کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6403367 | 1330894 | 2014 | 6 صفحه PDF | دانلود رایگان |
- Developed a low-cost colorimetric sensor array using chemical dyes printed on a plate.
- Chicken freshness was successfully evaluated by the colorimetric sensor array.
- A novel AdaBoost + OLDA algorithm was used for sensors data classification.
This paper attempted to evaluate chicken freshness using a low-cost colorimetric sensor array with the help of a classification algorithm. We fabricated a novel and low-cost colorimetric sensors array, with a specific colorific fingerprint to volatile compounds, using printing chemically responsive dyes on a C2 reverse silica-gel flat plate. In addition, we proposed a novel classification algorithm for sensors data classification - orthogonal linear discriminant analysis (OLDA) and adaptive boosting (AdaBoost) algorithm, namely AdaBoost-OLDA. And we compared it with two classical classification algorithms - linear discriminant analysis (LDA) and back propagation artificial neural network (BP-ANN). Experimental results showed classification results by AdaBoost-OLDA algorithm is superior to BP-ANN and LDA algorithms, the classification results by which are both 100% in the calibration and prediction sets. This study sufficiently demonstrated that the colorimetric sensors array with a classification algorithm has a high potential in evaluating chicken freshness, and AdaBoost-OLDA algorithm has a strong performance in solution to a complex data classification.
Journal: LWT - Food Science and Technology - Volume 57, Issue 2, July 2014, Pages 502-507