| Nitrate is a kind of nitrogen compound that people contact in nature frequently. It widely exists in soil, water and vegetables. For many years, nitrate pollution rarely caused acute poisoning because of the slow and covert toxicity and the nitrate didn't get enough attention to people. With the improvement of life condition and life level, especially the report of digestive system cancers increasingly year after year, the harm of nitrate to human body has aroused the universal attention of people. A large amount of study show that 80% of nitrate taken in from vegetables. So the detection of nitrate residues can control the nitrate ingestion quantity of people, and it has a large significance to guarantee human health.A new kind of detection method of nitrate deoxidation bacteria for nitrate residues in vegetables was showed in this study. On the basis of environment protection, the deoxidation technique of microorganism was used in the detection of nitrate in vegetables. It was a rapid, portable, qualitative and semi-quantitative method for the detection of nitrate in vegetables which was available to be used by common people. The main contents and results of this thesis are as following:1. The wavelength, optimal color conditions, the stability of color reaction, precision, and accuracy of nitrate and nitrite were studied by spectrometer. The detection wavelength was 420nm when nitrite and antipyrin in tartaric acid. The optimal detection wavelength was 296nm when nitrate and phenol in the sulfuric acid medium. The optimal color showing conditions of nitrite by the method of (3×3×3)orthogonal polynomials regressive design were as following: 0.7ml of 0.025g/mL antipyrin, 0.5ml of 0.05g/mL tartaric acid, reaction time is 30s. The optimal color showing conditions of nitrate are as following: 0.2mL of 0.01g/mL phenol, 1ml of sulfuric acid, reaction time is 60s. Absorbance didn't have an obvious change in 30min, and the curve of time scanning is nearly a beeline, so the color showing complex has a good stability. In the reaction of nitrite and antipyrin, RSD=0.0214 , CV=3.26%<5%. In the reaction of nitrate and phenol, RSD=0.07768,CV=2.35%<5%.2. The content of nitrate and nitrite were detected based on BP neural networks in Matlab. The repeating character of coloring showing reaction of nitrate and nitrite was detected on this system. The conclusion was got that the coefficient of variation of nitrate reaction and nitrite reaction are 0.0% and 0.28% (<5%), which means the repeating character of the two reactions and the precision are good.3. From the view of environment protection, the enriched and selective culture of miscellaneous bacterium in the soil and the detection of nitrate were conducted by combining the principle of bionomy and the theory of microorganism inheritance. The extraction conditions of the target bacteria are as following: anaerobic environment, glucose as carbon source, C/N = 1:1, 30℃, pH = 6.5±0.5. Through morphological observation and preliminary detection of biochemical experiment, the enriched bacteria from the soil may be the compound of Proteus, Micrococcus, Pseudomonas and Bacillus. The reduction ability of present bacteria was improved by inducement domestication method. Three kinds of bacteria were kept by periodic transplantation of solid slant media. The range of logarithmic growth period of three kinds of bacteria by the method of MPN counts is about 15~30h.4. The influence of pigment of sample, degree of crash, extraction reagent and extraction time on the extraction rate of nitrate residues in vegetables has been studied. The extraction conditions when the extraction rate reaches the optimum are as following: extraction reagent is ethanol water, homogenized time is 1min, extraction time is 3min, column filled by 5g activated carbon and 2g neutral alumina is used to eliminate pigment.5. The recovery and the limit of detection were detected, and the result is that the limit of detection for the method of deoxidation bacterium is DL = 1.04 (μg /kg), the standard deviation is S = 0.018<0.1, the coefficient of variation CV = 4.205 % <5%. The limit of detection for the method of Zn-Cd deoxidization is DL = 3.59(μg /kg), the standard deviation is S = 0.040<0.1, the coefficient of variation CV = 4.1 % <5 %.6. Use deoxidation bacterium as the reducing agent deoxidize the nitrate in vegetables plasm several times, the result indicated that all of the coefficient of variation are smaller than 5%. Which means that the repeating character of the method of deoxidation bacterium is very well, and it has a good dependability.7. Use the method of Zn-Cd deoxidization detect the nitrate in vegetables several times, the result indicated that all of the coefficient of variation are smaller than 5%. The detection range for nitrate in the cabbage is 1167~1220mg/kg. The range for nitrate in the celery is 1425mg/kg~1467mg/kg. And the result indicated that the two vegetables gone beyond the standard level. Meanwhile the deoxidization rate of the method of Zn-Cd deoxidization for deoxidation the nitrate is 95%.8. This paper studied the dynamics model of Nitrate deoxidation bacterium in the process of deoxidating nitrate, and respectively gained the nitrate consumption and nitrite generating mathematic model as follows (5-9) and (5-10), At the same time, this text adopt numerical value differential calculus and testify that the biochemistry reaction was belonged to zero steps of reaction, the velocity constant is: ks = 0.012433min-1.9. Contrast the difficulty, detecting effect and the uniformity & stability of reagent strip between the method of papermaking with paper pulp and the dipping in method of papermaking. The manufacture method of reagent strip for the detection of nitrite was determined: dipping in method of quantitative filter paper,φ1 8cmquantitative filter paper was dipped in 30ml mixture of 0.3g antipyrin and 0.6g tartaric acid, and then dried by oven at 60℃. Standard color card was manufactured for nitrite in order to detect nitrite qualitatively and semi-quantitatively by visual colorimetry, and provided a reference for the detection of nitrate residues. Through solid sensor detecting nitrite, precision of the method reaches 95%. This method provided a guarantee for the rapid detection of nitrate.10. The test data were disposal by BP neural networks in Matlab. This test got the solid sensor and tries slip of paper supporting the experiment data and got the JP-kind tries slip of paper detecting system. After checking the J P-quantitative filter paper coloration detecting diameter in Matlab, we got the relative standard deviation between the true value for nitrite and the forecasting value is RSD = 0.029~0.068≤0.1, the coefficient of transformation is CV = 0.2%~0.8%. |
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