ORCID Profile
0000-0001-7636-0481
Current Organisations
Griffith University
,
Department of Agriculture and Fisheries
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Publisher: Elsevier BV
Date: 11-2018
Publisher: Elsevier BV
Date: 04-2018
Publisher: Springer Science and Business Media LLC
Date: 14-08-2019
Publisher: Springer Science and Business Media LLC
Date: 30-10-2013
Publisher: Elsevier BV
Date: 08-2018
Publisher: MDPI AG
Date: 16-03-2021
DOI: 10.3390/RS13061128
Abstract: Hyperspectral imaging (HSI) is an emerging rapid and non-destructive technology that has promising application within feed mills and processing plants in poultry and other intensive animal industries. HSI may be advantageous over near infrared spectroscopy (NIRS) as it scans entire s les, which enables compositional gradients and s le heterogenicity to be visualised and analysed. This study was a preliminary investigation to compare the performance of HSI with that of NIRS for quality measurements of ground s les of Australian wheat and to identify the most important spectral regions for predicting carbon (C) and nitrogen (N) concentrations. In total, 69 s les were scanned using an NIRS (400–2500 nm), and two HSI cameras operated in 400–1000 nm (VNIR) and 1000–2500 nm (SWIR) spectral regions. Partial least square regression (PLSR) models were used to correlate C and N concentrations of 63 calibration s les with their spectral reflectance, with 6 additional s les used for testing the models. The accuracy of the HSI predictions (full spectra) were similar or slightly higher than those of NIRS (NIRS Rc2 for C = 0.90 and N = 0.96 vs. HSI Rc2 for C (VNIR) = 0.97 and N (SWIR) = 0.97). The most important spectral region for C prediction identified using HSI reflectance was 400–550 nm with R2 of 0.93 and RMSE of 0.17% in the calibration set and R2 of 0.86, RMSE of 0.21% and ratio of performance to deviation (RPD) of 2.03 in the test set. The most important spectral regions for predicting N concentrations in the feed s les included 1451–1600 nm, 1901–2050 nm and 2051–2200 nm, providing prediction with R2 ranging from 0.91 to 0.93, RMSE ranging from 0.06% to 0.07% in the calibration sets, R2 from 0.96 to 0.99, RMSE of 0.06% and RPD from 3.47 to 3.92 in the test sets. The prediction accuracy of HSI and NIRS were comparable possibly due to the larger statistical population (larger number of pixels) that HSI provided, despite the fact that HSI had smaller spectral range compared with that of NIRS. In addition, HSI enabled visualising the variability of C and N in the s les. Therefore, HSI is advantageous compared to NIRS as it is a multifunctional tool that poses many potential applications in data collection and quality assurance within feed mills and poultry processing plants. The ability to more accurately measure and visualise the properties of feed ingredients has potential economic benefits and therefore additional investigation and development of HSI in this application is warranted.
Publisher: MDPI AG
Date: 06-05-2021
DOI: 10.3390/RS13091807
Abstract: Hyperspectral image (HSI) analysis has the potential to estimate organic compounds in plants and foods. Curcumin is an important compound used to treat a range of medical conditions. Therefore, a method to rapidly determine rhizomes with high curcumin content on-farm would be of significant advantage for farmers. Curcumin content of rhizomes varies within, and between varieties but current chemical analysis methods are expensive and time consuming. This study compared curcumin in three turmeric (Curcuma longa) varieties and examined the potential for laboratory-based HSI to rapidly predict curcumin using the visible–near infrared (400–1000 nm) spectrum. Hyperspectral images (n = 152) of the fresh rhizome outer-skin and flesh were captured, using three local varieties (yellow, orange, and red). Distribution of curcuminoids and total curcumin was analysed. Partial least squares regression (PLSR) models were developed to predict total curcumin concentrations. Total curcumin and the proportion of three curcuminoids differed significantly among all varieties. Red turmeric had the highest total curcumin concentration (0.83 ± 0.21%) compared with orange (0.37 ± 0.12%) and yellow (0.02 ± 0.02%). PLSR models predicted curcumin using raw spectra of rhizome flesh and pooled data for all three varieties (R2c = 0.83, R2p = 0.55, ratio of prediction to deviation (RPD) = 1.51) and was slightly improved by using images of a single variety (orange) only (R2c = 0.85, R2p = 0.62, RPD = 1.65). However, prediction of curcumin using outer-skin of rhizomes was poor (R2c = 0.64, R2p = 0.37, RPD = 1.28). These models can discriminate between ‘low’ and ‘high’ values and so may be adapted into a two-level grading system. HSI has the potential to help identify turmeric rhizomes with high curcumin concentrations and allow for more efficient refinement into curcumin for medicinal purposes.
Publisher: Springer Science and Business Media LLC
Date: 05-08-2019
Publisher: Elsevier BV
Date: 04-2019
Publisher: Springer Science and Business Media LLC
Date: 31-05-2013
Publisher: MDPI AG
Date: 20-01-2022
Abstract: Improved nitrogen fertiliser management and increased nitrogen use efficiency (NUE) can be achieved by synchronising nitrogen (N) availability with plant uptake requirements. Organic materials in conjunction with inorganic fertilisers provide a strategy for supplying plant-available N over the growing season and reducing N loss. This study investigated whether a combined application of inorganic N with an organic soil amendment could improve nitrogen use efficiency by reducing N loss in runoff. Nitrogen runoff from a ryegrass (Lolium multiflorum) cover was investigated using a rainfall simulator. Nitrogen was applied at low, medium and high (50, 75 and 100 kg/ha) rates as either (NH4)2SO4 or in combination with a poultry manure-based organic material. We showed that the NUE in the combination (58–75%) was two-fold greater than in (NH4)2SO4 (24–42%). Furthermore, this combination also resulted in a two-fold lower N runoff compared with the inorganic fertiliser alone. This effect was attributed to the slower rate of N release from the organic amendment relative to the inorganic fertiliser. Here, we demonstrated that the combined use of inorganic and organic N substrates can reduce nutrient losses in surface runoff due to a better synchronisation of N availability with plant uptake requirements.
Publisher: MDPI AG
Date: 14-12-2019
DOI: 10.3390/W11122642
Abstract: Bayesian networks (BNs) are widely implemented as graphical decision support tools which use probability inferences to generate “what if?” and “which is best?” analyses of potential management options for water resource management, under climate change and socio-economic stressors. This paper presents a systematic quantitative literature review of applications of BNs for decision support in water resource management. The review quantifies to what extent different types of data (quantitative and/or qualitative) are used, to what extent optimization-based and/or scenario-based approaches are adopted for decision support, and to what extent different categories of adaptation measures are evaluated. Most reviewed publications applied scenario-based approaches (68%) to evaluate the performance of management measures, whilst relatively few studies (18%) applied optimization-based approaches to optimize management measures. Institutional and social measures (62%) were mostly applied to the management of water-related concerns, followed by technological and engineered measures (47%), and ecosystem-based measures (37%). There was no significant difference in the use of quantitative and/or qualitative data across different decision support approaches (p = 0.54), or in the evaluation of different categories of management measures (p = 0.25). However, there was significant dependence (p = 0.076) between the types of management measure(s) evaluated, and the decision support approaches used for that evaluation. The potential and limitations of BN applications as decision support systems are discussed along with solutions and recommendations, thereby further facilitating the application of this promising decision support tool for future research priorities and challenges surrounding uncertain and complex water resource systems driven by multiple interactions amongst climatic and non-climatic changes.
Publisher: Academic Journals
Date: 16-03-2012
DOI: 10.5897/AJMR11.967
Publisher: Elsevier BV
Date: 08-2018
Publisher: Springer Science and Business Media LLC
Date: 26-09-2017
DOI: 10.1007/S11356-017-0281-Y
Abstract: Ethylenediaminetetraacetic acid (EDTA) used with electrokinetic (EK) to remediate heavy metal-polluted soils is a toxic chelate for soil microorganisms. Therefore, this study aimed to evaluate the effects of alternative organic chelates to EDTA on improving the microbial properties of a heavy metal-polluted soil subjected to EK. Cow manure extract (CME), poultry manure extract (PME) and EDTA were applied to a lead (Pb) and zinc (Zn)-polluted calcareous soil which were subjected to two electric intensities (1.1 and 3.3 v/cm). Soil carbon pools, microbial activity, microbial abundance (e.g., fungal, actinomycetes and bacterial abundances) and diethylenetriaminepentaacetic acid (DTPA)-extractable Pb and Zn (available forms) were assessed in both cathodic and anodic soils. Applying the EK to soil decreased all the microbial variables in the cathodic and anodic soils in the absence or presence of chelates. Both CME and PME applied with two electric intensities decreased the negative effect of EK on soil microbial variables. The lowest values of soil microbial variables were observed when EK was combined with EDTA. The following order was observed in values of soil microbial variables after treating with EK and chelates: EK + CME or EK + PME > EK > EK + EDTA. The CME and PME could increase the concentrations of available Pb and Zn, although the increase was less than that of EDTA. Overall, despite increasing soil available Pb and Zn, the combination of EK with manures (CME or PME) mitigated the negative effects of using EK on soil microbial properties. This study suggested that the synthetic chelates such as EDTA could be replaced with manures to alleviate the environmental risks of EK application.
Publisher: Elsevier BV
Date: 09-2018
DOI: 10.1016/J.SCITOTENV.2018.04.278
Abstract: Biochar has been shown to affect soil microbial ersity and abundance. Soil microbes play a key role in soil nutrient cycling, but there is still a dearth of knowledge on the responses of soil microbes to biochar amendments, particularly for longer-term or repeated applications. We s led soil from a field trial to determine the in idual and combined effects of newly applied (1 year ago), re-applied (1 year ago into aged biochar) and aged (9 years ago) biochar amendments on soil bacterial communities, with the aim of identifying the potential underlying mechanisms or consequences of these effects. Soil bacterial ersity and community composition were analysed by sequencing of 16S rRNA using a Miseq platform. This investigation showed that biochar in soil after 1 year significantly increased bacterial ersity and the relative abundance of nitrifiers and bacteria consuming pyrogenic carbon (C). We also found that the reapplication of biochar had no significant effects on soil bacterial communities. Mantel correlation between bacterial ersity and soil chemical properties for four treatments showed that the changes in soil microbial community composition were well explained by soil pH, electrical conductivity (EC), extractable organic C and total extractable nitrogen (N). These results suggested that the effects of biochar amendment on soil bacterial communities were highly time-dependent. Our study highlighted the acclimation of soil bacteria on receiving repeated biochar amendment, leading to similar bacterial ersity and community structure among 9-years old applied biochar, repeated biochar treatments and control.
Publisher: Elsevier BV
Date: 02-2017
Publisher: MDPI AG
Date: 17-10-2020
DOI: 10.3390/RS12203409
Abstract: Fatty acid composition and mineral nutrient concentrations can affect the nutritional and postharvest properties of fruit and so assessing the chemistry of fresh produce is important for guaranteeing consistent quality throughout the value chain. Current laboratory methods for assessing fruit quality are time-consuming and often destructive. Non-destructive technologies are emerging that predict fruit quality and can minimise postharvest losses, but it may be difficult to develop such technologies for fruit with thick skin. This study aimed to develop laboratory-based hyperspectral imaging methods (400–1000 nm) for predicting proportions of six fatty acids, ratios of saturated and unsaturated fatty acids, and the concentrations of 14 mineral nutrients in Hass avocado fruit from 219 flesh and 194 skin images. Partial least squares regression (PLSR) models predicted the ratio of unsaturated to saturated fatty acids in avocado fruit from both flesh images (R2 = 0.79, ratio of prediction to deviation (RPD) = 2.06) and skin images (R2 = 0.62, RPD = 1.48). The best-fit models predicted parameters that affect postharvest processing such as the ratio of oleic:linoleic acid from flesh images (R2 = 0.67, RPD = 1.63) and the concentrations of boron (B) and calcium (Ca) from flesh images (B: R2 = 0.61, RPD = 1.51 Ca: R2 = 0.53, RPD = 1.71) and skin images (B: R2 = 0.60, RPD = 1.55 Ca: R2 = 0.68, RPD = 1.57). Many quality parameters predicted from flesh images could also be predicted from skin images. Hyperspectral imaging represents a promising tool to reduce postharvest losses of avocado fruit by determining internal fruit quality of in idual fruit quickly from flesh or skin images.
Publisher: Springer Science and Business Media LLC
Date: 15-06-2017
Publisher: Springer Science and Business Media LLC
Date: 19-05-2013
DOI: 10.1007/S10661-013-3217-0
Abstract: The application of electrical fields and chelating agents is an innovative hybrid technology used for the decontamination of soil polluted by heavy metals. The effects of four center-oriented electrical fields and chelating agents on active fractions of lead and zinc were investigated in this pot experiment. Ethylenediaminetetraacetic acid (EDTA) as a synthetic chelator and cow manure extract (CME) and poultry manure extract (PME) as natural chelators were applied to the pots (2 g kg(-1)) 30 days after the first irrigation. Two weeks later, four center-oriented electrical fields were applied in each pot (in three levels of 0, 10, and 30 V) for 1 h each day for 14 days. The soil near the cathode and anodes was collected and analyzed as cathodic and anodic soil, respectively. Results indicated that the soluble-exchangeable fraction of lead and zinc were decreased in the cathodic soil, while the carbonate-bound fractions were increased. In the anodic soil, however, the opposite result was observed. EDTA enhanced the soluble-exchangeable form of the metals in both anodic and cathodic soils. Furthermore, the amounts of carbonate-bound heavy metals were increased by the application of CME in both soils. The organic-bound fraction of the metals was increased by the application of natural chelators, while electrical fields had no significant impacts on this fraction.
Publisher: Springer Science and Business Media LLC
Date: 10-2015
DOI: 10.1007/S11356-015-5467-6
Abstract: The low efficiency of phytoremediation is a considerable problem that limits the application of this environmentally friendly method on heavy metal-polluted soils. The combination of chelate-assisted phytoextraction and electrokinetic remediation could offer new opportunities to improve the effectiveness of phytoextraction. The current experiment aims to investigate the effects of electrical fields and chelating agents on phytoremediation efficiency. In a pot experiment using mine soil, poultry manure extract (PME), cow manure extract (CME), and ethylenediaminetetraacetic acid (EDTA) were applied to soil as chelating agents (2 g kg(-1)) at the beginning of the flowering stage. A week later, Helianthus annuus (sunflower) was negatively charged by inserting a stainless steel needle with 10 and 30 V DC electricity in the lowest part of the stems for 1 h each day for a 14-day period. At the end of the experiment, the shoot and root dry weight, lead (Pb) concentration in plant organs, translocation factor (TF), metal uptake index (UI), and soil available Pb (diethylene triamine pentaacetic acid (DTPA) extractable) were detected. Results indicated that the application of electrical fields had no significant impact on the shoot and root dry weights, while Pb concentration and UI increased in the 10-V EDTA treatment by 500 % compared to control. There was no significant difference between UI in 30- and 10-V EDTA treatments. Soil available Pb significantly increased in the 30-V treated soil. A positive correlation was observed between the available Pb in soil near the root and Pb concentration in shoot, its TF, and UI. In conclusion, a negatively charged plant along with the application of EDTA significantly increased the phytoremediation efficiency.
No related grants have been discovered for Iman Tahmasbian.