Measurement of Soy Contents in Ground Beef Using Near-Infrared Spectroscopy

Abstract

Models for determining contents of soy products in ground beef were developed using near-infrared (NIR) spectroscopy. Samples were prepared by mixing four kinds of soybean protein products (Arconet, toasted soy grits, Profam and textured vegetable protein (TVP)) with ground beef (content from 0%-100%). NIR spectra of meat mixtures were measured with dispersive (400-2500 nm) and Fourier transform NIR (FT-NIR) spectrometers (1000-2500 nm). Partial least squares (PLS) regression with full leave-one-out cross-validation was used to build prediction models. The results based on dispersive NIR spectra revealed that the coefficient of determination for cross-validation (R cv 2 ) ranged from 0.91 for toasted soy grits to 0.99 for Arconet. The results based on FT-NIR spectra exhibited the best prediction for toasted soy grits (R cv 2 = 0.99) and R cv 2 > 0.98 for the other three soy types. For identification of different types of soy products, support vector machine (SVM) classification was used and the total accuracy for dispersive NIR and FT-NIR was 95% and 83.33%, respectively. These results suggest that either dispersive NIR or FT-NIR spectroscopy could be used to predict the content and the discrimination of different soy products added in ground beef products. In application, FT-NIR spectroscopy methods would be recommended if time is a consideration in practice.

The Creation of the FT-NIR Calibration for the Determination of the Amount of Corn Grain in Concentrated Feed

“…In this method, R 2 = 0.81 for the starch value of DDGS, R 2 = 0.88 for protein and R 2 = 0.87 for moisture (Paulsen et al 2010). In a study to determine protein, starch and fat content of maize by using of NIR device (Jiang et al 2017); protein, starch, and fat contents were found to be the same as the results determined by wet chemical method. The researchers concluded that the NIR method can be used to quickly detect protein, starch and fat content.…”

“…Although not the same type of studies, there are logically similar quantitative studies to detect adulteration tricks in feedstuffs or food for human consumption. From 0% to 30% of meat (0%, 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 15%,20%, 25% and 30%) Rcv2 (cross validation) value was determined in the range of 0.99-0.98 in adulteration study by adding 4 different soy flour (Jiang et al 2017). As a result, it was demonstrated by using the FT-NIR method that the soy products added to meat products such as sausage, salami and sausage can be quantitatively determined.…”

Detection of Haemonchus contortus nematode eggs in sheep faeces using near and mid-infrared spectroscopy

“…PC-1 showed that 97% of the total variance observed consisted of bands at 1450, 1880 and 2030 nm (Figure 5). Previous studies have shown that bands at approximately 1880 nm correspond to fatty acids 28 and 2023 nm correspond to N–H bond in amides. 29 Among the bands found in PC-2 that accounted for 2% of the total variance observed, only the peaks at 1450 and 1930 nm were previously identified as water.…”

Pencitraan Inframerah Dekat dari Lemak Sapi pada Model Lemak Tissue

“…Pada spektrum ini terlihat beberapa komponenkomponen penting yang terdapat didalamnya. Komponen air dimana pada prinsipnya daging yang diukur mengandung air yang terlihat pada daerah bilangan gelombang 7067 cm −1 dimana dijelaskan lebih khusus oleh [7] bahwa pada daerah panjang gelombang 1415 nm atau setara dengan energi pada bilangan gelombang 7067 cm −1 merupakan pengelompokan karakteristik untuk air, sedangkan untuk protein ditunjukan pada daerah bilangan gelombang 4578 cm −1 , hal ini juga sudah dijelaskan terlebih dahulu oleh [15] bahwa serapan protein terdapat pada panjang gelombang 2061 dan 2184 nm atau 4852 dan 4578 cm −1 . Selain itu komponen lemak juga terlihat muncul pada daerah bilangan gelombang 8280 cm −1 hal ini juga dapat disesuaikan dari gambar spektrum lemak yang disandingkan pada Gambar 3.…”