Distinguishing Grass-fed Beef from Grain-fed Beef Using Near-IR Spectroscopy
This article examines the use of Near-IR spectroscopy to separate grass-fed beef from grain-fed beef. Some cattle graze on pastures which are lands covered with grass. Other cattle are fed maize which is essentially corn or other types of grain. Grass-fed beef has superior nutritional quality as compared to grain-fed beef. It is also superior as far as safety and environmental friendliness is concerned compared to grain fed beef1. Figure 1 depicts the different feeding scenarios for the cattle.
Figure 1: Grass-fed vs Grain-fed feeding methods2
Figure 2, shows the difference between the two types of meat.
Figure2: Difference between Grass-fed and Corn-fed beef3
As can be seen in the figure, grass-fed beef on the right has less significant marbling than corn fed beef. It also has a distinguishable yellow fat due to the presence of vitamin A in the grass. There is also more variety in taste and texture between breeds and origins. The corn-fed beef on the other hand, is produced by feeding corn or other types of grain to the cattle, antibiotics and hormones to fatten them. The fat also appears more white in colour due to lack of vitamin A. There is also less variety between breeds and origins4.
Distinguishing between the two types of meat, especially if it is done using a fast non-intrusive method is quite useful for two reasons. First of all, the consumers can be aware of the higher quality of meat they are purchasing. Secondly, it stops the fraudulent activities which sell grain-fed beef at a higher price in place of grass-fed beef.
Near-IR spectroscopy is a suitable technique for this kind of investigation and a number of researchers have already examined the different spectra obtained from grain-fed and grass-fed beef1,5,6. Near infrared spectroscopy of intact beef (Beef that has not been minced) predicts various quality features such as fatty acid profiles and PH1. Handheld near IR spectrophotometers are readily available in the market that connect to Bluetooth and save the spectra on the smartphone (Android or IOS)1,6.
Figure 3, shows the difference in spectra between grain-fed and grass-fed intact beef samples5.
Figure 3: Difference in spectra between Pasture fed and Maize silage fed5
There are some distinct differences between the two spectra. First of all, the spectra of animals on maize silage had four absorption bands at 1732 nm, 1754 nm related to CH2 stretch first overtone (different lipid content) and at 2310 nm, 2350 nm related to CH combinations respectively. Secondly, differences in the region 1638 nm and between 2200 nm-2300 nm related to C-H and C=C groups suggest that differences in polyunsaturated fatty acids could contribute further to muscle classification (The differences appear in the absorption spectra). Using the NIR spectra, correct classification with a success rate of 80-83% were made for pasture fed beef and 79-80% for maize fed beef5.
The Nirvascan spectrophotometer offered by ASP Laser Inc. has been used in one of these studies1 and could successfully classify grain-fed beef and grass-fed beef with a success rate of greater than 85%. Both Linear Discriminant Analysis (LDA) and Partial Least Square Discriminant Analysis (PLS-DA) methods were used for classification.
Figure 4 shows a fiber optic model Nirvascan spectrophotometer, connected to an external 5 Watt source which also includes a collecting lens (DRP1) to measure from intact beef containing fat.
Figure 4: Fiber optic Nirvascan used with an external Halogen light source to measure intact beef absorption spectrum
Several absorption peaks including for CH bond (Fat, 1200 nm peak) and OH bond (Moisture, Protein, 1450 nm peak) are observed in the measured absorption spectrum.
For more information about the Nirvascan spectrophotometer and its different models, refer to the following link.
Portable vibrational spectroscopic methods can discriminate between grass-fed and grain-fed beef, C.Coobs et.al, JINRS, 2021
Visible/near infrared reflectance spectroscopy for predicting composition and tracing system of production of beef muscle, D.Cozzolino et.al, Animal science, 2002
Handheld near-infrared spectrometer allows on-line prediction of beef quality traits, A Goi et.al, Meat science, 184, 2022