Determination of the Mineral Composition of Foods by Infrared Spectroscopy: A Review of a Green Alternative

Milking system and diet forage type effect on milk quality of Italian Holstein-Friesian

Moving from conventional (CMS) to automatic (AMS) milking systems could affect milk quality. Moreover, the type and preservation methods of the forages used in the TMR, such as alfalfa hay (HTMR) or corn silage (STMR) have been demonstrated to modify milk composition. Thus, this study investigated the effect of implementing AMS and different diet forage types on the quality of Italian Holstein-Friesian bulk milk. Milk samples (n = 168) were collected monthly from 21 commercial farms in northern Italy during a period of 8 mo. Farms were categorized into 4 groups according to their milking system (CMS vs. AMS) and diet forage type (HTMR vs. STMR). Milk quality data were analyzed through the mixed procedure for repeated measurement of SAS with the milking system, diet forage type, and sampling day as fixed effects. Milking through the AMS led to lower milk fat, freezing point, and β-LG A; longer coagulation time; and higher K content, pH, and β-LG B than CMS. Cows fed STMR produced milk with greater fat, protein, casein, Mg content, titratable acidity, and β-LG A, but with reduced curd firming time, freezing point, and β-LG B than those fed HTMR. In conclusion, milk quality is not only altered by the diet's forage type and characteristics but also by the milking system.

Mid-infrared spectroscopy of liquids by using a modified button sample holder

A new approach for mid-infrared spectroscopy measurements of liquids is described. Thin layers of liquid samples are analyzed by using a modified button sample holder that incorporates a reservoir. To obtain spectra, buttons containing liquid samples are placed at the infrared beam focus of a praying mantis diffuse reflection optical system. Infrared radiation absorption path lengths can be adjusted by changing the quantity of liquid added to the reservoir. Thin film transflection spectra are similar to those obtained by transmission measurements. Transflection spectra of thicker layer liquids also resemble transmission measurements, but with increased relative intensities for low absorptivity peaks. Unlike transmission measurements, transflection spectra retain overlapping peak profiles for highly absorbing vibration bands due to multiple path length dynamic range effects. For a fixed effective path length (i.e. constant liquid volume), linear calibration plots of absorbance or integrated absorbance versus concentration are obtained. The button sample holder provides a methodology that is complementary to the transmission cell and attenuated total reflection (ATR) techniques for infrared analyses of neat solids and liquids, and is especially useful for characterizing thick samples and high absorptivity bands.

Analysis of Highly Concentrated Aqueous Solutions of Alkali Metal Chlorides Using Sonoluminescence Spectroscopy

The use of the sonoluminescence spectroscopy for the determination of main components in concentrated aqueous solution of alkali metal halides is examined. In concentrated RCl solutions (R = Li, Na, K; C = 100-600 g · dm^-3) the sonoluminescence intensity is inversely proportional to ultrasound frequency in the range from 2 Hz up to 5 Hz. In the CsCl case the inverse proportionality is disturbed at ultrasound frequencies higher than 3 MHz. This is the limiting value for the accurate analysis of the concentrated solutions of cesium chloride. The increase of initiating ultrasound frequency leads to a decrease of the main component determination in highly concentrated (more than 300 g ċ dm^-3) natural and artificial solutions. Nevertheless, the metrological characteristics of the results of the main substance determination in these solutions improve. The routines of express determination of the main substance in concentrated saline solutions were developed.

Performance of different portable and hand-held near-infrared spectrometers for predicting beef composition and quality characteristics in the abattoir without meat sampling

The availability of portable and handheld NIR instruments on the market opens up new possibilities in meat analysis. However, there is lack of research comparing different NIR instruments for evaluating beef characteristics from spectra obtained directly on the meat surface. Our aim, therefore, was to build and test calibration and prediction models for predicting beef characteristics, and to compare the performances of three NIR instruments differing in size and characteristics: a transportable visible-NIR spectrometer (Vis-NIRS), a portable (NIRS), and a hand-held Micro-NIRS. Spectra were collected from 178 beef samples (Longissimus thoracis muscle) from the meat surface in the abattoir. The spectra were subjected to different mathematical pretreatments then partial least square regressions. The results showed that all instruments predicted dry matter, protein and lipids with R²_VAL 0.23 to 0.70; pH and cooking loss R²_VAL 0.19 to 0.25; and color R²_VAL 0.35 to 0.77. Overall, the prediction performances of the three instruments were similar, although Micro-NIRS performed better in some respects.

Fiber Probe for Simultaneous Mid-Infrared and Fluorescence Spectroscopic Analysis

A multispectral fiber optic probe has been developed that enables simultaneous analysis of various liquid and solid samples using attenuated total reflection mid-infrared spectroscopy and fluorimetry. The probe design was optimized using ray-tracing simulation of the light propagation. Technical evaluation of the probe has confirmed its output signal quality that was comparable to that of respective probes for single methods. The capability of the probe to deliver complementary chemical information from the same measurement point has been illustrated using model samples of biological tissue. Qualitative analysis of the biological tissue is one of the most important applications of the developed multispectral probe.

Predicting the Content of 20 Minerals in Beef by Different Portable Near-Infrared (NIR) Spectrometers

The aim of this study was to test the predictability of a detailed mineral profile of beef using different portable near-infrared spectrometers (NIRS). These devices are rapid, chemical waste-free, cheap, nondestructive tools that can be used directly on the meat surface in the work environment without the need to take samples. We compared a transportable Visible-NIRS (weight 5.6 kg; wavelength 350-1830 nm), a portable NIRS (2.0 kg; 950-1650 nm), and a hand-held Micro-NIRS (0.06 kg; 905-1649 nm) to predict the contents of 20 minerals (measured by ICP-OES) in 178 beef samples (Longissimus thoracis muscle) using different mathematical pretreatments of the spectra and partial least square regressions. The externally validated results show that Fe, P, Mg, S, Na, and Pb have some potential for prediction with all instruments (R2VAL: 0.40-0.83). Overall, the prediction performances of the three instruments were similar, although the smallest (Micro-NIRS) exhibited certain advantages.

Application of a Handheld Near-Infrared Spectrometer to Predict Gelatinized Starch, Fiber Fractions, and Mineral Content of Ground and Intact Extruded Dry Dog Food

Simple Summary

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. Despite having some limitations related to the need to modify the production process or to have a laboratory to prepare the samples for analysis through desktop instruments, near-infrared spectroscopy is one of the most used technologies for inexpensive analysis of foodstuffs. Thus, the miniaturization of infrared devices allows a wider industrial applicability of this technique. Information on the use of miniaturized infrared tools in the pet food sector is currently very limited, and the present research is the first attempt to predict the total and gelatinized starch, insoluble fibrous fractions, and mineral content of ground and intact dry pet food using the handheld NIR scanner SCiO™. Results from the current study revealed no significant differences in the predictive ability of the instrument using both ground and intact samples. The instrument offers a potential for screening purposes of both total and gelatinized starch, revealing the potential to monitor their content and ratio in commercial dog food on a large scale. Improvements such as widening the wavelength range is expected to increase prediction models’ accuracy.

Abstract

The aim of the present study was to investigate the ability of a handheld near-infrared spectrometer to predict total and gelatinized starch, insoluble fibrous fractions, and mineral content in extruded dry dog food. Intact and ground samples were compared to determine if the homogenization could improve the prediction performance of the instrument. Reference analyses were performed on 81 samples for starch and 99 for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and minerals, and reflectance infrared spectra (740 to 1070 nm) were recorded with a SCiO™ near-infrared (NIR) spectrometer. Prediction models were developed using modified partial least squares regression and both internal (leave-one-out cross-validation) and external validation. The best prediction models in cross-validation using ground samples were obtained for gelatinized starch (residual predictive deviation, RPD = 2.54) and total starch (RPD = 2.33), and S (RPD = 1.92), while the best using intact samples were obtained for gelatinized starch (RPD = 2.45), total starch (RPD = 2.08), and K (RPD = 1.98). Through external validation, the best statistics were obtained for gelatinized starch, with an RPD of 2.55 and 2.03 in ground and intact samples, respectively. Overall, there was no difference in prediction models accuracy using ground or intact samples. In conclusion, the miniaturized NIR instrument offers the potential for screening purposes only for total and gelatinized starch, S, and K, whereas the results do not support its applicability for the other traits.

At-line Prediction of Gelatinized Starch and Fiber Fractions in Extruded Dry Dog Food Using Different Near-Infrared Spectroscopy Technologies

Simple Summary

Starch is a non-fibrous carbohydrate that represents an important percentage of pet food composition. The degree of its gelatinization, due to the cooking process, can be a useful indicator of starch digestibility in the diet. Moreover, fiber fractions are important for animals’ health and nutritional status, so pet food industry is interested in the development of an easy and cost-effective method to measure these parameters. Results of this study revealed the applicability of visible/near-infrared spectroscopy to predict total and gelatinized starch, neutral detergent fiber, acid detergent fiber, and acid detergent lignin in pet food. On the other hand, near-infrared transmittance technology showed a scarce accuracy. The developed prediction models for total and gelatinized starch and fiber fractions using visible/near-infrared spectroscopy could be applied during the manufacturing process to perform quality controls.

Abstract

This study aimed to assess the feasibility of visible/near-infrared reflectance (Vis-NIR) and near-infrared transmittance (NIT) spectroscopy to predict total and gelatinized starch and fiber fractions in extruded dry dog food. Reference laboratory analyses were performed on 81 samples, and the spectrum of each ground sample was obtained through Vis-NIR and NIT spectrometers. Prediction equations for each instrument were developed by modified partial least squares regressions and validated by cross- (CrV) and external validation (ExV) procedures. All studied traits were better predicted by Vis-NIR than NIT spectroscopy. With Vis-NIR, excellent prediction models were obtained for total starch (residual predictive deviation; RPD_CrV = 6.33; RPD_ExV = 4.43), gelatinized starch (RPD_CrV = 4.62; RPD_ExV = 4.36), neutral detergent fiber (NDF; RPD_CrV = 3.93; RPD_ExV = 4.31), and acid detergent fiber (ADF; RPD_CrV = 5.80; RPD_ExV = 5.67). With NIT, RPD_CrV ranged from 1.75 (ADF) to 2.61 (acid detergent lignin, ADL) and RPD_ExV from 1.71 (ADL) to 2.16 (total starch). In conclusion, results of the present study demonstrated the feasibility of at-line Vis-NIR spectroscopy in predicting total and gelatinized starch, NDF, and ADF, with lower accuracy for ADL, whereas results do not support the applicability of NIT spectroscopy to predict those traits.

Prediction of Mineral Composition in Commercial Extruded Dry Dog Food by Near-Infrared Reflectance Spectroscopy

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R² = 0.89), K (R² = 0.85), and Li (R² = 0.74), followed by P, B, and Sr (R² = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.

Determination of Inorganic Cations and Anions in Chitooligosaccharides by Ion Chromatography with Conductivity Detection

Chitooligosaccharides (COSs) are a promising drug candidate and food ingredient because they are innately biocompatible, non-toxic, and non-allergenic to living tissues. Therefore, the impurities in COSs must be clearly elucidated and precisely determined. As for COSs, most analytical methods focus on the determination of the average degrees of polymerization (DPs) and deacetylation (DD), as well as separation and analysis of the single COSs with different DPs. However, little is known about the concentrations of inorganic cations and anions in COSs. In the present study, an efficient and sensitive ion chromatography coupled with conductivity detection (IC-CD) for the determination of inorganic cations Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺, and chloride, acetate and lactate anions was developed. Detection limits were 0.01-0.05 μM for cations and 0.5-0.6 μM for anions. The linear range was 0.001-0.8 mM. The optimized analysis was carried out on IonPac CS12A and IonPac AS12A analytical column for cations and anions, respectively, using isocratic elution with 20 mM methanesulfonic acid and 4 mM sodium hydroxide aqueous solution as the mobile phase at a 1.0 mL/min flow rate. Quality parameters, including precision and accuracy, were fully validated and found to be satisfactory. The fully validated IC-CD method was readily applied for the quantification of various cations and anions in commercial COS technical concentrate.

Non-invasive sensing for food reassurance

The main food quality traits of interest using non-invasive sensing techniques are sensory characteristics, chemical composition, physicochemical properties, health-protecting properties, nutritional characteristics and safety. A wide range of non-invasive sensing techniques, from optical, acoustical, electrical, to nuclear magnetic, X-ray, biosensor, microwave and terahertz, are organized according to physical principle.