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Farenhorst A.,University of Manitoba | McQueen R.,University of Manitoba | Kookana R.S.,University of Adelaide | Singh B.,University of Manitoba | Malley D.,PDK Projects Inc.
ACS Symposium Series | Year: 2014

Pesticide fate models are useful in testing the impact of agricultural management practices on the quality of water resources. The sorption parameter is among the most sensitive of the input parameters used by pesticide fate models. Numerous pesticide sorption experiments have been conducted in the past 75 years, but mainly focussed on surface soils. The batch equilibrium procedure is a conventional technique to quantify sorption parameters. In this chapter, we summarize selected batch equilibrium studies to demonstrate that sorption parameters vary widely among sampling points within soil-landscapes. We recognize that probability density functions (PDFs) have been incorporated into stochastic simulations of pesticide fate to help account for sorption spatial variability, but also show that PDFs can vary widely for different pesticides and/or soil depth. We propose that near-infrared spectroscopy (NIRS) can be used in combination with batch equilibrium techniques to more rapidly quantify the sorption variability of herbicides. We demonstrate that NIRS can be integrated into the Pesticide Root Zone Model version 3.12.2 to improve spatial resolutions for calculating the mass of herbicide leached to depth at the field scale. Better quantification of herbicide sorption variability and hence leaching potential will provide greater confidence in using pesticide fate models in regulatory practices, as well as in management programs that promote both sustainable agriculture and adequate environmental protection of water resources. © 2014 American Chemical Society.


Sirisomboon P.,Curriculum of Agricultural Engineering | Chowbankrang R.,Curriculum of Agricultural Engineering | Williams P.,PDK Projects Inc.
Applied Spectroscopy | Year: 2012

Near-infrared spectroscopy in diffuse reflection mode was used to evaluate the apparent viscosity of Para rubber field latex and concentrated latex over the wavelength range of 1100 to 2500 nm, using partial least square regression (PLSR). The model with ten principal components (PCs) developed using the raw spectra accurately predicted the apparent viscosity with correlation coefficient (r), standard error of prediction (SEP), and bias of 0.974, 8.6 cP, and -0.4 cP, respectively. The ratio of the SEP to the standard deviation (RPD) and the ratio of the SEP to the range (RER) for the prediction were 4.4 and 16.7, respectively. Therefore, the model can be used for measurement of the apparent viscosity of field latex and concentrated latex in quality assurance and process control in the factory. © 2012 Society for Applied Spectroscopy.


Ulrich A.E.,Josefstrasse | Ulrich A.E.,ETH Zurich | Malley D.F.,PDK Projects Inc. | Watts P.D.,Institute of Arctic Ecophysiology
Science of the Total Environment | Year: 2016

Intensification of agricultural production worldwide has altered cycles of phosphorus (P) and water. In particular, loading of P on land in fertilizer applications is a global water quality concern. The Lake Winnipeg Basin (LWB) is a major agricultural area displaying extreme eutrophication. We examined the eutrophication problem in the context of the reemerging global concern about future accessibility of phosphate rock for fertilizer production and sustainable phosphorus management. An exploratory action research participatory design was applied to study options for proactivity within the LWB. The multiple methods, including stakeholder interviews and surveys, demonstrate emerging synergies between the goals of reversing eutrophication and promoting food security. Furthermore, shifting the prevalent pollutant-driven eutrophication management paradigm in the basin toward a systemic, holistic and ecocentric approach, integrating global resource challenges, requires a mutual learning process among stakeholders in the basin to act on and adapt to ecosystem vulnerabilities. It is suggested to continue aspects of this research in a transdisciplinary format, i.e., science with society, in response to globally-expanding needs and concerns, with a possible focus on enhanced engagement of indigenous peoples and elders. © 2015 Elsevier B.V.


Sirisomboon P.,King Mongkut's University of Technology Thonburi | Kaewkuptong A.,King Mongkut's University of Technology Thonburi | Williams P.,PDK Projects Inc.
Journal of Near Infrared Spectroscopy | Year: 2013

The analysis of the dry rubber content (DRC) of Para rubber latex, including field latex and concentrated latex, using near infrared spectroscopy was conducted using a Fourier transform near infrared (FT-NIR) spectrometer in diffuse reflection mode over the wavenumber range of 4000-10,000 cm -1. The proposed method is useful for industrial purposes. The best model was developed using the partial least square regression (PLSR) from the spectra, which were pretreated using the 2nd derivative method, where the correlation (r2), standard error of prediction (SEP) and bias were 0.997, 0.3398% and -0.0239%, respectively. The ratio of standard deviation (SD) to SEP of the reference data in the prediction sample set (RPD) was 18.18 and the ratio of the range to the SEP of the prediction set (RER) was 74.4. The model was validated using a new batch of samples and the prediction performance was good with an r2 of 0.999, a SEP of 0.3898% and a bias of -0.0008%. Therefore, the NIR spectroscopy technique can be used as an accurate and rapid method for estimating the DRC of Para rubber latex for both field and concentrated latex. © IM Publications LLP 2013. All rights reserved.


Sirisomboon P.,King Mongkut's University of Technology Thonburi | Tanaka M.,Saga University | Kojima T.,Saga University | Williams P.,PDK Projects Inc.
Journal of Food Engineering | Year: 2012

Near infrared spectroscopy offers the possibility to classify and predict the internal quality of fruits and vegetables. The objective of this study was to evaluate the ability of near infrared spectroscopy to classify the maturity level and to predict textural properties of tomatoes variety "Momotaro". Principal component analysis (PCA) and Soft independent modeling of class analogy (SIMCA) were used to distinguish among different maturities (mature green, pink and red). Partial least squares (PLS) regression was used to estimate textural properties, alcohol insoluble solids and soluble solids content of the tomatoes. The PCA calibration model with mean normalization pretreatment spectra of mature green tomatoes, gave the highest distinguishability (96.85%). It could classify 100.00% of red and pink tomatoes. The SIMCA model could not give better accuracy in maturity classification than individual PCA models. Among the textural parameters measured, the bioyield force from the puncture test with the near infrared (NIR) spectra (between 1100 and 1800 nm) pretreated by multiplicative scatter correction (MSC) had the highest correlation coefficient between NIR predicted and reference values (r = 0.95) and lowest standard error of prediction (SEP = 0.35 N) and bias of 0.19 N. The ratio of standard deviation of reference data of prediction set to standard error of prediction (RPD) was 2.71. In the case of Momotaro tomato, NIR spectroscopy by using PLS regression could not predict alcohol insoluble solids in fresh weight accurately but could predict soluble solids content well with r of 0.80, SEP of 0.210 %Brix and bias of 0.022 %Brix. © 2012 Elsevier Ltd. All rights reserved.


Kapper C.,CCL Nutricontrol | Kapper C.,VION Food Group | Klont R.E.,VION Food Group | Verdonk J.M.A.J.,CCL Nutricontrol | And 3 more authors.
Meat Science | Year: 2012

Longissimus dorsi samples (685) collected at four processing plants were used to develop prediction equations for meat quality with near infrared spectroscopy. Equations with R 2>0.70 and residual prediction deviation (RPD)≥2.0 were considered as applicable for screening. One production plant showed R 2 0.76 and RPD 2.05, other plants showed R 2<0.70 and RPD<2.0 for drip loss %. RPD values were ≤2.05 for drip loss%, for colour L *≤1.82 and pH ultimate (pHu)≤1.57. Samples were grouped for drip loss%; superior (<2.0%), moderate (2-4%), inferior (>4.0%). 64% from the superior group and 56% from the inferior group were predicted correctly. One equation could be used for screening drip loss %. Best prediction equation for L * did not meet the requirements (R 2 0.70 and RPD 1.82). pHu equation could not be used. Results suggest that prediction equations can be used for screening drip loss %. © 2012 Elsevier Ltd.


PubMed | Institute of Arctic Ecophysiology, PDK Projects Inc. and ETH Zurich
Type: Journal Article | Journal: The Science of the total environment | Year: 2015

Intensification of agricultural production worldwide has altered cycles of phosphorus (P) and water. In particular, loading of P on land in fertilizer applications is a global water quality concern. The Lake Winnipeg Basin (LWB) is a major agricultural area displaying extreme eutrophication. We examined the eutrophication problem in the context of the reemerging global concern about future accessibility of phosphate rock for fertilizer production and sustainable phosphorus management. An exploratory action research participatory design was applied to study options for proactivity within the LWB. The multiple methods, including stakeholder interviews and surveys, demonstrate emerging synergies between the goals of reversing eutrophication and promoting food security. Furthermore, shifting the prevalent pollutant-driven eutrophication management paradigm in the basin toward a systemic, holistic and ecocentric approach, integrating global resource challenges, requires a mutual learning process among stakeholders in the basin to act on and adapt to ecosystem vulnerabilities. It is suggested to continue aspects of this research in a transdisciplinary format, i.e., science with society, in response to globally-expanding needs and concerns, with a possible focus on enhanced engagement of indigenous peoples and elders.


Singh B.,University of Manitoba | Malley D.F.,PDK Projects Inc. | Farenhorst A.,University of Manitoba | Williams P.,PDK Projects Inc.
Journal of Agricultural and Food Chemistry | Year: 2012

Livestock manure contains natural steroid hormones, with the most potent being 17β-estradiol. The transport of steroid hormones from agricultural fields to adjacent water bodies can result in 17β-estradiol environmental contamination impacting aquatic organisms. Sorption coefficients are useful input into models that estimate risk of water contamination. The feasibility of applying near-infrared spectroscopy (NIRS) for determining sorption coefficients of 17β-estradiol in soil was investigated for two irregular undulating to hummocky terrain landscapes in Manitoba and Saskatchewan, Canada. A total of 609 soil samples in 140 soil profiles were collected from several horizons to a depth of 1 m. Air-dried and sieved (2 mm) soil samples were analyzed for soil organic carbon (SOC), soil pH, and soil texture. Sorption coefficients of 17β-estradiol were determined by a batch equilibrium process. Spectral data were collected from soil samples (25 g) using two instruments, the 45VISNIR Zeiss Corona (wavelength range 700-1690 nm) and the Foss NIRSystems 6500 (wavelength range 1100-2500 nm). Regardless of the site and instrument, the predictive models were excellent for both SOC and 17β-estradiol sorption coefficients. The data thus generated can be used as input parameters in fate models for efficient risk assessments and decision-making programs for environmental safety where soils are at risk of receiving inputs of 17β-estradiol. Calibration results for soil pH were also adequate with Corona outperforming the Foss instrument. Soil texture predictions were relatively unsuccessful regardless of the instrument and site. © 2012 American Chemical Society.


Singh B.,University of Manitoba | Farenhorst A.,University of Manitoba | McQueen R.,University of Manitoba | Malley D.F.,PDK Projects Inc.
Soil Science Society of America Journal | Year: 2016

Sorption parameters (such as Kd values) are among the most sensitive input parameters in pesticide fate models. This study demonstrates that near-infrared spectroscopy (NIRS), in combination with batch equilibrium techniques, can be used to estimate Kd values, thereby increasing throughput of the many samples required to characterize spatial variability of pesticide sorption within fields. The Pesticide Root Zone Model version 3.12.2 (PRZM- 3) was used to compare scenarios that used NIRS spectral data, pedotransfer functions, and batch equilibrium methods as inputs for the calculation of 2,4-dichlorophenoxyacetic acid (2,4-D) and atrazine leaching in 591 soil horizons. Based on the 3564 simulation runs conducted, we concluded that the added benefit of NIRS is most useful when the pesticides under study have small sorption potentials and short half-lives in soil. The 2,4-D and atrazine sorption by soil was highly correlated to soil organic C (SOC) content in the fields under study. The feasibility of using NIRS to predict pesticide Kd values largely relies on the sorption of the pesticide being significantly correlated to SOC. In addition, successful regional approaches to predicting Kd values from NIRS spectral data can also be developed when the calibration model is derived by combining a set of fields where each has a similar statistical population characteristic in Kd values. © 2016 Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA. All Rights reserved.


Malley D.F.,PDK Projects Inc. | Williams P.,PDK Projects Inc.
Aquatic Ecosystem Health and Management | Year: 2014

Lake sediments serve as archives that reflect biological and chemical conditions of lakes. Carbon, nitrogen and phosphorus are determined in sediments and in suspended material in lakes, termed seston, for a number of purposes. These include: assessment of sediment quality, identification of the trophic level of lakes, and study of contaminants. The use of near-infrared spectroscopy provides a rapid and cost-effective alternative for routine analysis of large numbers of samples. Calibration equations developed from spectral data and the results of conventional chemical analysis on an initial set of representative samples are used to predict constituents in future unknown samples of the same type. In sediment samples and seston, carbon, nitrogen and phosphorus were generally predicted very successfully by near-infrared spectroscopy. The best samples for analyzing sediment quality are generally those from the deepest part of a lake. Spatial variability in sediment quality of a lake was successfully explored by this method, suggesting that near-infrared spectroscopy is a potential complementary tool to standard methods for analyzing and characterizing sediments. © 2014, Copyright © AEHMS.

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