as year by weed density and year by crop presence or absence. If the treatment by year interaction was not significant, a contrast statement was used to test for a linear trend for dependent variables with increasing weed density, calculated separately for each weed species. All response variables, except canner yield, were square-root transformed to reduce both data skewness and variance heterogeneity before carrying out the mixed model ANOVA.Marketable yield decreased as the density of A. palmeri or D. sanguinalis increased. No treatment by year interaction for sweetpotato yield was observed ; therefore, data were combined over years. Marketable yield loss associated with A. palmeri density ranged from 50% with 1 A. palmeri plant m −1 of row to 79% with 8 plants m−1 of row, respectively, when compared with the weed-free check . Marketable yield reduction by D. sanguinalis was similar to marketable yield reduction caused by A. palmeri but at higher weed densities. Marketable yield was reduced by 35% and 76% with 1 and 16 D. sanguinalis plants m−1 of row, respectively . Loss of jumbo yield is a significant contributor to overall marketable yield loss at weed densities as low as 1 plant of either species m−1 . Jumbo grade had greater yield loss with 1 plant m−1 for A. palmeri and D. sanguinalis than the no. 1 gradefor both weed species at the same density . Results for estimated marketable yield loss per weed as weed density approaches zero for A. palmeri and D. sanguinalis were 119% and 61%, respectively. The higher estimated marketable yield loss as weed density approaches zero for A. palmeri relative to D. sanguinalis indicated higher competitive capacity of A. palmeri at low densities. These results for A. palmeri are consistent with another study in sweetpotato but higher than in soybean [Glycine max Merr.] , peanut , and corn . Estimated yield loss as weed density approaches zero in the present study indicates that A. palmeri and D. sanguinalis, even at low densities, can greatly reduce sweetpotato marketable yield. The initial yield loss as weed density approaches zero for D. sanguinalis was less than A. palmeri at lower densities. However, sweetpotato yield loss from interference byD. sanguinalis was higher than yield loss reported in snap bean . For parameter A, the asymptote of the regression model estimating the maximum yield loss due to weed density was 87% for A. palmeri and 83% for D. sanguinalis. Meyers et al. estimated a maximum marketable yield loss of 90% at A. palmeri densities of 6.5 plants m−1 of sweetpotato row. Findings from our study further support the findings of Meyers et al. , who also reported the highly competitive nature of A. palmeri with sweetpotato. To reduce interference of A. palmeri and D. sanguinalis, which are commonly reported in sweetpotato, growers should use a combination of efficacious PRE herbicides, as outlined by Meyers et al. , in combination with tillage, hand removal, and mowing . Although POST herbicides for A. palmeri are limited, POST herbicide options for selective grass control in sweetpotato are available and should be used when D. sanguinalis is less than 10 cm to minimize yield loss. If D. sanguinalis resistance is suspected, then alternative methods should be analyzed for control. Growers should not dismiss the impact of either weed, as a single A. palmeri or D. sanguinalis per meter of row reduced marketable yield by 50% and 35%, respectively . Reduction in marketable yield loss was due to a decrease in weight of no. 1 and jumbo sweetpotato grades.