[Separate Analysis of Loquat Fruit Pulp, Peel, and Pits to Calculate Pesticide Residue Levels in the Whole Commodity].

To evaluate the effects of handling "not detectable" residues (ND: <0.01 mg/kg) in the pulp and detectable residues in the pits on the calculation of pesticide residue in the whole fruit, residue levels in the pulp, peel, and pits of loquat fruits were separately analyzed. Following conventional Japanese agricultural practices, 16 pesticides were sprayed at the maximum application rates in three test fields. All target pesticides were detected at quantifiable levels in the peel (n=144). In contrast, the percentages of detected pesticides in the pulp and pits were 42% (n=61) and 36% (n=52), respectively. Most pesticide residues were present in the peel. For comparison, the pesticide residue levels in the whole fruits were determined based on three indices: the highest estimate (H), calculated using the measured residue levels in the pits and by replacing the ND residues in the pulp as the limit of quantification (LOQ) values; conventional estimate (C), calculated by neglecting all residues in the pits (0 mg/kg) and replacing the ND residues in the pulp as LOQ values; and the lowest estimate (L), calculated by neglecting all residues in the pits and the ND residues in the pulp (0 mg/kg). The L/C and H/C ratios ranged from 74% (L/C) to 106% (H/C). In seven of eighty-three cases with less than 90% difference, residue levels in the whole loquat fruits were low (≤0.06 mg/kg), with the actual range being equal to or below the minimum unit of 0.01. In comparison of three field datasets, the range of residue levels was estimated to be 2.77 mg/kg. Based on the results of separate analysis, handling of ND residues in the pulp and detectable residues in the pits did not significantly affect the calculated pesticide residue levels in the whole loquat fruits.

Comparison of adherence tendencies of pesticide residues sprayed on small-, medium-, and large-sized tomatoes.

Crop field trials were conducted to investigate the residues of sprayed pesticides on the different sizes of tomatoes. Pesticide residue data in tomatoes varied due to different locations of the three crop fields selected and/or physicochemical properties of the three pesticides tested. The pesticide residue levels in the medium- and small-sized tomatoes were 1.5 and 2.4 times higher than the level in large-sized tomatoes under similar spray conditions, whereas amount of pesticides adhered per unit surface area were approximately equal among all three sizes of tomatoes. The results of this study suggested that the differences in pesticide residue levels were due to differences in the degree of specific surface area of each tomato size. Resultant residue data of medium-sized tomatoes demonstrated a proportional relationship between pesticide residue levels and the specific surface area of tomatoes.

Inverse modeling of laboratory experiment to assess parameter transferability of pesticide environmental fate into outdoor experiments under paddy test systems.

BACKGROUND: Extraction of environmental fate parameters for pesticides by inverse modeling in laboratory experiments has evolved to become a common practice in higher tier exposure modeling. This study focuses on flooded paddy soil conditions using a simple container test system. Four active ingredients of paddy herbicide were tested. The results were parameterized and transferred to analyze the effect of formulation types on the outdoor experimental data via inverse analyses of two structurally-compatible mathematical models, namely: pesticide concentration in paddy field for laboratory (PCPF-LR) and PCPF for outdoors (PCPF-1Rv1.1 ). RESULTS: After in-laboratory calibration, the PCPF-LR model revealed statistically acceptable or ideal simulations of pesticide concentrations in both the aqueous and soil phases (e.g. Nash-Sutcliffe efficiency > 0.7), in addition to determining the apparent sorption from the laboratory data. The extracted persistence indicators (degradation half-life, DegT50 ) in the aqueous phase were 1.4-38.7 times higher than those of the dissipation (DT50 ) due to the exclusion of partitioning and phase transfer processes (diffusion and sorption). In the outdoor experiment, 72% of the outdoor-calibrated simulations of the PCPF-1Rv1.1 model, showed statistically acceptable representations of the concentrations in paddy water. Furthermore, the DegT50 as 'bulk' degradation in paddy water was statistically insignificant between the formulation types; however, the DT50 demonstrated statistically different results. CONCLUSION: The laboratory/outdoor data interconnections using proposed modeling approach facilitate the data-specific model calibration and analysis. These can be useful in the exposure modeling of paddy pesticide by manipulating the parameter uncertainties associated with the experimental constraints. © 2020 Society of Chemical Industry.

Influences of sample homogenization time and standing time before extraction on the determination of incurred pesticide residue levels in grapes.

To estimate the influence of sample processing with a blender, we conducted a homogeneity test using a bulk sample of pre-harvest grapes. Relative standard deviations (RSDs) were calculated from the concentrations of pesticides in the portions from the top, middle, and bottom of the homogenate with fine and rough particles. The results from adequate sample processing showed that the RSDs of the residue levels of all five pesticides in the fine-particle homogenate were lower than 10%. In contrast, the results under problematic conditions such as short blending times and long standing times after blending showed higher RSDs (>15%). The RSDs of nonpolar pesticides showed greater variabilities under the problematic conditions than those of polar pesticides. Separate analyses of the precipitate and supernatant phases suggested that the distribution bias of skin particles in the homogenate has a major effect on the concentration of nonpolar pesticides because of weighing errors in the extracted portions.

Performance evaluation of lysimeter experiments for simulating pesticide dissipation in paddy fields. Part 1: Submerged application of granular pesticides.

Three-year comprehensive experiments were conducted to compare the dissipation patterns of a total of 16 pesticides, including 3 metabolites, as granular formulations applied in lysimeters and paddy fields with two soil types. Analytical concentrations of the target pesticides in paddy water were analyzed using a granular kinetic model consisting of the following parameters: release rate, decrease rate, and dissolved concentration. Results of parameter grouping analyses of the kinetic models showed that 56% of data reproducibility (entire grouping) was obtained between replicates for the lysimeters. In comparisons between the lysimeters and paddy fields, 48% of decrease rates and 34% of release rates were grouped, although significant differences were observed with a nearly 90% difference for dissolved concentrations. These differences might be attributed to the hydrological components such as water management and meteorological covariates in paddy fields, the daily percolation in lysimeters and the adsorption-desorption kinetics between paddy water and soil.

Performance evaluation of lysimeter experiments for simulating pesticide dissipation in paddy fields. Part 2: Nursery-box application and foliar application.

Comparative experiments investigating the dissipation of four nursery-box-applied pesticides and three foliar-applied pesticides were conducted using lysimeters and in actual paddy fields. In the lysimeter experiments, there were test plots for submerged application for both application types. Analytical concentrations of the pesticides in paddy water were evaluated using appropriate kinetic models. The detection levels of pesticides in the paddy water for the nursery-box and foliar applications were 10-77% and 42-79% of the submerged application, respectively. The times required for 50% dissipation (DT 50s) in case of the nursery-box and foliar applications were 0.8-10.4 days and 0.5-2.7 days, respectively. Although overall dissipations were affected by the physicochemical properties of the pesticide and the experimental design in the test plots, the initial detection levels in the lysimeters, governed by the runoff at transplanting and the deposition at spraying, were comparable with those in the actual paddy fields.

Inverse analysis to estimate site-specific parameters of a mathematical model for simulating pesticide dissipations in paddy test systems.

BACKGROUND: In Japan, while experimental data for the dissipation behavior of paddy pesticides under a standardized test system are available, the application of a mathematical model is limited. This paper proposes a new model calibration procedure for inversely deriving the model parameters from the experimental data. This procedure is tested in the open software R by running an improved Pesticide Concentration in Paddy Field-1 (PCPF-1) model with R packages to analyze the dissipation of simetryn and molinate in flooded lysimeters and paddy fields. RESULTS: The model fitting was performed by a random minimization routine. Furthermore, the uncertainties of the model parameters envisioned by the global sensitivity analysis were successfully reduced using the Markov chain Monte Carlo technique. The calibrated simulation was validated at each test plot by confirming multiple statistical indices (i.e. Nash-Sutcliffe efficiency 0.88-1.00, percent bias <±5%). The dissipation pathways of two herbicides were quantitatively clarified by the mass balance of calibrated simulations and the effect of the unexpected herbicide runoff was quantified. The case study showed that the adjustment of daily percolation rate in the lysimeter experiment is the key to simulate the actual paddy field condition more accurately, especially in a case where pesticides show higher water solubility and soil mobility. CONCLUSION: The developed procedure can analyze the experimental data with acceptable accuracy and extract the unobservable information quantitatively. Our approach is applicable to the optimization of not only the model but also future experimental design. © 2018 Society of Chemical Industry.

Influence of various parts of sweet corn ears on pesticide residue levels.

Pesticide residue levels in various parts of sweet corn ears were analyzed. For this purpose, five pesticides were sprayed on corn in two different fields, and the harvested samples were separated into four portions, namely kernels, cobs, silks, and husks. Each of these portions was then separately analyzed. Pesticide residues were predominantly distributed in the silk and husk portions, which constituted ≥91% of the whole crop, whereas relatively minimal residues remained in the kernel and cob portions. Further, residue distributions in the silks and husks were found to differ between the two fields. The calculated residue levels in kernels with the cob and silk were obviously higher than the residue levels in the kernel alone (max. >62 times different). This result suggests that the silk portion could greatly affect pesticide residue levels in the edible portion of corn.

Effect of sample preparation on the estimation of residue levels of sprayed pesticides in separate analyses of turnip roots and leaves: inclusion or exclusion of the root-shoot junction.

The effect of inclusion or exclusion of the root-shoot junction on the estimation of pesticide residue levels in turnip roots and leaves was investigated. Turnips grown at two experimental sites were sprayed with six pesticides. At residue analysis, the turnips were divided in three segments: roots (R), leaves (L), and root-shoot junctions (J). The highest pesticide residue amounts were found in leaves ≥93% of total, with minimal amounts in roots. Residue amounts in root-shoot junctions were intermediate between those of leaves and roots. Residue levels were calculated for the root plus root-shoot junction, and were higher than those in roots: (R+J)/R=1.0-9.0. In contrast, residue levels in the leaf plus root-shoot junction were lower than in leaves only: (L+J)/L=0.76-0.91. The results indicate that the position of the cut between root and leaves could greatly affect the estimated pesticide residue levels when roots and leaves are analyzed separately.

Effect of sampling size on the determination of accurate pesticide residue levels in Japanese agricultural commodities.

The uncertainty in pesticide residue levels (UPRL) associated with sampling size was estimated using individual acetamiprid and cypermethrin residue data from preharvested apple, broccoli, cabbage, grape, and sweet pepper samples. The relative standard deviation from the mean of each sampling size (n = 2(x), where x = 1-6) of randomly selected samples was defined as the UPRL for each sampling size. The estimated UPRLs, which were calculated on the basis of the regulatory sampling size recommended by the OECD Guidelines on Crop Field Trials (weights from 1 to 5 kg, and commodity unit numbers from 12 to 24), ranged from 2.1% for cypermethrin in sweet peppers to 14.6% for cypermethrin in cabbage samples. The percentages of commodity exceeding the maximum residue limits (MRLs) specified by the Japanese Food Sanitation Law may be predicted from the equation derived from this study, which was based on samples of various size ranges with mean residue levels below the MRL. The estimated UPRLs have confirmed that sufficient sampling weight and numbers are required for analysis and/or re-examination of subsamples to provide accurate values of pesticide residue levels for the enforcement of MRLs. The equation derived from the present study would aid the estimation of more accurate residue levels even from small sampling sizes.

Comparison of the variability in the levels of pesticide residue observed in Japanese cabbage and grape units.

To estimate variations in pesticide residue levels in crops, the variability factors (VFs, the 97.5th percentile of the residue levels in the sample divided by the average residue levels in the lot) in residue levels of acetamiprid and cypermethrin applied to cabbage and grapes were investigated, respectively. The VFs in the residue levels of both pesticides in cabbage (2.00 and 2.39, respectively) were clearly higher than those in grapes (1.82 and 1.63, respectively). Although the residue levels of both pesticides in grapes showed a normal distribution, those values in cabbage were slightly skewed at lower residue levels. Individual residue levels in grapes had a good agreement between acetamiprid and cypermethrin. In contrast, the distribution of cypermethrin residue levels in cabbage was slightly skewed at higher residue levels as compared to that of acetamiprid. These results indicate that the difference in the relative distribution of the two pesticides between cabbage and grapes might be due to the influence of various factors such as differences in crop species, plant cultivation methods, and physicochemical properties of the pesticides.

[Effects of processing and cooking on the levels of pesticide residues in rice samples].

The effects of processing and cooking on the levels of pesticide residues in rice samples were investigated for 11 pesticides in pre-harvest (9 pesticides) and post-harvest (4 pesticides) samples. In the polishing process, the transfer ratio (%, total pesticide residue amount in product/that in brown rice) of rice bran ranged from 40% to 106%, and the transfer ratio of polished rice ranged from 9% to 65% in pre-harvest samples. These values varied from pesticide to pesticide. The processing factor (the concentration (mg/kg) of pesticide in product/that in the brown rice) of polished rice ranged from 0.11 to 0.73. The loss of pesticides during processing and/or cooking did not correlate to any single physical or chemical property. Investigation of changes of pesticide residues during processing and/or cooking is useful not only to establish MRLs, but also to recognize actual levels of pesticide residues in food.

[Effects of processing and cooking on the levels of pesticide residues in wheat samples].

The effects of processing and cooking on the levels of pesticide residues in wheat samples were investigated for 13 pesticides in pre-harvest (Pre, 9 pesticides) and post-harvest (Post, 6 pesticides) samples. In the milling process, the transfer ratios (%, total pesticide residue amount in product/that in wheat grain) of wheat bran were greater than 70% and 80% for pre-harvest and post-harvest samples, respectively. The transfer ratios of flour ranged from 1.7% to 23% (Pre) and 4.0% to 11% (Post). There was no significant difference in transfer ratio among the pesticides investigated. The processing factors (Pf, the concentration (mg/kg) of pesticide in product/that in the wheat grain) of flour ranged from 0.030 to 0.40 (Pre) and 0.069 to 0.18 (Post). The values in pre-harvest samples were higher than those in post-harvest samples. Investigation of changes of pesticide residues during processing and/or cooking is useful not only to establish MRLs, but also to recognize actual levels of pesticide residues in food.

[Effects of processing and cooking on the levels of pesticide residues in soybean samples].

The effects of processing and cooking on the levels of pesticide residues in soybean samples were investigated for 14 pesticides in pre-harvest samples. On soaking, the transfer ratios (%, total pesticide residue amount in product/that in soybean) of soaked soybean were greater than 60% for most of the pesticides investigated. The transfer ratio of soymilk ranged from 37% to 92%, and that of tofu ranged from 7% to 63%. The processing factor (Pf, the concentration (mg/kg) of pesticide in product/that in soybean) of tofu ranged from 0.026 to 0.28. These values varied among pesticides. There was a high correlation between the log P(ow) and the transfer ratio of tofu. The test described here should be useful to obtain the transfer ratios of pesticide residues in processing and/or cooking steps.