Determination of Meat Quality through Principal Components Analysis
نویسندگان
چکیده
In the present investigation, Principal Component Analysis (PCA) was applied to various variables to describe meat quality. Sixteen meat quality variables were examined, and the analysis showed that 60.71% of the total variation was explained by the first three principal components. L, a, b as colour data; odour, tenderness, flavour, acceptability as sensorial traits; hardness and chewiness as physical traits had the highest share in the total variation.
منابع مشابه
Chemical and Physical Indicators in Drinking Water and Water Sources of Boroujerd Using Principal Components Analysis
Abstract Background and Objective: Quality control of drinking water is important for maintaining health and safety of consumers, and the first step is to study the water quality variables. This study aimed to evaluate the chemical and physical indicators, water quality variables and qualitative classification of drinking water stations and water sources in Boroujerd. Material and Methods...
متن کاملDetermination of Adulteration and Authenticity of Meat and Meat Products Using Chemical Properties and PCR Technique in Tabriz
Background & objectives: Nowadays, consumers are demanding more accurate and clear food information than ever before, and meat products are no exception. Given the relatively high cost of raw meat, the possibility of adulteration is not unthinkable. The importance of detecting fraud meat products is due to the inclusion of other types of meat or cheap carcass components or the non-compliance of...
متن کاملApplication of Hyperspectral Imaging Technique for Determination of Pork Quality Attributes
Meat grading has always been a research subject because of its economical importance and the large variations among meat product qualities. In this study, a hyperspectral imaging system in the near-infrared (NIR) range (900-1700 nm) was developed for quality assessment of pork meat. Pork samples were classified in three quality grades, as reddish-pink, firm and non-exudative (RFN), pale, soft a...
متن کاملSparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains
In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification and quality detection in this paper is presented based on model learning concepts includ...
متن کاملProduction of Fish Chips from Sand Smelt (Atherina boyeri, RISSO 1810) and Determination of Some Quality Changes
In this study, changes in some quality parameters of fish chips produced from sand smelt (Atherina boyeri, RISSO 1810) during storage period (at -18 o C for 6 months) were determined. The difference between the amount of moisture, crude protein, crude fat and crude ash components of raw fish in fish chips was significant (P < 0.05). Pre-frying process resulted in a decrease in all fatty acid...
متن کامل