首页> 外文期刊>Applied Engineering in Agriculture >Detection of fecal/ingesta contaminants on poultry processing equipment surfaces by visible and near-infrared reflectance spectroscopy.
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Detection of fecal/ingesta contaminants on poultry processing equipment surfaces by visible and near-infrared reflectance spectroscopy.

机译:通过可见和近红外反射光谱法检测家禽加工设备表面上的粪便/肠粘膜污染物。

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摘要

Visible and near-infrared (NIR) spectra and samples for laboratory microbial analysis were acquired of fecal contaminants, ingesta contaminants, and bare processing equipment surfaces (rubber and stainless steel) in a commercial poultry processing plant. Spectra were analyzed in the visible region of 450 to 748 nm and the NIR region of 920 to 1680 nm and microbial sampling for Enterobacteriaceae counts (EBC) was conducted for 82 fecal contaminant samples, 59 ingesta contaminant samples, 40 bare rubber belt areas, and 40 bare stainless steel areas. Two-wavelength band ratios in the visible and NIR regions were selected for separating contaminants from equipment areas. Principal component analysis (PCA) was performed to analyze the spectral data set and 2-class soft independent modeling of class analogy (SIMCA) models were developed for comparison with band ratio classification. Fecal and ingesta contaminants were difficult to separate from each other but both were easily differentiated from the equipment areas. The visible ratio using 518 and 576 nm correctly classified 100% of contaminant samples and 92.5% of equipment area samples. The NIR ratio using 1565 and 1645 nm correctly classified 100% of the contaminant samples and 95% of the equipment area samples. Microbiological analysis found the highest EBC levels for fecal contaminants; mean EBC for ingesta contaminants was significantly lower than that for fecal contaminants. The high EBC levels for fecal contaminants indicate that these contaminants should be targeted for spectral-based detection methods for sanitation monitoring and verification purposes; although their EBC levels are significantly lower, ingesta contaminants should also be included due to difficulty of separation from fecal contaminants.
机译:在商业家禽加工厂中,采集了粪便污染物,食入污染物和裸露的加工设备表面(橡胶和不锈钢)的可见和近红外(NIR)光谱和用于实验室微生物分析的样品。在450至748 nm的可见光区域和920至1680 nm的NIR区域对光谱进行了分析,并对82粪便污染物样品,59摄入的污染物样品,40条裸露的橡胶带区域进行了肠细菌科计数的微生物取样(EBC) 40个裸露的不锈钢区域。选择可见光和近红外区域的两个波长带比率,以将污染物从设备区域中分离出来。进行了主成分分析(PCA)来分析光谱数据集,并开发了2类类比的软独立建模(SIMCA)模型以与谱带比分类进行比较。粪便和摄入的污染物很难相互分离,但是很容易与设备区域区分开。使用518和576 nm的可见光比率正确分类了100%的污染物样品和92.5%的设备面积样品。使用1565和1645 nm的NIR比率正确分类了100%的污染物样品和95%的设备区域样品。微生物分析发现粪便污染物的EBC含量最高。食入污染物的平均EBC明显低于粪便污染物的EBC。粪便污染物的EBC高水平表明,应将这些污染物作为基于光谱的检测方法的目标,以进行卫生监测和验证;尽管它们的EBC含量要低得多,但由于难以与粪便中的污染物分离,因此也应包括摄入的污染物。

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