Quality of agricultural products is a very important issue for consumers as well as for farmers in relation to price, health and flavour. One of the factors that determine the quality is the absence of pathogens that can cause diseases for products and also for consumers. An advanced method to sense pathogens and their antagonists is the use of Visible/Near Infrared (VIS/NIR) spectroscopy. In this paper, the VIS/NIR spectroscopy, with the help of two techniques of multivariate data analysis (MVDA); namely principal component analysis (PCA) and support vector machine (SVM)-classification; showed very reliable results for sensing two artificially inoculated fungi (Fusarium oxysporum f. sp. Lycopersici and Rhizoctonia solani), and two antagonistic bacteria (Bacillus atrophaeus and Pseudomonas aeruginosa). The two fungi cause loss of quality and quantity for tomatoes. The results showed that the lowest classification rates using VIS/NIR spectroscopy for pathogens, antagonistic and their combinations were 90%, 85% and 74%, respectively. These results open a wide range for using VIS/NIR spectroscopy sensor technology for agricultural commodities quality at quality control checkpoints.
The main aim of the present study was to predict the growth of the food spoilage yeast Debaryomyces hansenii by multivariate data analysis (MVDA) using temperature, pH and NaCl concentration as growth parameters. Growth of five strains of D. hansenii (DHI, DHII, DHIII, DHIV and DHV) was measured as optical density at 620 nm (OD620) at different values of temperature, pH and NaCl concentrations. It was found that salt was the most important factor, which affects yeast growth followed by temperature. The growth of all yeast strains was reduced by increasing salt concentration and decreasing temperature. On the other hand, pH was found to have a little effect on the growth of D. hansenii. Strain DHII was the most salt-tolerant strains among the five yeast strains investigated. Partial least squares (PLS) prediction model was created out using pH, temperature and NaCl concentration to predict the growth of D. hansenii. The model was acceptable with a correlation of 0.86. The developed PLS model will help in optimizing the food process conditions that will prevent food spoilage by D. hansenii.
Early detection of plant disease requires usually elaborating methods techniques and especially when symptoms are not visible. Olive Leaf Spot (OLS) infecting upper surface of olive leaves has a long latent infection period. In this work, VIS/NIR spectroscopy was used to determine the latent infection and severity of the pathogens. Two different classification methods were used, Partial Least Squared-Discrimination Analysis (PLS-DA) (linear method) and Support Vector Machine (SVM) (non-linear). SVM-classification was able to classify severity levels 0, 1, 2, 3, 4, and 5 with classification rates of 94, 90, 73, 79, 83 and 100%, respectively The overall classification rate was about 86%. PLS-DA was able to classify two different severity groups (first group with severity 0, 1, 2, 3, and second group with severity 4, 5), with a classification rate greater than 95%. The results promote further researches, and the possibility of evaluation OLS in-situ using portable VIS/NIR devices.
Since deuterium 2H (D) is an isotope of hydrogen 1H, the testing of the possibility of photochemical synthesis of marked chlorinated phenol, biphenyl and benzene using normal solvents was studied. The irradiation of full chlorinated compounds dissolved in normal solvents such as MeOH or n-hexane has led to a reaction substitution in which a chlorine atom was substituted by hydrogen atom forming less grade chlorinated chlorophenols, biphenyls and benzenes. The quantum yields of pentachlorophenol, decachlorobiphenyl and hexachlorobenzene under irradiation using polychromatic light were calculated and found to be 5.7 x 10-3, 1.6 x 10-2 and 1.2 x 10-2 Mol·Einstein-1, respectively. Depending on this study the production of marked chlorinated or non-chlorinated compounds using deuterated appropriate solvents such as MeOH d4 or n-hexane d14 is possible. However, more efforts should be made towards chromatographically separation of synthesized standards and byproducts in order to make the use of these marked compounds as standards in residue analysis feasible.
The problem of pollutants in drinking water networks is neglected in many places all over the developing countries. This problem is normally caused by either direct pollution source such as organic carbon, or from the maceration pollutants of network materials. The heavy metals in the network facilities and the DOC from the wastewater leakage on the formation of toxic by-product in the water network and the rate of halogenated hydrocarbons formation in the drinking water network was studied. Results showed that water has the same constituents of pollutants similar to that before its being stored for relatively long periods. The results showed also that the trend of halogenated hydrocarbons formation is correlated, but not restricted, to the availability of total organic carbons. The amount of CCl2Br and CClBr2 were the highest, which indicate that most of the halogens are originated from natural sources. The Strontium values where the most dominant in all sampling points followed by Barium and Boron, which are the most abundant trace metals normally found in the groundwater in Tulkarm area
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