Non-destructive imaging and spectroscopic techniques for assessment of carcass and meat quality in sheep and goats: a review

In the last decade, there has been a significant development in rapid, non-destructive and non-invasive techniques to evaluate carcass composition and meat quality of meat species. This article aims to review the recent technological advances of non-destructive and non-invasive techniques to provide objective data to evaluate carcass composition and quality traits of sheep and goat meat. We highlight imaging and spectroscopy techniques and practical aspects, such as accuracy, reliability, cost, portability, speed and ease of use. For the imaging techniques, recent improvements in the use of dual-energy X-ray absorptiometry, computed tomography and magnetic resonance imaging to assess sheep and goat carcass and meat quality will be addressed. Optical technologies are gaining importance for monitoring and evaluating the quality and safety of carcasses and meat and, among them, those that deserve more attention are visible and infrared reflectance spectroscopy, hyperspectral imagery and Raman spectroscopy. In this work, advances in research involving these techniques in their application to sheep and goats are presented and discussed. In recent years, there has been substantial investment and research in fast, non-destructive and easy-to-use technology to raise the standards of quality and food safety in all stages of sheep and goat meat production. © 2020 by the authors.Authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020); Laboratory of Carcass and Meat Quality of Agriculture School of Polytechnic Institute of Bragança ‘Cantinho do Alfredo’. The authors A. Teixeira and S. Rodrigues are members of the Healthy Meat network, funded by CYTED (ref. 119RT0568). CECAV authors are thankful to the project UIDB/CVT/00772/2020 funded by the Foundation for Science and Technology (FCT, Portugal).info:eu-repo/semantics/publishedVersio

Computed tomography evaluation of gilt growth performance and carcass quality under feeding restrictions and compensatory growth effects on the sensory quality of pork

Restricted feed can affect the body composition of pigs. Body composition can be studied non-destructively in live pigs using computed tomography (CT). The objective was to investigate the effect of different feeding restriction strategies on the productive and carcass quality parameters of gilts during growth via CT images and the effects of such strategies on meat quality, sensory properties and consumer preferences. Moreover, we sought to determine whether CT is a suitable tool for this purpose in this type of study. Thus, 36 Pietrain x (Large White x Landrace) gilts were assigned to the following three feeding strategies: 1) ad libitum feeding (AL) during all fattening periods (AL-AL); 2) AL feeding between 30 and 70 kg target body weight (TBW) followed by restriction (84% of AL) until 120 kg TBW (AL-RV); and 3) restriction feeding (78% of AL) between 30 and 70 kg TBW followed by AL until 120 kg TBW (RV-AL). When the pigs reached 30, 70, 100 and 120 kg, they were CT scanned to obtain the carcass composition parameters. At 120 kg TBW, the pigs were slaughtered, and the carcass and meat quality was determined. The loins were collected for trained panel evaluation and consumer tests. The panellists evaluated the odour, flavour and texture attributes of cooked loins. A total of 120 consumers scored the overall acceptability, tenderness, odour and flavour. The results showed a decrease of 76% and 80% in the average daily gain and average daily feed intake during the restriction period compared with the ad libitum in the growth phase, respectively, and a decrease of 89% and 87% in these parameters during the fattening phase, respectively. A restriction reduces the body fat content during the period of the restriction. Differences in the carcass and cut composition and meat quality were not observed at the end of the experiment among the treatments. Regarding sensory quality, meat from the animals in the AL-AL treatment was tougher than that from animals in the RV-AL and AL-RV treatments. Nevertheless, these differences were not detected by consumers, who did not provide significantly different scores for acceptability. Thus, when preparing feeding strategies, these results should be considered to optimize costs and increase benefits. Furthermore, computed tomography represents a non-destructive technology suitable for determining carcass composition before slaughter.info:eu-repo/semantics/acceptedVersio

Imaging technologies to study the composition of live pigs: A review

Image techniques are increasingly being applied to livestock animals. This paper overviews recent advances in image processing analysis for live pigs, including ultrasound, visual image analysis by monitoring, dual-energy X-ray absorptiometry, magnetic resonance imaging and computed tomography. The methodology for live pigs evaluation, advantages and disadvantages of different devices, the variables and measurements analysed, the predictions obtained using these measurements and their accuracy are discussed in the present paper. Utilities of these technologies for livestock purposes are also reviewed. Computed tomography and magnetic resonance imaging yield useful results for the estimation of the amount of fat and lean mass either in live pigs or in carcasses. Ultrasound is not sufficiently accurate when high precision in estimating pig body composition is necessary but can provide useful information in agriculture to classify pigs for breeding purposes or before slaughter. Improvements in factors, such as the speed of scanning, cost and image accuracy and processing, would advance the application of image processing technologies in livestock animals

Non-invasive methods for the determination of body and carcass composition in livestock: dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging and ultrasound: invited review

The ability to accurately measure body or carcass composition is important for performance testing, grading and finally selection or payment of meat-producing animals. Advances especially in non-invasive techniques are mainly based on the development of electronic and computer-driven methods in order to provide objective phenotypic data. The preference for a specific technique depends on the target animal species or carcass, combined with technical and practical aspects such as accuracy, reliability, cost, portability, speed, ease of use, safety and for in vivo measurements the need for fixation or sedation. The techniques rely on specific device-driven signals, which interact with tissues in the body or carcass at the atomic or molecular level, resulting in secondary or attenuated signals detected by the instruments and analyzed quantitatively. The electromagnetic signal produced by the instrument may originate from mechanical energy such as sound waves (ultrasound – US), ‘photon’ radiation (X-ray-computed tomography – CT, dual-energy X-ray absorptiometry – DXA) or radio frequency waves (magnetic resonance imaging – MRI). The signals detected by the corresponding instruments are processed to measure, for example, tissue depths, areas, volumes or distributions of fat, muscle (water, protein) and partly bone or bone mineral. Among the above techniques, CT is the most accurate one followed by MRI and DXA, whereas US can be used for all sizes of farm animal species even under field conditions. CT, MRI and US can provide volume data, whereas only DXA delivers immediate whole-body composition results without (2D) image manipulation. A combination of simple US and more expensive CT, MRI or DXA might be applied for farm animal selection programs in a stepwise approach

Evaluation of live growing pigs of different genotypes and sexes using computed tomography

Conocer la composición corporal en animales vivos y la deposición de los diferentes tejidos durante su crecimiento es de vital importancia para, entre otras cosas, caracterizar el efecto de una genética, la condición sexual, el manejo e incluso analizar la eficiencia alimentaria y adecuar la dieta a cada estadio de crecimiento, ya que la composición en tejido graso y muscular del cuerpo de los animal está influenciada tanto por factores intrínsecos como extrínsecos. La aplicación de la tomografía computerizada (CT) en animales vivos permite analizar, de manera no invasiva, la evolución de la composición corporal de un mismo animal a lo largo del período de crecimiento. Esto permite modelizar el crecimiento y desarrollo de los diferentes tejidos del cuerpo sin necesidad alguna de sacrificar el animal. Esta tesis propone conocer la evolución de la composición corporal de cerdos de distintas genéticas (experimento 1) o sexos (experimento 2). El experimento 1 estaba formado por 90 animales de tres genéticas distintas (todas ellas comerciales y altamente utilizadas en el sector), y el experimento 2 estaba formado por 92 animales de cuatro condiciones sexuales distintas (hembras (FE), machos enteros (EM), machos castrados quirúrgicamente (CM) y machos inmunocastrados (IM)). Los animales se evaluaron con el CT a 30, 70, 100 i 120 kg de peso objetivo. Una submuestra de animales de cada genética y sexo (n=5/genética y n=4/sexo) se sacrificaron a los diferentes pesos objetivo y se disecaron total o parcialmente. El resto de animales (animales de seguimiento), se evaluaron con el CT a cada peso objetivo y, al llegar a 120 kg, se sacrificaron. A partir de los animales sacrificados y disecados, se obtuvieron ecuaciones de predicción, de la composición corporal y de las diferentes piezas, que se usaron en el resto de animales de seguimiento. Las predicciones se hicieron para cada genética independientemente (Chapter 4) o bien generalizadas para todas las genéticas y sexos (Chapter 6). Ambas ecuaciones fueron adecuadas para la predicción de la composición corporal (Chapter 8). En este sentido, presentar las predicciones individuales según la genética reduce el error (RMSE entre 0.011 y 0.886). No obstante, la ecuacion global permite generalizar las predicciones para un mayor número de animales, así pues, es preferible usarla cuando la población está mezclada o cuando el parámetro estimado no requiere un alto valor de precisión. Cuando esta precisión se requiere, como es el caso de compañías genéticas, es preferible utilizar las ecuaciones individuales, específicamente desarrolladas para cada genética. Los resultados muestran que los tejidos crecen de manera diferente según la genética s y el sexo (Chapter 5 y 7). El tejido que mostró el mayor coeficiente alométrico fue la grasa, indicando el índice de deposición más rápido de este tejido. De entre las distintas genéticas, LA fue quien mostró la deposición de grasa más rápida (Chapter 5), mientras que respecto a los sexos, los CM e IM fueron los que tuvieron un índice de deposición de grasa más elevado y más lento en los EM y FE (Chapter 7). El comportamiento de la deposición de magro fue inverso al de la grasa. Añadir que, los IM y CM tuvieron un comportamiento muy similar respecto a la velocidad de deposición de grasa y magro, a pesar que los IM se comportaron como los EM hasta que recibieron la segunda dosis de la vacuna de immunocastración. Finalmente, en las condiciones de realización de este trabajo se puede concluir que el CT puede ser muy útil para la industria cárnica, porque los parámetros de calidad y composición de la canal se pueden conocer a pesos muy tempranos. Como resultado, el uso de esta información puede aportar beneficios económicos para todos los integrantes de la cadena alimenticia.Knowledge of the composition of animal bodies and animal tissue growth is very important for the characterization of the effect of a genotype, the sexual condition, the management or to analyze the feed efficiency and adjust the diet to growth states, because fat and lean composition are dependent on intrinsic and extrinsic factors. The application of computed tomography (CT) to living animals allows analyzing non-invasively the evolution of the body composition of a single animal through its growing period. Subsequently, growth and development of the different body tissues can be modeled, without the necessity to slaughter the animal. The PhD Thesis at hand investigates the evolution of the composition of pig bodies from different genetic types (experiment 1) and sexual conditions (experiment 2). Experiment 1 was performed on 90 pigs of three genetic types (all of them were commercial and very used in the swine industry), while experiment 2 was performed on 92 animals with four different sexual conditions (females, entire males, castrated males and immunocastrated males). The animals were scanned by CT at 30, 70, 100 and 120 kg live weigh. One subsample for each genetic type and sexual condition (n=5/genetic type and n=4/sexual condition) were slaughtered at the different target weights and were fully or partially dissected. The rest of the animals (animals of the study) were evaluated with the CT at each target weight and, once they reached 120 kg, they were slaughtered. Knowledge gained from slaughtered and dissected animals was used to formulate prediction equations for body and pieces composition. They were then applied to the animals of the study. Predictions were performed independently for each genetic type (Chapter 4) or generalized for all the genetic types and sexual conditions of this work (Chapter 6). Both equations produce good results for the prediction of body composition (Chapter 8). Presenting the individual predictions depending on the genetic type reduces the error (RMSE between 0.011 and 0.886). However, the global equation allows generalizing the predictions for a bigger number of animals, thus, it has preference if the population is mixed or if high level of accuracy is not required. If high accuracy is needed, for instance for genetic companies, individual equations specifically developed for each genetic type are prefered. Results show that tissues grow different depending on the genetic type and sexual condition (Chapter 5 and 7). Tissue that shows the highest allometric coefficient was the fat, corresponding to the fastest deposition. From the different genotypes, LA was the one that shows the fastest deposition of fat (Chapter 5). With respect to the sexual condition, CM and IM exert the highest deposition value for the fat, with EM and FE showing the lowest (Chapter 7). Lean tissue behaves in the opposite way as fat. The IM and CM had a very similar behavior with respect to the deposition speed of fat and lean, even IM behave as EM until the study animals received the second dose of the immunocastration vaccine. In conclusion, CT can be very useful for the meat industry due to its ability to predict quality parameters, as well as carcass composition, at early growth stage. This technique can thus bring economic benefits for all the livestock and food chain industry

Genetiske analyser av kjøtt-, fett- og slaktekvalitetsegenskaper målt med hurtigmetoder

The overall aim of this thesis was to analyse meat and fat quality traits using quantitative genetic methods. This study has demonstrated that it is possible to establish simple laboratory practices and high quality rapid analyses of meat and fat quality traits at a research abattoir. Developed multivariate calibration methods and Near-infrared spectroscopy (NIRS) data were used to predict many of the traits studied, and large-scale recordings provided the basis for the genetic analysis of the meat and fat quality traits. In addition, estimated genetic parameters of body composition traits from large-scale Computed tomography (CT) scan of live boars yielded new information about the growth of various body tissues. The results show that low labour, large-scale measuring methods can provide high heritabilities for several traits. The meat quality traits: pH in M. gluteus medius, M. gluteus profundus and M. longissimus dorsi and drip loss, meat colour and meat composition traits of M. longissimus dorsi showed heritabilities from 0.12 to 0.50 in Landrace and from 0.22 to 0.62 in Duroc. The fat quality traits: fatty acid composition, fat moisture content, and fat colour in subcutaneous fat showed heritabilities from 0.06 to 0.67 in Landrace and from 0.01 to 0.57 in Duroc. The CT traits: growth of muscle, fat, bone and internal organs showed heritabilities from 0.19 to 0.53 in Landrace and from 0.43 to 0.59 in Duroc. On the basis of the parameters estimated here, breeding for a higher lean meat percentage and lower feed convention ratio is expected to result in deterioration of meat and fat quality traits. In view of the genetic parameters and size of the heritabilities and genetic correlations, some new traits for meat, fat and carcass quality are recommended in the breeding programme for Norwegian Landrace and Duroc. Among the traits investigated, the traits of greatest importance are NIRS predicted intramuscular fat, drip loss, a* value in meat and NIRS-predicted moisture and fatty acids composition in subcutaneous fat. The percentage of oleic acid, C18:1n-9, from the NIRS analysis is highly heritable and may improve technological quality, sensory properties and human health. A selection for L* value or reflectance in meat is discouraged due to the undesirable influence of the IMF in the measuring. CT scanning makes it possible to select directly for the growth rate of muscle, fat, bones and internal organs of live boars. Pig meat has many qualities important for human nutrition, and is a good source for essential minerals and nutrients, e.g. heme iron, protein with a good amino acid profile and good fatty acids. This study has demonstrated the possibilities of selecting for some of these component traits.Hovedmålet med denne avhandlingen var å analysere kjøtt- og fettkvalitetsegenskaper med kvantitative genetiske analyser. Dette studiet har vist at det er mulig å etablere enkle laboratorierutiner og hurtige målemetoder av høy kvalitet for kjøtt- og fettkvalitetsegenskaper ved et forskningsslakteri. Utviklede multivariate kalibreringsmetoder og Near-infrared spektroskopi (NIRS) data ble brukt til a predikere mange av de studerte egenskapene. Storskala datafangst gir grunnlaget for genetisk analyse av kjøtt og fettkvalitetsegenskaper. I tillegg er det estimert genetiske parametere for kroppssammensetning fra storskala skanning med atatomografi (CT) av levende råner, som gir ny informasjon om veksten av ulike vev. Resultatene viser at lite arbeidskrevende, storskala målemetoder kan gi høye arvegrader for flere av egenskapene. Kjøttkvalitetsegenskaper som pH i M. gluteus medius, M. gluteus profundu og M. longissimus dorsi og drypptap, kjøttfarge og kjøttsammensetningsegenskaper av M. longissimus dorsi hadde arvegrader fra 0,12 til 0,50 hos landsvin og fra 0,22 til 0,62 hos duroc. Fettkvalitetsegenskaper som fettsyresammensetning, vannprosent i fett og fettfarge i subkutant fett hadde arvegrader fra 0,06 til 0,67 hos landsvin og fra 0,01 til 0,57 hos duroc. CT-egenskaper som vekst av muskel, fett, bein og indre organer hadde arvegrader fra 0,19 til 0,53 hos landsvin og fra 0,43 til 0,59 hos duroc. På bakgrunn av parameterne estimert her er det forventet at avl for en høyere kjøttprosent og fôrutnyttelse vil resultere i forringelse av kjøtt- og fettkvalitetsegenskapene. I lys av de genetiske parametere, størrelsen på arvegradene og de genetiske korrelasjonene, anbefales Norsvin å ta med noen nye kvalitetsegenskaper for kjøtt-, fett- og slaktekvalitet i avlsarbeidet for norsk landsvin og duroc. De viktigste egenskapene er NIRS-predikert intramuskulart fett, drypptap, a* verdi i kjøtt og NIRS-predikert vanninnhold og fettsyresammensetning i subkutant fett. Andelen oljesyre, C18:1n-9, målt med NIRS-analyse er høyt arvelig, og kan bedre den teknologiske og sensoriske kvaliteten samt human helse. Grunnet uønsket påvirkning av IMF, frarådes seleksjon for L* verdi og refleksjon i kjøtt. CT-skanning gjør det mulig å selektere direkte for tilvekst av muskel, fett, bein og indre organer. Svinekjøtt har mange positive kvaliteter for human ernæring og er en god kilde for viktige mineraler og næringsstoffer, f. eks heme jern, høykvalitets protein og gunstige fettsyrer. Denne studien har vist at det er mulig å selektere for noen av disse komponentegenskapene.Norsvin ; Norges Forskningsråd ; the Foundation for Research Levy on Agricultural Products